Coskun Bayrak
Dr. Coskun Bayrak is a professor in the department of Computer Science at the University of Arkansas at Little Rock (UALR). Also, at UALR, he has been serving on the Faculty of Bioinformatics since 2000. His primary research is in the intersection of software engineering, component based development, data mining, and Biomedical Engineering. However, he also has interest in modeling and simulation, cellular automata, mobile application development, health care application development, and monitoring and process control in health care. Dr. Bayrak has published over two hundred research articles in scientific conferences and journals, given tutorials at major conferences, and served on program committees for numerous international conferences and symposiums. Currently, he is serving as an Associate Editor for the special issue of Soft Computing in Software Engineering, a journal part of Applied Soft Computing, Elsevier (SCI). He is a member of IEEE and ACM. Dr. Bayrak holds a BS from Slippery Rock University of Pennsylvania, and a MS from Texas Tech University, and Ph.D. from Southern Methodist University in Computer Science.
Phone: 5015698137
Address: Computer Science Department,
College of Engineering and Information Technologies, Room, 577
2801 S. University Ave.
Little Rock, AR 72204
Phone: 5015698137
Address: Computer Science Department,
College of Engineering and Information Technologies, Room, 577
2801 S. University Ave.
Little Rock, AR 72204
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is satisfied with nonlinear geometry constraints to create an authentic human anatomy.
Methods GAML was used to create 3D difficult anatomical scenarios for virtual simulation of airway management techniques such as Endotracheal Intubation (ETI) and Cricothyroidotomy
(CCT). Difficult scenarios for each technique were defined and the model variations procedurally created with GAML.
Conclusion This study presents details of the GAML design, set of operators, types of constraints.
Cases of CCT and ETI difficulty were generated and confirmed by expert surgeons. Execution performance pertaining to an increasing complexity of constraints using nonlinear programming was in real‐time execution.
new model for software development. Or at least
that’s what many people want us to think. Most of
the growing open source community, which now boasts several corporate sponsored projects such as Netscape’s Mozilla, cites Linux operating system developer Linus Torvalds
as the messiah of this new model. Eric Raymond, in his important paper, “The Cathedral and the Bazaar,” claims that Torvalds’ cleverest and most consequential hack was not the construction of the Linux kernel itself, but rather his quasi-guidance of the Linux development model—a best practice
extraordinaire of OSD [7]. But what is this model
and why does it work? Here, we explore these
questions by examining the OSD model as a classically
defined distributed system.
past ten years has run rampant. The course it has taken has been
both swift and unpredictable. The largest distributed system in the
world began as a utopian notion of an interconnected and open
web of information, the dream of the academic and intellectual
alike. Today it is indeed a massive interconnected web of
communication and content, but the content, largely on the more
popular, if not pornographic, end of the mass media spectrum, is
not what the founders intended.
Coinciding with the rapid growth of the web has been the equally
speedy rise of the open source development community, which
can best be understood as a distributed system in its own right.
Indeed, the development of the web has been, outside of the Linux
project, the largest arena for open source development. And
current trends, witnessed by such significant open source projects
as Mozilla and Apache, seem to suggest that the open source way
of doing things is quickly becoming the web way of doing things.
However, there is a certain tension growing between those who
would like to control, for economic profit or for the gratification of
control itself, the direction of the web's development and those
open source developers who are responsible for a large portion of
that growth. This paper explores the natural relationship, as well
as the growing tension within this relationship, between the open
source development community and the World Wide Web.
health problem is the increase in the rate of preterm delivery, which is responsible for 75% of all deaths in newborns. In addition, preterm
delivery is associated with several cognitive and health problems in later life and enormous costs for the health system. A better understanding
of myometrial activities could help to reduce preterm deliveries and the costs associated with prematurity in the following years.
Therefore, the objective of this study was to determine whether using the Hilbert–Huang transform (HHT) to analyze the uterine contraction
data would help us gain a better insight of the myometrial activities of the human uterus during pregnancy.
Material and Methods: Uterine magnetomyographic (MMG) signals were recorded from pregnant patients at gestational ages of 32–38
weeks. The study was approved by the Human Research Advisory Board of the University of Arkansas for Medical Sciences (UAMS) and
performed after obtaining written consent from each patient. The recording of transabdominal MMG signals was conducted with the
SQUID Array for Reproductive Assessment (SARA, VSM MedTech Inc; Coquitlam, BC, Canada) system, which has 151 primary magnetic
sensors allocated approximately 3 cm apart over an area of 850 cm2. The arrangement of sensors is concave in nature and, in a similar
lateral distance, spans the maternal abdomen longitudinally from the symphysis pubis to the uterine fundus. The recording times ranged
from 12 to 28 min, and the sampling rate was 250 Hz. The data were down-sampled to 25 Hz to reduce the computational complexity
and post-processed with a bandpass filter (0.05–1 Hz) because the uterine contraction activity is a band-limited process (0.05–1 Hz). The
recordings of one intrauterine pressure catheter (IUPC) dataset and two mother-perceived contraction datasets were compared with the
HHT results, and HHT’s potential was explored through the development of a module and a series of experiments. The local energy and
the instantaneous frequency derived from the intrinsic mode functions (IMFs) through HHT provide a full energy-frequency-time distribution
of the data. Our objective was to determine whether HHT for each channel can help identify and localize contractions in the uterus.
Human studies have been reviewed by the appropriate ethics committee and have therefore been performed in accordance with the
ethical standards described in an appropriate version of the 1975 Declaration of Helsinki, as revised in 2000.
Results: After comparing the IUPC and other mother-perceived contraction (STIM) datasets with HHT results, we were able to visually detect
contraction locations in the HHT-processed uterine signals. For verification and validation purposes, when we further analyzed the delay time
between two signals, the mechanical activity (i.e., IUPC) following the electrical activity (i.e., magnetic signal) was observed. In conclusion, our
experimentations using the method introduced here revealed that there is a 75% correlation between the results obtained by HHT and IUPC data.
Conclusion: This study compared uterine contractions and changes in the intrauterine pressure with results obtained by HHT. In addition,
using IUPC data as a validation guide, we showed that the HHT approach can be used for noise removal. There is a need for time-saving
and non-subjective automatic contraction detection in the field of prenatal examination. (J Turk Ger Gynecol Assoc 2015; 16: 195-202)
Keywords: Uterine contraction, myometrium, magnetomyographic activity, Hilbert–Huang transform, empirical mode decomposition,
contraction analysis
health problem is the increase in the rate of preterm delivery, which is responsible for 75% of all deaths in newborns. In addition, preterm
delivery is associated with several cognitive and health problems in later life and enormous costs for the health system. A better understanding
of myometrial activities could help to reduce preterm deliveries and the costs associated with prematurity in the following years.
Therefore, the objective of this study was to determine whether using the Hilbert–Huang transform (HHT) to analyze the uterine contraction
data would help us gain a better insight of the myometrial activities of the human uterus during pregnancy.
Material and Methods: Uterine magnetomyographic (MMG) signals were recorded from pregnant patients at gestational ages of 32–38
weeks. The study was approved by the Human Research Advisory Board of the University of Arkansas for Medical Sciences (UAMS) and
performed after obtaining written consent from each patient. The recording of transabdominal MMG signals was conducted with the
SQUID Array for Reproductive Assessment (SARA, VSM MedTech Inc; Coquitlam, BC, Canada) system, which has 151 primary magnetic
sensors allocated approximately 3 cm apart over an area of 850 cm2. The arrangement of sensors is concave in nature and, in a similar
lateral distance, spans the maternal abdomen longitudinally from the symphysis pubis to the uterine fundus. The recording times ranged
from 12 to 28 min, and the sampling rate was 250 Hz. The data were down-sampled to 25 Hz to reduce the computational complexity
and post-processed with a bandpass filter (0.05–1 Hz) because the uterine contraction activity is a band-limited process (0.05–1 Hz). The
recordings of one intrauterine pressure catheter (IUPC) dataset and two mother-perceived contraction datasets were compared with the
HHT results, and HHT’s potential was explored through the development of a module and a series of experiments. The local energy and
the instantaneous frequency derived from the intrinsic mode functions (IMFs) through HHT provide a full energy-frequency-time distribution
of the data. Our objective was to determine whether HHT for each channel can help identify and localize contractions in the uterus.
Human studies have been reviewed by the appropriate ethics committee and have therefore been performed in accordance with the
ethical standards described in an appropriate version of the 1975 Declaration of Helsinki, as revised in 2000.
Results: After comparing the IUPC and other mother-perceived contraction (STIM) datasets with HHT results, we were able to visually detect
contraction locations in the HHT-processed uterine signals. For verification and validation purposes, when we further analyzed the delay time
between two signals, the mechanical activity (i.e., IUPC) following the electrical activity (i.e., magnetic signal) was observed. In conclusion, our
experimentations using the method introduced here revealed that there is a 75% correlation between the results obtained by HHT and IUPC data.
Conclusion: This study compared uterine contractions and changes in the intrauterine pressure with results obtained by HHT. In addition,
using IUPC data as a validation guide, we showed that the HHT approach can be used for noise removal. There is a need for time-saving
and non-subjective automatic contraction detection in the field of prenatal examination. (J Turk Ger Gynecol Assoc 2015; 16: 195-202)
Keywords: Uterine contraction, myometrium, magnetomyographic activity, Hilbert–Huang transform, empirical mode decomposition,
contraction analysis
is satisfied with nonlinear geometry constraints to create an authentic human anatomy.
Methods GAML was used to create 3D difficult anatomical scenarios for virtual simulation of airway management techniques such as Endotracheal Intubation (ETI) and Cricothyroidotomy
(CCT). Difficult scenarios for each technique were defined and the model variations procedurally created with GAML.
Conclusion This study presents details of the GAML design, set of operators, types of constraints.
Cases of CCT and ETI difficulty were generated and confirmed by expert surgeons. Execution performance pertaining to an increasing complexity of constraints using nonlinear programming was in real‐time execution.
new model for software development. Or at least
that’s what many people want us to think. Most of
the growing open source community, which now boasts several corporate sponsored projects such as Netscape’s Mozilla, cites Linux operating system developer Linus Torvalds
as the messiah of this new model. Eric Raymond, in his important paper, “The Cathedral and the Bazaar,” claims that Torvalds’ cleverest and most consequential hack was not the construction of the Linux kernel itself, but rather his quasi-guidance of the Linux development model—a best practice
extraordinaire of OSD [7]. But what is this model
and why does it work? Here, we explore these
questions by examining the OSD model as a classically
defined distributed system.
past ten years has run rampant. The course it has taken has been
both swift and unpredictable. The largest distributed system in the
world began as a utopian notion of an interconnected and open
web of information, the dream of the academic and intellectual
alike. Today it is indeed a massive interconnected web of
communication and content, but the content, largely on the more
popular, if not pornographic, end of the mass media spectrum, is
not what the founders intended.
Coinciding with the rapid growth of the web has been the equally
speedy rise of the open source development community, which
can best be understood as a distributed system in its own right.
Indeed, the development of the web has been, outside of the Linux
project, the largest arena for open source development. And
current trends, witnessed by such significant open source projects
as Mozilla and Apache, seem to suggest that the open source way
of doing things is quickly becoming the web way of doing things.
However, there is a certain tension growing between those who
would like to control, for economic profit or for the gratification of
control itself, the direction of the web's development and those
open source developers who are responsible for a large portion of
that growth. This paper explores the natural relationship, as well
as the growing tension within this relationship, between the open
source development community and the World Wide Web.
health problem is the increase in the rate of preterm delivery, which is responsible for 75% of all deaths in newborns. In addition, preterm
delivery is associated with several cognitive and health problems in later life and enormous costs for the health system. A better understanding
of myometrial activities could help to reduce preterm deliveries and the costs associated with prematurity in the following years.
Therefore, the objective of this study was to determine whether using the Hilbert–Huang transform (HHT) to analyze the uterine contraction
data would help us gain a better insight of the myometrial activities of the human uterus during pregnancy.
Material and Methods: Uterine magnetomyographic (MMG) signals were recorded from pregnant patients at gestational ages of 32–38
weeks. The study was approved by the Human Research Advisory Board of the University of Arkansas for Medical Sciences (UAMS) and
performed after obtaining written consent from each patient. The recording of transabdominal MMG signals was conducted with the
SQUID Array for Reproductive Assessment (SARA, VSM MedTech Inc; Coquitlam, BC, Canada) system, which has 151 primary magnetic
sensors allocated approximately 3 cm apart over an area of 850 cm2. The arrangement of sensors is concave in nature and, in a similar
lateral distance, spans the maternal abdomen longitudinally from the symphysis pubis to the uterine fundus. The recording times ranged
from 12 to 28 min, and the sampling rate was 250 Hz. The data were down-sampled to 25 Hz to reduce the computational complexity
and post-processed with a bandpass filter (0.05–1 Hz) because the uterine contraction activity is a band-limited process (0.05–1 Hz). The
recordings of one intrauterine pressure catheter (IUPC) dataset and two mother-perceived contraction datasets were compared with the
HHT results, and HHT’s potential was explored through the development of a module and a series of experiments. The local energy and
the instantaneous frequency derived from the intrinsic mode functions (IMFs) through HHT provide a full energy-frequency-time distribution
of the data. Our objective was to determine whether HHT for each channel can help identify and localize contractions in the uterus.
Human studies have been reviewed by the appropriate ethics committee and have therefore been performed in accordance with the
ethical standards described in an appropriate version of the 1975 Declaration of Helsinki, as revised in 2000.
Results: After comparing the IUPC and other mother-perceived contraction (STIM) datasets with HHT results, we were able to visually detect
contraction locations in the HHT-processed uterine signals. For verification and validation purposes, when we further analyzed the delay time
between two signals, the mechanical activity (i.e., IUPC) following the electrical activity (i.e., magnetic signal) was observed. In conclusion, our
experimentations using the method introduced here revealed that there is a 75% correlation between the results obtained by HHT and IUPC data.
Conclusion: This study compared uterine contractions and changes in the intrauterine pressure with results obtained by HHT. In addition,
using IUPC data as a validation guide, we showed that the HHT approach can be used for noise removal. There is a need for time-saving
and non-subjective automatic contraction detection in the field of prenatal examination. (J Turk Ger Gynecol Assoc 2015; 16: 195-202)
Keywords: Uterine contraction, myometrium, magnetomyographic activity, Hilbert–Huang transform, empirical mode decomposition,
contraction analysis
health problem is the increase in the rate of preterm delivery, which is responsible for 75% of all deaths in newborns. In addition, preterm
delivery is associated with several cognitive and health problems in later life and enormous costs for the health system. A better understanding
of myometrial activities could help to reduce preterm deliveries and the costs associated with prematurity in the following years.
Therefore, the objective of this study was to determine whether using the Hilbert–Huang transform (HHT) to analyze the uterine contraction
data would help us gain a better insight of the myometrial activities of the human uterus during pregnancy.
Material and Methods: Uterine magnetomyographic (MMG) signals were recorded from pregnant patients at gestational ages of 32–38
weeks. The study was approved by the Human Research Advisory Board of the University of Arkansas for Medical Sciences (UAMS) and
performed after obtaining written consent from each patient. The recording of transabdominal MMG signals was conducted with the
SQUID Array for Reproductive Assessment (SARA, VSM MedTech Inc; Coquitlam, BC, Canada) system, which has 151 primary magnetic
sensors allocated approximately 3 cm apart over an area of 850 cm2. The arrangement of sensors is concave in nature and, in a similar
lateral distance, spans the maternal abdomen longitudinally from the symphysis pubis to the uterine fundus. The recording times ranged
from 12 to 28 min, and the sampling rate was 250 Hz. The data were down-sampled to 25 Hz to reduce the computational complexity
and post-processed with a bandpass filter (0.05–1 Hz) because the uterine contraction activity is a band-limited process (0.05–1 Hz). The
recordings of one intrauterine pressure catheter (IUPC) dataset and two mother-perceived contraction datasets were compared with the
HHT results, and HHT’s potential was explored through the development of a module and a series of experiments. The local energy and
the instantaneous frequency derived from the intrinsic mode functions (IMFs) through HHT provide a full energy-frequency-time distribution
of the data. Our objective was to determine whether HHT for each channel can help identify and localize contractions in the uterus.
Human studies have been reviewed by the appropriate ethics committee and have therefore been performed in accordance with the
ethical standards described in an appropriate version of the 1975 Declaration of Helsinki, as revised in 2000.
Results: After comparing the IUPC and other mother-perceived contraction (STIM) datasets with HHT results, we were able to visually detect
contraction locations in the HHT-processed uterine signals. For verification and validation purposes, when we further analyzed the delay time
between two signals, the mechanical activity (i.e., IUPC) following the electrical activity (i.e., magnetic signal) was observed. In conclusion, our
experimentations using the method introduced here revealed that there is a 75% correlation between the results obtained by HHT and IUPC data.
Conclusion: This study compared uterine contractions and changes in the intrauterine pressure with results obtained by HHT. In addition,
using IUPC data as a validation guide, we showed that the HHT approach can be used for noise removal. There is a need for time-saving
and non-subjective automatic contraction detection in the field of prenatal examination. (J Turk Ger Gynecol Assoc 2015; 16: 195-202)
Keywords: Uterine contraction, myometrium, magnetomyographic activity, Hilbert–Huang transform, empirical mode decomposition,
contraction analysis