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You searched for publisher:("New Jersey Institute of Technology"). Showing records 1 – 30 of 3072 total matches.

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New Jersey Institute of Technology

1. Wang, Xiaolu. Silicon-germanium nanowire heterojunctions: Optical and electrical properties.

Degree: PhD, Electrical and Computer Engineering, 2016, New Jersey Institute of Technology

  Semiconductor nanowires are quasi-one-dimensional objects with unique physical properties and strong potential in nanophotonics, nanoelectronics, biosensing, and solar cell devices. The next challenge in… (more)

Subjects/Keywords: Nanowire; Heterojunction; Silicon-germanium; Strain; Electrical; Noise; Electrical and Electronics

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APA (6th Edition):

Wang, X. (2016). Silicon-germanium nanowire heterojunctions: Optical and electrical properties. (Doctoral Dissertation). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/dissertations/3

Chicago Manual of Style (16th Edition):

Wang, Xiaolu. “Silicon-germanium nanowire heterojunctions: Optical and electrical properties.” 2016. Doctoral Dissertation, New Jersey Institute of Technology. Accessed September 15, 2019. https://digitalcommons.njit.edu/dissertations/3.

MLA Handbook (7th Edition):

Wang, Xiaolu. “Silicon-germanium nanowire heterojunctions: Optical and electrical properties.” 2016. Web. 15 Sep 2019.

Vancouver:

Wang X. Silicon-germanium nanowire heterojunctions: Optical and electrical properties. [Internet] [Doctoral dissertation]. New Jersey Institute of Technology; 2016. [cited 2019 Sep 15]. Available from: https://digitalcommons.njit.edu/dissertations/3.

Council of Science Editors:

Wang X. Silicon-germanium nanowire heterojunctions: Optical and electrical properties. [Doctoral Dissertation]. New Jersey Institute of Technology; 2016. Available from: https://digitalcommons.njit.edu/dissertations/3


New Jersey Institute of Technology

2. Salloum, Dalia. Regulation of voltage-gated K+ currents in motor neurons: activity-dependence and neuromodulation.

Degree: PhD, Federated Department of Biological Sciences, 2016, New Jersey Institute of Technology

  Neuronal output is shaped by extrinsic modulation as well as modulation of intrinsic properties of individual neurons, mediated by activity-dependent changes in the expression… (more)

Subjects/Keywords: Neuronal excitability; Neuromodulation; K+ channels; Motor neurons; CPG; Activity dependent; Biology

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APA (6th Edition):

Salloum, D. (2016). Regulation of voltage-gated K+ currents in motor neurons: activity-dependence and neuromodulation. (Doctoral Dissertation). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/dissertations/5

Chicago Manual of Style (16th Edition):

Salloum, Dalia. “Regulation of voltage-gated K+ currents in motor neurons: activity-dependence and neuromodulation.” 2016. Doctoral Dissertation, New Jersey Institute of Technology. Accessed September 15, 2019. https://digitalcommons.njit.edu/dissertations/5.

MLA Handbook (7th Edition):

Salloum, Dalia. “Regulation of voltage-gated K+ currents in motor neurons: activity-dependence and neuromodulation.” 2016. Web. 15 Sep 2019.

Vancouver:

Salloum D. Regulation of voltage-gated K+ currents in motor neurons: activity-dependence and neuromodulation. [Internet] [Doctoral dissertation]. New Jersey Institute of Technology; 2016. [cited 2019 Sep 15]. Available from: https://digitalcommons.njit.edu/dissertations/5.

Council of Science Editors:

Salloum D. Regulation of voltage-gated K+ currents in motor neurons: activity-dependence and neuromodulation. [Doctoral Dissertation]. New Jersey Institute of Technology; 2016. Available from: https://digitalcommons.njit.edu/dissertations/5


New Jersey Institute of Technology

3. Zhang, Bo. Aerosol transport by coughing in a depressurized and air-conditioned chamber.

Degree: PhD, Mechanical and Industrial Engineering, 2016, New Jersey Institute of Technology

  Expiratory droplets from human coughing in an air-conditioned environment have always been considered to be potential carriers of pathogens, responsible for respiratory disease transmission.… (more)

Subjects/Keywords: Aerosol; Cough; CFD; Depressurization; Experiment; Parametric model; Mechanical Engineering

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APA (6th Edition):

Zhang, B. (2016). Aerosol transport by coughing in a depressurized and air-conditioned chamber. (Doctoral Dissertation). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/dissertations/6

Chicago Manual of Style (16th Edition):

Zhang, Bo. “Aerosol transport by coughing in a depressurized and air-conditioned chamber.” 2016. Doctoral Dissertation, New Jersey Institute of Technology. Accessed September 15, 2019. https://digitalcommons.njit.edu/dissertations/6.

MLA Handbook (7th Edition):

Zhang, Bo. “Aerosol transport by coughing in a depressurized and air-conditioned chamber.” 2016. Web. 15 Sep 2019.

Vancouver:

Zhang B. Aerosol transport by coughing in a depressurized and air-conditioned chamber. [Internet] [Doctoral dissertation]. New Jersey Institute of Technology; 2016. [cited 2019 Sep 15]. Available from: https://digitalcommons.njit.edu/dissertations/6.

Council of Science Editors:

Zhang B. Aerosol transport by coughing in a depressurized and air-conditioned chamber. [Doctoral Dissertation]. New Jersey Institute of Technology; 2016. Available from: https://digitalcommons.njit.edu/dissertations/6


New Jersey Institute of Technology

4. Pan, Haijun. A novel e-voting system with diverse security features.

Degree: PhD, Electrical and Computer Engineering, 2016, New Jersey Institute of Technology

  Internet-based E-voting systems can offer great benefits over traditional voting machines in areas, such as protecting voter and candidate privacy, providing accurate vote counting,… (more)

Subjects/Keywords: E-voting; Election; Voter fraud; Voter verification; Security; Cryptography; Electrical and Electronics

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APA (6th Edition):

Pan, H. (2016). A novel e-voting system with diverse security features. (Doctoral Dissertation). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/dissertations/8

Chicago Manual of Style (16th Edition):

Pan, Haijun. “A novel e-voting system with diverse security features.” 2016. Doctoral Dissertation, New Jersey Institute of Technology. Accessed September 15, 2019. https://digitalcommons.njit.edu/dissertations/8.

MLA Handbook (7th Edition):

Pan, Haijun. “A novel e-voting system with diverse security features.” 2016. Web. 15 Sep 2019.

Vancouver:

Pan H. A novel e-voting system with diverse security features. [Internet] [Doctoral dissertation]. New Jersey Institute of Technology; 2016. [cited 2019 Sep 15]. Available from: https://digitalcommons.njit.edu/dissertations/8.

Council of Science Editors:

Pan H. A novel e-voting system with diverse security features. [Doctoral Dissertation]. New Jersey Institute of Technology; 2016. Available from: https://digitalcommons.njit.edu/dissertations/8


New Jersey Institute of Technology

5. Xu, Guanshuo. Machine learning based digital image forensics and steganalysis.

Degree: PhD, Electrical and Computer Engineering, 2016, New Jersey Institute of Technology

  The security and trustworthiness of digital images have become crucial issues due to the simplicity of malicious processing. Therefore, the research on image steganalysis… (more)

Subjects/Keywords: Convolution neural networks; Deep learning; Steganalysis; Camera model identification; Tampering detection; Electrical and Electronics

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APA (6th Edition):

Xu, G. (2016). Machine learning based digital image forensics and steganalysis. (Doctoral Dissertation). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/dissertations/10

Chicago Manual of Style (16th Edition):

Xu, Guanshuo. “Machine learning based digital image forensics and steganalysis.” 2016. Doctoral Dissertation, New Jersey Institute of Technology. Accessed September 15, 2019. https://digitalcommons.njit.edu/dissertations/10.

MLA Handbook (7th Edition):

Xu, Guanshuo. “Machine learning based digital image forensics and steganalysis.” 2016. Web. 15 Sep 2019.

Vancouver:

Xu G. Machine learning based digital image forensics and steganalysis. [Internet] [Doctoral dissertation]. New Jersey Institute of Technology; 2016. [cited 2019 Sep 15]. Available from: https://digitalcommons.njit.edu/dissertations/10.

Council of Science Editors:

Xu G. Machine learning based digital image forensics and steganalysis. [Doctoral Dissertation]. New Jersey Institute of Technology; 2016. Available from: https://digitalcommons.njit.edu/dissertations/10


New Jersey Institute of Technology

6. Kim, Haley H. Sparsity based methods for target localization in multi-sensor radar.

Degree: PhD, Electrical and Computer Engineering, 2016, New Jersey Institute of Technology

  In this dissertation, several sparsity-based methods for ground moving target indicator (GMTI) radar with multiple-input multiple-output (MIMO) random arrays are proposed. MIMO random arrays… (more)

Subjects/Keywords: Compressive sensing; GMTI; MIMO; CFAR; Interference cancellation; Random arrays; Electrical and Electronics

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APA (6th Edition):

Kim, H. H. (2016). Sparsity based methods for target localization in multi-sensor radar. (Doctoral Dissertation). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/dissertations/11

Chicago Manual of Style (16th Edition):

Kim, Haley H. “Sparsity based methods for target localization in multi-sensor radar.” 2016. Doctoral Dissertation, New Jersey Institute of Technology. Accessed September 15, 2019. https://digitalcommons.njit.edu/dissertations/11.

MLA Handbook (7th Edition):

Kim, Haley H. “Sparsity based methods for target localization in multi-sensor radar.” 2016. Web. 15 Sep 2019.

Vancouver:

Kim HH. Sparsity based methods for target localization in multi-sensor radar. [Internet] [Doctoral dissertation]. New Jersey Institute of Technology; 2016. [cited 2019 Sep 15]. Available from: https://digitalcommons.njit.edu/dissertations/11.

Council of Science Editors:

Kim HH. Sparsity based methods for target localization in multi-sensor radar. [Doctoral Dissertation]. New Jersey Institute of Technology; 2016. Available from: https://digitalcommons.njit.edu/dissertations/11


New Jersey Institute of Technology

7. Hoseini, Babak. Appointment planning and scheduling in primary care.

Degree: PhD, Mechanical and Industrial Engineering, 2016, New Jersey Institute of Technology

  The Affordable Care Act (ACA) puts greater emphasis on disease prevention and better quality of care; as a result, primary care is becoming a… (more)

Subjects/Keywords: Healthcare systems; Overbooking; Stochastic scheduling; Newsvendor; Appointment planning; Joint pannel optimization; Industrial Engineering

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APA (6th Edition):

Hoseini, B. (2016). Appointment planning and scheduling in primary care. (Doctoral Dissertation). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/dissertations/12

Chicago Manual of Style (16th Edition):

Hoseini, Babak. “Appointment planning and scheduling in primary care.” 2016. Doctoral Dissertation, New Jersey Institute of Technology. Accessed September 15, 2019. https://digitalcommons.njit.edu/dissertations/12.

MLA Handbook (7th Edition):

Hoseini, Babak. “Appointment planning and scheduling in primary care.” 2016. Web. 15 Sep 2019.

Vancouver:

Hoseini B. Appointment planning and scheduling in primary care. [Internet] [Doctoral dissertation]. New Jersey Institute of Technology; 2016. [cited 2019 Sep 15]. Available from: https://digitalcommons.njit.edu/dissertations/12.

Council of Science Editors:

Hoseini B. Appointment planning and scheduling in primary care. [Doctoral Dissertation]. New Jersey Institute of Technology; 2016. Available from: https://digitalcommons.njit.edu/dissertations/12


New Jersey Institute of Technology

8. Jelis, Elias. Development of low alloy steel by direct metal laser sintering.

Degree: PhD, Committee for the Interdisciplinary Program in Materials Science and Engineering, 2016, New Jersey Institute of Technology

  The US Department of Defense is interested in developing, understanding, and optimizing process parameters for low alloy (4340/4140 steel) for the powder bed fusion… (more)

Subjects/Keywords: Laser; Powder; Sintering; Steel; Metal; Additive manufacturing; Materials Science and Engineering

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APA (6th Edition):

Jelis, E. (2016). Development of low alloy steel by direct metal laser sintering. (Doctoral Dissertation). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/dissertations/13

Chicago Manual of Style (16th Edition):

Jelis, Elias. “Development of low alloy steel by direct metal laser sintering.” 2016. Doctoral Dissertation, New Jersey Institute of Technology. Accessed September 15, 2019. https://digitalcommons.njit.edu/dissertations/13.

MLA Handbook (7th Edition):

Jelis, Elias. “Development of low alloy steel by direct metal laser sintering.” 2016. Web. 15 Sep 2019.

Vancouver:

Jelis E. Development of low alloy steel by direct metal laser sintering. [Internet] [Doctoral dissertation]. New Jersey Institute of Technology; 2016. [cited 2019 Sep 15]. Available from: https://digitalcommons.njit.edu/dissertations/13.

Council of Science Editors:

Jelis E. Development of low alloy steel by direct metal laser sintering. [Doctoral Dissertation]. New Jersey Institute of Technology; 2016. Available from: https://digitalcommons.njit.edu/dissertations/13


New Jersey Institute of Technology

9. Mema, Ensela. Mathematical models for polymer-nematic interactions.

Degree: PhD, Mathematical Sciences, 2016, New Jersey Institute of Technology

  This dissertation considers a mathematical model that consists of a nematic liquid crystal layer sandwiched between two parallel bounding plates, across which an external… (more)

Subjects/Keywords: Nematic liquid crystals; Mathematical models; Director gliding; Mathematics

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APA (6th Edition):

Mema, E. (2016). Mathematical models for polymer-nematic interactions. (Doctoral Dissertation). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/dissertations/15

Chicago Manual of Style (16th Edition):

Mema, Ensela. “Mathematical models for polymer-nematic interactions.” 2016. Doctoral Dissertation, New Jersey Institute of Technology. Accessed September 15, 2019. https://digitalcommons.njit.edu/dissertations/15.

MLA Handbook (7th Edition):

Mema, Ensela. “Mathematical models for polymer-nematic interactions.” 2016. Web. 15 Sep 2019.

Vancouver:

Mema E. Mathematical models for polymer-nematic interactions. [Internet] [Doctoral dissertation]. New Jersey Institute of Technology; 2016. [cited 2019 Sep 15]. Available from: https://digitalcommons.njit.edu/dissertations/15.

Council of Science Editors:

Mema E. Mathematical models for polymer-nematic interactions. [Doctoral Dissertation]. New Jersey Institute of Technology; 2016. Available from: https://digitalcommons.njit.edu/dissertations/15


New Jersey Institute of Technology

10. Byron, Kevin. Big data analytics in computational biology and bioinformatics.

Degree: PhD, Computer Science, 2017, New Jersey Institute of Technology

  Big data analytics in computational biology and bioinformatics refers to an array of operations including biological pattern discovery, classification, prediction, inference, clustering as well… (more)

Subjects/Keywords: Gene regulatory network; Reverse engineering; Data mining; Noncoding rna; Big data; Pattern discovery; Computer Sciences

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APA (6th Edition):

Byron, K. (2017). Big data analytics in computational biology and bioinformatics. (Doctoral Dissertation). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/dissertations/17

Chicago Manual of Style (16th Edition):

Byron, Kevin. “Big data analytics in computational biology and bioinformatics.” 2017. Doctoral Dissertation, New Jersey Institute of Technology. Accessed September 15, 2019. https://digitalcommons.njit.edu/dissertations/17.

MLA Handbook (7th Edition):

Byron, Kevin. “Big data analytics in computational biology and bioinformatics.” 2017. Web. 15 Sep 2019.

Vancouver:

Byron K. Big data analytics in computational biology and bioinformatics. [Internet] [Doctoral dissertation]. New Jersey Institute of Technology; 2017. [cited 2019 Sep 15]. Available from: https://digitalcommons.njit.edu/dissertations/17.

Council of Science Editors:

Byron K. Big data analytics in computational biology and bioinformatics. [Doctoral Dissertation]. New Jersey Institute of Technology; 2017. Available from: https://digitalcommons.njit.edu/dissertations/17


New Jersey Institute of Technology

11. Khayati, Khoosheh. Regulation of mTORC1 by homocysteine and its effects on autophagy in human and mouse neuronal tissues.

Degree: PhD, Federated Department of Biological Sciences, 2017, New Jersey Institute of Technology

  The molecular mechanisms leading to and responsible for age-related, sporadic Alzheimer’s disease (AD) remain largely unknown. It is well documented that aging patients with… (more)

Subjects/Keywords: Metabolism; Lysosomal clearance; Autophagy; Alzheimer's disease; Homocysteine; mTOR signaling; Biology

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APA (6th Edition):

Khayati, K. (2017). Regulation of mTORC1 by homocysteine and its effects on autophagy in human and mouse neuronal tissues. (Doctoral Dissertation). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/dissertations/19

Chicago Manual of Style (16th Edition):

Khayati, Khoosheh. “Regulation of mTORC1 by homocysteine and its effects on autophagy in human and mouse neuronal tissues.” 2017. Doctoral Dissertation, New Jersey Institute of Technology. Accessed September 15, 2019. https://digitalcommons.njit.edu/dissertations/19.

MLA Handbook (7th Edition):

Khayati, Khoosheh. “Regulation of mTORC1 by homocysteine and its effects on autophagy in human and mouse neuronal tissues.” 2017. Web. 15 Sep 2019.

Vancouver:

Khayati K. Regulation of mTORC1 by homocysteine and its effects on autophagy in human and mouse neuronal tissues. [Internet] [Doctoral dissertation]. New Jersey Institute of Technology; 2017. [cited 2019 Sep 15]. Available from: https://digitalcommons.njit.edu/dissertations/19.

Council of Science Editors:

Khayati K. Regulation of mTORC1 by homocysteine and its effects on autophagy in human and mouse neuronal tissues. [Doctoral Dissertation]. New Jersey Institute of Technology; 2017. Available from: https://digitalcommons.njit.edu/dissertations/19


New Jersey Institute of Technology

12. Liu, Qingfeng. Investigation of new learning methods for visual recognition.

Degree: PhD, Computer Science, 2017, New Jersey Institute of Technology

  Visual recognition is one of the most difficult and prevailing problems in computer vision and pattern recognition due to the challenges in understanding the… (more)

Subjects/Keywords: Visual recognition; Sparse representation; Metric learning; Classification; Kinship verification; Deep learning; Computer Sciences

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APA (6th Edition):

Liu, Q. (2017). Investigation of new learning methods for visual recognition. (Doctoral Dissertation). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/dissertations/20

Chicago Manual of Style (16th Edition):

Liu, Qingfeng. “Investigation of new learning methods for visual recognition.” 2017. Doctoral Dissertation, New Jersey Institute of Technology. Accessed September 15, 2019. https://digitalcommons.njit.edu/dissertations/20.

MLA Handbook (7th Edition):

Liu, Qingfeng. “Investigation of new learning methods for visual recognition.” 2017. Web. 15 Sep 2019.

Vancouver:

Liu Q. Investigation of new learning methods for visual recognition. [Internet] [Doctoral dissertation]. New Jersey Institute of Technology; 2017. [cited 2019 Sep 15]. Available from: https://digitalcommons.njit.edu/dissertations/20.

Council of Science Editors:

Liu Q. Investigation of new learning methods for visual recognition. [Doctoral Dissertation]. New Jersey Institute of Technology; 2017. Available from: https://digitalcommons.njit.edu/dissertations/20


New Jersey Institute of Technology

13. Onal, Sevilay. Design and optimization of an explosive storage policy in internet fulfillment warehouses.

Degree: PhD, Mechanical and Industrial Engineering, 2017, New Jersey Institute of Technology

  This research investigates the warehousing operations of internet retailers. The primary physical process in internet retail is fulfillment, which typically involves a large internet… (more)

Subjects/Keywords: Supply chain; Internet fulfillment; E-commerce; Explosive storage; Warehouse optimization; Seed algorithm; Industrial Engineering

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APA (6th Edition):

Onal, S. (2017). Design and optimization of an explosive storage policy in internet fulfillment warehouses. (Doctoral Dissertation). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/dissertations/21

Chicago Manual of Style (16th Edition):

Onal, Sevilay. “Design and optimization of an explosive storage policy in internet fulfillment warehouses.” 2017. Doctoral Dissertation, New Jersey Institute of Technology. Accessed September 15, 2019. https://digitalcommons.njit.edu/dissertations/21.

MLA Handbook (7th Edition):

Onal, Sevilay. “Design and optimization of an explosive storage policy in internet fulfillment warehouses.” 2017. Web. 15 Sep 2019.

Vancouver:

Onal S. Design and optimization of an explosive storage policy in internet fulfillment warehouses. [Internet] [Doctoral dissertation]. New Jersey Institute of Technology; 2017. [cited 2019 Sep 15]. Available from: https://digitalcommons.njit.edu/dissertations/21.

Council of Science Editors:

Onal S. Design and optimization of an explosive storage policy in internet fulfillment warehouses. [Doctoral Dissertation]. New Jersey Institute of Technology; 2017. Available from: https://digitalcommons.njit.edu/dissertations/21


New Jersey Institute of Technology

14. Huang, Xueqing. The design and optimization of cooperative mobile edge.

Degree: PhD, Electrical and Computer Engineering, 2017, New Jersey Institute of Technology

  As the world is charging towards the Internet of Things (IoT) era, an enormous amount of sensors will be rapidly empowered with internet connectivity.… (more)

Subjects/Keywords: Wireless communications and networking; Resource allocation and management; Cooperation data transmission; Renewable energy sharing; Mobile edge computing; Efficiencey and security; Electrical and Electronics

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APA (6th Edition):

Huang, X. (2017). The design and optimization of cooperative mobile edge. (Doctoral Dissertation). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/dissertations/22

Chicago Manual of Style (16th Edition):

Huang, Xueqing. “The design and optimization of cooperative mobile edge.” 2017. Doctoral Dissertation, New Jersey Institute of Technology. Accessed September 15, 2019. https://digitalcommons.njit.edu/dissertations/22.

MLA Handbook (7th Edition):

Huang, Xueqing. “The design and optimization of cooperative mobile edge.” 2017. Web. 15 Sep 2019.

Vancouver:

Huang X. The design and optimization of cooperative mobile edge. [Internet] [Doctoral dissertation]. New Jersey Institute of Technology; 2017. [cited 2019 Sep 15]. Available from: https://digitalcommons.njit.edu/dissertations/22.

Council of Science Editors:

Huang X. The design and optimization of cooperative mobile edge. [Doctoral Dissertation]. New Jersey Institute of Technology; 2017. Available from: https://digitalcommons.njit.edu/dissertations/22


New Jersey Institute of Technology

15. Rahman, Aminur. Qualitative modeling of chaotic logical circuits and walking droplets: a dynamical systems approach.

Degree: PhD, Mathematical Sciences, 2017, New Jersey Institute of Technology

  Logical circuits and wave-particle duality have been studied for most of the 20th century. During the current century scientists have been thinking differently about… (more)

Subjects/Keywords: Dynamical systems; Nonlinear dynamics; Electronics; Chaos; Difference equations; Fluid dynamics; Mathematics

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APA (6th Edition):

Rahman, A. (2017). Qualitative modeling of chaotic logical circuits and walking droplets: a dynamical systems approach. (Doctoral Dissertation). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/dissertations/23

Chicago Manual of Style (16th Edition):

Rahman, Aminur. “Qualitative modeling of chaotic logical circuits and walking droplets: a dynamical systems approach.” 2017. Doctoral Dissertation, New Jersey Institute of Technology. Accessed September 15, 2019. https://digitalcommons.njit.edu/dissertations/23.

MLA Handbook (7th Edition):

Rahman, Aminur. “Qualitative modeling of chaotic logical circuits and walking droplets: a dynamical systems approach.” 2017. Web. 15 Sep 2019.

Vancouver:

Rahman A. Qualitative modeling of chaotic logical circuits and walking droplets: a dynamical systems approach. [Internet] [Doctoral dissertation]. New Jersey Institute of Technology; 2017. [cited 2019 Sep 15]. Available from: https://digitalcommons.njit.edu/dissertations/23.

Council of Science Editors:

Rahman A. Qualitative modeling of chaotic logical circuits and walking droplets: a dynamical systems approach. [Doctoral Dissertation]. New Jersey Institute of Technology; 2017. Available from: https://digitalcommons.njit.edu/dissertations/23


New Jersey Institute of Technology

16. Sanaei, Pejman. Mathematical modeling of membrane filtration.

Degree: PhD, Mathematical Sciences, 2017, New Jersey Institute of Technology

  The purpose of this thesis is to formulate and investigate new mathematical models for membrane filtration. The work presented is divided into six chapters.… (more)

Subjects/Keywords: Modeling; Filtration; Low Reynolds number; Porous media; Suspensions; Fluid mechanics; Mathematics

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APA (6th Edition):

Sanaei, P. (2017). Mathematical modeling of membrane filtration. (Doctoral Dissertation). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/dissertations/24

Chicago Manual of Style (16th Edition):

Sanaei, Pejman. “Mathematical modeling of membrane filtration.” 2017. Doctoral Dissertation, New Jersey Institute of Technology. Accessed September 15, 2019. https://digitalcommons.njit.edu/dissertations/24.

MLA Handbook (7th Edition):

Sanaei, Pejman. “Mathematical modeling of membrane filtration.” 2017. Web. 15 Sep 2019.

Vancouver:

Sanaei P. Mathematical modeling of membrane filtration. [Internet] [Doctoral dissertation]. New Jersey Institute of Technology; 2017. [cited 2019 Sep 15]. Available from: https://digitalcommons.njit.edu/dissertations/24.

Council of Science Editors:

Sanaei P. Mathematical modeling of membrane filtration. [Doctoral Dissertation]. New Jersey Institute of Technology; 2017. Available from: https://digitalcommons.njit.edu/dissertations/24


New Jersey Institute of Technology

17. Shah, Kinnari. Field induced assembly of particulate systems.

Degree: PhD, Mechanical and Industrial Engineering, 2016, New Jersey Institute of Technology

  The primary focus of the first part of this dissertation is to study the AC field-driven assembly of monodisperse silica and glass particles on… (more)

Subjects/Keywords: Self-assembly; Dielectophoresis; Droplet; Lab-on chip; Air-liquid interface; Transmission probability; Mechanical Engineering

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APA (6th Edition):

Shah, K. (2016). Field induced assembly of particulate systems. (Doctoral Dissertation). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/dissertations/25

Chicago Manual of Style (16th Edition):

Shah, Kinnari. “Field induced assembly of particulate systems.” 2016. Doctoral Dissertation, New Jersey Institute of Technology. Accessed September 15, 2019. https://digitalcommons.njit.edu/dissertations/25.

MLA Handbook (7th Edition):

Shah, Kinnari. “Field induced assembly of particulate systems.” 2016. Web. 15 Sep 2019.

Vancouver:

Shah K. Field induced assembly of particulate systems. [Internet] [Doctoral dissertation]. New Jersey Institute of Technology; 2016. [cited 2019 Sep 15]. Available from: https://digitalcommons.njit.edu/dissertations/25.

Council of Science Editors:

Shah K. Field induced assembly of particulate systems. [Doctoral Dissertation]. New Jersey Institute of Technology; 2016. Available from: https://digitalcommons.njit.edu/dissertations/25


New Jersey Institute of Technology

18. Turki, Turki Talal. Development and evaluation of machine learning algorithms for biomedical applications.

Degree: PhD, Computer Science, 2017, New Jersey Institute of Technology

  Gene network inference and drug response prediction are two important problems in computational biomedicine. The former helps scientists better understand the functional elements and… (more)

Subjects/Keywords: Machine learning; Data mining; Medical informatics; Bioinformatics; Systems biology; Precision medicine; Computer Sciences

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APA (6th Edition):

Turki, T. T. (2017). Development and evaluation of machine learning algorithms for biomedical applications. (Doctoral Dissertation). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/dissertations/26

Chicago Manual of Style (16th Edition):

Turki, Turki Talal. “Development and evaluation of machine learning algorithms for biomedical applications.” 2017. Doctoral Dissertation, New Jersey Institute of Technology. Accessed September 15, 2019. https://digitalcommons.njit.edu/dissertations/26.

MLA Handbook (7th Edition):

Turki, Turki Talal. “Development and evaluation of machine learning algorithms for biomedical applications.” 2017. Web. 15 Sep 2019.

Vancouver:

Turki TT. Development and evaluation of machine learning algorithms for biomedical applications. [Internet] [Doctoral dissertation]. New Jersey Institute of Technology; 2017. [cited 2019 Sep 15]. Available from: https://digitalcommons.njit.edu/dissertations/26.

Council of Science Editors:

Turki TT. Development and evaluation of machine learning algorithms for biomedical applications. [Doctoral Dissertation]. New Jersey Institute of Technology; 2017. Available from: https://digitalcommons.njit.edu/dissertations/26


New Jersey Institute of Technology

19. Wang, Chong. Viewability prediction for display advertising.

Degree: PhD, Information Systems, 2017, New Jersey Institute of Technology

  As a massive industry, display advertising delivers advertisers’ marketing messages to attract customers through graphic banners on webpages. Display advertising is also the most… (more)

Subjects/Keywords: Ad viewability; Machine learning; Computational advertising; Deep learning; Predictive models; User behavior; Databases and Information Systems; Management Information Systems

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APA (6th Edition):

Wang, C. (2017). Viewability prediction for display advertising. (Doctoral Dissertation). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/dissertations/27

Chicago Manual of Style (16th Edition):

Wang, Chong. “Viewability prediction for display advertising.” 2017. Doctoral Dissertation, New Jersey Institute of Technology. Accessed September 15, 2019. https://digitalcommons.njit.edu/dissertations/27.

MLA Handbook (7th Edition):

Wang, Chong. “Viewability prediction for display advertising.” 2017. Web. 15 Sep 2019.

Vancouver:

Wang C. Viewability prediction for display advertising. [Internet] [Doctoral dissertation]. New Jersey Institute of Technology; 2017. [cited 2019 Sep 15]. Available from: https://digitalcommons.njit.edu/dissertations/27.

Council of Science Editors:

Wang C. Viewability prediction for display advertising. [Doctoral Dissertation]. New Jersey Institute of Technology; 2017. Available from: https://digitalcommons.njit.edu/dissertations/27


New Jersey Institute of Technology

20. Ye, Jingyu. Forensic research on detecting seam carving in digital images.

Degree: PhD, Electrical and Computer Engineering, 2017, New Jersey Institute of Technology

  Digital images have been playing an important role in our daily life for the last several decades. Naturally, image editing technologies have been tremendously… (more)

Subjects/Keywords: Digital image forensics; Seam carving detection; Support vector machine; Deep learning; Convolution neural network; Electrical and Electronics

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APA (6th Edition):

Ye, J. (2017). Forensic research on detecting seam carving in digital images. (Doctoral Dissertation). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/dissertations/28

Chicago Manual of Style (16th Edition):

Ye, Jingyu. “Forensic research on detecting seam carving in digital images.” 2017. Doctoral Dissertation, New Jersey Institute of Technology. Accessed September 15, 2019. https://digitalcommons.njit.edu/dissertations/28.

MLA Handbook (7th Edition):

Ye, Jingyu. “Forensic research on detecting seam carving in digital images.” 2017. Web. 15 Sep 2019.

Vancouver:

Ye J. Forensic research on detecting seam carving in digital images. [Internet] [Doctoral dissertation]. New Jersey Institute of Technology; 2017. [cited 2019 Sep 15]. Available from: https://digitalcommons.njit.edu/dissertations/28.

Council of Science Editors:

Ye J. Forensic research on detecting seam carving in digital images. [Doctoral Dissertation]. New Jersey Institute of Technology; 2017. Available from: https://digitalcommons.njit.edu/dissertations/28


New Jersey Institute of Technology

21. Zhang, Jie. Statistical learning methods for mining marketing and biological data.

Degree: PhD, Computer Science, 2017, New Jersey Institute of Technology

  Nowadays, the value of data has been broadly recognized and emphasized. More and more decisions are made based on data and analysis rather than… (more)

Subjects/Keywords: Change-point detection; Gender prediction; Sparse time series analysis; Multi-task learning; Empirical Bayes method; Data mining; Computer Sciences

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APA (6th Edition):

Zhang, J. (2017). Statistical learning methods for mining marketing and biological data. (Doctoral Dissertation). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/dissertations/29

Chicago Manual of Style (16th Edition):

Zhang, Jie. “Statistical learning methods for mining marketing and biological data.” 2017. Doctoral Dissertation, New Jersey Institute of Technology. Accessed September 15, 2019. https://digitalcommons.njit.edu/dissertations/29.

MLA Handbook (7th Edition):

Zhang, Jie. “Statistical learning methods for mining marketing and biological data.” 2017. Web. 15 Sep 2019.

Vancouver:

Zhang J. Statistical learning methods for mining marketing and biological data. [Internet] [Doctoral dissertation]. New Jersey Institute of Technology; 2017. [cited 2019 Sep 15]. Available from: https://digitalcommons.njit.edu/dissertations/29.

Council of Science Editors:

Zhang J. Statistical learning methods for mining marketing and biological data. [Doctoral Dissertation]. New Jersey Institute of Technology; 2017. Available from: https://digitalcommons.njit.edu/dissertations/29


New Jersey Institute of Technology

22. Musunuri, Naga Aditya. Study on the dispersion of particles at a fluid-liquid interface and its application in hydrophilous pollination.

Degree: PhD, Mechanical and Industrial Engineering, 2017, New Jersey Institute of Technology

  This dissertation work describes the physics of particle adsorption and the spontaneous dispersion of powders that occurs when they come in contact with a… (more)

Subjects/Keywords: Surface tension; Hydrophily; Ruppia Maritima; Adsorption; Particle image velocimetry; Mechanical Engineering

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APA (6th Edition):

Musunuri, N. A. (2017). Study on the dispersion of particles at a fluid-liquid interface and its application in hydrophilous pollination. (Doctoral Dissertation). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/dissertations/31

Chicago Manual of Style (16th Edition):

Musunuri, Naga Aditya. “Study on the dispersion of particles at a fluid-liquid interface and its application in hydrophilous pollination.” 2017. Doctoral Dissertation, New Jersey Institute of Technology. Accessed September 15, 2019. https://digitalcommons.njit.edu/dissertations/31.

MLA Handbook (7th Edition):

Musunuri, Naga Aditya. “Study on the dispersion of particles at a fluid-liquid interface and its application in hydrophilous pollination.” 2017. Web. 15 Sep 2019.

Vancouver:

Musunuri NA. Study on the dispersion of particles at a fluid-liquid interface and its application in hydrophilous pollination. [Internet] [Doctoral dissertation]. New Jersey Institute of Technology; 2017. [cited 2019 Sep 15]. Available from: https://digitalcommons.njit.edu/dissertations/31.

Council of Science Editors:

Musunuri NA. Study on the dispersion of particles at a fluid-liquid interface and its application in hydrophilous pollination. [Doctoral Dissertation]. New Jersey Institute of Technology; 2017. Available from: https://digitalcommons.njit.edu/dissertations/31


New Jersey Institute of Technology

23. Fu, Szu-Pei. Efficient coarse-grained brownian dynamics simulations for dna and lipid bilayer membrane with hydrodynamic interactions.

Degree: PhD, Mathematical Sciences, 2017, New Jersey Institute of Technology

  The coarse-grained molecular dynamics (CGMD) or Brownian dynamics (BD) simulation is a particle-based approach that has been applied to a wide range of biological… (more)

Subjects/Keywords: Metroplolis algorithm; Brownian dynamics; Fast multipole method; Coarse-grained modeling; Mathematics

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APA (6th Edition):

Fu, S. (2017). Efficient coarse-grained brownian dynamics simulations for dna and lipid bilayer membrane with hydrodynamic interactions. (Doctoral Dissertation). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/dissertations/32

Chicago Manual of Style (16th Edition):

Fu, Szu-Pei. “Efficient coarse-grained brownian dynamics simulations for dna and lipid bilayer membrane with hydrodynamic interactions.” 2017. Doctoral Dissertation, New Jersey Institute of Technology. Accessed September 15, 2019. https://digitalcommons.njit.edu/dissertations/32.

MLA Handbook (7th Edition):

Fu, Szu-Pei. “Efficient coarse-grained brownian dynamics simulations for dna and lipid bilayer membrane with hydrodynamic interactions.” 2017. Web. 15 Sep 2019.

Vancouver:

Fu S. Efficient coarse-grained brownian dynamics simulations for dna and lipid bilayer membrane with hydrodynamic interactions. [Internet] [Doctoral dissertation]. New Jersey Institute of Technology; 2017. [cited 2019 Sep 15]. Available from: https://digitalcommons.njit.edu/dissertations/32.

Council of Science Editors:

Fu S. Efficient coarse-grained brownian dynamics simulations for dna and lipid bilayer membrane with hydrodynamic interactions. [Doctoral Dissertation]. New Jersey Institute of Technology; 2017. Available from: https://digitalcommons.njit.edu/dissertations/32


New Jersey Institute of Technology

24. Al-Shuwaili, Ali. Mobile cloud computing and network function virtualization for 5g systems.

Degree: PhD, Electrical and Computer Engineering, 2017, New Jersey Institute of Technology

  The recent growth of the number of smart mobile devices and the emergence of complex multimedia mobile applications have brought new challenges to the… (more)

Subjects/Keywords: Mobile cloud computing; Fifth-generation systems; Network function virtualization; Augmented reality; Joint optimization and scheduling; Resource allocation; Electrical and Electronics

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APA (6th Edition):

Al-Shuwaili, A. (2017). Mobile cloud computing and network function virtualization for 5g systems. (Doctoral Dissertation). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/dissertations/33

Chicago Manual of Style (16th Edition):

Al-Shuwaili, Ali. “Mobile cloud computing and network function virtualization for 5g systems.” 2017. Doctoral Dissertation, New Jersey Institute of Technology. Accessed September 15, 2019. https://digitalcommons.njit.edu/dissertations/33.

MLA Handbook (7th Edition):

Al-Shuwaili, Ali. “Mobile cloud computing and network function virtualization for 5g systems.” 2017. Web. 15 Sep 2019.

Vancouver:

Al-Shuwaili A. Mobile cloud computing and network function virtualization for 5g systems. [Internet] [Doctoral dissertation]. New Jersey Institute of Technology; 2017. [cited 2019 Sep 15]. Available from: https://digitalcommons.njit.edu/dissertations/33.

Council of Science Editors:

Al-Shuwaili A. Mobile cloud computing and network function virtualization for 5g systems. [Doctoral Dissertation]. New Jersey Institute of Technology; 2017. Available from: https://digitalcommons.njit.edu/dissertations/33


New Jersey Institute of Technology

25. Arif, Tariq Mohammad. Fast estimation model of pressure-temperature response for planning focused ultrasound surgery.

Degree: PhD, Mechanical and Industrial Engineering, 2017, New Jersey Institute of Technology

  High Intensity Focused Ultrasound (HIFU) is becoming a widely accepted modality for extracorporeal non-invasive hyperthermia and surgical procedures. Since ultrasonic transducers need to operate… (more)

Subjects/Keywords: HIFU; Genetic algorithm; Optimization; Angular spectrum; Rayleigh-Sommerfeld; Ultrasound; Mechanical Engineering

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APA (6th Edition):

Arif, T. M. (2017). Fast estimation model of pressure-temperature response for planning focused ultrasound surgery. (Doctoral Dissertation). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/dissertations/34

Chicago Manual of Style (16th Edition):

Arif, Tariq Mohammad. “Fast estimation model of pressure-temperature response for planning focused ultrasound surgery.” 2017. Doctoral Dissertation, New Jersey Institute of Technology. Accessed September 15, 2019. https://digitalcommons.njit.edu/dissertations/34.

MLA Handbook (7th Edition):

Arif, Tariq Mohammad. “Fast estimation model of pressure-temperature response for planning focused ultrasound surgery.” 2017. Web. 15 Sep 2019.

Vancouver:

Arif TM. Fast estimation model of pressure-temperature response for planning focused ultrasound surgery. [Internet] [Doctoral dissertation]. New Jersey Institute of Technology; 2017. [cited 2019 Sep 15]. Available from: https://digitalcommons.njit.edu/dissertations/34.

Council of Science Editors:

Arif TM. Fast estimation model of pressure-temperature response for planning focused ultrasound surgery. [Doctoral Dissertation]. New Jersey Institute of Technology; 2017. Available from: https://digitalcommons.njit.edu/dissertations/34


New Jersey Institute of Technology

26. Kuroda, Natsuha. The analysis and the three-dimensional, forward-fit modeling of the hard x-ray and the microwave emissions of major solar flares.

Degree: PhD, Physics, 2017, New Jersey Institute of Technology

  Solar flares are one of the most violent and energetic space weather events that are known to cause various adverse effects on the Earth.… (more)

Subjects/Keywords: Solar physics; Solar flares; Hard x-ray and microwave; Space weather; Energetic particles; Observation and simulation; Other Physics

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APA (6th Edition):

Kuroda, N. (2017). The analysis and the three-dimensional, forward-fit modeling of the hard x-ray and the microwave emissions of major solar flares. (Doctoral Dissertation). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/dissertations/35

Chicago Manual of Style (16th Edition):

Kuroda, Natsuha. “The analysis and the three-dimensional, forward-fit modeling of the hard x-ray and the microwave emissions of major solar flares.” 2017. Doctoral Dissertation, New Jersey Institute of Technology. Accessed September 15, 2019. https://digitalcommons.njit.edu/dissertations/35.

MLA Handbook (7th Edition):

Kuroda, Natsuha. “The analysis and the three-dimensional, forward-fit modeling of the hard x-ray and the microwave emissions of major solar flares.” 2017. Web. 15 Sep 2019.

Vancouver:

Kuroda N. The analysis and the three-dimensional, forward-fit modeling of the hard x-ray and the microwave emissions of major solar flares. [Internet] [Doctoral dissertation]. New Jersey Institute of Technology; 2017. [cited 2019 Sep 15]. Available from: https://digitalcommons.njit.edu/dissertations/35.

Council of Science Editors:

Kuroda N. The analysis and the three-dimensional, forward-fit modeling of the hard x-ray and the microwave emissions of major solar flares. [Doctoral Dissertation]. New Jersey Institute of Technology; 2017. Available from: https://digitalcommons.njit.edu/dissertations/35


New Jersey Institute of Technology

27. Markson, Christopher R. Detecting user demographics in twitter to inform health trends in social media.

Degree: PhD, Informatics, 2017, New Jersey Institute of Technology

  The widespread and popular use of social media and social networking applications offer a promising opportunity for gaining knowledge and insights regarding population health… (more)

Subjects/Keywords: Social media; Topic extraction; Demographic extraction; Text mining; Public health; Twitter; Databases and Information Systems; Management Information Systems

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APA (6th Edition):

Markson, C. R. (2017). Detecting user demographics in twitter to inform health trends in social media. (Doctoral Dissertation). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/dissertations/36

Chicago Manual of Style (16th Edition):

Markson, Christopher R. “Detecting user demographics in twitter to inform health trends in social media.” 2017. Doctoral Dissertation, New Jersey Institute of Technology. Accessed September 15, 2019. https://digitalcommons.njit.edu/dissertations/36.

MLA Handbook (7th Edition):

Markson, Christopher R. “Detecting user demographics in twitter to inform health trends in social media.” 2017. Web. 15 Sep 2019.

Vancouver:

Markson CR. Detecting user demographics in twitter to inform health trends in social media. [Internet] [Doctoral dissertation]. New Jersey Institute of Technology; 2017. [cited 2019 Sep 15]. Available from: https://digitalcommons.njit.edu/dissertations/36.

Council of Science Editors:

Markson CR. Detecting user demographics in twitter to inform health trends in social media. [Doctoral Dissertation]. New Jersey Institute of Technology; 2017. Available from: https://digitalcommons.njit.edu/dissertations/36


New Jersey Institute of Technology

28. Qi, Haiyang. Boundary integral equation based numerical solutions of helmholtz transmission problems for composite scatters.

Degree: PhD, Mathematical Sciences, 2017, New Jersey Institute of Technology

  In this dissertation, an in-depth comparison between boundary integral equation solvers and Domain Decomposition Methods (DDM) for frequency domain Helmholtz transmission problems in composite… (more)

Subjects/Keywords: Helmholtz transmission problem; Boundary integral equation; Domain decomposition method; Mathematics

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APA (6th Edition):

Qi, H. (2017). Boundary integral equation based numerical solutions of helmholtz transmission problems for composite scatters. (Doctoral Dissertation). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/dissertations/38

Chicago Manual of Style (16th Edition):

Qi, Haiyang. “Boundary integral equation based numerical solutions of helmholtz transmission problems for composite scatters.” 2017. Doctoral Dissertation, New Jersey Institute of Technology. Accessed September 15, 2019. https://digitalcommons.njit.edu/dissertations/38.

MLA Handbook (7th Edition):

Qi, Haiyang. “Boundary integral equation based numerical solutions of helmholtz transmission problems for composite scatters.” 2017. Web. 15 Sep 2019.

Vancouver:

Qi H. Boundary integral equation based numerical solutions of helmholtz transmission problems for composite scatters. [Internet] [Doctoral dissertation]. New Jersey Institute of Technology; 2017. [cited 2019 Sep 15]. Available from: https://digitalcommons.njit.edu/dissertations/38.

Council of Science Editors:

Qi H. Boundary integral equation based numerical solutions of helmholtz transmission problems for composite scatters. [Doctoral Dissertation]. New Jersey Institute of Technology; 2017. Available from: https://digitalcommons.njit.edu/dissertations/38


New Jersey Institute of Technology

29. Seric, Ivana. Direct computations of marangoni driven flows using a volume of fluid method.

Degree: PhD, Mathematical Sciences, 2017, New Jersey Institute of Technology

  The volume of fluid (VoF) interface tracking methods have been used for simulating a wide range of interfacial flows. An improved accuracy of the… (more)

Subjects/Keywords: Marangoni flows; Surface tension; Computational Fluid Dynamics; Nanoflows; Liauid metals; Drops; Mathematics

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APA (6th Edition):

Seric, I. (2017). Direct computations of marangoni driven flows using a volume of fluid method. (Doctoral Dissertation). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/dissertations/40

Chicago Manual of Style (16th Edition):

Seric, Ivana. “Direct computations of marangoni driven flows using a volume of fluid method.” 2017. Doctoral Dissertation, New Jersey Institute of Technology. Accessed September 15, 2019. https://digitalcommons.njit.edu/dissertations/40.

MLA Handbook (7th Edition):

Seric, Ivana. “Direct computations of marangoni driven flows using a volume of fluid method.” 2017. Web. 15 Sep 2019.

Vancouver:

Seric I. Direct computations of marangoni driven flows using a volume of fluid method. [Internet] [Doctoral dissertation]. New Jersey Institute of Technology; 2017. [cited 2019 Sep 15]. Available from: https://digitalcommons.njit.edu/dissertations/40.

Council of Science Editors:

Seric I. Direct computations of marangoni driven flows using a volume of fluid method. [Doctoral Dissertation]. New Jersey Institute of Technology; 2017. Available from: https://digitalcommons.njit.edu/dissertations/40


New Jersey Institute of Technology

30. Shu, Tong. Performance optimization and energy efficiency of big-data computing workflows.

Degree: PhD, Computer Science, 2017, New Jersey Institute of Technology

  Next-generation e-science is producing colossal amounts of data, now frequently termed as Big Data, on the order of terabyte at present and petabyte or… (more)

Subjects/Keywords: Big data; Scientific workflow; Green computing; Cloud computing; Parallel computing; Map reduce; Computer Sciences

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Shu, T. (2017). Performance optimization and energy efficiency of big-data computing workflows. (Doctoral Dissertation). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/dissertations/41

Chicago Manual of Style (16th Edition):

Shu, Tong. “Performance optimization and energy efficiency of big-data computing workflows.” 2017. Doctoral Dissertation, New Jersey Institute of Technology. Accessed September 15, 2019. https://digitalcommons.njit.edu/dissertations/41.

MLA Handbook (7th Edition):

Shu, Tong. “Performance optimization and energy efficiency of big-data computing workflows.” 2017. Web. 15 Sep 2019.

Vancouver:

Shu T. Performance optimization and energy efficiency of big-data computing workflows. [Internet] [Doctoral dissertation]. New Jersey Institute of Technology; 2017. [cited 2019 Sep 15]. Available from: https://digitalcommons.njit.edu/dissertations/41.

Council of Science Editors:

Shu T. Performance optimization and energy efficiency of big-data computing workflows. [Doctoral Dissertation]. New Jersey Institute of Technology; 2017. Available from: https://digitalcommons.njit.edu/dissertations/41

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