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You searched for +publisher:"University of Cincinnati" +contributor:("Ralescu, Anca"). Showing records 1 – 27 of 27 total matches.

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University of Cincinnati

1. Musgrave, John. Cognitive Malice Representation and Identification.

Degree: MS, Engineering and Applied Science: Computer Science, 2019, University of Cincinnati

 Malice may be defined as intentional harm. In the context of a computing system, malice takes the form of various types of malware and the… (more)

Subjects/Keywords: Artificial Intelligence; AI; Security; Malware Analysis; Cognitive Architectures

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APA (6th Edition):

Musgrave, J. (2019). Cognitive Malice Representation and Identification. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1565348664149804

Chicago Manual of Style (16th Edition):

Musgrave, John. “Cognitive Malice Representation and Identification.” 2019. Masters Thesis, University of Cincinnati. Accessed October 28, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1565348664149804.

MLA Handbook (7th Edition):

Musgrave, John. “Cognitive Malice Representation and Identification.” 2019. Web. 28 Oct 2020.

Vancouver:

Musgrave J. Cognitive Malice Representation and Identification. [Internet] [Masters thesis]. University of Cincinnati; 2019. [cited 2020 Oct 28]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1565348664149804.

Council of Science Editors:

Musgrave J. Cognitive Malice Representation and Identification. [Masters Thesis]. University of Cincinnati; 2019. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1565348664149804

2. Toth, Samuel. Analyzing Binary Program Representation Through Evolution and Classification.

Degree: MS, Engineering and Applied Science: Computer Science, 2018, University of Cincinnati

 Binary Code is often represented in many different fashions- hex code, assembly, and even as '0's and '1's themselves. While this code is very useful… (more)

Subjects/Keywords: Computer Science; Genetic Algorithms; Cybersecurity; Machine learning

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APA (6th Edition):

Toth, S. (2018). Analyzing Binary Program Representation Through Evolution and Classification. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1544000100127796

Chicago Manual of Style (16th Edition):

Toth, Samuel. “Analyzing Binary Program Representation Through Evolution and Classification.” 2018. Masters Thesis, University of Cincinnati. Accessed October 28, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1544000100127796.

MLA Handbook (7th Edition):

Toth, Samuel. “Analyzing Binary Program Representation Through Evolution and Classification.” 2018. Web. 28 Oct 2020.

Vancouver:

Toth S. Analyzing Binary Program Representation Through Evolution and Classification. [Internet] [Masters thesis]. University of Cincinnati; 2018. [cited 2020 Oct 28]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1544000100127796.

Council of Science Editors:

Toth S. Analyzing Binary Program Representation Through Evolution and Classification. [Masters Thesis]. University of Cincinnati; 2018. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1544000100127796


University of Cincinnati

3. Rawashdeh, Mohammad Y. A Relational Framework for Clustering and Cluster Validity and the Generalization of the Silhouette Measure.

Degree: PhD, Engineering and Applied Science: Computer Science and Engineering, 2014, University of Cincinnati

 By clustering one seeks to partition a given set of points into a number of clusters such that points in the same cluster are similar… (more)

Subjects/Keywords: Computer Science; relational framework; silhouettes; fuzzy clustering; cluster validity; intracluster; intercluster

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APA (6th Edition):

Rawashdeh, M. Y. (2014). A Relational Framework for Clustering and Cluster Validity and the Generalization of the Silhouette Measure. (Doctoral Dissertation). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1394725536

Chicago Manual of Style (16th Edition):

Rawashdeh, Mohammad Y. “A Relational Framework for Clustering and Cluster Validity and the Generalization of the Silhouette Measure.” 2014. Doctoral Dissertation, University of Cincinnati. Accessed October 28, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1394725536.

MLA Handbook (7th Edition):

Rawashdeh, Mohammad Y. “A Relational Framework for Clustering and Cluster Validity and the Generalization of the Silhouette Measure.” 2014. Web. 28 Oct 2020.

Vancouver:

Rawashdeh MY. A Relational Framework for Clustering and Cluster Validity and the Generalization of the Silhouette Measure. [Internet] [Doctoral dissertation]. University of Cincinnati; 2014. [cited 2020 Oct 28]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1394725536.

Council of Science Editors:

Rawashdeh MY. A Relational Framework for Clustering and Cluster Validity and the Generalization of the Silhouette Measure. [Doctoral Dissertation]. University of Cincinnati; 2014. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1394725536


University of Cincinnati

4. Fang, Chunsheng. Novel Frameworks for Mining Heterogeneous and Dynamic Networks.

Degree: PhD, Engineering and Applied Science: Computer Science and Engineering, 2011, University of Cincinnati

 Graphs serve as an important tool for discrete data representation. Recently, graph representations have made possible very powerful machine learning algorithms, such as manifold learning,… (more)

Subjects/Keywords: Computer Science; machine learning; social network; data mining; manifold learning; graph embedding; dynamic graph

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APA (6th Edition):

Fang, C. (2011). Novel Frameworks for Mining Heterogeneous and Dynamic Networks. (Doctoral Dissertation). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1321369978

Chicago Manual of Style (16th Edition):

Fang, Chunsheng. “Novel Frameworks for Mining Heterogeneous and Dynamic Networks.” 2011. Doctoral Dissertation, University of Cincinnati. Accessed October 28, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1321369978.

MLA Handbook (7th Edition):

Fang, Chunsheng. “Novel Frameworks for Mining Heterogeneous and Dynamic Networks.” 2011. Web. 28 Oct 2020.

Vancouver:

Fang C. Novel Frameworks for Mining Heterogeneous and Dynamic Networks. [Internet] [Doctoral dissertation]. University of Cincinnati; 2011. [cited 2020 Oct 28]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1321369978.

Council of Science Editors:

Fang C. Novel Frameworks for Mining Heterogeneous and Dynamic Networks. [Doctoral Dissertation]. University of Cincinnati; 2011. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1321369978


University of Cincinnati

5. Wang, Mengxia. Design of a Modified P300 Speller System Based on Prediction by Partial Matching Language Model.

Degree: MS, Engineering and Applied Science: Computer Science, 2012, University of Cincinnati

 In recent decades, the field of Brain-Computer Interface (BCI) technologies has been vigorously developed by research groups from all over the world. A BCI system… (more)

Subjects/Keywords: Computer Science; Brain-computer interface; P300 speller; Prediction by partial matching language model

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APA (6th Edition):

Wang, M. (2012). Design of a Modified P300 Speller System Based on Prediction by Partial Matching Language Model. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1342464270

Chicago Manual of Style (16th Edition):

Wang, Mengxia. “Design of a Modified P300 Speller System Based on Prediction by Partial Matching Language Model.” 2012. Masters Thesis, University of Cincinnati. Accessed October 28, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1342464270.

MLA Handbook (7th Edition):

Wang, Mengxia. “Design of a Modified P300 Speller System Based on Prediction by Partial Matching Language Model.” 2012. Web. 28 Oct 2020.

Vancouver:

Wang M. Design of a Modified P300 Speller System Based on Prediction by Partial Matching Language Model. [Internet] [Masters thesis]. University of Cincinnati; 2012. [cited 2020 Oct 28]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1342464270.

Council of Science Editors:

Wang M. Design of a Modified P300 Speller System Based on Prediction by Partial Matching Language Model. [Masters Thesis]. University of Cincinnati; 2012. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1342464270


University of Cincinnati

6. Rawashdeh, Ahmad. Semantic Similarity of Node Profiles in Social Networks.

Degree: PhD, Engineering and Applied Science: Computer Science and Engineering, 2015, University of Cincinnati

 It can be said, without exaggeration, that social networks have taken a large segment of populationby a storm. Regardless of the actual geographical location, of… (more)

Subjects/Keywords: Computer Science; Social Networks; Wordnet; Semantic; Machine Learning; Link Prediction

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APA (6th Edition):

Rawashdeh, A. (2015). Semantic Similarity of Node Profiles in Social Networks. (Doctoral Dissertation). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1439279922

Chicago Manual of Style (16th Edition):

Rawashdeh, Ahmad. “Semantic Similarity of Node Profiles in Social Networks.” 2015. Doctoral Dissertation, University of Cincinnati. Accessed October 28, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1439279922.

MLA Handbook (7th Edition):

Rawashdeh, Ahmad. “Semantic Similarity of Node Profiles in Social Networks.” 2015. Web. 28 Oct 2020.

Vancouver:

Rawashdeh A. Semantic Similarity of Node Profiles in Social Networks. [Internet] [Doctoral dissertation]. University of Cincinnati; 2015. [cited 2020 Oct 28]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1439279922.

Council of Science Editors:

Rawashdeh A. Semantic Similarity of Node Profiles in Social Networks. [Doctoral Dissertation]. University of Cincinnati; 2015. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1439279922


University of Cincinnati

7. Agarwal, Akrita. Exploring the Noise Resilience of Combined Sturges Algorithm.

Degree: MS, Engineering and Applied Science: Computer Science, 2015, University of Cincinnati

 Over the years, various Classification algorithms have been developed.Two of the most popular Classification algorithms are - Naive Bayes and κnn. They are both unique… (more)

Subjects/Keywords: Computer Science; Noise Resilience; Machine Learning Algorithms; Combined Sturges; Naive Bayes; k nearest neighbor

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APA (6th Edition):

Agarwal, A. (2015). Exploring the Noise Resilience of Combined Sturges Algorithm. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1447070335

Chicago Manual of Style (16th Edition):

Agarwal, Akrita. “Exploring the Noise Resilience of Combined Sturges Algorithm.” 2015. Masters Thesis, University of Cincinnati. Accessed October 28, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1447070335.

MLA Handbook (7th Edition):

Agarwal, Akrita. “Exploring the Noise Resilience of Combined Sturges Algorithm.” 2015. Web. 28 Oct 2020.

Vancouver:

Agarwal A. Exploring the Noise Resilience of Combined Sturges Algorithm. [Internet] [Masters thesis]. University of Cincinnati; 2015. [cited 2020 Oct 28]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1447070335.

Council of Science Editors:

Agarwal A. Exploring the Noise Resilience of Combined Sturges Algorithm. [Masters Thesis]. University of Cincinnati; 2015. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1447070335


University of Cincinnati

8. Khazanova, Yekaterina. Experiments with Neural Network Libraries.

Degree: MS, Engineering and Applied Science: Computer Science, 2013, University of Cincinnati

 When solving problems using neural networks, the user/developer is usually limited by the number of neural networks he or she has already studied or descriptions… (more)

Subjects/Keywords: Artificial Intelligence

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APA (6th Edition):

Khazanova, Y. (2013). Experiments with Neural Network Libraries. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1527607591612278

Chicago Manual of Style (16th Edition):

Khazanova, Yekaterina. “Experiments with Neural Network Libraries.” 2013. Masters Thesis, University of Cincinnati. Accessed October 28, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1527607591612278.

MLA Handbook (7th Edition):

Khazanova, Yekaterina. “Experiments with Neural Network Libraries.” 2013. Web. 28 Oct 2020.

Vancouver:

Khazanova Y. Experiments with Neural Network Libraries. [Internet] [Masters thesis]. University of Cincinnati; 2013. [cited 2020 Oct 28]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1527607591612278.

Council of Science Editors:

Khazanova Y. Experiments with Neural Network Libraries. [Masters Thesis]. University of Cincinnati; 2013. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1527607591612278


University of Cincinnati

9. Al-Anssari, Jalal. Solid Vector Subtraction Operation and 3-D Gradient and Laplacian Spatial Filters of a Field of Vectors for Geometrical Edges Magnitude and Direction Detection in Point Cloud Surfaces.

Degree: PhD, Engineering and Applied Science: Computer Science and Engineering, 2020, University of Cincinnati

 Detecting geometrical edges magnitude of the surface of the point clouds is still an important problem that has a wide range of applications such as… (more)

Subjects/Keywords: Computer Engineering; solid vector subtraction; 3d gradient of a field of vector; 3d laplacian of a field of vector; geometrical edge detection; 3d spatial filters; point cloud

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APA (6th Edition):

Al-Anssari, J. (2020). Solid Vector Subtraction Operation and 3-D Gradient and Laplacian Spatial Filters of a Field of Vectors for Geometrical Edges Magnitude and Direction Detection in Point Cloud Surfaces. (Doctoral Dissertation). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin159213571577484

Chicago Manual of Style (16th Edition):

Al-Anssari, Jalal. “Solid Vector Subtraction Operation and 3-D Gradient and Laplacian Spatial Filters of a Field of Vectors for Geometrical Edges Magnitude and Direction Detection in Point Cloud Surfaces.” 2020. Doctoral Dissertation, University of Cincinnati. Accessed October 28, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin159213571577484.

MLA Handbook (7th Edition):

Al-Anssari, Jalal. “Solid Vector Subtraction Operation and 3-D Gradient and Laplacian Spatial Filters of a Field of Vectors for Geometrical Edges Magnitude and Direction Detection in Point Cloud Surfaces.” 2020. Web. 28 Oct 2020.

Vancouver:

Al-Anssari J. Solid Vector Subtraction Operation and 3-D Gradient and Laplacian Spatial Filters of a Field of Vectors for Geometrical Edges Magnitude and Direction Detection in Point Cloud Surfaces. [Internet] [Doctoral dissertation]. University of Cincinnati; 2020. [cited 2020 Oct 28]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin159213571577484.

Council of Science Editors:

Al-Anssari J. Solid Vector Subtraction Operation and 3-D Gradient and Laplacian Spatial Filters of a Field of Vectors for Geometrical Edges Magnitude and Direction Detection in Point Cloud Surfaces. [Doctoral Dissertation]. University of Cincinnati; 2020. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin159213571577484


University of Cincinnati

10. Sommer, Nathan. A Machine Learning Approach to Controlling Musical Synthesizer Parameters in Real-Time Live Performance.

Degree: PhD, Engineering and Applied Science: Computer Science and Engineering, 2020, University of Cincinnati

 Musicians who perform with electronic synthesizers often adjust synthesisparameters during live performance to achieve more expressive sounds. Enablingthe performer to teach a computer to make… (more)

Subjects/Keywords: Computer Science; machine learning; neural networks; computer music; supervised learning; interactive machine learning; audio synthesizers

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APA (6th Edition):

Sommer, N. (2020). A Machine Learning Approach to Controlling Musical Synthesizer Parameters in Real-Time Live Performance. (Doctoral Dissertation). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1592168963826025

Chicago Manual of Style (16th Edition):

Sommer, Nathan. “A Machine Learning Approach to Controlling Musical Synthesizer Parameters in Real-Time Live Performance.” 2020. Doctoral Dissertation, University of Cincinnati. Accessed October 28, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1592168963826025.

MLA Handbook (7th Edition):

Sommer, Nathan. “A Machine Learning Approach to Controlling Musical Synthesizer Parameters in Real-Time Live Performance.” 2020. Web. 28 Oct 2020.

Vancouver:

Sommer N. A Machine Learning Approach to Controlling Musical Synthesizer Parameters in Real-Time Live Performance. [Internet] [Doctoral dissertation]. University of Cincinnati; 2020. [cited 2020 Oct 28]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1592168963826025.

Council of Science Editors:

Sommer N. A Machine Learning Approach to Controlling Musical Synthesizer Parameters in Real-Time Live Performance. [Doctoral Dissertation]. University of Cincinnati; 2020. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1592168963826025


University of Cincinnati

11. Singh, Vineeta. Segmentation of Regions with Complex Boundaries.

Degree: MS, Engineering and Applied Science: Electrical Engineering, 2016, University of Cincinnati

 Image segmentation is a core component of image processing. It is a very importantpart of image understanding. It is the technique of partitioning an image… (more)

Subjects/Keywords: Electrical Engineering; Image segmentation; Region growing algorithm; Edge detection; Hybrid technique; Lung; boundaries

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APA (6th Edition):

Singh, V. (2016). Segmentation of Regions with Complex Boundaries. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1479821009146599

Chicago Manual of Style (16th Edition):

Singh, Vineeta. “Segmentation of Regions with Complex Boundaries.” 2016. Masters Thesis, University of Cincinnati. Accessed October 28, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1479821009146599.

MLA Handbook (7th Edition):

Singh, Vineeta. “Segmentation of Regions with Complex Boundaries.” 2016. Web. 28 Oct 2020.

Vancouver:

Singh V. Segmentation of Regions with Complex Boundaries. [Internet] [Masters thesis]. University of Cincinnati; 2016. [cited 2020 Oct 28]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1479821009146599.

Council of Science Editors:

Singh V. Segmentation of Regions with Complex Boundaries. [Masters Thesis]. University of Cincinnati; 2016. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1479821009146599


University of Cincinnati

12. Baskaran, Balaji. Detection of Malicious Applications in Android using Machine Learning.

Degree: MS, Engineering and Applied Science: Computer Science, 2016, University of Cincinnati

 Android OS is one of the widely used mobile Operating Systems. Given Android’spopularity, the number of malicious applications and adwares are increasing constantlyon par with… (more)

Subjects/Keywords: Computer Science; Android OS; Machine Learning

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APA (6th Edition):

Baskaran, B. (2016). Detection of Malicious Applications in Android using Machine Learning. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1479822331991128

Chicago Manual of Style (16th Edition):

Baskaran, Balaji. “Detection of Malicious Applications in Android using Machine Learning.” 2016. Masters Thesis, University of Cincinnati. Accessed October 28, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1479822331991128.

MLA Handbook (7th Edition):

Baskaran, Balaji. “Detection of Malicious Applications in Android using Machine Learning.” 2016. Web. 28 Oct 2020.

Vancouver:

Baskaran B. Detection of Malicious Applications in Android using Machine Learning. [Internet] [Masters thesis]. University of Cincinnati; 2016. [cited 2020 Oct 28]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1479822331991128.

Council of Science Editors:

Baskaran B. Detection of Malicious Applications in Android using Machine Learning. [Masters Thesis]. University of Cincinnati; 2016. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1479822331991128


University of Cincinnati

13. Sista, Subrahmanya Srivathsava. Adversarial Game Playing Using Monte Carlo Tree Search.

Degree: MS, Engineering and Applied Science: Computer Science, 2016, University of Cincinnati

 Monte Carlo methods are a general collection of computational algorithms that obtain results by random sampling. Monte Carlo techniques, while great for simulation, have also… (more)

Subjects/Keywords: Computer Science; monte carlo tree search; artificial intelligence; game playing; tic tac toe

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APA (6th Edition):

Sista, S. S. (2016). Adversarial Game Playing Using Monte Carlo Tree Search. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1479820656701076

Chicago Manual of Style (16th Edition):

Sista, Subrahmanya Srivathsava. “Adversarial Game Playing Using Monte Carlo Tree Search.” 2016. Masters Thesis, University of Cincinnati. Accessed October 28, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1479820656701076.

MLA Handbook (7th Edition):

Sista, Subrahmanya Srivathsava. “Adversarial Game Playing Using Monte Carlo Tree Search.” 2016. Web. 28 Oct 2020.

Vancouver:

Sista SS. Adversarial Game Playing Using Monte Carlo Tree Search. [Internet] [Masters thesis]. University of Cincinnati; 2016. [cited 2020 Oct 28]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1479820656701076.

Council of Science Editors:

Sista SS. Adversarial Game Playing Using Monte Carlo Tree Search. [Masters Thesis]. University of Cincinnati; 2016. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1479820656701076


University of Cincinnati

14. Subramanian, Nandita. Analysis of Rank Distance for Malware Classification.

Degree: MS, Engineering and Applied Science: Computer Science, 2016, University of Cincinnati

 Malicious Cyber Adversaries may compromise the security of a system by denying access to legitimate users. This is often coupled with immeasurable loss of confidential… (more)

Subjects/Keywords: Computer Science; Rank Distance; Malware Classification; Mutual Information; Text Mining; Similarity Measures; Windows Malware

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APA (6th Edition):

Subramanian, N. (2016). Analysis of Rank Distance for Malware Classification. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1479823187035784

Chicago Manual of Style (16th Edition):

Subramanian, Nandita. “Analysis of Rank Distance for Malware Classification.” 2016. Masters Thesis, University of Cincinnati. Accessed October 28, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1479823187035784.

MLA Handbook (7th Edition):

Subramanian, Nandita. “Analysis of Rank Distance for Malware Classification.” 2016. Web. 28 Oct 2020.

Vancouver:

Subramanian N. Analysis of Rank Distance for Malware Classification. [Internet] [Masters thesis]. University of Cincinnati; 2016. [cited 2020 Oct 28]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1479823187035784.

Council of Science Editors:

Subramanian N. Analysis of Rank Distance for Malware Classification. [Masters Thesis]. University of Cincinnati; 2016. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1479823187035784

15. Girish, Deeptha S. Thresholded K-means Algorithm for Image Segmentation.

Degree: MS, Engineering and Applied Science: Electrical Engineering, 2016, University of Cincinnati

 Image processing aims to derive relevant information from an image or a group of images. Most traditional image processing algorithms that perform basic functions on… (more)

Subjects/Keywords: Electrical Engineering; Extended pixel representation; optimal number of clusters; K-means algorithm; Thresholded K-means algorithm; image segmentation; clusters

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APA (6th Edition):

Girish, D. S. (2016). Thresholded K-means Algorithm for Image Segmentation. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1479815784173769

Chicago Manual of Style (16th Edition):

Girish, Deeptha S. “Thresholded K-means Algorithm for Image Segmentation.” 2016. Masters Thesis, University of Cincinnati. Accessed October 28, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1479815784173769.

MLA Handbook (7th Edition):

Girish, Deeptha S. “Thresholded K-means Algorithm for Image Segmentation.” 2016. Web. 28 Oct 2020.

Vancouver:

Girish DS. Thresholded K-means Algorithm for Image Segmentation. [Internet] [Masters thesis]. University of Cincinnati; 2016. [cited 2020 Oct 28]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1479815784173769.

Council of Science Editors:

Girish DS. Thresholded K-means Algorithm for Image Segmentation. [Masters Thesis]. University of Cincinnati; 2016. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1479815784173769

16. Bogard, Britney A. Topic modeling: a novel approach to drug repositioning using metadata.

Degree: MS, Engineering and Applied Science: Computer Science, 2014, University of Cincinnati

 The expense of researching and developing new drugs is growing and restricting our opportunities to treat people effectively. Drug repositioning offers a less expensive and… (more)

Subjects/Keywords: Computer Science; drug repositioning; topic modeling; drug-disease similarity

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APA (6th Edition):

Bogard, B. A. (2014). Topic modeling: a novel approach to drug repositioning using metadata. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1415625843

Chicago Manual of Style (16th Edition):

Bogard, Britney A. “Topic modeling: a novel approach to drug repositioning using metadata.” 2014. Masters Thesis, University of Cincinnati. Accessed October 28, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1415625843.

MLA Handbook (7th Edition):

Bogard, Britney A. “Topic modeling: a novel approach to drug repositioning using metadata.” 2014. Web. 28 Oct 2020.

Vancouver:

Bogard BA. Topic modeling: a novel approach to drug repositioning using metadata. [Internet] [Masters thesis]. University of Cincinnati; 2014. [cited 2020 Oct 28]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1415625843.

Council of Science Editors:

Bogard BA. Topic modeling: a novel approach to drug repositioning using metadata. [Masters Thesis]. University of Cincinnati; 2014. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1415625843

17. Chaganti, Shikha. Image Analysis of Glioblastoma Histopathology.

Degree: MS, Engineering and Applied Science: Computer Science, 2014, University of Cincinnati

 Glioblastoma is a form of malignant brain tumor in humans involving glial or non-neuronal cells. The state-of-the-art diagnosis of Glioblastoma is predominantly based on subjective… (more)

Subjects/Keywords: Computer Science; Image Analysis; Clustering; Computer aided diagnosis; Glioblastoma; Histopathology

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APA (6th Edition):

Chaganti, S. (2014). Image Analysis of Glioblastoma Histopathology. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1406820611

Chicago Manual of Style (16th Edition):

Chaganti, Shikha. “Image Analysis of Glioblastoma Histopathology.” 2014. Masters Thesis, University of Cincinnati. Accessed October 28, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1406820611.

MLA Handbook (7th Edition):

Chaganti, Shikha. “Image Analysis of Glioblastoma Histopathology.” 2014. Web. 28 Oct 2020.

Vancouver:

Chaganti S. Image Analysis of Glioblastoma Histopathology. [Internet] [Masters thesis]. University of Cincinnati; 2014. [cited 2020 Oct 28]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1406820611.

Council of Science Editors:

Chaganti S. Image Analysis of Glioblastoma Histopathology. [Masters Thesis]. University of Cincinnati; 2014. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1406820611

18. Munimadugu, Hareendra. Tie Inducement using Closure Analysis in Information Networks.

Degree: MS, Engineering and Applied Science: Computer Engineering, 2012, University of Cincinnati

  This work addresses one important problem in Social Networks Analysis, namely link prediction. Link Prediction is important to understand and evaluate the change in… (more)

Subjects/Keywords: Computer Engineering

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APA (6th Edition):

Munimadugu, H. (2012). Tie Inducement using Closure Analysis in Information Networks. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1353099669

Chicago Manual of Style (16th Edition):

Munimadugu, Hareendra. “Tie Inducement using Closure Analysis in Information Networks.” 2012. Masters Thesis, University of Cincinnati. Accessed October 28, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1353099669.

MLA Handbook (7th Edition):

Munimadugu, Hareendra. “Tie Inducement using Closure Analysis in Information Networks.” 2012. Web. 28 Oct 2020.

Vancouver:

Munimadugu H. Tie Inducement using Closure Analysis in Information Networks. [Internet] [Masters thesis]. University of Cincinnati; 2012. [cited 2020 Oct 28]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1353099669.

Council of Science Editors:

Munimadugu H. Tie Inducement using Closure Analysis in Information Networks. [Masters Thesis]. University of Cincinnati; 2012. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1353099669

19. Pangaonkar, Manali. Exploratory Study of Fuzzy Clustering and Set-Distance Based Validation Indexes.

Degree: MS, Engineering and Applied Science: Computer Science, 2012, University of Cincinnati

 This thesis is concerned with issues related to clustering. In particular, it addresses the con-vergence speed of fuzzy c-means family of algorithms and cluster validation.… (more)

Subjects/Keywords: Computer Science; Fuzzy Clustering; Cluster Validation; Compactness; Separation; Set Distance; Cluster Comparison

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APA (6th Edition):

Pangaonkar, M. (2012). Exploratory Study of Fuzzy Clustering and Set-Distance Based Validation Indexes. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1353342433

Chicago Manual of Style (16th Edition):

Pangaonkar, Manali. “Exploratory Study of Fuzzy Clustering and Set-Distance Based Validation Indexes.” 2012. Masters Thesis, University of Cincinnati. Accessed October 28, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1353342433.

MLA Handbook (7th Edition):

Pangaonkar, Manali. “Exploratory Study of Fuzzy Clustering and Set-Distance Based Validation Indexes.” 2012. Web. 28 Oct 2020.

Vancouver:

Pangaonkar M. Exploratory Study of Fuzzy Clustering and Set-Distance Based Validation Indexes. [Internet] [Masters thesis]. University of Cincinnati; 2012. [cited 2020 Oct 28]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1353342433.

Council of Science Editors:

Pangaonkar M. Exploratory Study of Fuzzy Clustering and Set-Distance Based Validation Indexes. [Masters Thesis]. University of Cincinnati; 2012. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1353342433

20. Mayfield, James L., IV. A Parameterized Framework for Quantum Computation.

Degree: PhD, Engineering and Applied Science: Computer Science and Engineering, 2012, University of Cincinnati

  The primary focus of this dissertation is the development of a framework for the design and analysis of quantum circuits and quantum algorithms based… (more)

Subjects/Keywords: Computer Science; Quantum Computing; Theoretical Computer Science

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APA (6th Edition):

Mayfield, James L., I. (2012). A Parameterized Framework for Quantum Computation. (Doctoral Dissertation). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1342543546

Chicago Manual of Style (16th Edition):

Mayfield, James L., IV. “A Parameterized Framework for Quantum Computation.” 2012. Doctoral Dissertation, University of Cincinnati. Accessed October 28, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1342543546.

MLA Handbook (7th Edition):

Mayfield, James L., IV. “A Parameterized Framework for Quantum Computation.” 2012. Web. 28 Oct 2020.

Vancouver:

Mayfield, James L. I. A Parameterized Framework for Quantum Computation. [Internet] [Doctoral dissertation]. University of Cincinnati; 2012. [cited 2020 Oct 28]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1342543546.

Council of Science Editors:

Mayfield, James L. I. A Parameterized Framework for Quantum Computation. [Doctoral Dissertation]. University of Cincinnati; 2012. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1342543546

21. Kohram, Mojtaba. Experiments with Support Vector Machines and Kernels.

Degree: MS, Engineering and Applied Science: Computer Science, 2013, University of Cincinnati

 Support Vector Machines (SVM) have been used extensively in different areas of science and engineering for classification and regression tasks. In this thesis we test… (more)

Subjects/Keywords: Computer Science; Support Vector Machines; SVM kernel; RBF kernel; Gaussian Radial Basis Function; Spectral Information Divergence; Spectral Angle Mapper; RNA-protein interaction; PSSM matrix

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APA (6th Edition):

Kohram, M. (2013). Experiments with Support Vector Machines and Kernels. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1378112059

Chicago Manual of Style (16th Edition):

Kohram, Mojtaba. “Experiments with Support Vector Machines and Kernels.” 2013. Masters Thesis, University of Cincinnati. Accessed October 28, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1378112059.

MLA Handbook (7th Edition):

Kohram, Mojtaba. “Experiments with Support Vector Machines and Kernels.” 2013. Web. 28 Oct 2020.

Vancouver:

Kohram M. Experiments with Support Vector Machines and Kernels. [Internet] [Masters thesis]. University of Cincinnati; 2013. [cited 2020 Oct 28]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1378112059.

Council of Science Editors:

Kohram M. Experiments with Support Vector Machines and Kernels. [Masters Thesis]. University of Cincinnati; 2013. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1378112059

22. Nsang, Augustine S. An Empirical Study of Novel Approaches to Dimensionality Reduction and Applications.

Degree: PhD, Engineering and Applied Science: Computer Science and Engineering, 2011, University of Cincinnati

  Dimensionality reduction is becoming increasingly important in the field of machine learning. In this thesis, we examine several traditional methods of dimensionality reduction, which… (more)

Subjects/Keywords: Computer Science; dimensionality reduction; random projections; clustering; classification; queries; web data

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APA (6th Edition):

Nsang, A. S. (2011). An Empirical Study of Novel Approaches to Dimensionality Reduction and Applications. (Doctoral Dissertation). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1312294067

Chicago Manual of Style (16th Edition):

Nsang, Augustine S. “An Empirical Study of Novel Approaches to Dimensionality Reduction and Applications.” 2011. Doctoral Dissertation, University of Cincinnati. Accessed October 28, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1312294067.

MLA Handbook (7th Edition):

Nsang, Augustine S. “An Empirical Study of Novel Approaches to Dimensionality Reduction and Applications.” 2011. Web. 28 Oct 2020.

Vancouver:

Nsang AS. An Empirical Study of Novel Approaches to Dimensionality Reduction and Applications. [Internet] [Doctoral dissertation]. University of Cincinnati; 2011. [cited 2020 Oct 28]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1312294067.

Council of Science Editors:

Nsang AS. An Empirical Study of Novel Approaches to Dimensionality Reduction and Applications. [Doctoral Dissertation]. University of Cincinnati; 2011. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1312294067

23. Seethakkagari, Swathi, M.S. Identifying Interesting Posts on Social Media Sites.

Degree: MS, Engineering and Applied Science: Computer Engineering, 2012, University of Cincinnati

 This thesis work considers the classification of messages posted on social networking sites as astep towards identifying interesting/uninteresting messages. As first approximation, a message isrepresented… (more)

Subjects/Keywords: Computer Science; Social networks; k-nearest neighbors; Naive Bayes Classi- fication; Confusion Matrix

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APA (6th Edition):

Seethakkagari, Swathi, M. S. (2012). Identifying Interesting Posts on Social Media Sites. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1337888634

Chicago Manual of Style (16th Edition):

Seethakkagari, Swathi, M S. “Identifying Interesting Posts on Social Media Sites.” 2012. Masters Thesis, University of Cincinnati. Accessed October 28, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1337888634.

MLA Handbook (7th Edition):

Seethakkagari, Swathi, M S. “Identifying Interesting Posts on Social Media Sites.” 2012. Web. 28 Oct 2020.

Vancouver:

Seethakkagari, Swathi MS. Identifying Interesting Posts on Social Media Sites. [Internet] [Masters thesis]. University of Cincinnati; 2012. [cited 2020 Oct 28]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1337888634.

Council of Science Editors:

Seethakkagari, Swathi MS. Identifying Interesting Posts on Social Media Sites. [Masters Thesis]. University of Cincinnati; 2012. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1337888634


University of Cincinnati

24. Greer, Jeremiah. Unsupervised Interpretable Feature Extraction for Binary Executables using LIBCAISE.

Degree: MS, Engineering and Applied Science: Computer Science, 2019, University of Cincinnati

 Traditional approaches to understanding program behavior involve either classifying programs with supervised machine learning algorithms or manually reverse engineering software. While many powerful classifiers exist,… (more)

Subjects/Keywords: Computer Science; Natural Language Processing; Cybersecurity; Program Analysis; Software; Assembly; Unsupervised

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APA (6th Edition):

Greer, J. (2019). Unsupervised Interpretable Feature Extraction for Binary Executables using LIBCAISE. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1560866693877849

Chicago Manual of Style (16th Edition):

Greer, Jeremiah. “Unsupervised Interpretable Feature Extraction for Binary Executables using LIBCAISE.” 2019. Masters Thesis, University of Cincinnati. Accessed October 28, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1560866693877849.

MLA Handbook (7th Edition):

Greer, Jeremiah. “Unsupervised Interpretable Feature Extraction for Binary Executables using LIBCAISE.” 2019. Web. 28 Oct 2020.

Vancouver:

Greer J. Unsupervised Interpretable Feature Extraction for Binary Executables using LIBCAISE. [Internet] [Masters thesis]. University of Cincinnati; 2019. [cited 2020 Oct 28]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1560866693877849.

Council of Science Editors:

Greer J. Unsupervised Interpretable Feature Extraction for Binary Executables using LIBCAISE. [Masters Thesis]. University of Cincinnati; 2019. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1560866693877849


University of Cincinnati

25. Hadish, Mulugeta. Extended Multidimensional Conceptual Spaces in Document Classification.

Degree: MS, Engineering : Computer Science, 2008, University of Cincinnati

 Content based retrieval, entailing knowledge representation, can be essentially described as assessing the similarity between objects which constitute primitives as their building blocks. This thesis… (more)

Subjects/Keywords: Computer Science; Conceptual spaces; Document classification; ranking; knowledge representiaton; Fuzzy set; Fuzzy sets cardinality; Fuzzy sets cardinality aggregation document

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APA (6th Edition):

Hadish, M. (2008). Extended Multidimensional Conceptual Spaces in Document Classification. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1227158181

Chicago Manual of Style (16th Edition):

Hadish, Mulugeta. “Extended Multidimensional Conceptual Spaces in Document Classification.” 2008. Masters Thesis, University of Cincinnati. Accessed October 28, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1227158181.

MLA Handbook (7th Edition):

Hadish, Mulugeta. “Extended Multidimensional Conceptual Spaces in Document Classification.” 2008. Web. 28 Oct 2020.

Vancouver:

Hadish M. Extended Multidimensional Conceptual Spaces in Document Classification. [Internet] [Masters thesis]. University of Cincinnati; 2008. [cited 2020 Oct 28]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1227158181.

Council of Science Editors:

Hadish M. Extended Multidimensional Conceptual Spaces in Document Classification. [Masters Thesis]. University of Cincinnati; 2008. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1227158181


University of Cincinnati

26. POPOVICI, STEFANA A. On evaluating similarity between heterogeneous data.

Degree: MS, Engineering : Computer Science, 2008, University of Cincinnati

  Heterogeneous data are multidimensional data whose attributes belong to different domains. Processing heterogeneous data has become an important problem in data mining. However, due… (more)

Subjects/Keywords: Computer Science; similarity; heterogeneous data

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APA (6th Edition):

POPOVICI, S. A. (2008). On evaluating similarity between heterogeneous data. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1212172030

Chicago Manual of Style (16th Edition):

POPOVICI, STEFANA A. “On evaluating similarity between heterogeneous data.” 2008. Masters Thesis, University of Cincinnati. Accessed October 28, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1212172030.

MLA Handbook (7th Edition):

POPOVICI, STEFANA A. “On evaluating similarity between heterogeneous data.” 2008. Web. 28 Oct 2020.

Vancouver:

POPOVICI SA. On evaluating similarity between heterogeneous data. [Internet] [Masters thesis]. University of Cincinnati; 2008. [cited 2020 Oct 28]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1212172030.

Council of Science Editors:

POPOVICI SA. On evaluating similarity between heterogeneous data. [Masters Thesis]. University of Cincinnati; 2008. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1212172030


University of Cincinnati

27. Visa, Sofia. Comparative Study of Methods for Linguistic Modeling of Numerical Data.

Degree: MS, Engineering : Computer Science, 2002, University of Cincinnati

  This thesis investigates the performance of four different classifiers on a common real data set. A review of the current classification models is presented… (more)

Subjects/Keywords: Computer Science; classifier; fuzzy systems; neural networks; support vectors machine; minimum distance classifier; ROC; confusion matrix; Yule statistic; bias-variance tradeoff.

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APA (6th Edition):

Visa, S. (2002). Comparative Study of Methods for Linguistic Modeling of Numerical Data. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1043254774

Chicago Manual of Style (16th Edition):

Visa, Sofia. “Comparative Study of Methods for Linguistic Modeling of Numerical Data.” 2002. Masters Thesis, University of Cincinnati. Accessed October 28, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1043254774.

MLA Handbook (7th Edition):

Visa, Sofia. “Comparative Study of Methods for Linguistic Modeling of Numerical Data.” 2002. Web. 28 Oct 2020.

Vancouver:

Visa S. Comparative Study of Methods for Linguistic Modeling of Numerical Data. [Internet] [Masters thesis]. University of Cincinnati; 2002. [cited 2020 Oct 28]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1043254774.

Council of Science Editors:

Visa S. Comparative Study of Methods for Linguistic Modeling of Numerical Data. [Masters Thesis]. University of Cincinnati; 2002. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1043254774

.