Publications

@article{Reese2009,
abstract = {Ad-Hoc Sensory Networks present a cheap and efficient way to collect data through wireless transmissions between sensors. These transmissions create new problems that need to be overcome in order to insure that the data being collected is reliable. This paper surveys the latest research in Jamming Avoidance in Ad-Hoc Sensory Networks.},
address = {Frederick, Maryland},
author = {Reese, Kristopher and Salem, Ahmed},
issn = {1937-4771},
journal = {Journal of Computing Sciences in Colleges},
keywords = {Computer science,Computer security,Jamming,Sensory system,Wireless},
month = {Jan},
number = {3},
pages = {93--98},
title = {{A survey on jamming avoidance in ad-hoc sensory networks}},
volume = {24},
year = {2009},
url = {https://filedn.com/lQRiSepE26b5IDMd7aq0fqS/ResearchPapers/Reese%2C%20Salem%20-%202008%20-%20A%20Survey%20on%20Jamming%20Avoidance%20in%20Wireless%20Ad-Hoc%20Sensory%20Networks.pdf}
}

@inproceedings{Reese2013,
abstract = {The understanding of medical test results is markedly improved through the use of visual analytics. While traditional theorists in the field of healthcare analytics seek to improve decision making through data mining and machine learning, Visual Analytics augments that intelligence by providing an interface to integrate all of the data in a composite image. KnowYourColors™ is a visual analytics interface providing many dashboards to help the healthcare and insurance providers make better decisions in treatment and spending. This paper discusses many of the visualizations that are used in those applications. This includes new visualizations focused around polar area diagrams that are designed for showing blood metrics and visualizations of prior research work that help in the decision making process. This paper also demonstrates the effectiveness of the application and the reactions of physicians and patients. {\textcopyright} 2013 IEEE.},
address = {Athens, Greece},
author = {Reese, Kristopher and Bessette, Russell and Hancock, Pricilla},
booktitle = {IEEE International Symposium on Signal Processing and Information Technology, IEEE ISSPIT 2013},
doi = {10.1109/ISSPIT.2013.6781845},
month = {Oct},
publisher = {IEEE},
title = {{KnowYourColors: Visual dashboards for blood metrics and healthcare analytics}},
year = {2013}
}

@inproceedings{Zheng2013,
abstract = {Current multispectral night vision (NV) colorization techniques can manipulate images to produce colorized images that closely resemble natural scenes. The colorized NV images can enhance human perception by improving observer object classification and reaction times especially for low light conditions. This paper focuses on the qualitative (subjective) evaluations and comparisons of six NV colorization methods. The multispectral images include visible (Red-Green- Blue), near infrared (NIR), and long wave infrared (LWIR) images. The six colorization methods are channel-based color fusion (CBCF), statistic matching (SM), histogram matching (HM), joint-histogram matching (JHM), statistic matching then joint-histogram matching (SM-JHM), and the lookup table (LUT). Four categries of quality measurements are used for the qualitative evaluations, which are contrast, detail, colorfulness, and overall quality. The score of each measurement is rated from 1 to 3 scale to represent low, average, and high quality, respectively. Specifically, high contrast (of rated score 3) means an adequate level of brightness and contrast. The high detail represents high clarity of detailed contents while maintaining low artifacts. The high colorfulness preserves more natural colors (i.e., closely resembles the daylight image). Overall quality is determined from the NV image compared to the reference image. Nine sets of multispectral NV images were used in our experiments. For each set, the six colorized NV images (produced from NIR and LWIR images) are concurrently presented to users along with the reference color (RGB) image (taken at daytime). A total of 67 subjects passed a screening test (“Ishihara Color Blindness Test”) and were asked to evaluate the 9-set colorized images. The experimental results showed the quality order of colorization methods from the best to the worst: CBCF < SM < SM-JHM < LUT < JHM < HM. It is anticipated that this work will provide a benchmark for NV colorization and for quantitative evaluation using an objective metric such as objective evaluation index (OEI).},
address = {Baltimore, Maryland},
author = {Zheng, Yufeng and Reese, Kristopher and Blasch, Erik and McManamon, Paul},
booktitle = {Proceedings of the International Society of Optics and Photonics: Signal Processing, Sensor Fusion, and Target Recognition XXII},
doi = {10.1117/12.2016643},
isbn = {9780819495365},
issn = {0277786X},
month = {Apr},
pages = {8745.1 -- 8745.11},
publisher = {SPIE},
title = {{Qualitative evaluations and comparisons of six night-vision colorization methods}},
volume = {8745},
year = {2013}
}

@inproceedings{Ouch2013,
abstract = {The Maximum Clique Problem (MCP) has been studied for decades and is well known in graph theory as a problem that is difficult as it as it is known to be NP-complete. The MCP has a vast domain of application such as finance, biochemistry, bioinformatics, and many more. Many niching methods have been successfully applied in Genetic Algorithms (GA) to diversify the population and avoid getting trapped within local optima. In this paper, we propose an approach using the Sharing method and a Hybrid Genetic Algorithm (HGA) for the maximum clique problem. We also propose a non-evolutionary approach using a migration mechanism to boost the current HGA.},
address = {New Albany, Indiana},
author = {Ouch, Roger and Reese, Kristopher and Yampolskiy, Roman V.},
booktitle = {Proceedings of the 24th Midwest Artificial Intelligence and Cognitive Sciences Conference (MAICS 2013)},
issn = {16130073},
month = {Apr},
pages = {79--84},
title = {{Hybrid Genetic Algorithm for the Maximum Clique Problem combining Sharing and migration}},
volume = {1348},
year = {2013},
url = {http://cecs.louisville.edu/security/Papers/ga_paper_MAICS_2.0.pdf}
}

@inproceedings{Zheng2012,
abstract = {Score fusion combines several scores from multiple matchers and/or multiple modalities, which can increase the accuracy of face recognition. In a real system, high accuracy rate and low false accept rates (FAR) are equally important. In this paper, we propose to improve the accuracy using score fusion of multispectral images and reduce the FAR using decision fusion of stereo images. The stereo face images are taken with two identical cameras aiming at a subject, which include two bands, visible and thermal. Specifically, the score fusion combines the face scores from three selected matchers, face pattern byte, linear discriminant analysis, and elastic bunch graph matching, and from two-band images (visible and thermal). The decision fusion combines the results (genuine or impostor) from left face and right face in stereo imaging. We present the score-fusion results using k-nearest neighbor fusion, and hidden Markov model fusion, and the decision-fusion results using logical rules, OR and AND. Our experiments are conducted with the ASUMSS face dataset that currently consists of the stereo face images of two spectral bands from 55 subjects. The experimental results show that score fusion can significantly improve the accuracy, and the decision fusion (with AND rule) can reduce the FAR with a slight decrease of the accuracy. {\textcopyright} 2012 IEEE.},
address = {Saigon, Vietnam},
author = {Zheng, Yufeng and Elmaghraby, Adel S. and Reese, Kristopher},
booktitle = {2012 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2012},
doi = {10.1109/ISSPIT.2012.6621301},
isbn = {9781467356060},
keywords = {Decision fusion,Face pattern byte (FPB),Nmiispectrai face recognition,Score fusion,Stereo face imaging},
month = {Dec},
pages = {280--285},
publisher = {IEEE},
title = {{Performance improvement of face recognition using multispectral images and stereo images}},
year = {2012}
}

@inproceedings{Reese2012a,
abstract = {Face Detection is the first step of facial recognition algorithms and has been widely researched in the visible spectrum. Current research has shown that thermal facial recognition is as accurate as the visible spectrum recognition algorithms. This paper presents three face detection algorithms in both long-wavelength infrared (LWIR) images and visible spectrum images. The paper compares the Viola- Jones algorithm, Gabor feature extraction and classification using support vector machines, and a Projection Profile Analysis algorithm. The Gabor feature extraction method can detect faces in both spectrums with separate training, but the algorithm is extremely slow. The Project Profile Analysis method can find faces in LWIR images, but is not applicable to visible spectrum images. Our experimental results show that the Viola-Jones algorithm is the most reliable and efficient solution for the implementation of a real-time face detection system using either visible or thermal spectrum images.},
address = {Amsterdam, Netherlands},
author = {Reese, Kristopher and Zheng, Yufeng and Elmaghraby, Adel},
booktitle = {Int'l Conf. on Advances in Computer Science and Application (CSA 2012)},
month = {Jun},
pages = {49--53},
publisher = {IEEE},
title = {{A Comparison of Face Detection Algorithms in the Visible and Thermal Spectrums}},
year = {2012},
doi = {10.1007/978-3-319-70353-4_44},
url = {https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.681.8119&rep=rep1&type=pdf}
}

@inproceedings{Reese2012,
abstract = {Tonal music has had a rich history in Video Games and movies, and in fact, music generation has played a minor role in the history of game music as well. Recent developments in Music Theory has derived representions of chord progressions using geometric topologies. Unlike prior generative music, the framework proposed in this paper attempts to approach tonal music generation by building networks of chords using the geometric topologies. This geometric network of chords can then be used inside of reinforcement learning models for learning the best motions in the progression. The proposed method uses Q Learning models, by rewarding acceptable chords, such as Major and minor chords. Rewards are also given to chords within a specified scale. The proposed framework approaches tonal chord progressions by keeping a tonal center in the progression. Methods for creating interactive and unique music for video games are also discussed. {\textcopyright} 2012 IEEE.},
address = {Louisville, Kentucky},
author = {Reese, Kristopher and Yampolskiy, Roman and Elmaghraby, Adel},
booktitle = {Proceedings of the 17th International Conference on Computer Games: AI, Animation, Mobile, Interactive Multimedia, Educational and Serious Games (CGAMES 2012)},
doi = {10.1109/CGames.2012.6314564},
isbn = {9781467311199},
keywords = {Generative,Interactive,Music,Q-Learning},
month = {Aug},
pages = {131--137},
publisher = {IEEE},
title = {{A framework for interactive generation of music for games}},
year = {2012}
}

@inproceedings{Reese2009a,
abstract = {Hand-Computer interaction is a frequently researched topic in the field of computer gaming. However, very few of the devices or techniques used for Hand interaction with are accessible within many smaller groups, especially those with disabilities. For this paper, we have developed a tool to show several of the techniques used in gaming research and describe how these techniques could be implemented in Human- Computing Interaction with a focus on accessibility for the physically challenged. A Bare-Hand tracking technique is used to track the location of the Hand in relation to a single web camera. This proof of concept interface offers a look at how future devices could be both fun for typical users without sacrificing on accessibility. {\textcopyright} 2009 The University of Wolverhampton.},
address = {Louisville, Kentucky},
author = {Reese, Kristopher and Salem, Ahmed and Dimitoglou, George},
booktitle = {Proceedings of the 14th International Conference on Computer Games: AI, Animation, Mobile, Interactive Multimedia, Educational and Serious Games (CGAMES '09)},
isbn = {9780954901677},
keywords = {Accessibility,Bare-hand controls,Computer vision,Future interfaces,Human factors,Human-computer interaction,Object detection},
month = {Aug},
pages = {40--46},
publisher = {IEEE},
title = {{Gaming concepts in accessible HCI for Bare-Hand computer interaction}},
year = {2009},
url = {https://filedn.com/lQRiSepE26b5IDMd7aq0fqS/ResearchPapers/Reese%2C%20Salem%2C%20Dimitoglou%20-%202009%20-%20Gaming%20concepts%20in%20accessible%20HCI%20for%20Bare-Hand%20computer%20interaction.pdf}
}

@inproceedings{Reese2008,
abstract = {As wireless networks become more common in both government and industry settings, jamming becomes a major issue. This paper provides a mathematical approach and equations for analysis of signal strength jamming detection, over the more commonly used packet-loss jamming detection. The approach offered alleviates issues with battery life by cutting the overhead cost of sending and receiving multiple packets before the network can determine that it is being jammed.},
address = {Honolulu, Hawaii},
author = {Reese, Kristopher and Salem, Ahmed and Dimitoglou, George},
booktitle = {21st International Conference on Computer Applications in Industry and Engineering, CAINE 2008},
isbn = {9781605606170},
keywords = {Ad-Hoc networks,Jamming,Jamming avoidance,Jamming detection,Sensory network,Wireless transmission},
pages = {250--254},
publisher = {ACM},
title = {{Using standard deviation in signal strength detection to determine jamming in wireless networks}},
year = {2008},
url = {https://filedn.com/lQRiSepE26b5IDMd7aq0fqS/ResearchPapers/Reese%2C%20Salem%2C%20Dimitoglou%20-%202008%20-%20Using%20Standard%20Deviation%20in%20Signal%20Strength%20Detection%20to%20Determine%20Jamming%20in%20Wireless%20Networks.pdf}
}

@phdthesis{Reese2020,
abstract = {The rise of technology proliferating into the workplace has increased the threat of loss of intellectual property, classified, and proprietary information for companies, governments, and academics. This can cause economic damage to the creators of new IP, companies, and whole economies. This technology proliferation has also assisted terror groups and lone wolf actors in pushing their message to a larger audience or finding similar tribal groups that share common, sometimes flawed, beliefs across var- ious social media platforms. These types of challenges have created numerous studies in psycholinguistics, as well as commercial tools, that look to assist in identifying po- tential threats before they have an opportunity to conduct malicious acts. This has led to an area of study that this dissertation defines as “Computational Behavioral Analytics.” A common practice espoused in various Natural Language Processing studies (both commercial and academic) conducted on foreign language text is the use of Machine Translation (MT) systems before conducting NLP tasks. In this dissertation, we explore three psycholinguistic traits conducted on foreign language text. We explore the effects (and failures) of MT systems in these types of psycholinguistic tasks in order to help push the field of study into a direction that will greatly improve the efficacy of such systems. Given the results of the experimentation in this dissertation, it is highly recom- mended to avoid the use of translations whenever the greatest levels of accuracy are necessary, such as for National Security and Law Enforcement purposes. If trans- lations must be used for any reason, scientist should conduct a full analysis of the impact of their chosen translation system on their estimates to determine which traits are more significantly affected. This will help ensure that analysts and scientists are better informed of the potential inaccuracies and change any resulting decisions from the data accordingly. This dissertation introduces psycholinguistics and the benefits of using Machine Learning technologies in estimating various psychological traits, and provides a brief discussion on the potential privacy and legal issues that should be addressed in order to avoid the abuse of such systems in Chapter I. Chapter II outlines the datasets that are used during the experimentation and evaluation of the algorithms. Chapter III discusses each of the various implementations of the algorithms used in the three psycholinguistic tasks - Affect Analysis, Authorship Attribution, and Personality Es- timation. Chapter IV discusses the experiments that were run in order to understand the effects of MT on the psycholinguistic tasks, and to understand how these tasks can be accomplished in the face of MT limitations, including rationale on the selec- tion of the MT system used in this study. The dissertation concludes with Chapter V, providing a discussion and speculating on the findings and future experimentation that should be done.},
address = {Louisville, Kentucky},
author = {Reese, Kristopher },
school = {University of Louisville (UofL)},
title = {{Computational Behavioral Analytics: Estimating Psychological Traits in Foreign Languages}},
year = {2020},
doi = {10.18297/etd/3568},
url = {https://ir.library.louisville.edu/cgi/viewcontent.cgi?article=4765&context=etd}
}

@mastersthesis{Reese2011,
abstract = {Computers and music have shared a rich history since the 1950s. Many languages and standards have been built around music. Yet even before the advent of the computer, music shared algorithmic ideas with mathematics which brought about many new styles over the centuries. Today's computers provide even more power, and with Intelligence algorithms, are able to create complex systems for generating art. Music is no exception, but very little has been done in generating music using such algorithms. Reinforcement Learning provides a means of learning good motions of chord progressions in music theory. Dmitri Tymoczko's Latent model for the underlying chord structure creates a mesh orbifoidal network capturing voice leading and surrounding chords. This presentation discusses experimentation in the latent model with a combination of the ideas taught in traditional Tonal Harmonic theory. Unlike David Cope's work in mimicking composer styles using machine learning, this approach attempts to tackle the problem head on through experimentation with Tymoczko's latent model for chords. Reinforcement Learning provides a means for learning this network and reward states in order to reach a terminal goal (taught in music theory as cadencing chords). Using Reinforcement Learning we are then able to use the reinforced model to generate chord progressions which have a tonal center (a center of gravity pulling the chords towards a certain pitch class). Further, a discussion of the implemented algorithm is also given.},
address = {Louisville, Kentucky},
author = {Reese, Kristopher},
doi = {10.18297/etd/1195},
school = {University of Louisville},
title = {{Computationally generated music using reinforcement learning.}},
year = {2011},
url = {https://ir.library.louisville.edu/cgi/viewcontent.cgi?article=2194&context=etd}
}

@article{Reese2009b,
abstract = {There are numerous path‐planning algorithms for autonomous robotics. This survey attempts to cover a number of the most commonly used heuristic and non‐heuristic techniques in an effort to categorize and classify them. The algorithms range from very old ones, such as path planning based on Voronoi diagrams, to more modern algorithms such as A* and ARA*. The objective is not to determine the best algorithmic technique but to provide a matrix‐like comparison that illustrates the types, advantages, disadvantages and applicability of these techniques in solving path‐planning problems.},
address = {Frederick, Maryland},
author = {Reese, Kristopher and Dimitoglou, George},
journal = {Journal of Computing Sciences in Colleges},
month = {Jan},
number = {3},
title = {{A Survey of Path Planning Algorithms for Autonomous Robotics}},
volume = {24},
year = {2009},
file = {https://filedn.com/lQRiSepE26b5IDMd7aq0fqS/ResearchPapers/Reese, Dimitiglou - 2008 - A Survey of Path Planning Algorithms for Autonomous Robotics (POSTER).pdf},
url = {https://filedn.com/lQRiSepE26b5IDMd7aq0fqS/ResearchPapers/Reese, Dimitiglou - 2008 - A Survey of Path Planning Algorithms for Autonomous Robotics (POSTER)(2).pdf}
}

@inproceedings{Reese2018,
address = {Gainesville, FL},
author = {Reese, Kristopher },
booktitle = {Florida Institute for CyberSecurity Conference},
month = {Feb},
publisher = {University of Florida},
title = {{The Future of Identity Science}},
year = {2018}
}

@inproceedings{Reese2012b,
address = {Alcorn, Mississippi},
author = {Reese, Kristopher },
booktitle = {Joint DoD and DHS workshop on Image Analysis II},
month = {Jun},
publisher = {Alcorn State University},
title = {{A Technical Survey of Facial Recognition Techniques - Past Achievements and Future Applications}},
year = {2012}
}

@inproceedings{Reese2011a,
address = {Louisville, Kentucky},
author = {Reese, Kristopher },
booktitle = {Doctoral Seminar},
month = {Mar},
publisher = {University of Louisville},
title = {{Generative Chord Progressions using Reinforcement Learning}},
year = {2011}
}