Graphics and Human Computer Interfaces Commons^™

Fuzzy Algorithms: Applying Fuzzy Logic To The Golden Ratio Search To Find Solutions Faster, Stephany Coffman-Wolph

MAICS: The Modern Artificial Intelligence and Cognitive Science Conference

Applying the concept of fuzzy logic (an abstract version of Boolean logic) to well-known algorithms generates an abstract version (i.e., fuzzy algorithm) that often results in computational improvements. Precision may be reduced but counteracted by gaining computational efficiency. The trade-offs (e.g., small increase in space, loss of precision) for a variety of applications are deemed acceptable. The fuzzification of an algorithm can be accomplished using a simple three-step framework. Creating a new fuzzy algorithm goes beyond simply converting the data from raw data into fuzzy data by additionally converting the operators and concepts into their abstract equivalents. This paper demonstrates: …

The Webid Protocol Enhanced With Group Access, Biometrics, And Access Policies, Cory Sabol, William Nick, Maya Earl, Joseph Shelton, Albert Esterline

MAICS: The Modern Artificial Intelligence and Cognitive Science Conference

The WebID protocol solves the challenge of remembering usernames and passwords. We enhance this protocol in three ways. First, we give it the ability to manage groups of agents and control their access to resources on the Web. Second, we add support for biometric access control to enhance security. Finally, we add support for OWL-based policies that may be federated and result in flexible access control.

Real-Time Unsupervised Clustering, Gabriel Ferrer

MAICS: The Modern Artificial Intelligence and Cognitive Science Conference

In our research program, we are developing machine learning algorithms to enable a mobile robot to build a compact representation of its environment. This requires the processing of each new input to terminate in constant time. Existing machine learning algorithms are either incapable of meeting this constraint or deliver problematic results. In this paper, we describe a new algorithm for real-time unsupervised clustering, Bounded Self-Organizing Clustering. It executes in constant time for each input, and it produces clusterings that are significantly better than those created by the Self-Organizing Map, its closest competitor, on sensor data acquired from a physically embodied …

Front Matter: Proceedings Of The Maics 2016 Conference, University Of Dayton

Content presented at the MAICS conference

Front matter contains:

• A list of program chairs and committee members
• Foreword to the proceedings by James P. Buckley, conference chair; Saverio Perugini, general chair

Editors: Phu H. Phung, University of Dayton; Ju Shen, University of Dayton; Michael Glass, Valparaiso University

Revisiting The Futamura Projections: A Diagrammatic Approach, Brandon Williams, Saverio Perugini

Computer Science Faculty Publications

The advent of language implementation tools such as PyPy and Truffle/Graal have reinvigorated and broadened interest in topics related to automatic compiler generation and optimization. Given this broader interest, we revisit the Futamura Projections using a novel diagram scheme. Through these diagrams we emphasize the recurring patterns in the Futamura Projections while addressing their complexity and abstract nature. We anticipate that this approach will improve the accessibility of the Futamura Projections and help foster analysis of those new tools through the lens of partial evaluation.

Un Indicator De Incluziune Cu Aplicaţii În Computer Vision, Florentin Smarandache, Ovidiu Ilie Sandru

Branch Mathematics and Statistics Faculty and Staff Publications

În aceasta lucrare vom prezenta un procedeu de algoritmizare a operatiilor necesare deplasarii automate a unui obiect predefinit dintr-o imagine video data intr-o regiune tinta a acelei imagini, menit a facilita realizarea de aplicatii software specializate in rezolvarea acestui gen de probleme.

An Indicator Of Inclusion With Applications To Computer Vision, Florentin Smarandache, Ovidiu Ilie Sandru

Branch Mathematics and Statistics Faculty and Staff Publications

In this paper we present an algorithmic process of necessary operations for the automatic movement of a predefined object from a video image in the target region of that image, intended to facilitate the implementation of specialized software applications in solving this kind of problems.

Salad: A Multimodal Approach For Contextual Video Advertising, Chen Xiang, Tam Nguyen, Mohan Kankanhalli

Computer Science Faculty Publications

The explosive growth of multimedia data on Internet has created huge opportunities for online video advertising. In this paper, we propose a novel advertising technique called SalAd, which utilizes textual information, visual content and the webpage saliency, to automatically associate the most suitable companion ads with online videos. Unlike most existing approaches that only focus on selecting the most relevant ads, SalAd further considers the saliency of selected ads to reduce intentional ignorance. SalAd consists of three basic steps. Given an online video and a set of advertisements, we first roughly identify a set of relevant ads based on the …

An Immersive Telepresence System Using Rgb-D Sensors And Head-Mounted Display, Xinzhong Lu, Ju Shen, Saverio Perugini, Jianjun Yang

Computer Science Faculty Publications

We present a tele-immersive system that enables people to interact with each other in a virtual world using body gestures in addition to verbal communication. Beyond the obvious applications, including general online conversations and gaming, we hypothesize that our proposed system would be particularly beneficial to education by offering rich visual contents and interactivity. One distinct feature is the integration of egocentric pose recognition that allows participants to use their gestures to demonstrate and manipulate virtual objects simultaneously. This functionality enables the instructor to effectively and efficiently explain and illustrate complex concepts or sophisticated problems in an intuitive manner. The …

The Digital Incunabula: Rock • Paper • Pixels, Patrick Aievoli

Zea E-Books Collection

“The Digital Incunabula is Patrick Aievoli’s personal sonnet through media, interaction and communication design. He carefully crafts each evolutionary step into ripples that are supported by his own storied professional and academic experiences. It’s full of facts, terms and historical information which makes it perfect for anyone looking to flat out learn!” ● James Pannafino, Professor, Millersville University & Interaction Design

“This is a serious work that will find a broad community of readers. The depth and breadth of Aievoli’s experience in the publication industry give his voice and ideas credibility in the extreme. This book will inspire deep reflection.” …

A-Maze-D: Advanced Maze Development Kit Using Constraint Databases, Shruti Daggumarti, Peter Revesz, Corey Svehla

School of Computing: Conference and Workshop Papers

In this paper, we describe the A-Maze-D system which shows that constraint databases can be applied conveniently and efficiently to the design of maze games. A-Maze-D provides a versatile set of features by a combination of a MATLAB library and the MLPQ constraint database system. A-Maze-D is the first system that uses constraint databases to build maze games and opens new ideas in video game development.

Sense Beyond Expressions: Cuteness, Kang Wang, Tam Nguyen, Jiashi Feng, Jose Sepulveda

Computer Science Faculty Publications

With the development of Internet culture, cute has become a popular concept. Many people are curious about what factors making a person look cute. However, there is rare research to answer this interesting question. In this work, we construct a dataset of personal images with comprehensively annotated cuteness scores and facial attributes to investigate this high-level concept in depth. Based on this dataset, through an automatic attributes mining process, we find several critical attributes determining the cuteness of a person.

We also develop a novel Continuous Latent Support Vector Machine (C-LSVM) method to predict the cuteness score of one person …

Adaptive Nonparametric Image Parsing, Tam Nguyen, Canyi Lu, Jose Sepulveda, Shuicheng Yan

Computer Science Faculty Publications

In this paper, we present an adaptive nonparametric solution to the image parsing task, namely, annotating each image pixel with its corresponding category label. For a given test image, first, a locality-aware retrieval set is extracted from the training data based on superpixel matching similarities, which are augmented with feature extraction for better differentiation of local superpixels. Then, the category of each superpixel is initialized by the majority vote of the k -nearest-neighbor superpixels in the retrieval set. Instead of fixing k as in traditional nonparametric approaches, here, we propose a novel adaptive nonparametric approach that determines the sample-specific k …

An Interactive User Interface Improves Data Visualization In R, Nathan Sweem

STAR Program Research Presentations

An interactive user interface application was created using the R statistical computing environment and the Shiny package to visualize historical data on the performance of mutual funds and exchange-traded funds (ETFs). Historical data for these funds is scraped from the Yahoo! Finance webpage. The application allows the user to analyze this historical data by category and fund family, which are also scraped from Yahoo! Finance. The application generates interactive plots to compare the performance of selected mutual funds and ETFs given the baseline and center determined by the user. The application has been modified to attentively match the data with …

Teaching Big Data By Three Levels Of Projects, Jianjun Yang, Ju Shen

Computer Science Faculty Publications

Big Data is a new topic and it is very hot nowadays. However, it is difficult to teach Big Data effectively by regular lecture. In this paper, we present a unique way to teach students Big Data by developing three levels of projects from easy to difficult. The three levels projects are initializing project, designing project, and comprehensive projects. They are developed to involve students in Big Data, train students' skills to analyze concrete problems of Big Data, and develop students' creative abilities and their abilities to solve real setting problems.

Automatic Video Self Modeling For Voice Disorder, Ju Shen, Changpeng Ti, Anusha Raghunathan, Sen-Ching S. Cheung, Rita Patel

Computer Science Faculty Publications

Video self modeling (VSM) is a behavioral intervention technique in which a learner models a target behavior by watching a video of him- or herself. In the field of speech language pathology, the approach of VSM has been successfully used for treatment of language in children with Autism and in individuals with fluency disorder of stuttering. Technical challenges remain in creating VSM contents that depict previously unseen behaviors. In this paper, we propose a novel system that synthesizes new video sequences for VSM treatment of patients with voice disorders. Starting with a video recording of a voice-disorder patient, the proposed …

Salient Object Detection Via Augmented Hypotheses, Tam Nguyen, Jose Sepulveda

Computer Science Faculty Publications

In this paper, we propose using augmented hypotheses which consider objectness, foreground, and compactness for salient object detection. Our algorithm consists of four basic steps. First, our method generates the objectness map via objectness hypotheses. Based on the objectness map, we estimate the foreground margin and compute the corresponding foreground map which prefers the foreground objects. From the objectness map and the foreground map, the compactness map is formed to favor the compact objects. We then derive a saliency measure that produces a pixel-accurate saliency map which uniformly covers the objects of interest and consistently separates foreground and background.

We …

Between Worlds: Securing Mixed Javascript/Actionscript Multi-Party Web Content, Phu Huu Phung, Maliheh Monshizadeh, Meera Sridhar, Kevin W. Hamlen, V. N. Venkatakrishnan

Computer Science Faculty Publications

Mixed Flash and JavaScript content has become increasingly prevalent; its purveyance of dynamic features unique to each platform has popularized it for myriad Web development projects. Although Flash and JavaScript security has been examined extensively, the security of untrusted content that combines both has received considerably less attention. This article considers this fusion in detail, outlining several practical scenarios that threaten the security of Web applications. The severity of these attacks warrants the development of new techniques that address the security of Flash-JavaScript content considered as a whole, in contrast to prior solutions that have examined Flash or JavaScript security …

Compression Of Video Tracking And Bandwidth Balancing Routing In Wireless Multimedia Sensor Networks, Yin Wang, Jianjun Yang, Ju Shen, Bryson Payne, Juan Guo, Kun Hua

Computer Science Faculty Publications

There has been a tremendous growth in multimedia applications over wireless networks. Wireless Multimedia Sensor Networks(WMSNs) have become the premier choice in many research communities and industry. Many state-of-art applications, such as surveillance, traffic monitoring, and remote heath care are essentially video tracking and transmission in WMSNs. The transmission speed is constrained by the big file size of video data and fixed bandwidth allocation in constant routing paths. In this paper, we present a CamShift based algorithm to compress the tracking of videos. Then we propose a bandwidth balancing strategy in which each sensor node is able to dynamically select …

Leading Undergraduate Students To Big Data Generation, Jianjun Yang, Ju Shen

Computer Science Faculty Publications

People are facing a flood of data today. Data are being collected at unprecedented scale in many areas, such as networking, image processing, virtualization, scientific computation, and algorithms. The huge data nowadays are called Big Data. Big data is an all encompassing term for any collection of data sets so large and complex that it becomes difficult to process them using traditional data processing applications. In this article, the authors present a unique way which uses network simulator and tools of image processing to train students abilities to learn, analyze, manipulate, and apply Big Data. Thus they develop students hands-on …

Hole Detection And Shape-Free Representation And Double Landmarks Based Geographic Routing In Wireless Sensor Networks, Jianjun Yang, Zongming Fei, Ju Shen

Computer Science Faculty Publications

In wireless sensor networks, an important issue of geographic routing is “local minimum” problem, which is caused by a “hole” that blocks the greedy forwarding process. Existing geographic routing algorithms use perimeter routing strategies to find a long detour path when such a situation occurs. To avoid the long detour path, recent research focuses on detecting the hole in advance, then the nodes located on the boundary of the hole advertise the hole information to the nodes near the hole. Hence the long detour path can be avoided in future routing. We propose a heuristic hole detecting algorithm which identifies …

Perfect Graphs, Chinh T. Hoang, R. Sritharan

Computer Science Faculty Publications

This chapter is a survey on perfect graphs with an algorithmic flavor. Our emphasis is on important classes of perfect graphs for which there are fast and efficient recognition and optimization algorithms. The classes of graphs we discuss in this chapter are chordal, comparability, interval, perfectly orderable, weakly chordal, perfectly contractile, and chi-bound graphs. For each of these classes, when appropriate, we discuss the complexity of the recognition algorithm and algorithms for finding a minimum coloring, and a largest clique in the graph and its complement.

Salient Object Detection Via Objectness Proposals, Tam Nguyen

Computer Science Faculty Publications

Salient object detection has gradually become a popular topic in robotics and computer vision research. This paper presents a real-time system that detects salient objects by integrating objectness, foreground, and compactness measures. Our algorithm consists of four basic steps. First, our method generates the objectness map via object proposals. Based on the objectness map, we estimate the background margin and compute the corresponding foreground map which prefers the foreground objects. From the objectness map and the foreground map, the compactness map is formed to favor the compact objects. We then integrate those cues to form a pixel-accurate saliency map which …

Metalogic Notes, Saverio Perugini

Computer Science Working Papers

A collection of notes, formulas, theorems, postulates and terminology in symbolic logic, syntactic notions, semantic notions, linkages between syntax and semantics, soundness and completeness, quantified logic, first-order theories, Goedel's First Incompleteness Theorem and more.

Statistics Notes, Saverio Perugini

Computer Science Working Papers

A collection of terms, definitions, formulas and explanations about statistics.

Choice Of Human–Computer Interaction Mode In Stroke Rehabilitation, Hossein Mousavi Hondori, Maryam Khademi, Lucy Dodakian, Alison Mackenzie, Cristina V. Lopes, Steven C. Cramer

Physical Therapy Faculty Articles and Research

Background and Objective. Advances in technology are providing new forms of human–computer interaction. The current study examined one form of human–computer interaction, augmented reality (AR), whereby subjects train in the real-world workspace with virtual objects projected by the computer. Motor performances were compared with those obtained while subjects used a traditional human–computer interaction, that is, a personal computer (PC) with a mouse. Methods. Patients used goal-directed arm movements to play AR and PC versions of the Fruit Ninja video game. The 2 versions required the same arm movements to control the game but had different cognitive demands. With …

Designing A Bayer Filter With Smooth Hue Transition Interpolation Using The Xilinx System Generator, Zhiqiang Li, Peter Revesz

School of Computing: Conference and Workshop Papers

This paper describes the design of a Bayer filter with smooth hue transition using the System Generator for DSP. We describe and compare experimentally two different designs, one based on a MATLAB implementation and the other based on a modification of the Bayer filter using bilinear interpolation.

Taming The Software Chaos: True To Its Promise, Iftdss Eases The Burden Of Fuels Treatment Planning—And Does A Lot More Besides, Gail Wells

Joint Fire Science Program Digests

A key problem reported by the fuels treatment planning community is the difficulty and inefficiency of evaluating and then applying many planning tools and applications. Fuels specialists have struggled to find, load, and learn all the different fuels and fire planning models, not to mention the interface of running, adjusting, and inputting data specific to each model without the ability to easily share inputs/outputs between models.

The Interagency Fuels Treatment Decision Support System (IFTDSS) was conceived as a way for users to learn one interface, access a variety of data and models all in one place, and pass data (inputs …

Seeing Human Weight From A Single Rgb-D Image, Tam Nguyen, Jiashi Feng, Shuicheng Yan

Computer Science Faculty Publications

Human weight estimation is useful in a variety of potential applications, e.g., targeted advertisement, entertainment scenarios and forensic science. However, estimating weight only from color cues is particularly challenging since these cues are quite sensitive to lighting and imaging conditions. In this article, we propose a novel weight estimator based on a single RGB-D image, which utilizes the visual color cues and depth information. Our main contributions are three-fold.

First, we construct the W8-RGBD dataset including RGB-D images of different people with ground truth weight.

Second, the novel sideview shape feature and the feature fusion model are proposed to facilitate …

Structure Preserving Large Imagery Reconstruction, Ju Shen, Jianjun Yang, Sami Taha Abu Sneineh, Bryson Payne, Markus Hitz

Computer Science Faculty Publications

With the explosive growth of web-based cameras and mobile devices, billions of photographs are uploaded to the internet. We can trivially collect a huge number of photo streams for various goals, such as image clustering, 3D scene reconstruction, and other big data applications. However, such tasks are not easy due to the fact the retrieved photos can have large variations in their view perspectives, resolutions, lighting, noises, and distortions. Furthermore, with the occlusion of unexpected objects like people, vehicles, it is even more challenging to find feature correspondences and reconstruct realistic scenes. In this paper, we propose a structure-based image …