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Feature Extraction To Improve Nowcasting Using Social Media Event Detection On Cloud Computing And Sentiment Analysis, David L. Kimmey 2016 Indiana University - Purdue University Fort Wayne

Feature Extraction To Improve Nowcasting Using Social Media Event Detection On Cloud Computing And Sentiment Analysis, David L. Kimmey

Masters' Theses

Nowcasting is defined as the prediction of the present, the very near future, and the very recent past using real-time data. Nowcasting with social media creates challenges because of the HACE characteristics of big data (i.e., heterogeneous, autonomous, complex, and evolving associations). Thus, this thesis proposes a feature extraction method to improve nowcasting with social media. The proposed social media event detection algorithm utilizes K-SPRE methodology and the results are processed with sentiment analysis. In addition, we develop a parallel algorithm of the methodology on a cloud environment, and we adapt an artificial neural network to build a predictive ...


Latent Semantic Indexing In The Discovery Of Cyber-Bullying In Online Text, Jacob L. Bigelow 2016 Ursinus College

Latent Semantic Indexing In The Discovery Of Cyber-Bullying In Online Text, Jacob L. Bigelow

Computer Science Summer Fellows

The rise in the use of social media and particularly the rise of adolescent use has led to a new means of bullying. Cyber-bullying has proven consequential to youth internet users causing a need for a response. In order to effectively stop this problem we need a verified method of detecting cyber-bullying in online text; we aim to find that method. For this project we look at thirteen thousand labeled posts from Formspring and create a bank of words used in the posts. First the posts are cleaned up by taking out punctuation, normalizing emoticons, and removing high and low ...


Detection Of Cyberbullying In Sms Messaging, Bryan W. Bradley 2016 Ursinus College

Detection Of Cyberbullying In Sms Messaging, Bryan W. Bradley

Computer Science Summer Fellows

Cyberbullying is a type of bullying that uses technology such as cell phones to harass or malign another person. To detect acts of cyberbullying, we are developing an algorithm that will detect cyberbullying in SMS (text) messages. Over 80,000 text messages have been collected by software installed on cell phones carried by participants in our study. This paper describes the development of the algorithm to detect cyberbullying messages, using the cell phone data collected previously. The algorithm works by first separating the messages into conversations in an automated way. The algorithm then analyzes the conversations and scores the severity ...


Formalization Of The Ad Hominem Argumentation Scheme, Douglas Walton 2016 University of Windsor

Formalization Of The Ad Hominem Argumentation Scheme, Douglas Walton

Douglas Walton

In this paper, several examples from the literature, and one central new one, are used as case studies of texts of discourse containing an argumentation scheme that has now been widely investigated in literature on argumentation. Argumentation schemes represent common patterns of reasoning used in everyday conversational discourse. The most typical ones represent defeasible arguments based on nonmonotonic reasoning. Each scheme has a matching set of critical questions used to evaluate a particular argument fitting that scheme. The project is to study how to build a formal computational model of this scheme for the circumstantial ad hominem argument using argumentation ...


Signal Processing Based On Stable Radix-2 Dct I-Iv Algorithms Having Orthogonal Factors, Sirani K. M. Perera 2016 Embry-Riddle Aeronautical University - Daytona Beach

Signal Processing Based On Stable Radix-2 Dct I-Iv Algorithms Having Orthogonal Factors, Sirani K. M. Perera

Electronic Journal of Linear Algebra

This paper presents stable, radix-2, completely recursive discrete cosine transform algorithms DCT-I and DCT-III solely based on DCT-I, DCT-II, DCT-III, and DCT-IV having sparse and orthogonal factors. Error bounds for computing the completely recursive DCT-I, DCT-II, DCT-III, and DCT-IV algorithms having sparse and orthogonal factors are addressed. Signal flow graphs are demonstrated based on the completely recursive DCT-I, DCT-II, DCT-III, and DCT-IV algorithms having orthogonal factors. Finally image compression results are presented based on the recursive 2D DCT-II and DCT-IV algorithms for image size 512 by 512 pixels with transfer block sizes 8 by 8, 16 by 16, and 32 ...


Packet Filter Approach To Detect Denial Of Service Attacks, Essa Yahya M Muharish 2016 California State University, San Bernardino

Packet Filter Approach To Detect Denial Of Service Attacks, Essa Yahya M Muharish

Electronic Theses, Projects, and Dissertations

Denial of service attacks (DoS) are a common threat to many online services. These attacks aim to overcome the availability of an online service with massive traffic from multiple sources. By spoofing legitimate users, an attacker floods a target system with a high quantity of packets or connections to crash its network resources, bandwidth, equipment, or servers. Packet filtering methods are the most known way to prevent these attacks via identifying and blocking the spoofed attack from reaching its target. In this project, the extent of the DoS attacks problem and attempts to prevent it are explored. The attacks categories ...


The Contributions Of Anatol Rapoport To Game Theory, Erika Simpson 2016 Western University

The Contributions Of Anatol Rapoport To Game Theory, Erika Simpson

Political Science Publications

Game theory is used to rationally and dispassionately examine the strategic behaviour of nations, especially superpower behaviour. This article explains how basic game theory - at its simplest level - was used by Anatol Rapoport to generate ideas about how to enhance world peace. Rapoport was at the forefront of the game theoreticians who sought to conceptualize strategies that could promote international cooperation. Accordingly, the basic logic of game theory is explained using the game models of ‘Chicken’ and ‘Prisoner’s Dilemma’. These models were used by Rapoport in his books and lectures in simple and complex ways. Then Rapoport’s revolutionary ...


Applying Novelty Search To The Construction Of Ensemble Systems, Hieu Kinh Le 2016 Dickinson College

Applying Novelty Search To The Construction Of Ensemble Systems, Hieu Kinh Le

Honors Theses By Year

Ensemble methods are widely applied in classification problems. Ensemble methods combine results from multiple classifiers to overcome the possible deficiency of any single classifier. One important question is how to construct an ensemble system so that it can utilize all individuals most efficiently to improve classification results. An ensemble system thus needs some level of diversity in terms of error among individuals to avoid group mistakes. Novelty Search is a recently published approach in evolutionary computation in which individuals evolve based on a novelty metric, which evaluates how different their behavior is in addition to an objective metric that shows ...


Whiteboard Scanning Using Super-Resolution, Wode Ni 2016 Dickinson College

Whiteboard Scanning Using Super-Resolution, Wode Ni

Honors Theses By Year

In this project, we investigated the effectiveness of the Super-Resolution algorithm on a distant whiteboard scenario. Imagine a person taking a video or an image sequence of a whiteboard from a distance. Due to the limitation of camera resolution and the distance, the words in the whiteboard images are sometimes illegible. Though there exist applications to enhance the image quality, the resolution limit caused by the distance is difficult to overcome. Super-resolution, a class of techniques in the field of Computer Vision, enables us to enhance the quality of the images by utilizing the information of multiple low quality images ...


Pain Management: Formal Verification Of An Android Application Using Eventb2sql, Graham Peter Williams 2016 Dickinson College

Pain Management: Formal Verification Of An Android Application Using Eventb2sql, Graham Peter Williams

Honors Theses By Year

This project is a case study on formal verification of an Android application used for pain management. When it comes to healthcare applications, the consistency of the application is crucial, as it may affect the wellbeing of the user. The application will check for trends in the user reports of pain, stress, etc. and notify the user accordingly. The model that specifies these trends is defined in Event-B using an Eclipse-based IDE called Rodin. We used the automated and interactive theorem provers built into Rodin to verify that the model always gives the user consistent information. The Event-B model is ...


Identifying Relationships Between Scientific Datasets, Abdussalam Alawini 2016 Portland State University

Identifying Relationships Between Scientific Datasets, Abdussalam Alawini

Dissertations and Theses

Scientific datasets associated with a research project can proliferate over time as a result of activities such as sharing datasets among collaborators, extending existing datasets with new measurements, and extracting subsets of data for analysis. As such datasets begin to accumulate, it becomes increasingly difficult for a scientist to keep track of their derivation history, which complicates data sharing, provenance tracking, and scientific reproducibility. Understanding what relationships exist between datasets can help scientists recall their original derivation history. For instance, if dataset A is contained in dataset B, then the connection between A and B could be that A was ...


Ant Colony Optimization For Continuous Spaces, Rachel Findley 2016 University of Arkansas, Fayetteville

Ant Colony Optimization For Continuous Spaces, Rachel Findley

Computer Science and Computer Engineering Undergraduate Honors Theses

Ant Colony Optimization (ACO) is an optimization algorithm designed to find semi-optimal solutions to Combinatorial Optimization Problems. The challenge of modifying this algorithm to effectively optimize over a continuous domain is one that has been tackled by several researchers. In this paper, ACO has been modified to use several variations of the algorithm for continuous spaces. An aspect of ACO which is crucial to its success when optimizing over a continuous space is choosing the appropriate object (solution component) out of an infinite set to add to the ant's path. This step is highly important in shaping good solutions ...


Sparse Feature Learning For Image Analysis In Segmentation, Classification, And Disease Diagnosis., Ehsan Hosseini-Asl 2016 University of Louisville

Sparse Feature Learning For Image Analysis In Segmentation, Classification, And Disease Diagnosis., Ehsan Hosseini-Asl

Electronic Theses and Dissertations

The success of machine learning algorithms generally depends on intermediate data representation, called features that disentangle the hidden factors of variation in data. Moreover, machine learning models are required to be generalized, in order to reduce the specificity or bias toward the training dataset. Unsupervised feature learning is useful in taking advantage of large amount of unlabeled data, which is available to capture these variations. However, learned features are required to capture variational patterns in data space. In this dissertation, unsupervised feature learning with sparsity is investigated for sparse and local feature extraction with application to lung segmentation, interpretable deep ...


User Interface Design, Moritz Stefaner, Sebastien Ferre, Saverio Perugini, Jonathan Koren, Yi Zhang 2016 University of Dayton

User Interface Design, Moritz Stefaner, Sebastien Ferre, Saverio Perugini, Jonathan Koren, Yi Zhang

Saverio Perugini

As detailed in Chap. 1, system implementations for dynamic taxonomies and faceted search allow a wide range of query possibilities on the data. Only when these are made accessible by appropriate user interfaces, the resulting applications can support a variety of search, browsing and analysis tasks. User interface design in this area is confronted with specific challenges. This chapter presents an overview of both established and novel principles and solutions.


Program Transformations For Information Personalization, Saverio Perugini, Naren Ramakrishnan 2016 University of Dayton

Program Transformations For Information Personalization, Saverio Perugini, Naren Ramakrishnan

Saverio Perugini

Personalization constitutes the mechanisms necessary to automatically customize information content, structure, and presentation to the end user to reduce information overload. Unlike traditional approaches to personalization, the central theme of our approach is to model a website as a program and conduct website transformation for personalization by program transformation (e.g., partial evaluation, program slicing). The goal of this paper is study personalization through a program transformation lens and develop a formal model, based on program transformations, for personalized interaction with hierarchical hypermedia. The specific research issues addressed involve identifying and developing program representations and transformations suitable for classes of ...


A Study Of Android Malware Detection Techniques And Machine Learning, Balaji Baskaran, Anca Ralescu 2016 University of Cincinnati - Main Campus

A Study Of Android Malware Detection Techniques And Machine Learning, Balaji Baskaran, Anca Ralescu

MAICS: The Modern Artificial Intelligence and Cognitive Science Conference

Android OS is one of the widely used mobile Operating Systems. The number of malicious applications and adwares are increasing constantly on par with the number of mobile devices. A great number of commercial signature based tools are available on the market which prevent to an extent the penetration and distribution of malicious applications. Numerous researches have been conducted which claims that traditional signature based detection system work well up to certain level and malware authors use numerous techniques to evade these tools. So given this state of affairs, there is an increasing need for an alternative, really tough malware ...


Extended Pixel Representation For Image Segmentation, Deeptha Girish, Vineeta Singh, Anca Ralescu 2016 University of Cincinnati - Main Campus

Extended Pixel Representation For Image Segmentation, Deeptha Girish, Vineeta Singh, Anca Ralescu

MAICS: The Modern Artificial Intelligence and Cognitive Science Conference

We explore the use of extended pixel representation for color based image segmentation using the K-means clustering algorithm. Various extended pixel representations have been implemented in this paper and their results have been compared. By extending the representation of pixels an image is mapped to a higher dimensional space. Unlike other approaches, where data is mapped into an implicit features space of higher dimension (kernel methods), in the approach considered here, the higher dimensions are defined explicitly. Preliminary experimental results which illustrate the proposed approach are promising.


An Autonomic Computing System Based On A Rule-Based Policy Engine And Artificial Immune Systems, Rahmira Rufus, William Nick, Joseph Shelton, Albert Esterline 2016 North Carolina A & T State University

An Autonomic Computing System Based On A Rule-Based Policy Engine And Artificial Immune Systems, Rahmira Rufus, William Nick, Joseph Shelton, Albert Esterline

MAICS: The Modern Artificial Intelligence and Cognitive Science Conference

Autonomic computing systems arose from the notion that complex computing systems should have properties like those of the autonomic nervous system, which coordinates bodily functions and allows attention to be directed to more pressing needs. An autonomic system allows the system administrator to specify high-level policies, which the system maintains without administrator assistance. Policy enforcement can be done with a rule based system such as Jess (a java expert system shell). An autonomic system must be able to monitor itself, and this is often a limiting factor. We are developing an automatic system that has a policy engine and uses ...


Towards The Development Of A Cyber Analysis & Advisement Tool (Caat) For Mitigating De-Anonymization Attacks, Siobahn Day, Henry Williams, Joseph Shelton, Gerry Dozier 2016 North Carolina A & T State University

Towards The Development Of A Cyber Analysis & Advisement Tool (Caat) For Mitigating De-Anonymization Attacks, Siobahn Day, Henry Williams, Joseph Shelton, Gerry Dozier

MAICS: The Modern Artificial Intelligence and Cognitive Science Conference

We are seeing a rise in the number of Anonymous Social Networks (ASN) that claim to provide a sense of user anonymity. However, what many users of ASNs do not know that a person can be identified by their writing style.

In this paper, we provide an overview of a number of author concealment techniques, their impact on the semantic meaning of an author's original text, and introduce AuthorCAAT, an application for mitigating de-anonymization attacks. Our results show that iterative paraphrasing performs the best in terms of author concealment and performs well with respect to Latent Semantic Analysis.


Situations And Evidence For Identity Using Dempster-Shafer Theory, William Nick, Yenny Dominguez, Albert Esterline 2016 North Carolina A & T State University

Situations And Evidence For Identity Using Dempster-Shafer Theory, William Nick, Yenny Dominguez, Albert Esterline

MAICS: The Modern Artificial Intelligence and Cognitive Science Conference

We present a computational framework for identity based on Barwise and Devlin’s situation theory. We present an example with constellations of situations identifying an individual to create what we call id-situations, where id-actions are performed, along with supporting situations. We use Semantic Web standards to represent and reason about the situations in our example. We show how to represent the strength of the evidence, within the situations, as a measure of the support for judgments reached in the id-situation. To measure evidence of an identity from the supporting situations, we use the Dempster-Shafer theory of evidence. We enhance Dempster- ...


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