On Abstract Modular Inference Systems And Solvers, 2016 University of Nebraska at Omaha
On Abstract Modular Inference Systems And Solvers, Yuliya Lierler, Miroslaw Truszczyński
Computer Science Faculty Publications
Integrating diverse formalisms into modular knowledge representation systems offers increased expressivity, modeling convenience, and computational benefits. We introduce the concepts of abstract inference modules and abstract modular inference systems to study general principles behind the design and analysis of model generating programs, or solvers, for integrated multi-logic systems. We show how modules and modular systems give rise to transition graphs, which are a natural and convenient representation of solvers, an idea pioneered by the SAT community. These graphs lend themselves well to extensions that capture such important solver design features as learning. In the paper, we consider two flavors of ...
Factors That Affect Information And Communication Technology Adoption By Small Businesses In China, 2016 University of Nebraska at Omaha
Factors That Affect Information And Communication Technology Adoption By Small Businesses In China, Jie Xiong, Sajda Qureshi, Lotfollah Najjar
Emerging economies appear to be powering growth in their regions. While China is seen to lead growth in the emerging markets of Asia, 98% of its manufacturing and production base is powered by small businesses. These businesses represent the majority of all businesses in emerging countries and their growth increases with their successful adoption of Information Technology. As the driving force behind the economic growth of China, Information and Communications Technologies (ICTs) are shaping the ways in which small businesses are able to grow. The majority of current research into the user acceptance and adoption of ICTs focusses on the ...
A Model Of Icts Adoption For Sustainable Development: An Investigation Of Small Business In The United States And China, 2016 University of Nebraska at Omaha
A Model Of Icts Adoption For Sustainable Development: An Investigation Of Small Business In The United States And China, Jie Xiong, Sajda Qureshi
No abstract provided.
Can Information And Communication Technologies Lead To Community Capital? An Analysis Of Development, 2016 University of Nebraska at Omaha
Can Information And Communication Technologies Lead To Community Capital? An Analysis Of Development, Dave Kocsis, Sajda Qureshi, Jie Xiong
While it is widely accepted that the increasing interconnectedness of the world economy has been fueled by the innovative uses of Information and Communication Technologies (ICTs), little attention has been paid to the increasing inequalities within developed and developing countries. These inequalities manifest themselves in the form of communities in which incomes are considerably below the rest of the country and there is a rise in poverty. This paper investigates this trend by taking a community capital perspective to investigate how ICTs may or may not enable businesses to grow. As micro-enterprises are seen to contribute to the growth of ...
Factors Affecting Information And Communications Technology Adoption Of Small Businesses: Studies In China And United States, 2016 University of Nebraska at Omaha
Factors Affecting Information And Communications Technology Adoption Of Small Businesses: Studies In China And United States, Jie Xiong, Sajda Qureshi
Small businesses in China and United States generate the largest share of economic activity and employment. As the driving force behind the economic growth of both countries, Information and Communications Technology (ICTs) has fundamentally shaped the two countries. This research-in-progress paper reports the research model we conduct to analyze the factors that will affect ICTs adoption of small businesses in both countries. The purpose of the paper is to (1) report proposals of the current status of the research project (2) build an understanding of ICTs adoption in both countries (3) build the framework to explore the relationship between ICTs ...
Rasp-Qs: Efficient And Confidential Query Services In The Cloud, 2016 Wright State University - Main Campus
Rasp-Qs: Efficient And Confidential Query Services In The Cloud, Zohreh S. Alavi, Lu Zhou, James L. Powers, Keke Chen
Hosting data query services in public clouds is an attractive solution for its great scalability and significant cost savings. However, data owners also have concerns on data privacy due to the lost control of the infrastructure. This demonstration shows a prototype for efficient and confidential range/kNN query services built on top of the random space perturbation (RASP) method. The RASP approach provides a privacy guarantee practical to the setting of cloudbased computing, while enabling much faster query processing compared to the encryption-based approach. This demonstration will allow users to more intuitively understand the technical merits of the RASP approach ...
Two Roads, One Destination: A Journey Of Discovery, 2016 Bond University
Two Roads, One Destination: A Journey Of Discovery, Karen Joc, Peta J. Hopkins, Jessie Donaghey, Wendy Abbott
The adoption of resource discovery platforms has been a growing trend in libraries. However, few libraries have reported on the transition from one discovery layer to another, and only a few institutions have discussed two discovery layers available in the same institution at the same time. Bond University Library recently implemented Alma as its library management system, and with this change a new discovery platform, Primo, was implemented to supersede the existing Summon platform. This paper presents the results of a usability study undertaken at Bond University Library in the move from one discovery layer to another.
Energy Consumption Prediction With Big Data: Balancing Prediction Accuracy And Computational Resources, Katarina Grolinger, Miriam Am Capretz, Luke Seewald
Electrical and Computer Engineering Publications
In recent years, advances in sensor technologies and expansion of smart meters have resulted in massive growth of energy data sets. These Big Data have created new opportunities for energy prediction, but at the same time, they impose new challenges for traditional technologies. On the other hand, new approaches for handling and processing these Big Data have emerged, such as MapReduce, Spark, Storm, and Oxdata H2O. This paper explores how findings from machine learning with Big Data can benefit energy consumption prediction. An approach based on local learning with support vector regression (SVR) is presented. Although local learning itself is ...
Using A Data Quality Framework To Clean Data Extracted From The Electronic Health Record: A Case Study., 2016 University of Colorado, College of Nursing, Anschutz Medical Campus
Using A Data Quality Framework To Clean Data Extracted From The Electronic Health Record: A Case Study., Oliwier Dziadkowiec, Tiffany Callahan, Mustafa Ozkaynak, Blaine Reeder, John Welton
eGEMs (Generating Evidence & Methods to improve patient outcomes)
Objectives: Examine (1) the appropriateness of using a data quality (DQ) framework developed for relational databases as a data-cleaning tool for a dataset extracted from two EPIC databases; and (2) the differences in statistical parameter estimates on a dataset cleaned with the DQ framework and dataset not cleaned with the DQ framework.
Background: The use of data contained within electronic health records (EHRs) has the potential to open doors for a new wave of innovative research. Without adequate preparation of such large datasets for analysis, the results might be erroneous, which might affect clinical decision making or results of Comparative ...
Exploring The Human Body Space: A Geographical Information System Based Anatomical Atlas, 2016 The University of Maine
Exploring The Human Body Space: A Geographical Information System Based Anatomical Atlas, Antonio Barbeito, Marco Painho, Pedro Cabral, João Goyri O'Neill
Journal of Spatial Information Science
Anatomical atlases allow mapping the anatomical structures of the human body. Early versions of these systems consisted of analogical representations with informative text and labeled images of the human body. With computer systems, digital versions emerged and the third and fourth dimensions were introduced. Consequently, these systems increased their efficiency, allowing more realistic visualizations with improved interactivity and functionality. The 4D atlases allow modeling changes over time on the structures represented. The anatomical atlases based on geographic information system (GIS) environments allow the creation of platforms with a high degree of interactivity and new tools to explore and analyze the ...
A Context-Sensitive Conceptual Framework For Activity Modeling, 2016 The University of Maine
A Context-Sensitive Conceptual Framework For Activity Modeling, Rahul Deb Das, Stephan Winter
Journal of Spatial Information Science
Human motion trajectories, however captured, provide a rich spatiotemporal data source for human activity recognition, and the rich literature in motion trajectory analysis provides the tools to bridge the gap between this data and its semantic interpretation. But activity is an ambiguous term across research communities. For example, in urban transport research activities are generally characterized around certain locations assuming the opportunities and resources are present in that location, and traveling happens between these locations for activity participation, i.e., travel is not an activity, rather a mean to overcome spatial constraints. In contrast, in human-computer interaction (HCI) research and ...
Μ-Shapes: Delineating Urban Neighborhoods Using Volunteered Geographic Information, 2016 The University of Maine
Μ-Shapes: Delineating Urban Neighborhoods Using Volunteered Geographic Information, Matt Aadland, Christopher Farah, Kevin Magee
Journal of Spatial Information Science
Urban neighborhoods are a unique form of geography in that their boundaries rely on a social definition rather than a well-defined physical or administrative boundary. Currently, geographic gazetteers capture little more than then the centroid of a neighborhood, limiting potential applications of the data. In this paper, we present µ-shapes, an algorithm that employs fuzzy-set theory to model neighborhood boundaries suitable for populating gazetteers using volunteered geographic information (VGI). The algorithm is evaluated using a reference dataset and VGI from the Map Kibera Project. A confusion matrix comparison between the reference dataset and µ-shape's output demonstrated high sensitivity and ...
Creating The 2011 Area Classification For Output Areas (2011 Oac), 2016 The University of Maine
Creating The 2011 Area Classification For Output Areas (2011 Oac), Christopher G. Gale, Alexander D. Singleton, Andrew G. Bates, Paul A. Longley
Journal of Spatial Information Science
This paper presents the methodology that has been used to create the 2011 Area Classification for Output Areas (2011 OAC). This extends a lineage of widely used public domain census-only geodemographic classifications in the UK. It provides an update to the successful 2001 OAC methodology, and summarizes the social and physical structure of neighborhoods using data from the 2011 UK Census. The results of a user engagement exercise that underpinned the creation of an updated methodology for the 2011 OAC are also presented. The 2011 OAC comprises 8 Supergroups, 26 Groups, and 76 Subgroups. An example of the results of ...
Dna Analysis Using Grammatical Inference, 2016 San Jose State University
Dna Analysis Using Grammatical Inference, Cory Cook
An accurate language definition capable of distinguishing between coding and non-coding DNA has important applications and analytical significance to the field of computational biology. The method proposed here uses positive sample grammatical inference and statistical information to infer languages for coding DNA.
An algorithm is proposed for the searching of an optimal subset of input sequences for the inference of regular grammars by optimizing a relevant accuracy metric. The algorithm does not guarantee the finding of the optimal subset; however, testing shows improvement in accuracy and performance over the basis algorithm.
Testing shows that the accuracy of inferred languages for ...
Analysis On Alergia Algorithm: Pattern Recognition By Automata Theory, 2016 San Jose State University
Analysis On Alergia Algorithm: Pattern Recognition By Automata Theory, Xuanyi Qi
Based on Kolmogorov Complexity, a finite set x of strings has a pattern if the set x can be output by a Turing machine of length that is less than minimum of all |x|; this Turing machine, that may not be unique, is called a pattern of the finite set of string. In order to find a pattern of a given finite set of strings (assuming such a pattern exists), the ALERGIA algorithm is used to approximate such a pattern (Turing machine) in terms of finite automata. Note that each finite automaton defines a partition on formal language Σ*, ALERGIA ...
Analyze Large Multidimensional Datasets Using Algebraic Topology, 2016 San Jose State University
Analyze Large Multidimensional Datasets Using Algebraic Topology, David Le
This paper presents an efficient algorithm to extract knowledge from high-dimensionality, high- complexity datasets using algebraic topology, namely simplicial complexes. Based on concept of isomorphism of relations, our method turn a relational table into a geometric object (a simplicial complex is a polyhedron). So, conceptually association rule searching is turned into a geometric traversal problem. By leveraging on the core concepts behind Simplicial Complex, we use a new technique (in computer science) that improves the performance over existing methods and uses far less memory. It was designed and developed with a strong emphasis on scalability, reliability, and extensibility. This paper ...
Signal Processing Based On Stable Radix-2 Dct I-Iv Algorithms Having Orthogonal Factors, 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 ...
Machine Learning On The Cloud For Pattern Recognition, 2016 San Jose State University
Machine Learning On The Cloud For Pattern Recognition, Tien Nguyen
Pattern recognition is a field of machine learning with applications to areas such as text recognition and computer vision. Machine learning algorithms, such as convolutional neural networks, may be trained to classify images. However, such tasks may be computationally intensive for a commercial computer for larger volumes or larger sizes of images. Cloud computing allows one to overcome the processing and memory constraints of average commercial computers, allowing computations on larger amounts of data. In this project, we developed a system for detection and tracking of moving human and vehicle objects in videos in real time or near real time ...
VigenèRe Score For Malware Detection, 2016 San Jose State University
VigenèRe Score For Malware Detection, Suchita Deshmukh
Previous research has applied classic cryptanalytic techniques to the malware detection problem. Speci cally, scores based on simple substitution cipher cryptanal- ysis and various generalizations have been considered. In this research, we analyze two new malware scoring techniques based on classic cryptanalysis. Our rst ap- proach relies on the Index of Coincidence, which is used, for example, to determine the length of the keyword in a Vigenère ciphertext. We also consider a score based on a more complete cryptanalysis of a Vigenère cipher. We nd that the Vigenère score is competitive with previous statistical-based malware scores.
Static And Dynamic Analysis For Android Malware Detection, 2016 San Jose State University
Static And Dynamic Analysis For Android Malware Detection, Ankita Kapratwar
Static analysis relies on features extracted without executing code, while dynamic analysis extracts features based on code execution (or emulation). In general, static analysis is more e cient, while static analysis is often more informative, particularly in cases of highly obfuscated code. Static analysis of an Android application can rely on features extracted from the manifest le or the Java bytecode, while dynamic analysis of Android applications can deal with features involving dynamic code loading and system calls that are collected while the application is running. In this research, we analyzed the e ectiveness of combining static and dynamic features ...