Open Access. Powered by Scholars. Published by Universities.®
Databases and Information Systems Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Institution
-
- Singapore Management University (7)
- San Jose State University (3)
- University of Dayton (3)
- University of South Florida (2)
- California State University, San Bernardino (1)
-
- City University of New York (CUNY) (1)
- Georgia Southern University (1)
- Selected Works (1)
- SelectedWorks (1)
- The University of Akron (1)
- The University of Southern Mississippi (1)
- University of Connecticut (1)
- University of Nebraska - Lincoln (1)
- University of Tennessee, Knoxville (1)
- Walden University (1)
- Wayne State University (1)
- Keyword
-
- Anomaly Detection (2)
- Big Data (2)
- Clustering (2)
- Computer Science (2)
- 3D Printing (1)
-
- 3D Scanning (1)
- Adaptive Resonance Theory (1)
- Adaptive duty cycle (1)
- Adaptive parameter tuning (1)
- Adaptive resonance theory (1)
- Adaptive resonance theory (ART) (1)
- Additive Manufacturing (1)
- Analytics (1)
- Android Operating System (1)
- Anesthesia Information System (1)
- BLOSUM (1)
- Big social media data (1)
- Bioinformatics (1)
- Biology (1)
- Bootstrap (1)
- Business Intelligence (1)
- CSS3 (1)
- Choice (1)
- Cloud computing (1)
- Command and Control (1)
- Computer Engineering (1)
- Continuous-time Markov chain (1)
- Cybersecurity (1)
- Cyberspace Operations (1)
- Data Mart (1)
- Publication
-
- Research Collection School Of Computing and Information Systems (7)
- Electrical and Computer Engineering Faculty Publications (3)
- Inaugural CSU IR Conference, 2015 (3)
- Chancellor’s Honors Program Projects (1)
- Department of Electrical and Computer Engineering: Faculty Publications (1)
-
- Dissertations (1)
- Electronic Theses and Dissertations (1)
- Electronic Theses, Projects, and Dissertations (1)
- Honors Scholar Theses (1)
- Jeremy Straub (1)
- Military Cyber Affairs (1)
- Publications and Research (1)
- USF Tampa Graduate Theses and Dissertations (1)
- Walden Dissertations and Doctoral Studies (1)
- Wayne State University Dissertations (1)
- Williams Honors College, Honors Research Projects (1)
- Wilson A Higashino (1)
- Publication Type
Articles 1 - 27 of 27
Full-Text Articles in Databases and Information Systems
Data To Decisions For Cyberspace Operations, Steve Stone
Data To Decisions For Cyberspace Operations, Steve Stone
Military Cyber Affairs
In 2011, the United States (U.S.) Department of Defense (DOD) named cyberspace a new operational domain. The U.S. Cyber Command and the Military Services are working to make the cyberspace environment a suitable place for achieving national objectives and enabling military command and control (C2). To effectively conduct cyberspace operations, DOD requires data and analysis of the Mission, Network, and Adversary. However, the DOD’s current data processing and analysis capabilities do not meet mission needs within critical operational timelines. This paper presents a summary of the data processing and analytics necessary to effectively conduct cyberspace operations.
Adaptive Scaling Of Cluster Boundaries For Large-Scale Social Media Data Clustering, Lei Meng, Ah-Hwee Tan, Donald C. Wunsch
Adaptive Scaling Of Cluster Boundaries For Large-Scale Social Media Data Clustering, Lei Meng, Ah-Hwee Tan, Donald C. Wunsch
Research Collection School Of Computing and Information Systems
The large scale and complex nature of social media data raises the need to scale clustering techniques to big data and make them capable of automatically identifying data clusters with few empirical settings. In this paper, we present our investigation and three algorithms based on the fuzzy adaptive resonance theory (Fuzzy ART) that have linear computational complexity, use a single parameter, i.e., the vigilance parameter to identify data clusters, and are robust to modest parameter settings. The contribution of this paper lies in two aspects. First, we theoretically demonstrate how complement coding, commonly known as a normalization method, changes the …
Adaptive Duty Cycling In Sensor Networks With Energy Harvesting Using Continuous-Time Markov Chain And Fluid Models, Ronald Wai Hong Chan, Pengfei Zhang, Ido Nevat, Sai Ganesh Nagarajan, Alvin Cerdena Valera, Hwee Xian Tan
Adaptive Duty Cycling In Sensor Networks With Energy Harvesting Using Continuous-Time Markov Chain And Fluid Models, Ronald Wai Hong Chan, Pengfei Zhang, Ido Nevat, Sai Ganesh Nagarajan, Alvin Cerdena Valera, Hwee Xian Tan
Research Collection School Of Computing and Information Systems
The dynamic and unpredictable nature of energy harvesting sources available for wireless sensor networks, and the time variation in network statistics like packet transmission rates and link qualities, necessitate the use of adaptive duty cycling techniques. Such adaptive control allows sensor nodes to achieve long-run energy neutrality, where energy supply and demand are balanced in a dynamic environment such that the nodes function continuously. In this paper, we develop a new framework enabling an adaptive duty cycling scheme for sensor networks that takes into account the node battery level, ambient energy that can be harvested, and application-level QoS requirements. We …
Lesinn: Detecting Anomalies By Identifying Least Similar Nearest Neighbours, Guansong Pang, Kai Ming Ting, David Albrecht
Lesinn: Detecting Anomalies By Identifying Least Similar Nearest Neighbours, Guansong Pang, Kai Ming Ting, David Albrecht
Research Collection School Of Computing and Information Systems
We introduce the concept of Least Similar Nearest Neighbours (LeSiNN) and use LeSiNN to detect anomalies directly. Although there is an existing method which is a special case of LeSiNN, this paper is the first to clearly articulate the underlying concept, as far as we know. LeSiNN is the first ensemble method which works well with models trained using samples of one instance. LeSiNN has linear time complexity with respect to data size and the number of dimensions, and it is one of the few anomaly detectors which can apply directly to both numeric and categorical data sets. Our extensive …
Spatiotemporal Sensing And Informatics For Complex Systems Monitoring, Fault Identification And Root Cause Diagnostics, Gang Liu
USF Tampa Graduate Theses and Dissertations
In order to cope with system complexity and dynamic environments, modern industries are investing in a variety of sensor networks and data acquisition systems to increase information visibility. Multi-sensor systems bring the proliferation of high-dimensional functional Big Data that capture rich information on the evolving dynamics of natural and engineered processes. With spatially and temporally dense data readily available, there is an urgent need to develop advanced methodologies and associated tools that will enable and assist (i) the handling of the big data communicated by the contemporary complex systems, (ii) the extraction and identification of pertinent knowledge about the environmental …
Bioinformatics Approaches To Single-Cell Analysis In Developmental Biology, Dicle Yalcin, Zeynep M. Hakguder, Hasan H. Otu
Bioinformatics Approaches To Single-Cell Analysis In Developmental Biology, Dicle Yalcin, Zeynep M. Hakguder, Hasan H. Otu
Department of Electrical and Computer Engineering: Faculty Publications
Individual cells within the same population show various degrees of heterogeneity, which may be better handled with single-cell analysis to address biological and clinical questions. Single-cell analysis is especially important in developmental biology as subtle spatial and temporal differences in cells have significant associations with cell fate decisions during differentiation and with the description of a particular state of a cell exhibiting an aberrant phenotype. Biotechnological advances, especially in the area of microfluidics, have led to a robust, massively parallel and multi-dimensional capturing, sorting, and lysis of single-cells and amplification of related macromolecules, which have enabled the use of imaging …
Developing Java Programs On Android Mobile Phones Using Speech Recognition, Santhrushna Gande
Developing Java Programs On Android Mobile Phones Using Speech Recognition, Santhrushna Gande
Electronic Theses, Projects, and Dissertations
Nowadays Android operating system based mobile phones and tablets are widely used and had millions of users around the world. The popularity of this operating system is due to its multi-tasking, ease of access and diverse device options. “Java Programming Speech Recognition Application” is an Android application used for handicapped individuals who are not able or have difficultation to type on a keyboard. This application allows the user to write a compute program (in Java Language) by dictating the words and without using a keyboard. The user needs to speak out the commands and symbols required for his/her program. The …
Neural Modeling Of Sequential Inferences And Learning Over Episodic Memory, Budhitama Subagdja, Ah-Hwee Tan
Neural Modeling Of Sequential Inferences And Learning Over Episodic Memory, Budhitama Subagdja, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Episodic memory is a significant part of cognition for reasoning and decision making. Retrieval in episodic memory depends on the order relationships of memory items which provides flexibility in reasoning and inferences regarding sequential relations for spatio-temporal domain. However, it is still unclear how they are encoded and how they differ from representations in other types of memory like semantic or procedural memory. This paper presents a neural model of sequential representation and inferences on episodic memory. It contrasts with the common views on sequential representation in neural networks that instead of maintaining transitions between events to represent sequences, they …
State Preserving Extreme Learning Machine For Face Recognition, Md. Zahangir Alom, Paheding Sidike, Vijayan K. Asari, Tarek M. Taha
State Preserving Extreme Learning Machine For Face Recognition, Md. Zahangir Alom, Paheding Sidike, Vijayan K. Asari, Tarek M. Taha
Electrical and Computer Engineering Faculty Publications
Extreme Learning Machine (ELM) has been introduced as a new algorithm for training single hidden layer feed-forward neural networks (SLFNs) instead of the classical gradient-based algorithms. Based on the consistency property of data, which enforce similar samples to share similar properties, ELM is a biologically inspired learning algorithm with SLFNs that learns much faster with good generalization and performs well in classification applications. However, the random generation of the weight matrix in current ELM based techniques leads to the possibility of unstable outputs in the learning and testing phases. Therefore, we present a novel approach for computing the weight matrix …
A Modular Approach For Key-Frame Selection In Wide Area Surveillance Video Analysis, Almabrok Essa, Paheding Sidike, Vijayan K. Asari
A Modular Approach For Key-Frame Selection In Wide Area Surveillance Video Analysis, Almabrok Essa, Paheding Sidike, Vijayan K. Asari
Electrical and Computer Engineering Faculty Publications
This paper presents an efficient preprocessing algorithm for big data analysis. Our proposed key-frame selection method utilizes the statistical differences among subsequent frames to automatically select only the frames that contain the desired contextual information and discard the rest of the insignificant frames.
We anticipate that such key frame selection technique will have significant impact on wide area surveillance applications such as automatic object detection and recognition in aerial imagery. Three real-world datasets are used for evaluation and testing and the observed results are encouraging.
Data Management In Cloud Environments: Nosql And Newsql Data Stores, Katarina Grolinger, Wilson A. Higashino, Abhinav Tiwari, Miriam Am Capretz
Data Management In Cloud Environments: Nosql And Newsql Data Stores, Katarina Grolinger, Wilson A. Higashino, Abhinav Tiwari, Miriam Am Capretz
Wilson A Higashino
: Advances in Web technology and the proliferation of mobile devices and sensors connected to the Internet have resulted in immense processing and storage requirements. Cloud computing has emerged as a paradigm that promises to meet these requirements. This work focuses on the storage aspect of cloud computing, specifically on data management in cloud environments. Traditional relational databases were designed in a different hardware and software era and are facing challenges in meeting the performance and scale requirements of Big Data. NoSQL and NewSQL data stores present themselves as alternatives that can handle huge volume of data. Because of the …
Self-Organizing Neural Networks Integrating Domain Knowledge And Reinforcement Learning, Teck-Hou Teng, Ah-Hwee Tan, Jacek M. Zurada
Self-Organizing Neural Networks Integrating Domain Knowledge And Reinforcement Learning, Teck-Hou Teng, Ah-Hwee Tan, Jacek M. Zurada
Research Collection School Of Computing and Information Systems
The use of domain knowledge in learning systems is expected to improve learning efficiency and reduce model complexity. However, due to the incompatibility with knowledge structure of the learning systems and real-time exploratory nature of reinforcement learning (RL), domain knowledge cannot be inserted directly. In this paper, we show how self-organizing neural networks designed for online and incremental adaptation can integrate domain knowledge and RL. Specifically, symbol-based domain knowledge is translated into numeric patterns before inserting into the self-organizing neural networks. To ensure effective use of domain knowledge, we present an analysis of how the inserted knowledge is used by …
Mining Patterns Of Unsatisfiable Constraints To Detect Infeasible Paths, Sun Ding, Hee Beng Kuan Tan, Lwin Khin Shar
Mining Patterns Of Unsatisfiable Constraints To Detect Infeasible Paths, Sun Ding, Hee Beng Kuan Tan, Lwin Khin Shar
Research Collection School Of Computing and Information Systems
Detection of infeasible paths is required in many areas including test coverage analysis, test case generation, security vulnerability analysis, etc. Existing approaches typically use static analysis coupled with symbolic evaluation, heuristics, or path-pattern analysis. This paper is related to these approaches but with a different objective. It is to analyze code of real systems to build patterns of unsatisfiable constraints in infeasible paths. The resulting patterns can be used to detect infeasible paths without the use of constraint solver and evaluation of function calls involved, thus improving scalability. The patterns can be built gradually. Evaluation of the proposed approach shows …
Design, Programming, And User-Experience, Kaila G. Manca
Design, Programming, And User-Experience, Kaila G. Manca
Honors Scholar Theses
This thesis is a culmination of my individualized major in Human-Computer Interaction. As such, it showcases my knowledge of design, computer engineering, user-experience research, and puts into practice my background in psychology, com- munications, and neuroscience.
I provided full-service design and development for a web application to be used by the Digital Media and Design Department and their students.This process involved several iterations of user-experience research, testing, concepting, branding and strategy, ideation, and design. It lead to two products.
The first product is full-scale development and optimization of the web appli- cation.The web application adheres to best practices. It was …
Secure And Reliable Routing Protocol For Transmission Data In Wireless Sensor Mesh Networks, Nooh Adel Bany Muhammad
Secure And Reliable Routing Protocol For Transmission Data In Wireless Sensor Mesh Networks, Nooh Adel Bany Muhammad
Dissertations
Abstract
Sensor nodes collect data from the physical world then exchange it until it reaches the intended destination. This information can be sensitive, such as battlefield surveillance. Therefore, providing secure and continuous data transmissions among sensor nodes in wireless network environments is crucial. Wireless sensor networks (WSN) have limited resources, limited computation capabilities, and the exchange of data through the air and deployment in accessible areas makes the energy, security, and routing major concerns in WSN. In this research we are looking at security issues for the above reasons. WSN is susceptible to malicious activities such as hacking and physical …
Cpas - Campus Parking Availability System, Jacob Lambert
Cpas - Campus Parking Availability System, Jacob Lambert
Chancellor’s Honors Program Projects
No abstract provided.
Using Google Tag Manager And Google Analytics, (Code{4}Lib Journal), Suzanna Conrad
Using Google Tag Manager And Google Analytics, (Code{4}Lib Journal), Suzanna Conrad
Inaugural CSU IR Conference, 2015
Suzanna Conrad, Digital Initiatives Librarian, Cal Poly Pomona
What’S New Since The April 2013 Stim Ir Subcommittee Report To Cold: Hydra, Islandora And Dspace, Aaron Collier, Suzanna Conrad, Carmen Mitchell, Joan Parker, Andrew Weiss, Jeremy C. Shellhase
What’S New Since The April 2013 Stim Ir Subcommittee Report To Cold: Hydra, Islandora And Dspace, Aaron Collier, Suzanna Conrad, Carmen Mitchell, Joan Parker, Andrew Weiss, Jeremy C. Shellhase
Inaugural CSU IR Conference, 2015
Aaron Collier, Digital Repository Services Manager, Chancellor’s Office
Suzanna Conrad, Digital Initiatives Librarian, Cal Poly Pomona
Carmen Mitchell, Institutional Repository Librarian, CSU San Marcos
Joan Parker, Librarian, Moss Landing Marine Laboratories
Andrew Weiss, Digital Services Librarian, CSU Northridge
Jeremy Shellhase, Head of Information Services & Systems Department, Humboldt State University
The State Of Scholarworks, Aaron Collier
The State Of Scholarworks, Aaron Collier
Inaugural CSU IR Conference, 2015
Aaron Collier, Digital Repository Services Manager, Chancellor’s Office
Three-Dimensional Printing And Scanning Web-Based Job Management System, Stephanie Hollman, Dalyn Limesand, Jeremy Straub, Scott Kerlin
Three-Dimensional Printing And Scanning Web-Based Job Management System, Stephanie Hollman, Dalyn Limesand, Jeremy Straub, Scott Kerlin
Jeremy Straub
Three-dimensional (3D) printers have gained popularity for use for many different projects. The work presented herein aims to make this process simpler. This poster discusses a system that will allow individuals from all over campus to submit object files for printing, without having to schedule appointments and schedule 3D scanning appointments and retrieve scan results.
Intensity And Resolution Enhancement Of Local Regions For Object Detection And Tracking In Wide Area Surveillance, Evan Krieger, Vijayan K. Asari, Saibabu Arigela, Theus H. Aspiras
Intensity And Resolution Enhancement Of Local Regions For Object Detection And Tracking In Wide Area Surveillance, Evan Krieger, Vijayan K. Asari, Saibabu Arigela, Theus H. Aspiras
Electrical and Computer Engineering Faculty Publications
Object tracking in wide area motion imagery is a complex problem that consists of object detection and target tracking over time. This challenge can be solved by human analysts who naturally have the ability to keep track of an object in a scene. A computer vision solution for object tracking has the potential to be a much faster and efficient solution. However, a computer vision solution faces certain challenges that do not affect a human analyst. To overcome these challenges, a tracking process is proposed that is inspired by the known advantages of a human analyst.
First, the focus of …
Exploring Discriminative Features For Anomaly Detection In Public Spaces, Shriguru Nayak, Archan Misra, Kasthuri Jeyarajah, Philips Kokoh Prasetyo, Ee-Peng Lim
Exploring Discriminative Features For Anomaly Detection In Public Spaces, Shriguru Nayak, Archan Misra, Kasthuri Jeyarajah, Philips Kokoh Prasetyo, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
Context data, collected either from mobile devices or from user-generated social media content, can help identify abnormal behavioural patterns in public spaces (e.g., shopping malls, college campuses or downtown city areas). Spatiotemporal analysis of such data streams provides a compelling new approach towards automatically creating real-time urban situational awareness, especially about events that are unanticipated or that evolve very rapidly. In this work, we use real-life datasets collected via SMU's LiveLabs testbed or via SMU's Palanteer software, to explore various discriminative features (both spatial and temporal - e.g., occupancy volumes, rate of change in topic{specific tweets or probabilistic distribution of …
Evaluation Of The Signature Molecular Descriptor With Blosum62 And An All-Atom Description For Use In Sequence Alignment Of Proteins, Lindsay M. Aichinger
Evaluation Of The Signature Molecular Descriptor With Blosum62 And An All-Atom Description For Use In Sequence Alignment Of Proteins, Lindsay M. Aichinger
Williams Honors College, Honors Research Projects
This Honors Project focused on a few aspects of this topic. The second is comparing the molecular signature kernels to three of the BLOSUM matrices (30, 62, and 90) to test the accuracy of the mathematical model. The kernel matrix was manipulated in order to improve the relationship by focusing on side groups and also by changing how the structure was represented in the matrix by increasing the initial height distance from the central atom (Height 1 and Height 2 included).
There were multiple design constraints for this project. The first was the comparison with the BLOSUM matrices (30, 62, …
Framing The Question, "Who Governs The Internet?", Robert J. Domanski
Framing The Question, "Who Governs The Internet?", Robert J. Domanski
Publications and Research
There remains a widespread perception among both the public and elements of academia that the Internet is “ungovernable”. However, this idea, as well as the notion that the Internet has become some type of cyber-libertarian utopia, is wholly inaccurate. Governments may certainly encounter tremendous difficulty in attempting to regulate the Internet, but numerous types of authority have nevertheless become pervasive. So who, then, governs the Internet? This book will contend that the Internet is, in fact, being governed, that it is being governed by specific and identifiable networks of policy actors, and that an argument can be made as to …
Novel Incorportation Of Biomedical Engineering Algorithms (Bispectral Index Guided Or Anesthetic Concentration Guided) In Real-Time Decision Support To Prevent Intraoperative Awareness Using An Electronic Anesthesia Information Mananagement System, Amy Melanie Shanks
Wayne State University Dissertations
Background: Intraoperative awareness with explicit recall (AWR) is a feared complication of surgery that can lead to significant psychological distress. Several large prospective trials have been completed comparing two methods of monitoring anesthetic depth [minimum alveolar concentration (MAC) or electroencephalography (EEG) monitoring using the bispectral index (BIS)] for the prevention of AWR. However, these trials were conducted in high risk populations, limiting generalizability.
Research Hypothesis: Real-time decision support with Anesthesia Information Management System alerts based on a novel anesthetic concentration algorithm (incorporating the use of intravenous anesthetics) or an EEG-guided algorithm will reduce the known incidence of AWR.
Methods: First, …
Testing Data Vault-Based Data Warehouse, Connard N. Williams
Testing Data Vault-Based Data Warehouse, Connard N. Williams
Electronic Theses and Dissertations
Data warehouse (DW) projects are undertakings that require integration of disparate sources of data, a well-defined mapping of the source data to the reconciled data, and effective Extract, Transform, and Load (ETL) processes. Owing to the complexity of data warehouse projects, great emphasis must be placed on an agile-based approach with properly developed and executed test plans throughout the various stages of designing, developing, and implementing the data warehouse to mitigate against budget overruns, missed deadlines, low customer satisfaction, and outright project failures. Yet, there are often attempts to test the data warehouse exactly like traditional back-end databases and legacy …
Behavioral Operations Management In Federal Governance, Frederick Leonard Mobley
Behavioral Operations Management In Federal Governance, Frederick Leonard Mobley
Walden Dissertations and Doctoral Studies
The environmental uncertainty of federal politics and acquisition outsourcing in competitive markets requires an adaptive decision-analysis structure. Practitioners oriented toward exclusively static methods face severe challenges in understanding qualitative aspects of organizational governance. The purpose of this grounded theory study was to examine and understand behavioral relationship attributes within intuitive, choice, judgment, or preference decision-making processes. The problem addressed in this study was the detrimental effects of organizational citizenship behavior (OCB), compulsory citizenship behavior (CCB), and social exchange theory (SET) on the acquisition management relationship The OCB, CCB, SET dictates that sound business development, relationship acumen, emotional intelligence and perceptiveness …