Trends In Commercial-Off-The-Shelf Vs. Proprietary Applications,
2016
University of Nebraska at Kearney
Trends In Commercial-Off-The-Shelf Vs. Proprietary Applications, Vijay K. Agrawal, Vipin K. Agrawal, A. Ross Taylor
Journal of International Technology and Information Management
This study examines factors valued by IS managers in deciding if COTS software is a viable alternative to proprietary software. The results indicate managers who anticipate increased usage of COTS packages in 5 years used the same top three factors in the formation of their decisions to adopt COTS as their colleagues who anticipated either zero change in COTS usage or an increased usage of proprietary software used in deciding not to adopt COTS software. Managers anticipating increased COTS usage had a statistically significant higher value for each of those items compared to managers not anticipating growth in COTS software.
Online Trust Cues: Perceptions And Application,
2016
Emporia State University
Online Trust Cues: Perceptions And Application, Antonina A. Bauman
Journal of International Technology and Information Management
This qualitative study analyzes perceptions of online trust cues as identified by shoppers from three countries: Germany, Russia, and the USA. A novel approach of the repertory grid method is used to study online trust cues in business-to-consumers commercial online transactions. This study resulted in the list of web site elements and features that consumers recognize as trust cues and use to evaluate e-vendor’s trustworthiness. Findings show that out of fourteen categories of online trust cues, identified by online shoppers, three categories of online trust cues are found to be common across three cultures while eleven categories are culture specific. …
Evaluation Of Classification And Ensemble Algorithms For Bank Customer Marketing Response Prediction,
2016
Tilburg University
Evaluation Of Classification And Ensemble Algorithms For Bank Customer Marketing Response Prediction, Olatunji Apampa
Journal of International Technology and Information Management
This article attempts to improve the performance of classification algorithms used in the bank customer marketing response prediction of an unnamed Portuguese bank using the Random Forest ensemble. A thorough exploratory data analysis (EDA) was conducted on the data in order to ascertain the presence of anomalies such as outliers and extreme values. The EDA revealed that the bank data had 45, 211 instances and 17 features, with 11.7% positive responses. This was in addition to the detection of outliers and extreme values. Classification algorithms used for modelling the bank dataset include; Logistic Regression, Decision Tree, Naïve Bayes and the …
The Perceived Business Benefit Of Cloud Computing: An Exploratory Study,
2016
Global ECommerce Service, Inc
The Perceived Business Benefit Of Cloud Computing: An Exploratory Study, Thomas Chen, Ta-Tao Chuang, Kazuo Nakatani
Journal of International Technology and Information Management
The objective of the research is to study the benefits of cloud computing perceived by adopters and examine the impact of moderating factors on the relationship between the type of cloud computing and the perceived benefit. The moderating factors include firm size and value-chain activities. A measurement instrument of a 5-point Likert scale was administered on businesses of different sizes in Taiwan. The benefit of cloud computing measured in the study were: cost reduction, improved capability and enhanced scalability. The results show that the perceived benefit of cloud computing varies depending on the type of cloud computing, the value chain …
The Efficient Recovery Of Deleted Data From Nand Flash Memory,
2016
University of Northern Iowa
The Efficient Recovery Of Deleted Data From Nand Flash Memory, Lisa Diercks
Honors Program Theses
NAND flash memory is used in flash drives, smart phones, and memory cards for digital cameras. While there are ways to recover data from deleted memory, there are no universal or efficient ways to recover data from NAND flash memory. When a user clicks “delete” on a file in this type of memory, the file is not necessarily deleted, but may just be hidden. This means these files are still on the chip, but are inaccessible through normal means. The ability to recover this lost data could help computer forensic examiners during investigations and corporations working to use secure deletion …
Table Of Contents,
2016
California State University, San Bernardino
Table Of Contents
Journal of International Technology and Information Management
Table of Contents for Volume 25 Number 4
Conceptual Models On The Effectiveness Of E-Marketing Strategies In Engaging Consumers,
2016
Texas Woman's University
Conceptual Models On The Effectiveness Of E-Marketing Strategies In Engaging Consumers, Cheristena Bolos, Efosa C. Idemudia, Phoebe Mai, Mahesh Rasinghani, Shelley Smith
Journal of International Technology and Information Management
Effective marketing has always been an important factor in business success. Without the ability to identify customers and convince them to purchase the product or service being offered, businesses would not survive. Recent advancements in technology have given rise to new opportunities to engage customers through the use of electronic marketing (e-marketing). E- marketing draws from traditional marketing principles, while also expanding the types of strategies available to companies. Websites, social media, and online marketplaces are just some examples of how businesses are leveraging e-marketing approaches to connect with potential customers. In formulating sound e-marketing strategies, it is important for …
Healthcare System-Use Behavior: A Systematic Review Of Its Determinants,
2016
California State University, East Bay
Healthcare System-Use Behavior: A Systematic Review Of Its Determinants, Jiming Wu
Journal of International Technology and Information Management
To understand patient and physician behavior, researchers have investigated the determinants of using healthcare information systems. Although this stream of research has produced important findings, it has yet to appreciably advance our understanding of system-use behavior in healthcare. To fill this gap, the current paper employs a systematic review to synthesize past research, reveal the key determinants of healthcare system usage, and illuminate a deeper understanding of the topic. This study thus helps healthcare researchers expand their baseline knowledge of these core determinants and conduct more fruitful future research on system-use behavior in healthcare.
Optimizing Virtual Machine I/O Performance In Cloud Environments,
2016
Virginia Commonwealth University
Optimizing Virtual Machine I/O Performance In Cloud Environments, Tao Lu
Theses and Dissertations
Maintaining closeness between data sources and data consumers is crucial for workload I/O performance. In cloud environments, this kind of closeness can be violated by system administrative events and storage architecture barriers. VM migration events are frequent in cloud environments. VM migration changes VM runtime inter-connection or cache contexts, significantly degrading VM I/O performance. Virtualization is the backbone of cloud platforms. I/O virtualization adds additional hops to workload data access path, prolonging I/O latencies. I/O virtualization overheads cap the throughput of high-speed storage devices and imposes high CPU utilizations and energy consumptions to cloud infrastructures. To maintain the closeness between …
Defining A Smart Nation: The Case Of Singapore,
2016
Singapore Management University
Defining A Smart Nation: The Case Of Singapore, Siu Loon Hoe
Research Collection School Of Computing and Information Systems
Purpose - The purpose of this paper is to identify the key characteristics and propose a working definition of a smart nation.Design/methodology/approach - A case study of Singapore through an analysis of the key speeches made by senior Singapore leaders, publicly available government documents and news reports since the launch of the smart nation initiative in December 2014 was carried out.Findings - Just like smart cities, the idea of a smart nation is an evolving concept. However, there are some emerging characteristics that define a smart nation.Research limitations/implications - The paper provides an initial understanding of the key characteristics and …
Active Analytics: Adapting Web Pages Automatically Based On Analytics Data,
2016
University of North Florida
Active Analytics: Adapting Web Pages Automatically Based On Analytics Data, William R. Carle Ii
UNF Graduate Theses and Dissertations
Web designers are expected to perform the difficult task of adapting a site’s design to fit changing usage trends. Web analytics tools give designers a window into website usage patterns, but they must be analyzed and applied to a website's user interface design manually. A framework for marrying live analytics data with user interface design could allow for interfaces that adapt dynamically to usage patterns, with little or no action from the designers. The goal of this research is to create a framework that utilizes web analytics data to automatically update and enhance web user interfaces. In this research, we …
Data To Decisions For Cyberspace Operations,
2015
Robert Morris University
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.
Modeling Information Reliability And Maintenance: A Systematic Literature Review,
2015
University of Arkansas, Fayetteville
Modeling Information Reliability And Maintenance: A Systematic Literature Review, Daysi A. Guerra Garcia
Industrial Engineering Undergraduate Honors Theses
Operating a business efficiently depends on effective everyday decision-making. In turn, those decisions are influenced by the quality of data used in the decision-making process, and maintaining good data quality becomes more challenging as a business expands. Protecting the quality of the data and the information it generates is a challenge faced by many companies across all industrial sectors. As companies begin to use data from these large data bases they will need to begin to develop strategies for maintaining and assessing the reliability of the information they generate using this data. A considerable amount of literature exists on data …
Estimation On Gibbs Entropy For An Ensemble,
2015
Lekhya Sai Sake
Estimation On Gibbs Entropy For An Ensemble, Lekhya Sai Sake
Electronic Theses, Projects, and Dissertations
In this world of growing technology, any small improvement in the present scenario would create a revolution. One of the popular revolutions in the computer science field is parallel computing. A single parallel execution is not sufficient to see its non-deterministic features, as same execution with the same data at different time would end up with a different path. In order to see how non deterministic a parallel execution can extend up to, creates the need of the ensemble of executions. This project implements a program to estimate the Gibbs Entropy for an ensemble of parallel executions. The goal is …
Learning Query And Image Similarities With Ranking Canonical Correlation Analysis,
2015
Singapore Management University
Learning Query And Image Similarities With Ranking Canonical Correlation Analysis, Ting Yao, Tao Mei, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
One of the fundamental problems in image search is to learn the ranking functions, i.e., similarity between the query and image. The research on this topic has evolved through two paradigms: feature-based vector model and image ranker learning. The former relies on the image surrounding texts, while the latter learns a ranker based on human labeled query-image pairs. Each of the paradigms has its own limitation. The vector model is sensitive to the quality of text descriptions, and the learning paradigm is difficult to be scaled up as human labeling is always too expensive to obtain. We demonstrate in this …
Vireo-Tno @ Trecvid 2015: Multimedia Event Detection,
2015
Singapore Management University
Vireo-Tno @ Trecvid 2015: Multimedia Event Detection, Hao Zhang, Yi-Jie Lu, Maaike De Boer, Frank Ter Haar, Zhaofan Qiu, Klamer Schutte, Wessel Kraaij, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
This paper presents an overview and comparative analysis of our systems designed for the TRECVID 2015 [1] multimedia event detection (MED) task. We submitted 17 runs, of which 5 each for the zeroexample, 10-example and 100-example subtasks for the Pre-Specified (PS) event detection and 2 runs for the 10-example subtask for the Ad-Hoc (AH) event detection. We did not participate in the Interactive Run. This year we focus on three different parts of the MED task: 1) extending the size of our concept bank and combining it with improved dense trajectories; 2) exploring strategies for semantic query generation (SQG); and …
Lesinn: Detecting Anomalies By Identifying Least Similar Nearest Neighbours,
2015
Singapore Management University
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 …
Deep Multimodal Learning For Affective Analysis And Retrieval,
2015
Singapore Management University
Deep Multimodal Learning For Affective Analysis And Retrieval, Lei Pang, Shiai Zhu, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Social media has been a convenient platform for voicing opinions through posting messages, ranging from tweeting a short text to uploading a media file, or any combination of messages. Understanding the perceived emotions inherently underlying these user-generated contents (UGC) could bring light to emerging applications such as advertising and media analytics. Existing research efforts on affective computation are mostly dedicated to single media, either text captions or visual content. Few attempts for combined analysis of multiple media are made, despite that emotion can be viewed as an expression of multimodal experience. In this paper, we explore the learning of highly …
Direct Or Indirect Match? Selecting Right Concepts For Zero-Example Case,
2015
Singapore Management University
Direct Or Indirect Match? Selecting Right Concepts For Zero-Example Case, Yi-Jie Lu, Maaike De Boer, Hao Zhang, Klamer Schutte, Wessel Kraaij, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
No abstract provided.
Big Data Proteogenomics And High Performance Computing: Challenges And Opportunities,
2015
Western Michigan University
Big Data Proteogenomics And High Performance Computing: Challenges And Opportunities, Fahad Saeed
Parallel Computing and Data Science Lab Technical Reports
Proteogenomics is an emerging field of systems biology research at the intersection of proteomics and genomics. Two high-throughput technologies, Mass Spectrometry (MS) for proteomics and Next Generation Sequencing (NGS) machines for genomics are required to conduct proteogenomics studies. Independently both MS and NGS technologies are inflicted with data deluge which creates problems of storage, transfer, analysis and visualization. Integrating these big data sets (NGS+MS) for proteogenomics studies compounds all of the associated computational problems. Existing sequential algorithms for these proteogenomics datasets analysis are inadequate for big data and high performance computing (HPC) solutions are almost non-existent. The purpose of this …
