Assessing Value Added In The Use Of Electronic Medical Records In Nigeria,
2015
Walden University
Assessing Value Added In The Use Of Electronic Medical Records In Nigeria, Isaiah Gbenga Abimbola
Walden Dissertations and Doctoral Studies
Electronic medical records (EMRs) or electronic health records have been in use for years in hospitals around the world as a time-saving system for patient record keeping. Despite its widespread use, some physicians disagree with the assertion that EMRs save time. The purpose of this study was to explore whether any time saved with the use of the EMR system was actually devoted by doctors to patient-care and thereby to improved patient-care efficiency. The conceptual support for this study was predicated employing the task-technology fit theory. Task-technology theorists argue that information technology is likely to have a positive impact in …
The Value Of Diagnostic Software And Doctors' Decision Making,
2015
Walden University
The Value Of Diagnostic Software And Doctors' Decision Making, Babatunde Ayodele Alaofin
Walden Dissertations and Doctoral Studies
The prevalence of medical misdiagnosis has remained high despite the adoption of diagnostic software. This ongoing controversy about the role of technology in mitigating the problem of misdiagnosis centers on the question of whether diagnostic software does reduce the incidence of misdiagnosis if properly relied upon by physicians. The purpose of this quantitative, cross-sectional study based on planned behavior theory was to measure doctors' opinions of diagnostic technology's medical utility. Recruitment e-mails were sent to 3,100 AMA-accredited physicians through their database that yielded a sample of 99 physicians for the study. One-sample t tests and, where appropriate because of non-normal …
Impact Of Eu Medical Device Directive On Medical Device Software,
2015
Walden University
Impact Of Eu Medical Device Directive On Medical Device Software, Guy Foe Owono
Walden Dissertations and Doctoral Studies
Directive 2007/47/EC of the European Parliament amending Medical Device Directive (MDD) provides medical device manufacturers with a compliance framework. However, the effects of the amendments to the MDD on competition in the U.S. medical device software industry are unknown. This study examined the impact of this directive on the competitiveness of U.S. medical device software companies, the safety and efficacy of medical device software, employee training, and recruitment. The conceptual framework for this study included 3 dimensions of medical device regulations: safety, performance, and reliability. The overall research design was a concurrent mixed method study using both quantitative and qualitative …
Enhancing Workplace Productivity And Competitiveness In Trinidad And Tobago Through Ict Adoption,
2015
Walden University
Enhancing Workplace Productivity And Competitiveness In Trinidad And Tobago Through Ict Adoption, Kennedy Jerome Swaratsingh
Walden Dissertations and Doctoral Studies
The productivity of Trinidad and Tobago's public sector workplaces is related to their absorptive capacity for technological adoption. Guided by the technology acceptance model, which suggests that individuals' and institutions' use of technology increases in relation to perceived ease of use and apparent value, this case study explored how Trinidad and Tobago used information and communications technology from 2001 - 2010 to improve public sector workplace productivity. Study data were collected from 22 individual interviews with senior executives from the government of Trinidad and Tobago, members of the e-business roundtable, and local industry experts, and from reviewing the archives of …
Effects Of Investor Sentiment Using Social Media On Corporate Financial Distress,
2015
Walden University
Effects Of Investor Sentiment Using Social Media On Corporate Financial Distress, Tarek Hoteit
Walden Dissertations and Doctoral Studies
The mainstream quantitative models in the finance literature have been ineffective in detecting possible bankruptcies during the 2007 to 2009 financial crisis. Coinciding with the same period, various researchers suggested that sentiments in social media can predict future events. The purpose of the study was to examine the relationship between investor sentiment within the social media and the financial distress of firms Grounded on the social amplification of risk framework that shows the media as an amplified channel for risk events, the central hypothesis of the study was that investor sentiments in the social media could predict t he level …
Toward Mobile Robots Reasoning Like Humans,
2015
Singapore Management University
Toward Mobile Robots Reasoning Like Humans, Jean Oh, Arne Suppe, Felix Duvallet, Abdeslam Boularias, Luis Navarro-Serment, Martial Hebert, Anthony Stentz, Jerry Vinokurov, Oscar Romero, Christian Lebiere, Robert Dean
Research Collection School Of Computing and Information Systems
Robots are increasingly becoming key players in human-robot teams. To become effective teammates, robots must possess profound understanding of an environment, be able to reason about the desired commands and goals within a specific context, and be able to communicate with human teammates in a clear and natural way. To address these challenges, we have developed an intelligence architecture that combines cognitive components to carry out high-level cognitive tasks, semantic perception to label regions in the world, and a natural language component to reason about the command and its relationship to the objects in the world. This paper describes recent …
Modeling Neuromorphic Persistent Firing Networks,
2015
Singapore Management University
Modeling Neuromorphic Persistent Firing Networks, Ning Ning, Guoqi Li, Wei He, Kejie Huang, Li Pan, Kiruthika Ramanathan, Rong Zhao, Luping Shi
Research Collection School Of Computing and Information Systems
Neurons are believed to be the brain computational engines of the brain. A recent discovery in neurophysiology reveals that interneurons can slowly integrate spiking, share the output across a coupled network of axons and respond with persistent firing even in the absence of input to the soma or dendrites, which has not been understood and could be very important for exploring the mechanism of human cognition. The conventional models are incapable of simulating the important newly-discovered phenomenon of persistent firing induced by axonal slow integration. In this paper, we propose a computationally efficient model of neurons through modeling the axon …
Semi-Universal Portfolios With Transaction Costs,
2015
East China University of Science and Technology
Semi-Universal Portfolios With Transaction Costs, Dingjiang Huang, Yan Zhu, Bin Li, Shuigeng Zhou, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
Online portfolio selection (PS) has been extensively studied in artificial intelligence and machine learning communities in recent years. An important practical issue of online PS is transaction cost, which is unavoidable and nontrivial in real financial trading markets. Most existing strategies, such as universal portfolio (UP) based strategies, often rebalance their target portfolio vectors at every investment period, and thus the total transaction cost increases rapidly and the final cumulative wealth degrades severely. To overcome the limitation, in this paper we investigate new investment strategies that rebalances its portfolio only at some selected instants. Specifically, we design a novel on-line …
Drip - Data Rich, Information Poor: A Concise Synopsis Of Data Mining,
2014
Southern Polytechnic State University
Drip - Data Rich, Information Poor: A Concise Synopsis Of Data Mining, Muhammad Obeidat, Max North, Lloyd Burgess, Sarah North
Faculty Articles
As production of data is exponentially growing with a drastically lower cost, the importance of data mining required to extract and discover valuable information is becoming more paramount. To be functional in any business or industry, data must be capable of supporting sound decision-making and plausible prediction. The purpose of this paper is concisely but broadly to provide a synopsis of the technology and theory of data mining, providing an enhanced comprehension of the methods by which massive data can be transferred into meaningful information.
Major Challenges And Solutions For Utilizing Big Data In The Maritime Industry,
2014
World Maritime University
Major Challenges And Solutions For Utilizing Big Data In The Maritime Industry, Sadaharu Koga
World Maritime University Dissertations
The dissertation is a study of big data for the use in the maritime industry. Today’s society is information-intensive. The term “big data” is becoming more common. In fact, some maritime companies and institutions have already been trying to utilize big data for enhancing maritime safety and environmental protection. In order to promote this trend, the dissertation tries to identify common and important challenges for the whole maritime industry in terms of the utilization of big data and propose corresponding solutions. First, by reviewing the definitions of big data, three major features are identified. Big data takes electronic form, is …
Optimizing Data Movement In Hybrid Analytic Systems,
2014
Portland State University
Optimizing Data Movement In Hybrid Analytic Systems, Patrick Michael Leyshock
Dissertations and Theses
Hybrid systems for analyzing big data integrate an analytic tool and a dedicated data-management platform, storing data and operating on the data at both components. While hybrid systems have benefits over alternative architectures, in order to be effective, data movement between the two hybrid components must be minimized. Extant hybrid systems either fail to address performance problems stemming from inter-component data movement, or else require the user to explicitly reason about and manage data movement. My work presents the design, implementation, and evaluation of a hybrid analytic system for array-structured data that automatically minimizes data movement between the hybrid components. …
A Gis-Centric Approach For Modeling Vessel Management Behavior System Data To Determine Oyster Vessel Behavior On Public Oyster Grounds In Louisiana,
2014
University of New Orleans
A Gis-Centric Approach For Modeling Vessel Management Behavior System Data To Determine Oyster Vessel Behavior On Public Oyster Grounds In Louisiana, David X. Gallegos
LSU New Orleans Theses and Dissertations
The satellite communications system called the Vessel Management System was used to provide geospatial data on oyster fishing over the nearly 1.7 million acres of the public water bottoms in Louisiana. An algorithm to analyze the data was developed in order to model vessel behaviors including docked, gearing, fishing and traveling. Vessel speeds were calculated via the Haversine formula at small and large intervals and compared to derive a measure of linearity. The algorithm was implemented into software using Python and inserted into a PostgreSQL database supporting geospatial information. Queries were developed to obtain reports on vessel activities and daily …
A Content-Sensitive Wiki Help System,
2014
San Jose State University
A Content-Sensitive Wiki Help System, Eswara Satya Pavan Rajesh Pinapala
Master's Projects
Context-sensitive help is a software application component that enables users to open help pertaining to their state, location, or the action they are performing within the software. Context-sensitive “wiki” help, on the other hand, is help powered by a wiki system with all the features of context-sensitive help. A context-sensitive wiki help system aims to make the context-sensitive help collaborative; in addition to seeking help, users can directly contribute to the help system. I have implemented a context-sensitive wiki help system into Yioop, an open source search engine and software portal created by Dr. Chris Pollett, in order to measure …
Facilitating Natural Conversational Agent Interactions: Lessons From A Deception Experiment,
2014
University of Nebraska at Omaha
Facilitating Natural Conversational Agent Interactions: Lessons From A Deception Experiment, Ryan M. Schuetzler, Mark Grimes, Justin Scott Giboney, Joesph Buckman
Information Systems and Quantitative Analysis Faculty Proceedings & Presentations
This study reports the results of a laboratory experiment exploring interactions between humans and a conversational agent. Using the ChatScript language, we created a chat bot that asked participants to describe a series of images. The two objectives of this study were (1) to analyze the impact of dynamic responses on participants’ perceptions of the conversational agent, and (2) to explore behavioral changes in interactions with the chat bot (i.e. response latency and pauses) when participants engaged in deception. We discovered that a chat bot that provides adaptive responses based on the participant’s input dramatically increases the perceived humanness and …
From Cells To Streets: Estimating Mobile Paths With Cellular-Side Data,
2014
Singapore Management University
From Cells To Streets: Estimating Mobile Paths With Cellular-Side Data, Qatar Computing Research Institute, University Of Birmingham, Seattle University Of Washington, Haewoon Kwak
Research Collection School Of Computing and Information Systems
Through their normal operation, cellular networks are a repository of continuous location information from their subscribed devices. Such information, however, comes at a coarse granularity both in terms of space, as well as time. For otherwise inactive devices, location information can be obtained at the granularity of the associated cellular sector, and at infrequent points in time, that are sensitive to the structure of the network itself, and the level of mobility of the device. In this paper, we are asking the question of whether such sparse information can help to identify the paths followed by mobile connected devices throughout …
Towards Intelligent Caring Agents For Aging-In-Place: Issues And Challenges,
2014
Singapore Management University
Towards Intelligent Caring Agents For Aging-In-Place: Issues And Challenges, Di Wang, Budhitama Subagdja, Yilin Kang, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
The aging of the world’s population presents vast societal and individual challenges. The relatively shrinking workforce to support the growing population of the elderly leads to a rapidly increasing amount of technological innovations in the field of elderly care. In this paper, we present an integrated framework consisting of various intelligent agents with their own expertise and responsibilities working in a holistic manner to assist, care, and accompany the elderly around the clock in the home environment. To support the independence of the elderly for Aging-In-Place (AIP), the intelligent agents must well understand the elderly, be fully aware of the …
Android Or Ios For Better Privacy Protection?,
2014
Singapore Management University
Android Or Ios For Better Privacy Protection?, Jin Han, Qiang Yan, Debin Gao, Jianying Zhou, Huijie Robert Deng
Research Collection School Of Computing and Information Systems
With the rapid growth of the mobile market, security of mobile platforms is receiving increasing attention from both research community as well as the public. In this paper, we make the first attempt to establish a baseline for security comparison between the two most popular mobile platforms. We investigate applications that run on both Android and iOS and examine the difference in the usage of their security sensitive APIs (SS-APIs). Our analysis over 2,600 applications shows that iOS applications consistently access more SS-APIs than their counterparts on Android. The additional privileges gained on iOS are often associated with accessing private …
High-Dimensional Data Stream Classification Via Sparse Online Learning,
2014
Nanyang Technological University, Singapore
High-Dimensional Data Stream Classification Via Sparse Online Learning, Dayong Wang, Pengcheng Wu, Peilin Zhao, Yue Wu, Chunyan Miao, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
The amount of data in our society has been exploding in the era of big data today. In this paper, we address several open challenges of big data stream classification, including high volume, high velocity, high dimensionality, and high sparsity. Many existing studies in data mining literature solve data stream classification tasks in a batch learning setting, which suffers from poor efficiency and scalability when dealing with big data. To overcome the limitations, this paper investigates an online learning framework for big data stream classification tasks. Unlike some existing online data stream classification techniques that are often based on first-order …
A Deep Search Architecture For Capturing Product Ontologies,
2014
University of Arkansas, Fayetteville
A Deep Search Architecture For Capturing Product Ontologies, Tejeshwar Sangameswaran
Graduate Theses and Dissertations
This thesis describes a method to populate very large product ontologies quickly. We discuss a deep search architecture to text-mine online e-commerce market places and build a taxonomy of products and their corresponding descriptions and parent categories. The goal is to automatically construct an open database of products, which are aggregated from different online retailers. The database contains extensive metadata on each object, which can be queried and analyzed. Such a public database currently does not exist; instead the information currently resides siloed within various organizations. In this thesis, we describe the tools, data structures and software architectures that allowed …
Detecting Flow Anomalies In Distributed Systems,
2014
Singapore Management University
Detecting Flow Anomalies In Distributed Systems, Freddy Chong-Tat Chua, Ee Peng Lim, Bernardo Huberman
Research Collection School Of Computing and Information Systems
Deep within the networks of distributed systems, one often finds anomalies that affect their efficiency and performance. These anomalies are difficult to detect because the distributed systems may not have sufficient sensors to monitor the flow of traffic within the interconnected nodes of the networks. Without early detection and making corrections, these anomalies may aggravate over time and could possibly cause disastrous outcomes in the system in the unforeseeable future. Using only coarse-grained information from the two end points of network flows, we propose a network transmission model and a localization algorithm, to detect the location of anomalies and rank …
