Databases and Information Systems Commons^™

Strategies To Implement Big Data Analytics In Telecommunications Organizations, Delton Aneato

Walden Dissertations and Doctoral Studies

Information Technology (IT) leaders who do not invest in big data projects may struggle to gain a competitive advantage and business insights to improve performance. Grounded in the Kotter’s change and Six Sigma models, the purpose of this qualitative multiple case study was to explore strategies IT leaders used to implement big data analytics successfully. The participants comprised 4 IT leaders from 2 telecommunication organizations in the United States of America, who effectively used strategies to promote and maximize competitive advantage using big data analytics. Data were collected from semistructured interviews, company documents, and project-related documents and were analyzed using …

Information Technology Disaster Recovery Planning By Florida Nonprofit Organizations, Derek Keith Erfourth

Walden Dissertations and Doctoral Studies

Inadequate information technology (IT) disaster recovery planning (DRP) by nonprofit organizations could lead to organizational failure post-large-scale natural disasters. Without proper funding and planning, organizations may not be able to withstand the effects of a natural disaster resulting in the closure and the community losing a critical need service. Grounded in resilience theory, the purpose of this qualitative multiple case study was to explore strategies utilized by Florida-based nonprofit organization technology managers to adopt and implement an IT DRP to aid in post-natural disaster recovery efforts. The data collection included interviews with 5 IT managers and reviews of 4 business …

Implementing Cloud-Based Enterprise Resource Planning Solutions In Small And Medium Enterprises, Ali Hamdar

Walden Dissertations and Doctoral Studies

Lacking strategies to implement a cloud-based enterprise resource planning (ERP) solution in small and medium-sized enterprises (SMEs) can lead to a failed implementation. SME owners can improve company performance by integrating company processes by successfully implementing a cloud-based ERP solution. Grounded in the diffusion of innovation theory augmented with business process management design for Six Sigma, the purpose of this qualitative multiple case study was to explore strategies SME owners use to implement cloud-based ERP solutions. The participants consisted of 4 SME owners in Lebanon who successfully implemented a cloud-based ERP solution and improved company performance and growth. Data were …

Comparing Tagging Suggestion Models On Discrete Corpora, Bojan Bozic, Andre Rios, Sarah Jane Delany

Articles

This paper aims to investigate the methods for the prediction of tags on a textual corpus that describes diverse data sets based on short messages; as an example, the authors demonstrate the usage of methods based on hotel staff inputs in a ticketing system as well as the publicly available StackOverflow corpus. The aim is to improve the tagging process and find the most suitable method for suggesting tags for a new text entry.

Factors That Influence The Perception Of Higher Education Leaders In The Adoption Process Of Instructional Technology And Distance Education, Diego Tibaquirá

Theses and Dissertations

The problem addressed by this study was that many administrators at institutions of higher learning are faced with the task of finding ways to provide the latest technologies while being extremely constricted by budgets and the rising cost of education. The purpose of this study was to determine the factors that influence the perceptions of higher education leaders in the adoption process of Instructional Technology and Distance Education. This included an examination of the decision-making process and what determined if Instructional Technology and Distance Education were either implemented or upgraded at various higher learning institutions.

The researcher implemented a mixed-methods …

A Study On Real-Time Database Technology And Its Applications, Geethmi Nimantha Dissanayake

Masters Theses

No abstract provided.

The Trust Principles For Digital Repositories, Dawei Lin, Jonathan Crabtree, Ingrid Dillo, Robert R. Downs, Rorie Edmunds, David Giaretta, Marisa De Giusti, Hervé L'Hours, Wim Hugo, Reyna Jenkyns, Varsha Khodiyar, Maryann E. Martone, Mustapha Mokrane, Vivek Navale, Jonathan Petters, Barbara Sierman, Dina V. Sokolova, Martina Stockhause, John Westbrook

Copyright, Fair Use, Scholarly Communication, etc.

As information and communication technology has become pervasive in our society, we are increasingly dependent on both digital data and repositories that provide access to and enable the use of such resources. Repositories must earn the trust of the communities they intend to serve and demonstrate that they are reliable and capable of appropriately managing the data they hold.

Following a year-long public discussion and building on existing community consensus , several stakeholders, representing various segments of the digital repository community, have collaboratively developed and endorsed a set of guiding principles to demonstrate digital repository trustworthiness. Transparency, Responsibility, User focus, …

Telecommunications Database, Tristan Hess

Williams Honors College, Honors Research Projects

The final goal of this project was to create a web application that is specifically tailored to make management of data for the Telecommunications department easier. The software that the department uses for phone service generates monthly reports that cannot be stored into their current database system. The Telecommunications Database project is a four-tier web application that was developed to store the monthly report information and alleviate the burden of manually searching through the reports for information. The web application implements basic database functionality for searching, inserting, updating, and deleting data contained in the monthly reports. Advanced searching functionality and …

Measuring Differential Forest Growth In The Sheepscot River Headwaters With Bitemporal Lidar, Soren Denlinger

Honors Theses

In recent years, lidar has proven itself as a forestry tool capable of accurate, large- scale inventories. Lidar has even shown utility in multitemporal analysis and growth assessment, given high-resolution or small-scale point clouds. However, lidar’s efficacy as a multitemporal tool with relatively low-resolution, large-scale datasets is comparatively unknown. In this study, I compared forest in Midcoast Maine bitemporally, with publicly available datasets from the years 2007 and 2012. Specifically, I compared differences in growth characteristics of riparian, wetland, and upland forests. Although the 2007 dataset (created for geomorphological research) and the 2012 dataset (statewide, general-purpose) possess varying point densities …

Building Something With The Raspberry Pi, Richard Kordel

Presidential Research Grants

In 2017 Ryan Korn and I submitted a grant proposal in the annual Harrisburg University President’s Grant process. Our proposal was to partner with a local high school to install a classroom of 20 Raspberry Pi’s, along with the requisite peripherals. In that classroom students would be challenged to design something that combined programming with physical computing. In our presentation to the school we suggested that this project would give students the opportunity to be “amazing.”

As part of the grant, the top three students would be given scholarships to HU and the top five finalists would all be permitted …

Scalable, Adaptable And Fast Estimation Of Transient Downtime In Virtual Infrastructures Using Convex Decomposition And Sample Path Randomization, Zhiling Guo, Jin Li, Ram Ramesh

Research Collection School Of Computing and Information Systems

Network function virtualization enables efficient cloud-resource planning by virtualizing network services and applications into software running on commodity servers. A cloud-service provider needs to manage and ensure service availability of a network of concurrent virtualized network functions (VNFs). The downtime distribution of a network of VNFs can be estimated using sample-path randomization on the underlying birth–death process. An integrated modeling approach for this purpose is limited by its scalability and computational load because of the high dimensionality of the integrated birth–death process. We propose a generalized convex decomposition of the integrated birth-death process, which transforms the high-dimensional multi-VNF process into …

The Topicality Of The Learning Organization: Is The Concept Still Relevant Today?, Siu Loon Hoe

Research Collection School Of Computing and Information Systems

This chapter introduces the current level of interest in the learning organization and usefulness of the concept at the present time. It reviews authors who have recently and explicitly commented on the topicality of the learning organization, offers a qualitative content analysis of recent journal publications on learning organizations justifying the need for the concept, and uses quantitative research using print media indicators and Google Trends to identify the number of publications related to the learning organization over time. The results suggest that while the level of interest in the learning organization among scientific researchers has grown, the level of …

Coupled Rain Streak And Background Estimation Via Separable Element-Wise Attention, Yinjie Tan, Qiang Wen, Jing Qin, Jianbo Jiao, Guoqiang Han, Shengfeng He

Research Collection School Of Computing and Information Systems

Single image de-raining is challenging especially in the scenarios with dense rain streaks. Existing methods resolve this problem by predicting the rain streaks of the image, which constrains the network to focus on local rain streaks features. However, dense rain streaks are visually similar to mist or fog (with large intensities), in this case, the training objective should be shifted to image recovery instead of extracting rain streaks. In this paper, we propose a coupled rain streak and background estimation network that explores the intrinsic relations between two tasks. In particular, our network produces task-dependent feature maps, each part of …

Recent Advances In Deep Learning For Object Detection, Xiongwei Wu, Doyen Sahoo, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Object detection is a fundamental visual recognition problem in computer vision and has been widely studied in the past decades. Visual object detection aims to find objects of certain target classes with precise localization in a given image and assign each object instance a corresponding class label. Due to the tremendous successes of deep learning based image classification, object detection techniques using deep learning have been actively studied in recent years. In this paper, we give a comprehensive survey of recent advances in visual object detection with deep learning. By reviewing a large body of recent related work in literature, …

Development And Field Testing Of A Mall For Filipino With A Reusable Framework For Mobile-Based Drills, Jenilyn Agapito, Dominique Marie Antoinette Manahan, Ma. Monica L. Moreno, Jose Isidro Beraquit, Ingrid Yvonne Herras, Kevin Arnel C. Mora, Johanna Marion R. Torres, Ma. Mercedes T. Rodrigo

Department of Information Systems & Computer Science Faculty Publications

This paper describes the development and field testing of Ibigkas! Filipino, a mobile game that exercises learners’ fluency in identifying synonyms (kasingkahulugan) and antonyms (kasalungat) in the Filipino language. Twenty-four students from Grades 4, 5, and 6 were invited to play and answer comprehension tests to determine whether the game helped them improve their understanding of the content. Self-report questionnaires assessed the extent to which they enjoyed it. Additionally, three teachers were invited to a focus group discussion (FGD) to gather their insights about the game and how they may use it in their classes. Self-report feedback from students showed …

Predicting Stag And Hare Hunting Behaviors Using Hidden Markov Model, Rex Bringula, Ma. Mercedes T. Rodrigo

Department of Information Systems & Computer Science Faculty Publications

In this paper, we used Hidden Markov Model (HMM) to describe the gaming behaviors of students and whether they will exhibit “stag” or “hare” hunting behavior in a mobile game for mathematics learning. We found that there is a 99% probability that the students will stay either as stag or hare hunters. Our results also suggest that they would choose arithmetic problems involving addition. These game behaviors are not beneficial to learning because they are only exhibiting mathematical skills they already know. The results of the study show that stag and hare hunters have unique traits that separate the one …

Structure-Priority Image Restoration Through Genetic Algorithm Optimization, Zhaoxia Wang, Haibo Pen, Ting Yang, Quan Wang

Research Collection School Of Computing and Information Systems

With the significant increase in the use of image information, image restoration has been gaining much attention by researchers. Restoring the structural information as well as the textural information of a damaged image to produce visually plausible restorations is a challenging task. Genetic algorithm (GA) and its variants have been applied in many fields due to their global optimization capabilities. However, the applications of GA to the image restoration domain still remain an emerging discipline. It is still challenging and difficult to restore a damaged image by leveraging GA optimization. To address this problem, this paper proposes a novel GA-based …

Med-Asa Smart Task-Volunteer Matching System, Taweesin Wongpinkaew

Chulalongkorn University Theses and Dissertations (Chula ETD)

In the context of healthcare, volunteers play an important role in improving the patient's experience and lowering the operational cost. However, the process which facilitate their management is reported to be problematic. In this thesis, the problems of the current system is explored, and a potential solution of a new IT system is outlined. The system was tested for a duration of 2 month during the COVID-19 outbreak in Thailand. SUS and an in-depth interview was conducted in order to gauge the usability and the effectiveness the system. The time it takes for the volunteers to go through with the …

Repositories For Taxonomic Data: Where We Are And What Is Missing, Aurélian Miralles, Teddy Bruy, Katherine Wolcott, Mark D. Scherz, Dominik Begerow, Bank Beszteri, Michael Bonkowski, Janine Felden, Birgit Gemeinholzer, Frank Glaw, Frank Oliver Glöckner, Oliver Hawlitschek, Ivaylo Kostadinov, Tim W. Nattkemper, Christian Printzen, Jasmin Renz, Nataliya Rybalka, Marc Stadler, Tanja Weibulat, Thomas Wilke, Susanne S. Renner, Miguel Vences

Harold W. Manter Laboratory: Library Materials

Natural history collections are leading successful large-scale projects of specimen digitization (images, metadata, DNA barcodes), thereby transforming taxonomy into a big data science. Yet, little effort has been directed towards safeguarding and subsequently mobilizing the considerable amount of original data generated during the process of naming 15,000–20,000 species every year. From the perspective of alpha-taxonomists, we provide a review of the properties and diversity of taxonomic data, assess their volume and use, and establish criteria for optimizing data repositories. We surveyed 4,113 alpha-taxonomic studies in representative journals for 2002, 2010, and 2018, and found an increasing yet comparatively limited use …

Optimal Feature Selection For Learning-Based Algorithms For Sentiment Classification, Zhaoxia Wang, Zhiping Lin

Research Collection School Of Computing and Information Systems

Sentiment classification is an important branch of cognitive computation—thus the further studies of properties of sentiment analysis is important. Sentiment classification on text data has been an active topic for the last two decades and learning-based methods are very popular and widely used in various applications. For learning-based methods, a lot of enhanced technical strategies have been used to improve the performance of the methods. Feature selection is one of these strategies and it has been studied by many researchers. However, an existing unsolved difficult problem is the choice of a suitable number of features for obtaining the best sentiment …