Physical Sciences and Mathematics Commons^™

Cloud Computing And Enterprise Data Reliability, Luan Gashi

UBT International Conference

Cloud services offer many benefits from information and communication technology that to be credible must first be secured. To use the potential of cloud computing, data is transferred, processed and stored in the infrastructures of these service providers. This indicates that the owners of data, particularly enterprises, have puzzled when storing their data is done outside the scope of their control.

Research conducted on this topic show how this should be addressed unequivocally. The provided information on the organization of cloud computing models, services and standards, with a focus on security aspects in protecting enterprise data where emphasis shows how …

The Role Of Knowledge Management In The Information System, Sejdi Xhemaili

UBT International Conference

We are living in a world in which the knowledge is a precious commodity. The fast pace of the development of the companies both for trade and service require management of the acquired knowledge in the best possible way.

This paper would show the influence of the knowledge management in the information system that is what is achieved when knowledge management itself is applied to the information system. The accumulated knowledge in terms of innovation, management of the staff and its training, competitiveness on the wide market and improvement of the level of the business processes and performance tend to …

The Importance Of Big Data Analytics, Eljona Proko

UBT International Conference

Identified as the tendency of IT, Big Data gained global attention. Advances in data analytics are changing the way businesses compete, enabling them to make faster and better decisions based on real-time analysis. Big Data introduces a new set of challenges. Three characteristics define Big Data: volume, variety, and velocity. Big Data requires tools and methods that can be applied to analyze and extract patterns from large-scale data. Companies generate enormous volumes of poly-structured data from Web, social network posts, sensors, mobile devices, emails, and many other sources. Companies need a cost-effective, massively scalable solution for capturing, storing, and analyzing …

Traditional Mathematics And New Methods Of Teaching Through Programming Together With Students, Robert Kosova, Teuta Thanasi, Lindita Mukli, Loreta Nakuçi Pëllumbi

UBT International Conference

We are used to the traditional methods of teaching mathematics. The textbook, the blackboard and a chalk have been for centuries a wonderful part of teaching. And, they always will be. Traditional teaching methods of mathematics are a wonderful legacy of our educational system that have educated generations of teachers, engineers, administrators, managers, leaders, and economists. American universities websites, the video- lectures of the best professors of well-known disciplines such as statistics, operational research, number theory, algebra, game theory, show impressing large blackboards, all over the auditor's walls. We always will need and admire traditional mathematics. But, beyond the lessons, …

State Preserving Extreme Learning Machine For Face Recognition, Md. Zahangir Alom, Paheding Sidike, Vijayan K. Asari, Tarek M. Taha

Vijayan K. Asari

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 …

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

Vijayan K. Asari

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 …

A Modular Approach For Key-Frame Selection In Wide Area Surveillance Video Analysis, Almabrok Essa, Paheding Sidike, Vijayan K. Asari

Vijayan K. Asari

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.

Women On The Board Of Directors And Their Impact On The Financial Performance Of A Firm: An Empirical Investigation Of Female Directors In The United States Technology Sector, Obinna Mogbogu

Theses and Dissertations

This study uses a sample of S&P 500 firms in the United States technology sector to investigate the likely relationship between female directors and financial performance of firms measured by return on average assets and return on average equity as the two accounting based measures of performance. Reasonable theoretical arguments drawn from resource dependency, human capital, agency, and social psychology theory, suggests that the gender diversity of the board of directors may have either a positive, negative, or neutral effect on the financial performance of the firm. Using nonparametric statistics approach, we find a small negative relationship between female directors …

Github: An Introduction, Craig A. Boman

Roesch Library Staff Presentations

Tech startups have been using version control software to maximize their collaborative technology projects since their inception, but what more can librarians do to leverage this suite of tools? In this presentation, we will briefly describe how version control apps like Github may drastically improve technology collaborations in your library, specifically ILS web refreshes. After the Github introduction, those who participated in the pre-conference "hackathon" session will discuss their projects and talk about the successes and challenges they encountered.

Rediscovering Physical Collections Through The Digital Archive: The Jesuit Libraries Provenance Project, Kyle Roberts

History: Faculty Publications and Other Works

Historic library collections offer a rich and underexplored resource for teaching undergraduate and graduate students about new digital approaches, methodologies, and platforms. Their scope and scale can make them difficult to analyze in their physical form, but remediated onto a digital platform, they offer valuable insights into the process of archive creation and the importance of making their content available to audiences that cannot normally access it. The Jesuit Libraries Provenance Project (JLPP) was launched by students, faculty, and library professionals in 2014 to create an online archive of marks of ownership—bookplates, stamps, inscriptions—contained within books from the original library …

Active Snort Rules And The Needs For Computing Resources: Computing Resources Needed To Activate Different Numbers Of Snort Rules, Chad A. Arney, Xinli Wang

School of Technology Publications

This project was designed to discover the relationship between the number of enabled rules maintained by Snort and the amount of computing resources necessary to operate this intrusion detection system (IDS) as a sensor. A physical environment was set up to loosely simulate a network and an IDS sensor monitoring it.

The experiment was conducted in five trials. A different number of Snort rules was enabled in each trial and the corresponding utilization of computing resources was measured. Remarkable variation and a clear trend of CPU usage were observed in the experiment.

Development And Semantic Exploitation Of A Relational Data Model For Service Delivery In South African Municipalities, Kgotatso Desmond Mogotlane, Jean Vincent Fonou Dombeu

The African Journal of Information Systems

Relational databases (RDB) are the main sources of structured data for government institutions and businesses. Since these databases are dependent on autonomous hardware and software they create problems of data integration and interoperability. Solutions have been proposed to convert RDB into ontology to enable their sharing, reuse and integration on the Semantic Web. However, the proposed methods and techniques remain highly technical and there is lack of research that focuses on the empirical application of these methods and techniques in information systems (IS) domains. This study develops and semantically exploits a relational data model of the South African Municipalities Information …

Ubiquitous Electronic Medical Record (Emr) For Developing Countries, Nasser Mohammed Alkathiri

Master's Theses (2009 -)

Around the globe, Healthcare Information Technology (HIT) has been evolved either by governments or healthcare providers. The utilization of these technologies has resulted in the improvement of healthcare services all over the world. This evolution has been characterized by availability, reliability, serviceability to patients, and has been enhanced with increased cost and time efficiency. As such, new systems and terms have been established. Electronic Medical Record (EMR), which can also be used interchangeably with Electronic Health Record (EHR) is considered to be the main transformation in healthcare information technologies. EMR has been aimed to reduce and eliminate existing paper based …

Inferring Links Between Concerns And Methods With Multi-Abstraction Vector Space Model, Yun Zhang, David Lo, Xin Xia, Tien-Duy B. Le, Giuseppe Scanniello, Jianling Sun

Research Collection School Of Computing and Information Systems

Concern localization refers to the process of locating code units that match a particular textual description. It takes as input textual documents such as bug reports and feature requests and outputs a list of candidate code units that are relevant to the bug reports or feature requests. Many information retrieval (IR) based concern localization techniques have been proposed in the literature. These techniques typically represent code units and textual descriptions as a bag of tokens at one level of abstraction, e.g., each token is a word, or each token is a topic. In this work, we propose a multi-abstraction concern …

Arise-Pie: A People Information Integration Engine Over The Web, Vincent W. Zheng, Tao Hoang, Penghe Chen, Yuan Fang, Xiaoyan Yang

Research Collection School Of Computing and Information Systems

Searching for people information on the Web is a common practice in life. However, it is time consuming to search for such information manually. In this paper, we aim to develop an automatic people information search system, named ARISE-PIE. To build such a system, we tackle two major technical challenges: data harvesting and data integration. For data harvesting, we study how to leverage search engine to help crawl the relevant Web pages for a target entity; then we propose a novel learning to query model that can automatically select a set of "best" queries to maximize collective utility (e.g., precision …

Deep-Based Ingredient Recognition For Cooking Recipe Retrieval, Jingjing Chen, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Retrieving recipes corresponding to given dish pictures facilitates the estimation of nutrition facts, which is crucial to various health relevant applications. The current approaches mostly focus on recognition of food category based on global dish appearance without explicit analysis of ingredient composition. Such approaches are incapable for retrieval of recipes with unknown food categories, a problem referred to as zero-shot retrieval. On the other hand, content-based retrieval without knowledge of food categories is also difficult to attain satisfactory performance due to large visual variations in food appearance and ingredient composition. As the number of ingredients is far less than food …

Plackett-Luce Regression Mixture Model For Heterogeneous Rankings, Maksim Tkachenko, Hady W. Lauw

Research Collection School Of Computing and Information Systems

Learning to rank is an important problem in many scenarios, such as information retrieval, natural language processing, recommender systems, etc. The objective is to learn a function that ranks a number of instances based on their features. In the vast majority of the learning to rank literature, there is an implicit assumption that the population of ranking instances are homogeneous, and thus can be modeled by a single central ranking function. In this work, we are concerned with learning to rank for a heterogeneous population, which may consist of a number of sub-populations, each of which may rank objects dierently. …

Fast And Adaptive Indexing Of Multi-Dimensional Observational Data, Sheng Wang, David Maier, Beng Chin Ooi

Computer Science Faculty Publications and Presentations

Sensing devices generate tremendous amounts of data each day, which include large quantities of multi-dimensional measurements. These data are expected to be immediately available for real-time analytics as they are streamed into storage. Such scenarios pose challenges to state-of-the-art indexing methods, as they must not only support efficient queries but also frequent updates. We propose here a novel indexing method that ingests multi-dimensional observational data in real time. This method primarily guarantees extremely high throughput for data ingestion, while it can be continuously refined in the background to improve query efficiency. Instead of representing collections of points using Minimal Bounding …

Satt: Tailoring Code Metric Thresholds For Different Software Architectures, Maurício Aniche, Christoph Treude, Andy Zaidman, Arie Van Deursen, Marco Aurélio Gerosa

Research Collection School Of Computing and Information Systems

Code metric analysis is a well-known approach for assessing the quality of a software system. However, current tools and techniques do not take the system architecture (e.g., MVC, Android) into account. This means that all classes are assessed similarly, regardless of their specific responsibilities. In this paper, we propose SATT (Software Architecture Tailored Thresholds), an approach that detects whether an architectural role is considerably different from others in the system in terms of code metrics, and provides a specific threshold for that role. We evaluated our approach on 2 different architectures (MVC and Android) in more than 400 projects. We …

Mabic: Mobile Application Builder For Interactive Communication, Huy Manh Nguyen

Masters Theses & Specialist Projects

Nowadays, the web services and mobile technology advance to a whole new level. These technologies make the modern communication faster and more convenient than the traditional way. People can also easily share data, picture, image and video instantly. It also saves time and money. For example: sending an email or text message is cheaper and faster than a letter. Interactive communication allows the instant exchange of feedback and enables two-way communication between people and people, or people and computer. It increases the engagement of sender and receiver in communication.

Although many systems such as REDCap and Taverna are built for …

Online Adaptive Passive-Aggressive Methods For Non-Negative Matrix Factorization And Its Applications, Chenghao Liu, Hoi, Steven C. H., Peilin Zhao, Jianling Sun, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

This paper aims to investigate efficient and scalable machine learning algorithms for resolving Non-negative Matrix Factorization (NMF), which is important for many real-world applications, particularly for collaborative filtering and recommender systems. Unlike traditional batch learning methods, a recently proposed online learning technique named "NN-PA" tackles NMF by applying the popular Passive-Aggressive (PA) online learning, and found promising results. Despite its simplicity and high efficiency, NN-PA falls short in at least two critical limitations: (i) it only exploits the first-order information and thus may converge slowly especially at the beginning of online learning tasks; (ii) it is sensitive to some key …

Attractiveness Versus Competition: Towards An Unified Model For User Visitation, Thanh-Nam Doan, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Modeling user check-in behavior provides useful insights about venues as well as the users visiting them. These insights can be used in urban planning and recommender system applications. Unlike previous works that focus on modeling distance effect on user’s choice of check-in venues, this paper studies check-in behaviors affected by two venue-related factors, namely, area attractiveness and neighborhood competitiveness. The former refers to the ability of an area with multiple venues to collectively attract checkins from users, while the latter represents the ability of a venue to compete with its neighbors in the same area for check-ins. We first embark …

Tracking Virality And Susceptibility In Social Media, Tuan Anh Hoang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

In social media, the magnitude of information propagation hinges on the virality and susceptibility of users spreading and receiving the information respectively, as well as the virality of information items. These users' and items' behavioral factors evolve dynamically at the same time interacting with one another. Previous works however measure the factors statically and independently in a restricted case: each user has only a single adoption on each item, and/or users' exposure to items are observable. In this work, we investigate the inter-relationship among the factors and users' multiple adoptions on items to propose both new static and temporal models …

Behavior Analysis In Social Networks: Challenges, Technologies, And Trends, Meng Wang, Ee-Peng Lim, Lei Li, Mehmet Orgun

Research Collection School Of Computing and Information Systems

The research on social networks has advanced significantly, which can be attributed to the prevalence of the online social websites and instant messaging systems as well as the popularity of mobile apps that support easy access to online social networks. These social networks are usually characterized by the complex network structures and rich contextual information. They now become the key platforms for, among others, content dissemination, professional networking, recommendation, alerting, and political campaigns. As online social network users perform activities on the social networks, they leave data traces of human behavior which allow the latter to be studied at scale. …

Data Visualizations And Infographics, Darren Sweeper

Sprague Library Scholarship and Creative Works

No abstract provided.

Two Roads, One Destination: A Journey Of Discovery, Karen Joc, Peta J. Hopkins, Jessie Donaghey, Wendy Abbott

Peta Hopkins

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.

Product Complexity: A Definition And Impacts On Operations, Mark A. Jacobs

Mark A. Jacobs

The difficulty for organizations arises because neither complexity nor its impacts on performance are well understood (Fisher & Ittner, 1999b). The mechanisms through which it affects cost, quality, delivery, and flexibility need to be explained (Ramdas, 2003). However, this cannot happen until complexity can be explained theoretically. But, to build theory there must first be a common understanding about the construct of interest (Wacker, 2004). Only then can researchers operationalize it and search for meaningful relationships. In light of this, I develop a definition of complexity below. A sampling of the operations management literature is then presented within the context …

Volume And Cost Implications Of Product Portfolio Complexity, Mark A. Jacobs

Mark A. Jacobs

Business leaders are concerned about the impacts of increasing levels of product portfolio complexity since many sense that complexity related costs such as order management, procurement, and inventory threaten to undermine operational efficiencies and consume profits. Even so, managers do not fully understand the extent and breadth of the impacts of product portfolio complexity. A more complete understanding of the operational effects of product portfolio complexity is lacking partially because researchers have not yet offered a robust theoretical perspective or studied it in a focused controlled way; until now. Herein, measures of product portfolio complexity are developed and related to …

Get Me To My Gate On Time: Efficiently Solving General-Sum Bayesian Threat Screening Games, Aaron Schlenker, Matthew Brown, Arunesh Sinha, Milind Tambe, Ruta Mehta

Research Collection School Of Computing and Information Systems

Threat Screening Games (TSGs) are used in domains where there is a set of individuals or objects to screen with a limited amount of screening resources available to screen them. TSGs are broadly applicable to domains like airport passenger screening, stadium screening, cargo container screening, etc. Previous work on TSGs focused only on the Bayesian zero-sum case and provided the MGA algorithm to solve these games. In this paper, we solve Bayesian general-sum TSGs which we prove are NP-hard even when exploiting a compact marginal representation. We also present an algorithm based upon a adversary type hierarchical tree decomposition and …

Microblogging Content Propagation Modeling Using Topic-Specific Behavioral Factors, Tuan Anh Hoang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

When a microblogging user adopts some content propagated to her, we can attribute that to three behavioral factors, namely, topic virality, user virality, and user susceptibility. Topic virality measures the degree to which a topic attracts propagations by users. User virality and susceptibility refer to the ability of a user to propagate content to other users, and the propensity of a user adopting content propagated to her, respectively. In this paper, we study the problem of mining these behavioral factors specific to topics from microblogging content propagation data. We first construct a three dimensional tensor for representing the propagation instances. …