Databases and Information Systems Commons^™

Healthcare It In Skilled Nursing And Post-Acute Care Facilities: Reducing Hospital Admissions And Re-Admissions, Improving Reimbursement And Improving Clinical Operations, Scott L. Hopes

USF Tampa Graduate Theses and Dissertations

Health information technology (HIT), which includes electronic health record (EHR) systems and clinical data analytics, has become a major component of all health care delivery and care management. The adoption of HIT by physicians, hospitals, post-acute care organizations, pharmacies and other health care providers has been accepted as a necessary (and recently, a government required) step toward improved quality, care coordination and reduced costs: “Better coordination of care provides a path to improving communication, improving quality of care, and reducing unnecessary emergency room use and hospital readmissions. LTPAC providers play a critical role in achieving these goals” (HealthIT.gov, 2013).

Though …

Modeling Habitat Suitability Of Invasive Carps In The Upper Missisisippi River System, Charlotte Alexander, Robert F. Allen, Kevin J. Aagard

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

A Conversation Centric Approach To Understanding And Supporting The Coordination Of Social Group-Activities, Richard P. Schuler

Dissertations

Despite the widespread and large variety of communication tools available to us such as, text messaging, Skype, email, twitter, Facebook, instant messaging, GroupMe, WhatsApp, Snapchat, etc., many people still routinely find coordinating activities with our friends to be a very frustrating experience. Everyone, has at least once, encountered the difficulties involved with deciding what to do as a group. Some friends may be busy, others may have already seen the movie that the others want to see, and some do not like Mexican food. It is a challenge everyone has faced and continue to face. This is a result of …

Cross-Modal Recipe Retrieval With Rich Food Attributes, Jingjing Chen, Chong-Wah Ngo, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Food is rich of visible (e.g., colour, shape) and procedural (e.g., cutting, cooking) attributes. Proper leveraging of these attributes, particularly the interplay among ingredients, cutting and cooking methods, for health-related applications has not been previously explored. This paper investigates cross-modal retrieval of recipes, specifically to retrieve a text-based recipe given a food picture as query. As similar ingredient composition can end up with wildly different dishes depending on the cooking and cutting procedures, the difficulty of retrieval originates from fine-grained recognition of rich attributes from pictures. With a multi-task deep learning model, this paper provides insights on the feasibility of …

Visual Sentiment Analysis For Review Images With Item-Oriented And User-Oriented Cnn, Quoc Tuan Truong, Hady W. Lauw

Research Collection School Of Computing and Information Systems

Online reviews are prevalent. When recounting their experience with a product, service, or venue, in addition to textual narration, a reviewer frequently includes images as photographic record. While textual sentiment analysis has been widely studied, in this paper we are interested in visual sentiment analysis to infer whether a given image included as part of a review expresses the overall positive or negative sentiment of that review. Visual sentiment analysis can be formulated as image classification using deep learning methods such as Convolutional Neural Networks or CNN. However, we observe that the sentiment captured within an image may be affected …

Delving Into Salient Object Subitizing And Detection, Shengfeng He, Jianbo Jiao, Xiaodan Zhang, Guoqiang Han, Rynson W.H Lau

Research Collection School Of Computing and Information Systems

Subitizing (i.e., instant judgement on the number) and detection of salient objects are human inborn abilities. These two tasks influence each other in the human visual system. In this paper, we delve into the complementarity of these two tasks. We propose a multi-task deep neural network with weight prediction for salient object detection, where the parameters of an adaptive weight layer are dynamically determined by an auxiliary subitizing network. The numerical representation of salient objects is therefore embedded into the spatial representation. The proposed joint network can be trained end-to-end using backpropagation. Experiments show the proposed multi-task network outperforms existing …

Tensor Factorization For Low-Rank Tensor Completion, Pan Zhou, Canyi Lu, Zhouchen Lin, Chao Zhang

Research Collection School Of Computing and Information Systems

Recently, a tensor nuclear norm (TNN) based method [1] was proposed to solve the tensor completion problem, which has achieved state-of-the-art performance on image and video inpainting tasks. However, it requires computing tensor singular value decomposition (t-SVD), which costs much computation and thus cannot efficiently handle tensor data, due to its natural large scale. Motivated by TNN, we propose a novel low-rank tensor factorization method for efficiently solving the 3-way tensor completion problem. Our method preserves the lowrank structure of a tensor by factorizing it into the product of two tensors of smaller sizes. In the optimization process, our method …

Interactive Visual Analytics Application For Spatiotemporal Movement Data Vast Challenge 2017 Mini-Challenge 1: Award For Actionable And Detailed Analysis, Yifei Guan, Tin Seong Kam

Research Collection School Of Computing and Information Systems

The Visual Analytics Science and Technology (VAST) Challenge 2017 Mini-Challenge 1 dataset mirrored the challenging scenarios in analysing large spatiotemporal movement tracking datasets. The datasets provided contains a 13-month movement data generated by five types of sensors, for six types of vehicles passing through the Boonsong Lekagul Nature Preserve. We present an application developed with the market leading visualisation software Tableau to provide an interactive visual analysis of the multi-dimensional spatiotemporal datasets. Our interactive application allows the user to perform an interactive analysis to observe movement patterns, study vehicle trajectories and identify movement anomalies while allowing them to customise the …

Tagscan: Simultaneous Target Imaging And Material Identification With Commodity Rfid Devices, Ju Wang, Jie Xiong, Xiaojiang Chen, Hongbo Jiang, Rajesh Krishna Balan, Dingyi Fang

Research Collection School Of Computing and Information Systems

Target imaging and material identification play an important role in many real-life applications. This paper introduces TagScan, a system that can identify the material type and image the horizontal cut of a target simultaneously with cheap commercial of-the-shelf (COTS) RFID devices. The key intuition is that different materials and target sizes cause different amounts of phase and RSS (Received Signal Strength) changes when radio frequency (RF) signal penetrates through the target. Multiple challenges need to be addressed before we can turn the idea into a functional system including (i) indoor environments exhibit rich multipath which breaks the linear relationship between …

Vungle Inc. Improves Monetization Using Big-Data Analytics, Bert De Reyck, Ioannis Fragkos, Yael Gruksha-Cockayne, Casey Lichtendahl, Hammond Guerin, Andre Kritzer

Research Collection Lee Kong Chian School Of Business

The advent of big data has created opportunities for firms to customize their products and services to unprecedented levels of granularity. Using big data to personalize an offering in real time, however, remains a major challenge. In the mobile advertising industry, once a customer enters the network, an ad-serving decision must be made in a matter of milliseconds. In this work, we describe the design and implementation of an ad-serving algorithm that incorporates machine-learning methods to make personalized ad-serving decisions within milliseconds. We developed this algorithm for Vungle Inc., one of the largest global mobile ad networks. Our approach also …

Every Step You Take, I’Ll Be Watching You: Practical Stepauth-Entication Of Rfid Paths, Kai Bu, Yingjiu Li

Research Collection School Of Computing and Information Systems

Path authentication thwarts counterfeits in RFID-based supply chains. Its motivation is that tagged products taking invalid paths are likely faked and injected by adversaries at certain supply chain partners/steps. Existing solutions are path-grained in that they simply regard a product as genuine if it takes any valid path. Furthermore, they enforce distributed authentication by offloading the sets of valid paths to some or all steps from a centralized issuer. This not only imposes network and storage overhead but also leaks transaction privacy. We present StepAuth, the first step-grained path authentication protocol that is practically efficient for authenticating products with strict …

Every Step You Take, I’Ll Be Watching You: Practical Stepauth-Entication Of Rfid Paths, Kai Bu, Yingjiu Li

Research Collection School Of Computing and Information Systems

Path authentication thwarts counterfeits in RFID-based supply chains. Its motivation is that tagged products taking invalid paths are likely faked and injected by adversaries at certain supply chain partners/steps. Existing solutions are path-grained in that they simply regard a product as genuine if it takes any valid path. Furthermore, they enforce distributed authentication by offloading the sets of valid paths to some or all steps from a centralized issuer. This not only imposes network and storage overhead but also leaks transaction privacy. We present StepAuth, the first step-grained path authentication protocol that is practically efficient for authenticating products with strict …

Benchmarking Single-Image Reflection Removal Algorithms, Renjie Wan, Boxin Shi, Ling-Yu Duan, Ah-Hwee Tan, Alex C. Kot

Research Collection School Of Computing and Information Systems

Removing undesired reflections from a photo taken in front of a glass is of great importance for enhancing the efficiency of visual computing systems. Various approaches have been proposed and shown to be visually plausible on small datasets collected by their authors. A quantitative comparison of existing approaches using the same dataset has never been conducted due to the lack of suitable benchmark data with ground truth. This paper presents the first captured Single-image Reflection Removal dataset `SIR 2 ' with 40 controlled and 100 wild scenes, ground truth of background and reflection. For each controlled scene, we further provide …

Pic2dish: A Customized Cooking Assistant System, Yongsheng An, Yu Cao, Jingjing Chen, Chong-Wah Ngo, Jia Jia, Huanbo Luan, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

The art of cooking is always fascinating. Nevertheless, reproducing a delicious dish that one has never encountered before is not easy. Even if the name of dish is known and the corresponding recipe could be retrieved, the right ingredients for cooking the dish may not be available due to factors such as geography region or season. Furthermore, knowing how to cut, cook and control timing may be challenging for one whose has no cooking experience. In this paper, an all-around cooking assistant mobile app, named Pic2Dish, is developed to help users who would like to cook a dish but neither …

Spatiotemporal Identification Of Anomalies In A Wildlife Preserve, Bharadwaj Kishan, Jason Guan Jie Ong, Yanrong Zhang, Tin Seong Kam

Research Collection School Of Computing and Information Systems

The datasets released for the VAST Challenge 2017 comprise vehicle movement data captured with RFID sensors, chemical emission data from factories captured by gas sensors, and image attributes of the wildlife plant health obtained from satellites, all pertaining to a fictional wildlife preserve. Using visual analytics, a compelling hypothesis is established to link the spatiotemporal datasets to the phenomenon, where the count of a bird specimen is found to decline over a given year. Anomalies in vehicle traffic patterns are linked to proximal factory emissions, and further associated with satellite imagery that show proof of degradation in plant quality in …

Systematic Analysis Of Enterprise Perception Towards Cloud Adoption In The African States: The Nigerian Perspective, George A. Oguntala, Prof. Raed A. Abd-Alhameed, Dr. Janet O. Odeyemi

The African Journal of Information Systems

The desirous benefits of cloud computing such as high return on investment through efficient resource management, high application throughput and on-demand capabilities have resulted in the unprecedented global acceptance of the computing paradigm. However, research on cloud adoption indicates that fewer organisations in the African states are adopting cloud services. Thus, the purview of the paper is to examine the factors responsible for the poor adoption of cloud computing in most African enterprises using Nigeria as a case study. The study focus on the perception of IT and non-IT employees towards cloud computing. Moreover, the paper reviews the literature on …

Enhancing The Internet Of Things Architecture With Flow Semantics, Allen Ronald Deserranno

USF Tampa Graduate Theses and Dissertations

Internet of Things (‘IoT’) systems are complex, asynchronous solutions often comprised of various software and hardware components developed in isolation of each other. These components function with different degrees of reliability and performance over an inherently unreliable network, the Internet. Many IoT systems are developed within silos that do not provide the ability to communicate or be interoperable with other systems and platforms. Literature exists on how these systems should be designed, how they should interoperate, and how they could be improved, but practice does not always consult literature.

The work brings together a proposed reference architecture for the IoT …

A System For Stratified Sampling Of Entity Resolution Results To Assess And Improve Accuracy With Minimal Clerical Review Effort, Daniel L. Pullen

Theses and Dissertations

Organizations across many industries from banking to medicine depend on master data that describe their customers, products and services. Data integration and unique representations of master data are supported by Entity Resolution processes to link records for the same master entity. Master data is key to the core operations of these organizations. Unfortunately, many of these organizations do not use a systematic method, or in some cases, use no method for measuring and improving the quality of record linkage provided by Entity Resolution. This research presents an implementation and proposed methodology for routinely and systematically measuring the quality of Entity …

Combining Machine-Based And Econometrics Methods For Policy Analytics Insights, Robert J. Kauffman, Kwansoo Kim, Sang-Yong Tom Lee, Ai Phuong Hoang, Jing Ren

Research Collection School Of Computing and Information Systems

Computational Social Science (CSS) has become a mainstream approach in the empirical study of policy analytics issues in various domains of e-commerce research. This article is intended to represent recent advances that have been made for the discovery of new policy-related insights in business, consumer, and social settings. The approach discussed is fusion analytics, which combines machine-based methods from Computer Science (CS) and explanatory empiricism involving advanced Econometrics and Statistics. It explores several efforts to conduct research inquiry in different functional areas of Electronic Commerce and Information Systems (IS), with applications that represent different functional areas of business, as well …

Micro-Review Synthesis For Multi-Entity Summarization, Thanh-Son Nguyen, Hady W. Lauw, Panayiotis Tsaparas

Research Collection School Of Computing and Information Systems

Location-based social networks (LBSNs), exemplified by Foursquare, are fast gaining popularity. One important feature of LBSNs is micro-review. Upon check-in at a particular venue, a user may leave a short review (up to 200 characters long), also known as a tip. These tips are an important source of information for others to know more about various aspects of an entity (e.g., restaurant), such as food, waiting time, or service. However, a user is often interested not in one particular entity, but rather in several entities collectively, for instance within a neighborhood or a category. In this paper, we address the …

Clsters: A General System For Reducing Errors Of Trajectories Under Challenging Localization Situations, Hao Wu, Weiwei Sun, Baihua Zheng, Li Yang, Wei Zhou

Research Collection School Of Computing and Information Systems

Trajectory data generated by outdoor activities have great potential for location based services. However, depending on the localization technique used, certain trajectory data could contain large errors. For example, the error of trajectories generated by cellular-based localization techniques is around 100m which is ten times larger than that of GPS-based trajectories. Hence, enhancing the utility of those large-error trajectories becomes a challenge. In this paper we show how to improve the quality of trajectory data having large errors. Some existing works reduce the error through hardware which requires information such as the time of arrival (TOA), received signal strength indication …

Vurle: Automatic Vulnerability Detection And Repair By Learning From Examples, Ma Siqi, Ferdian Thung, David Lo, Cong Sun, Robert H. Deng

Research Collection School Of Computing and Information Systems

Vulnerability becomes a major threat to the security of many systems. Attackers can steal private information and perform harmful actions by exploiting unpatched vulnerabilities. Vulnerabilities often remain undetected for a long time as they may not affect typical systems’ functionalities. Furthermore, it is often difficult for a developer to fix a vulnerability correctly if he/she is not a security expert. To assist developers to deal with multiple types of vulnerabilities, we propose a new tool, called VuRLE, for automatic detection and repair of vulnerabilities. VuRLE (1) learns transformative edits and their contexts (i.e., code characterizing edit locations) from examples of …

On-Demand Developer Documentation, Martin P. Robillard, Andrian Marcus, Christoph Treude, Gabriele Bavota, Oscar Chaparro, Neil Ernst, Marco Aurélio Gerosa, Michael Godfrey, Michele Lanza, Mario Linares-Vasquez, Gail C. Murphy, Laura Moreno, David Shepherd, Edmund Wong

Research Collection School Of Computing and Information Systems

We advocate for a paradigm shift in supporting the information needs of developers, centered around the concept of automated on-demand developer documentation. Currently, developer information needs are fulfilled by asking experts or consulting documentation. Unfortunately, traditional documentation practices are inefficient because of, among others, the manual nature of its creation and the gap between the creators and consumers. We discuss the major challenges we face in realizing such a paradigm shift, highlight existing research that can be leveraged to this end, and promote opportunities for increased convergence in research on software documentation.

Vcksm: Verifiable Conjunctive Keyword Search Over Mobile E-Health Cloud In Shared Multi-Owner Settings, Yinbin Miao, Jianfeng Ma, Ximeng Liu, Qi Jiang, Junwei Zhang, Limin Shen, Zhiquan Liu

Research Collection School Of Computing and Information Systems

Searchable encryption (SE) is a promising technique which enables cloud users to conduct search over encrypted cloud data in a privacy-preserving way, especially for the electronic health record (EHR) system that contains plenty of medical history, diagnosis, radiology images, etc. In this paper, we focus on a more practical scenario, also named as the shared multi-owner settings, where each e-health record is co-owned by a fixed number of parties. Although the existing SE schemes under the unshared multi-owner settings can be adapted to this shared scenario, these schemes have to build multiple indexes,which definitely incur higher computational overhead. To save …

Personalized Microtopic Recommendation On Microblogs, Yang Li, Jing Jiang, Ting Liu, Minghui Qiu, Xiaofei Sun

Research Collection School Of Computing and Information Systems

Microblogging services such as Sina Weibo and Twitter allow users to create tags explicitly indicated by the # symbol. In Sina Weibo, these tags are called microtopics, and in Twitter, they are called hashtags. In Sina Weibo, each microtopic has a designate page and can be directly visited or commented on. Recommending these microtopics to users based on their interests can help users efficiently acquire information. However, it is non-trivial to recommend microtopics to users to satisfy their information needs. In this article, we investigate the task of personalized microtopic recommendation, which exhibits two challenges. First, users usually do not …

Understanding Stack Overflow Code Fragments, Christoph Treude, Martin P. Robillard

Research Collection School Of Computing and Information Systems

Code fragments posted in answers on Q&A forums can form an important source of developer knowledge. However, effective reuse of code fragments found online often requires information other than the code fragment alone. We report on the results of a survey-based study to investigate to what extent developers perceive Stack Overflow code fragments to be self-explanatory. As part of the study, we also investigated the types of information missing from fragments that were not self-explanatory. We find that less than half of the Stack Overflow code fragments in our sample are considered to be self-explanatory by the 321 participants who …

Machine Learning Based Protein Sequence To (Un)Structure Mapping And Interaction Prediction, Sumaiya Iqbal

LSU New Orleans Theses and Dissertations

Proteins are the fundamental macromolecules within a cell that carry out most of the biological functions. The computational study of protein structure and its functions, using machine learning and data analytics, is elemental in advancing the life-science research due to the fast-growing biological data and the extensive complexities involved in their analyses towards discovering meaningful insights. Mapping of protein’s primary sequence is not only limited to its structure, we extend that to its disordered component known as Intrinsically Disordered Proteins or Regions in proteins (IDPs/IDRs), and hence the involved dynamics, which help us explain complex interaction within a cell that …

Ancr—An Adaptive Network Coding Routing Scheme For Wsns With Different-Success-Rate Links †, Xiang Ji, Anwen Wang, Chunyu Li, Chun Ma, Yao Peng, Dajin Wang, Qingyi Hua, Feng Chen, Dingyi Fang

Department of Computer Science Faculty Scholarship and Creative Works

As the underlying infrastructure of the Internet of Things (IoT), wireless sensor networks (WSNs) have been widely used in many applications. Network coding is a technique in WSNs to combine multiple channels of data in one transmission, wherever possible, to save node’s energy as well as increase the network throughput. So far most works on network coding are based on two assumptions to determine coding opportunities: (1) All the links in the network have the same transmission success rate; (2) Each link is bidirectional, and has the same transmission success rate on both ways. However, these assumptions may not be …

Detect Rumors In Microblog Posts Using Propagation Structure Via Kernel Learning, Jing Ma, Wei Gao, Kam-Fai Wong

Research Collection School Of Computing and Information Systems

How fake news goes viral via social media? How does its propagation pattern differ from real stories? In this paper, we attempt to address the problem of identifying rumors, i.e., fake information, out of microblog posts based on their propagation structure. We firstly model microblog posts diffusion with propagation trees, which provide valuable clues on how an original message is transmitted and developed over time. We then propose a kernel-based method called Propagation Tree Kernel, which captures high-order patterns differentiating different types of rumors by evaluating the similarities between their propagation tree structures. Experimental results on two real-world datasets demonstrate …

Predicting Locations Of Pollution Sources Using Convolutional Neural Networks, Yiheng Chi, Nickolas D. Winovich, Guang Lin

The Summer Undergraduate Research Fellowship (SURF) Symposium

Pollution is a severe problem today, and the main challenge in water and air pollution controls and eliminations is detecting and locating pollution sources. This research project aims to predict the locations of pollution sources given diffusion information of pollution in the form of array or image data. These predictions are done using machine learning. The relations between time, location, and pollution concentration are first formulated as pollution diffusion equations, which are partial differential equations (PDEs), and then deep convolutional neural networks are built and trained to solve these PDEs. The convolutional neural networks consist of convolutional layers, reLU layers …