Databases and Information Systems Commons^™

Bing: Binarized Normed Gradients For Objectness Estimation At 300fps, Ming-Ming Cheng, Yun Liu, Wen-Yan Lin, Ziming Zhang, Paul L. Rosin, Philip H. S. Torr

Research Collection School Of Computing and Information Systems

Training a generic objectness measure to produce object proposals has recently become of significant interest. We observe that generic objects with well-defined closed boundaries can be detected by looking at the norm of gradients, with a suitable resizing of their corresponding image windows to a small fixed size. Based on this observation and computational reasons, we propose to resize the window to 8 × 8 and use the norm of the gradients as a simple 64D feature to describe it, for explicitly training a generic objectness measure. We further show how the binarized version of this feature, namely binarized normed …

Kaggle And Click-Through Rate Prediction, Todd W. Neller

Computer Science Faculty Publications

Neller presented a look at Kaggle.com, an online Data Science and Machine Learning learning community, as a place to seek rapid, experiential peer education for most any Data Science topic. Using the specific challenge of Click-Through Rate Prediction (CTRP), he focused on lessons learned from relevant Kaggle competitions on how to perform CTRP.

Astria Ontology: Open, Standards-Based, Data-Aggregated Representation Of Space Objects, Jennie Wolfgang, Kathleen Krysher, Michael Slovenski, Unmil P. Karadkar, Shiva Iyer, Moriba K. Jah

Space Traffic Management Conference

The necessity for standards-based ontologies for long-term sustainability of space operations and safety of increasing space flights has been well-established [6, 7]. Current ontologies, such as DARPA’s OrbitOutlook [5], are not publicly available, complicating efforts for their broad adoption. Most sensor data is siloed in proprietary databases [2] and provided only to authorized users, further complicating efforts to create a holistic view of resident space objects (RSOs) in order to enhance space situational awareness (SSA).

The ASTRIA project is developing an open data model with the goal of aggregating data about RSOs, parts, space weather, and governing policies in order …

Towards Secure Data Flow Oriented Multi-Vendor Ict Governance Model, Lars Magnusson, Patrik Elm, Anita Mirijamdotter

International Journal of Business and Technology

Today, still, ICT Governance is being regarded as a departmental concern, not an overall organizational concern. History has shown us that implementation strategies, which are based on departments, results in fractional implementations leading to ad hoc solutions with no central control and stagnation for the in-house ICT strategy. Further, this recently has created an opinion trend; many are talking about the ICT department as being redundant, a dying out breed, which should be replaced by on-demand specialized external services. Clearly, the evermore changing surroundings do force organizations to accelerate the pace of new adaptations within their ICT plans, more vivacious …

Implications Of Eu-Gdpr In Low-Grade Social, Activist And Ngo Settings, Lars Magnusson, Sarfraz Iqbal

International Journal of Business and Technology

Social support services are becoming popular among the citizens of every country and every age. Though, social support services easily accessible on mobile phones are used in different contexts, ranging from extending your presence and connectivity to friends, family and colleagues to using social media services for being a social activist seeking to help individuals confined in miserable situations such as homeless community, drug addicts or even revolutionists fighting against dictatorships etc. However, a very recent development in the European Parliament’s law (2016/679) on the processing and free movement of personal data in terms of EU-GDPR (General data protection rules) …

An Approach To Information Security For Smes Based On The Resource-Based View Theory, Blerton Abazi

International Journal of Business and Technology

The main focus of this proposal is to analyze implementation challenges, benefits and requirements in implementation of Information Systems and managing information security in small and medium size companies in Western Balkans countries. In relation to the study, the proposal will focus in the following questions to investigate: What are the benefits that companies mostly find after the implementation of Information Systems has been implemented, efficiency, how to they manage security of the information’s, competitive advantage, return of investments etc. The study should give a clear approach to Information Systems implementation, information security, maintenance, measurable benefits, challenges companies have gone …

Some Issues In The Testing Of Computer Simulation Models, David J. Murray-Smith

International Journal of Business and Technology

The testing of simulation models has much in common with testing processes in other types of application involving software development. However, there are also important differences associated with the fact that simulation model testing involves two distinct aspects, which are known as verification and validation. Model validation is concerned with investigation of modelling errors and model limitations while verification involves checking that the simulation program is an accurate representation of the mathematical and logical structure of the underlying model. Success in model validation depends upon the availability of detailed information about all aspects of the system being modelled. It also …

Nifty Data Structures Projects, Ed Jorgensen, Laxmi Gewali

UNLV Best Teaching Practices Expo

For computer science, and many technical fields, it is recognized that projects with real-world applicability play a significant roll in what students get out of the course. Creating applicable projects for upper division such as our data structures classes is very difficult and time consuming. We have utilized the Nifty assignments concept and applied it locally to an upper division data structures course. Our primary goal is to provide a forum for the sharing of data structure project ideas and materials (as applicable).

Trends In Women’S Participation In Computer Industry Subfields, Tristyn Maalouf

The Kabod

The participation of women in specific subfields of computer science (CS) and information technology (IT) will be investigated to determine the existence of any trends that may exist indicating special interest amongst women. Specifically, the subfield of database administration will be considered to determine if women tend to enter this subfield more frequently than other subfields. Research will also acknowledge statistics regarding male participation in database administration and other relevant subfields to determine if any trends in women’s participation are unique to women or if they exist across the board. Conclusions will be drawn based on the data and any …

Question Answering For Suicide Risk Assessment Using Reddit, Amanuel Alambo, Usha Lokala, Ugur Kursuncu, Krishnaprasad Thirunarayan, Amelia Gyrard, Randon S. Welton, Jyotishman Pathak, Amit P. Sheth

Kno.e.sis Publications

Mental Health America designed ten questionnaires that are used to determine the risk of mental disorders. They are also commonly used by Mental Health Professionals (MHPs) to assess suicidality. Specifically, the Columbia Suicide Severity Rating Scale (C-SSRS), a widely used suicide assessment questionnaire, helps MHPs determine the severity of suicide risk and offer an appropriate treatment. A major challenge in suicide treatment is the social stigma wherein the patient feels reluctance in discussing his/her conditions with an MHP, which leads to inaccurate assessment and treatment of patients. On the other hand, the same patient is comfortable freely discussing his/her mental …

Cs04all: Machine Learning Module, Hunter R. Johnson

Open Educational Resources

These are materials that may be used in a CS0 course as a light introduction to machine learning.

The materials are mostly Jupyter notebooks which contain a combination of labwork and lecture notes. There are notebooks on Classification, An Introduction to Numpy, and An Introduction to Pandas.

There are also two assessments that could be assigned to students. One is an essay assignment in which students are asked to read and respond to an article on machine bias. The other is a lab-like exercise in which students use pandas and numpy to extract useful information about subway ridership in NYC. …

Vistanet: Visual Aspect Attention Network For Multimodal Sentiment Analysis, Quoc Tuan Truong, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

Detecting the sentiment expressed by a document is a key task for many applications, e.g., modeling user preferences, monitoring consumer behaviors, assessing product quality. Traditionally, the sentiment analysis task primarily relies on textual content. Fueled by the rise of mobile phones that are often the only cameras on hand, documents on the Web (e.g., reviews, blog posts, tweets) are increasingly multimodal in nature, with photos in addition to textual content. A question arises whether the visual component could be useful for sentiment analysis as well. In this work, we propose Visual Aspect Attention Network or VistaNet, leveraging both textual and …

Gamification Of Enterprise Systems, Fiona Fui-Hoon Nah, B. Eschenbrenner, C. Claybaugh, P. Koob

Research Collection School Of Computing and Information Systems

Enterprise systems have become an integral part of an organization’s operations. However, they also pose many challenges to organizations from the perspective of implementation, user training, as well as use and acceptance. Without effective usage, enterprise systems may not be able to provide the strategic or competitive advantages that organizations desire. Therefore, organizations mayconsider gamification to enhance training, acceptance, and usage. We discuss the various ways in whichenterprise system challenges can be addressed through the lens of gamification and present a frameworkforgamificationofenterprisesystems. Theframeworkiscomprisedofbasicprinciplesand key design elements of gamification, as well as their application to enterprise systems. The specific principles of …

Partially Observable Multi-Sensor Sequential Change Detection: A Combinatorial Multi-Armed Bandit Approach, Chen Zhang, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

This paper explores machine learning to address a problem of Partially Observable Multi-sensor Sequential Change Detection (POMSCD), where only a subset of sensors can be observed to monitor a target system for change-point detection at each online learning round. In contrast to traditional Multisensor Sequential Change Detection tasks where all the sensors are observable, POMSCD is much more challenging because the learner not only needs to detect on-the-fly whether a change occurs based on partially observed multi-sensor data streams, but also needs to cleverly choose a subset of informative sensors to be observed in the next learning round, in order …

Risk Pooling, Supply Chain Hierarchy, And Analysts' Forecasts, Nan Hu, Jian-Yu Ke, Ling Liu, Yue Zhang

Research Collection School Of Computing and Information Systems

We investigate whether a firm's risk pooling affects its analysts' forecasts, specifically in terms of forecast accuracy and their use of public vs. private information, and how risk pooling interacts with a firm's position in the supply chain to affect analysts' forecasts. We use a social network analysis method to operationalize risk pooling and supply chain hierarchy, and find that risk pooling significantly reduces analysts' forecast errors and increases (decreases) their use of public (private) information. We also find that the positive (negative) relationships between risk pooling and analyst forecast accuracy and analysts' use of public (private) information are more …

Robust Estimation Of Similarity Transformation For Visual Object Tracking, Yang Li, Jianke Zhu, Steven C. H. Hoi, Wenjie Song, Zhefeng Wang, Hantang Liu

Research Collection School Of Computing and Information Systems

Most of existing correlation filter-based tracking approaches only estimate simple axis-aligned bounding boxes, and very few of them is capable of recovering the underlying similarity transformation. To tackle this challenging problem, in this paper, we propose a new correlation filter-based tracker with a novel robust estimation of similarity transformation on the large displacements. In order to efficiently search in such a large 4-DoF space in real-time, we formulate the problem into two 2-DoF sub-problems and apply an efficient Block Coordinates Descent solver to optimize the estimation result. Specifically, we employ an efficient phase correlation scheme to deal with both scale …

A Coordination Framework For Multi-Agent Persuasion And Adviser Systems, Budhitama Subagdja, Ah-Hwee Tan, Yilin Kang

Research Collection School Of Computing and Information Systems

Assistive agents have been used to give advices to the users regarding activities in daily lives. Although adviser bots are getting smarter and gaining more popularity these days they are usually developed and deployed independent from each other. When several agents operate together in the same context, their advices may no longer be effective since they may instead overwhelm or confuse the user if not properly arranged. Only little attentions have been paid to coordinating different agents to give different advices to a user within the same environment. However, aligning the advices on-the-fly with the appropriate presentation timing at the …

Send Hardest Problems My Way: Probabilistic Path Prioritization For Hybrid Fuzzing, Lei Zhao, Yue Duan, Jifeng Xuan

Research Collection School Of Computing and Information Systems

Hybrid fuzzing which combines fuzzing and concolic execution has become an advanced technique for software vulnerability detection. Based on the observation that fuzzing and concolic execution are complementary in nature, the state-of-the-art hybrid fuzzing systems deploy ``demand launch'' and ``optimal switch'' strategies. Although these ideas sound intriguing, we point out several fundamental limitations in them, due to oversimplified assumptions. We then propose a novel ``discriminative dispatch'' strategy to better utilize the capability of concolic execution. We design a novel Monte Carlo based probabilistic path prioritization model to quantify each path's difficulty and prioritize them for concolic execution. This model treats …

Adaptive Cost-Sensitive Online Classification, Peilin Zhao, Yifan Zhang, Min Wu, Steven C. H. Hoi, Mingkui Tan, Junzhou Huang

Research Collection School Of Computing and Information Systems

Cost-Sensitive Online Classification has drawn extensive attention in recent years, where the main approach is to directly online optimize two well-known cost-sensitive metrics: (i) weighted sum of sensitivity and specificity; (ii) weighted misclassification cost. However, previous existing methods only considered first-order information of data stream. It is insufficient in practice, since many recent studies have proved that incorporating second-order information enhances the prediction performance of classification models. Thus, we propose a family of cost-sensitive online classification algorithms with adaptive regularization in this paper. We theoretically analyze the proposed algorithms and empirically validate their effectiveness and properties in extensive experiments. Then, …

Discrete Social Recommendation, Chenghao Liu, Xin Wang, Tao Lu, Wenwu Zhu, Jianling Sun, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Social recommendation, which aims at improving the performance of traditional recommender systems by considering social information, has attracted broad range of interests. As one of the most widely used methods, matrix factorization typically uses continuous vectors to represent user/item latent features. However, the large volume of user/item latent features results in expensive storage and computation cost, particularly on terminal user devices where the computation resource to operate model is very limited. Thus when taking extra social information into account, precisely extracting K most relevant items for a given user from massive candidates tends to consume even more time and memory, …

Social Media Mining For Journalism, Arkaitz Zubiaga, Bahareh Heravi, Jisun An, Haewoon Kwak

Research Collection School Of Computing and Information Systems

The exponential growth of social media as a central communication practice, and its agility in capturing and announcing breaking news events more rapidly than traditional media, has changed the journalistic landscape: social media has been adopted as a significant source by professional journalists, and conversely, citizens are able to use social media as a form of direct reportage. This brings along new opportunities for newsrooms and journalists by providing new means for newsgathering through access to a wealth of citizen reportage and updates about current affairs, as well as an additional showcase for news dissemination.

Comparelda: A Topic Model For Document Comparison, Maksim Tkachenko, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

A number of real-world applications require comparison of entities based on their textual representations. In this work, we develop a topic model supervised by pairwise comparisons of documents. Such a model seeks to yield topics that help to differentiate entities along some dimension of interest, which may vary from one application to another. While previous supervised topic models consider document labels in an independent and pointwise manner, our proposed Comparative Latent Dirichlet Allocation (CompareLDA) learns predictive topic distributions that comply with the pairwise comparison observations. To fit the model, we derive a maximum likelihood estimation method via augmented variational approximation …

Explainable Reasoning Over Knowledge Graphs For Recommendation, Xiang Wang, Dingxian Wang, Canran Xu, Xiangnan He, Yixin Cao, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Incorporating knowledge graph into recommender systems has attracted increasing attention in recent years. By exploring the interlinks within a knowledge graph, the connectivity between users and items can be discovered as paths, which provide rich and complementary information to user-item interactions. Such connectivity not only reveals the semantics of entities and relations, but also helps to comprehend a user’s interest. However, existing efforts have not fully explored this connectivity to infer user preferences, especially in terms of modeling the sequential dependencies within and holistic semantics of a path. In this paper, we contribute a new model named Knowledgeaware Path Recurrent …

Multi-Task Learning With Multi-View Attention For Answer Selection And Knowledge Base Question Answering, Yang Deng, Yuexiang Xie, Yaliang Li, Min Yang, Nan Du, Wei Fan, Kai Lei, Ying Shen

Research Collection School Of Computing and Information Systems

Answer selection and knowledge base question answering (KBQA) are two important tasks of question answering (QA) systems. Existing methods solve these two tasks separately, which requires large number of repetitive work and neglects the rich correlation information between tasks. In this paper, we tackle answer selection and KBQA tasks simultaneously via multi-task learning (MTL), motivated by the following motivations. First, both answer selection and KBQA can be regarded as a ranking problem, with one at text-level while the other at knowledge-level. Second, these two tasks can benefit each other: answer selection can incorporate the external knowledge from knowledge base (KB), …

Dish: Democracy In State Houses, Nicholas A. Russo

Master's Theses

In our current political climate, state level legislators have become increasingly impor- tant. Due to cuts in funding and growing focus at the national level, public oversight for these legislators has drastically decreased. This makes it difficult for citizens and activists to understand the relationships and commonalities between legislators. This thesis provides three contributions to address this issue. First, we created a data set containing over 1200 features focused on a legislator’s activity on bills. Second, we created embeddings that represented a legislator’s level of activity and engagement for a given bill using a custom model called Democracy2Vec. Third, we …

Improving Vix Futures Forecasts Using Machine Learning Methods, James Hosker, Slobodan Djurdjevic, Hieu Nguyen, Robert Slater

SMU Data Science Review

The problem of forecasting market volatility is a difficult task for most fund managers. Volatility forecasts are used for risk management, alpha (risk) trading, and the reduction of trading friction. Improving the forecasts of future market volatility assists fund managers in adding or reducing risk in their portfolios as well as in increasing hedges to protect their portfolios in anticipation of a market sell-off event. Our analysis compares three existing financial models that forecast future market volatility using the Chicago Board Options Exchange Volatility Index (VIX) to six machine/deep learning supervised regression methods. This analysis determines which models provide best …

The Complexities Of Open Data, Hector Dominguez

Systems Science Friday Noon Seminar Series

Hector Dominguez is the current Open Data Coordinator at the City of Portland, and there are several lessons learned and strategies developed in the several months of work in this position. Hector will share some challenges on creating trusted and reliable data and information services, as well as the opportunities to work with Urban Data to resolve city challenges and to support achieving the City's goals in the coming years.

In this talk, Hector will share how modeling and defining the right metrics are not the only factors to implementing a citywide program, but rather, how ethics, communications and strategy …

Providers’ Perception Of Alert Fatigue After Implementation Of User-Filtered Warnings, Hina Afaq, Sahaana Mukundan, Sadaf Zia, Alisa K. Escano Dr., Rebecca Lear Dr., Casey Washington Dr.

Pharmacotherapy and Outcomes Science Publications

Alert fatigue is a complex problem that many health institutions face when using an electronic health record (EHR). The addition of user-filtered warnings (UFW) is a physicians’ proposed intervention at Inova Health System (IHS), a large 5-hospital health system in Northern Virginia, that allows prescribers to filter out specific drug-drug interactions and pregnancy and lactation medication alerts for a 30-day period. This study aims to determine the impact of UFW on physicians’ perception of alert fatigue and to calculate the reduction of medication alerts. It was hypothesized that the reduction in alerts will significantly impact physicians’ perception of alert fatigue …

Automatic Identification Of Individual Drugs In Death Certificates, Soon Jye Kho, Amit Sheth, Olivier Bodenreider

Kno.e.sis Publications

Background:

Establishing trends of drug overdoses requires the identification of individual drugs in death certificates, not supported by coding with the International Classification of Diseases. However, identifying drug mentions from the literal portion of death certificates remains challenging due to the variability of drug names.

Objectives:

To automatically identify individual drugs in death certificates.

Methods:

We use RxNorm to collect variants for drug names (generic names, synonyms, brand names) and we algorithmically generate common misspellings. We use this automatically compiled list to identify drug mentions from 703,106 death certificates and compare the performance of our automated approach to that of …

Made Simple With Sivvu, Esther Cha, Douglas A. Vander Griend

Summer Research

To further the advancement of science, newer and better ways to regulate as well as optimize complex systems are continuously sought after. The previous efforts of this project have demonstrated the ability of characterizing selfassembling supramolecular systems in astounding detail. Although these systems were initially designed with a single chemical target, this project has allowed discovery of how homogenous solutions always contain additional assemblages. In this project, different systems are studied with UV-Vis, CD, NMR, and Mass Spec. The necessary methods that are used to conduct this research include analysis of spectrophotometric titrations as well as the utilization of computational …