Databases and Information Systems Commons^™

Challenges In Learning Uml: From The Perspective Of Diagrammatic Representation And Reasoning, Z. Shen, S. Tan, Keng Siau

Research Collection School Of Computing and Information Systems

Unified modeling language (UML) is widely taught in the information systems (IS) curriculum. To understand UML in IS education, this paper reports on an empirical study that taps into students’ learning of UML. The study uses a concept-mapping technique to identify the challenges in learning UML notational elements. It reveals that some technical properties of UML diagrammatic representation, coupled with students’ cognitive attributes, hinder both perceptual and conceptual processes involved in searching, recognizing, and inferring visual information, which creates learning barriers. This paper also discusses how to facilitate perceptual and conceptual processes in instruction to overcome learning challenges. The study …

A Strategic Value Appropriation Path For Cloud Computing, Abhishek Kathuria, Arti Mann, Jiban Khuntia, Robert J. Kauffman

Research Collection School Of Computing and Information Systems

Cloud-based information management is one of the leading competitive differentiation strategies for firms. With the increasing criticality of information management in value creation and process support, establishing an integrated capability with cloud computing is vital for organizational success in the changing landscape of business competition. These issues have received scant attention, however. We draw on the resource-based view, dynamic capability hierarchy concepts, and the perspective of operand and operant resources to suggest a cloud value appropriation model for firms. We argue that, to appropriate business value from cloud computing, the firm needs to effectively deploy cloud computing and leverage cloud …

Implicit Linking Of Food Entities In Social Media, Wen Haw Chong, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Dining is an important part in people’s lives and this explains why food-related microblogs and reviews are popular in social media. Identifying food entities in food-related posts is important to food lover profiling and food (or restaurant) recommendations. In this work, we conduct Implicit Entity Linking (IEL) to link food-related posts to food entities in a knowledge base. In IEL, we link posts even if they do not contain explicit entity mentions. We first show empirically that food venues are entity-focused and associated with a limited number of food entities each. Hence same-venue posts are likely to share common food …

Talent Flow Analytics In Online Professional Network, Richard J. Oentaryo, Ee-Peng Lim, Xavier Jayaraj Siddarth Ashok, Philips Kokoh Prasetyo

Research Collection School Of Computing and Information Systems

Analyzing job hopping behavior is important for understanding job preference and career progression of working individuals. When analyzed at the workforce population level, job hop analysis helps to gain insights of talent flow among different jobs and organizations. Traditionally, surveys are conducted on job seekers and employers to study job hop behavior. Beyond surveys, job hop behavior can also be studied in a highly scalable and timely manner using a data-driven approach in response to fast-changing job landscape. Fortunately, the advent of online professional networks (OPNs) has made it possible to perform a large-scale analysis of talent flow. In this …

Jobcomposer: Career Path Optimization Via Multicriteria Utility Learning, Richard J. Oentaryo, Xavier Jayaraj Siddarth Ashok, Ee-Peng Lim, Philips Kokoh Prasetyo

Research Collection School Of Computing and Information Systems

With online professional network platforms (OPNs, e.g., LinkedIn, Xing, etc.)becoming popular on the web, people are now turning to these platforms tocreate and share their professional profiles, to connect with others who sharesimilar professional aspirations and to explore new career opportunities. Theseplatforms however do not offer a long-term roadmap to guide career progressionand improve workforce employability. The career trajectories of OPN users canserve as a reference but they are not always optimal. A career plan can also bedevised through consultation with career coaches, whose knowledge may howeverbe limited to a few industries. To address the above limitations, we present anovel …

Are You On The Right Track? Learning Career Tracks For Job Movement Analysis, Meng-Fen Chiang, Ee-Peng Lim, Wang-Chien Lee, Yuan Tian, Chih-Chieh Hung

Research Collection School Of Computing and Information Systems

Career track represents a vertical career pathway, where one can gradually move up to take up higher job appointments when relevant skills are acquired. Understanding the propensity of career movements in an evolving job market can enable timely career guidance to job seekers and working professionals. To this end, we harvest career trajectories from online professional network (OPN). Our focus lies on obtaining a macro view on career movements at the track granularity. Specifically, we propose a semi-supervised career track labelling framework to automatically assign career tracks for large set of jobs. To contextually label jobs, we collect example jobs …

Assessing Carbon Pollution Standards: Electric Power Generation Pathways And Their Water Impacts, Kustini Lim-Wavde, Haibo Zhai, Robert John Kauffman, Edward S. Rubin

Research Collection School Of Computing and Information Systems

Highlights•Without carbon regulations, CO2 emissions and water use are highly affected by fuel prices.•Carbon regulations reduce both CO2 emissions and water use.•Without incentives, carbon capture is not competitive with cheap natural gas and renewables.•A stringent constraint on water withdrawal lowers the fleet share of once-through cooling.AbstractThis study evaluates transition pathways in electricity generation and their future water impacts. Scenarios that do or do not comply with the carbon pollution standards – based on the U.S. New Source Performance Standards and Clean Power Plan – are evaluated. Using the Electric Reliability Council of Texas region as an illustration, the scenarios with …

A Hybrid Model For Identity Obfuscation By Face Replacement, Qianru Sun, Ayush Tewari, Weipeng Xu, Mario Fritz, Christian Theobalt, Bernt Schiele

Research Collection School Of Computing and Information Systems

As more and more personal photos are shared and tagged in social media, avoiding privacy risks such as unintended recognition, becomes increasingly challenging. We propose a new hybrid approach to obfuscate identities in photos by head replacement. Our approach combines state of the art parametric face synthesis with latest advances in Generative Adversarial Networks (GAN) for data-driven image synthesis. On the one hand, the parametric part of our method gives us control over the facial parameters and allows for explicit manipulation of the identity. On the other hand, the data-driven aspects allow for adding fine details and overall realism as …

Cognitive Antecedents Of Family Business Bias In Investment Decisions: A Commentary On 'Risky Decisions And The Family Firm Bias: An Experimental Study Based On Prospect Theory, H. Fang, Keng Siau, E. Memili, J. Dou

Research Collection School Of Computing and Information Systems

Lude and Prügl explored “family business bias,” a cognitive tendency where the family nature of a firm can often reduce investors’ perceived risk in investments. As a result, investors would display lower risk-avoidance in the gain domain and reinforced risk-seeking in the loss domain. We expanded the authors’ work by introducing four cognitive factors (anchoring, representativeness, stereotype heuristic, and information availability) that can explain the underlying mechanisms behind the prevalence of “family business bias” and other cognitive misperceptions surrounding family businesses when it comes to investment decisions.

Wasserstein Divergence For Gans, J. Wu, Zhiwu Huang, J. Thoma, D. Acharya, Gool L. Van

Research Collection School Of Computing and Information Systems

In many domains of computer vision, generative adversarial networks (GANs) have achieved great success, among which the family of Wasserstein GANs (WGANs) is considered to be state-of-the-art due to the theoretical contributions and competitive qualitative performance. However, it is very challenging to approximate the k-Lipschitz constraint required by the Wasserstein-1 metric (W-met). In this paper, we propose a novel Wasserstein divergence (W-div), which is a relaxed version of W-met and does not require the k-Lipschitz constraint. As a concrete application, we introduce a Wasserstein divergence objective for GANs (WGAN-div), which can faithfully approximate W-div through optimization. Under various settings, including …

Question-Guided Hybrid Convolution For Visual Question Answering, Peng Gao, Pan Lu, Hongsheng Li, Shuang Li, Yikang Li, Steven C. H. Hoi, Xiaogang Wang

Research Collection School Of Computing and Information Systems

In this paper, we propose a novel Question-Guided Hybrid Convolution (QGHC) network for Visual Question Answering (VQA). Most state-of-the-art VQA methods fuse the high-level textual and visual features from the neural network and abandon the visual spatial information when learning multi-modal features.To address these problems, question-guided kernels generated from the input question are designed to convolute with visual features for capturing the textual and visual relationship in the early stage. The question-guided convolution can tightly couple the textual and visual information but also introduce more parameters when learning kernels. We apply the group convolution, which consists of question-independent kernels and …

Diversity In Online Advertising: A Case Study Of 69 Brands On Social Media, Jisun An, Ingmar Weber

Research Collection School Of Computing and Information Systems

Lack of diversity in advertising is a long-standing problem. Despite growing cultural awareness and missed business opportunities, many minorities remain under- or inappropriately represented in advertising. Previous research has studied how people react to culturally embedded ads, but such work focused mostly on print media or television using lab experiments. In this work, we look at diversity in content posted by 69 U.S. brands on two social media platforms, Instagram and Facebook. Using face detection technology, we infer the gender, race, and age of both the faces in the ads and of the users engaging with ads. Using this dataset, …

A Two-Stage Mechanism For Ordinal Peer Assessment, Zhize Li, Le Zhang, Zhixuan Fang, Jian Li

Research Collection School Of Computing and Information Systems

Peer assessment is a major method for evaluating the performance of employee, accessing the contributions of individuals within a group, making social decisions and many other scenarios. The idea is to ask the individuals of the same group to assess the performance of the others. Scores or rankings are then determined based on these evaluations. However, peer assessment can be biased and manipulated, especially when there is a conflict of interests. In this paper, we consider the problem of eliciting the underlying ordering (i.e. ground truth) of n strategic agents with respect to their performances, e.g., quality of work, contributions, …

The Influence Of Conversational Agent Embodiment And Conversational Relevance On Socially Desirable Responding, Ryan M. Schuetzler, Justin Scott Giboney, G. Mark Grimes, Jay F. Nunamaker Jr.

Information Systems and Quantitative Analysis Faculty Publications

Conversational agents (CAs) are becoming an increasingly common component in a wide range of information systems. A great deal of research to date has focused on enhancing traits that make CAs more humanlike. However, few studies have examined the influence such traits have on information disclosure. This research builds on self-disclosure, social desirability, and social presence theories to explain how CA anthropomorphism affects disclosure of personally sensitive information. Taken together, these theories suggest that as CAs become more humanlike, the social desirability of user responses will increase. In this study, we use a laboratory experiment to examine the influence of …

A Linked Coptic Dictionary Online, Frank Feder, Maxim Kupreyev, Emma Manning, Caroline T. Schroeder, Amir Zeldes

College of the Pacific Faculty Presentations

We describe a new project publishing a freely available online dictionary for Coptic. The dictionary encompasses comprehensive cross-referencing mechanisms, including linking entries to an online scanned edition of Crum’s Coptic Dictionary, internal cross-references and etymological information, translated searchable definitions in English, French and German, and linked corpus data which provides frequencies and corpus look-up for headwords and multiword expressions. Headwords are available for linking in external projects using a REST API. We describe the challenges in encoding our dictionary using TEI XML and implementing linking mechanisms to construct a Web interface querying frequency information, which draw on NLP tools to …

Expected Length Of The Longest Chain In Linear Hashing, Pongthip Srivarangkul, Hemanta K. Maji

The Summer Undergraduate Research Fellowship (SURF) Symposium

Hash table with chaining is a data structure that chains objects with identical hash values together with an entry or a memory address. It works by calculating a hash value from an input then placing the input in the hash table entry. When we place two inputs in the same entry, they chain together in a linear linked list. We are interested in the expected length of the longest chain in linear hashing and methods to reduce the length because the worst-case look-up time is directly proportional to it.

The linear hash function used to calculate hash value is defined …

Predict The Failure Of Hydraulic Pumps By Different Machine Learning Algorithms, Yifei Zhou, Monika Ivantysynova, Nathan Keller

The Summer Undergraduate Research Fellowship (SURF) Symposium

Pump failure is a general concerned problem in the hydraulic field. Once happening, it will cause a huge property loss and even the life loss. The common methods to prevent the occurrence of pump failure is by preventative maintenance and breakdown maintenance, however, both of them have significant drawbacks. This research focuses on the axial piston pump and provides a new solution by the prognostic of pump failure using the classification of machine learning. Different kinds of sensors (temperature, acceleration and etc.) were installed into a good condition pump and three different kinds of damaged pumps to measure 10 of …

Sort Vs. Hash Join On Knights Landing Architecture, Victor L. Pan, Felix Lin

The Summer Undergraduate Research Fellowship (SURF) Symposium

With the increasing amount of information stored, there is a need for efficient database algorithms. One of the most important database operations is “join”. This involves combining columns from two tables and grouping common values in the same row in order to minimize redundant data. The two main algorithms used are hash join and sort merge join. Hash join builds a hash table to allow for faster searching. Sort merge join first sorts the two tables to make it more efficient when comparing values. There has been a lot of debate over which approach is superior. At first, hash join …

Zero Textbook Cost Syllabus For Cis 2200h (Introduction To Information Systems And Technologies), Curtis Izen

Open Educational Resources

This course introduces students to information systems in business. Due to the rapid developments in Information Technology (IT) and the dramatic changes brought by these new technologies in the way companies operate, compete and do business, familiarity with information systems has become indispensable for the leaders of today and tomorrow's organizations.

Proactive And Reactive Resource/Task Allocation For Agent Teams In Uncertain Environments, Pritee Agrawal

Dissertations and Theses Collection (Open Access)

Synergistic interactions between task/resource allocation and multi-agent coordinated planning/assignment exist in many problem domains such as trans- portation and logistics, disaster rescue, security patrolling, sensor networks, power distribution networks, etc. These domains often feature dynamic environments where allocations of tasks/resources may have complex dependencies and agents may leave the team due to unforeseen conditions (e.g., emergency, accident or violation, damage to agent, reconfiguration of environment).