Reviewerly/exHarmony huggingface dataset:
Assessing Visualization Abilities In Minority Engineering Students

The numbers of minority students in the academic areas of science and engineering (S&E) have increased significantly in recent years.Despite initial success in recruitment efforts, the numbers of these minority students not completing their studies still remain higher than that of their non-minority peers.Visualization is a significant factor in the creation of mental models and in interacting with the often abstract concepts that are important for success in S&E fields.An ongoing study recently found that a particular sample of minority engineering and technology students at a historically black university scored statistically significantly lower on the Purdue Spatial Visualization Test: Visualization of Rotations (PSVT) than did a sample of non-minority engineering students at a primarily majority serving institution.This paper discusses those PSVT pretest results and the results of the same test given as a posttest following a semester of instruction.The pretest scores of the initial sample of minority subjects are also compared to another group of minority subjects who took the same course in a following semester.Factors potentially affecting the success and preparation level of the subjects are also addressed including previous academic achievement, scores on standardized tests, and entry requirements of the different institutions the subjects attend.
On Unravelling Opinions of Issue Specific-Silent Users in Social Media

Social media has become a popular platform for people to share opinions. Among the social media mining research projects that study user opinions and issues, most focus on analyzing posted and shared content. They could run into the danger of non-representative findings as the opinions of users who do not post content are overlooked, which often happens in today's marketing, recommendation, and social sensing research. For a more complete and representative profiling of user opinions on various topical issues, we need to investigate the opinions of the users even when they stay silent on these issues. We call these users the issue specific-silent users (i-silent users). To study them and their opinions, we conduct an opinion survey on a set of users for two popular social media platforms, Twitter and Facebook. We further analyze their contributed personal social media data. Our main findings are that more than half of our users who are interested in issue i are i-silent users in Twitter. The same has been observed for our Facebook users. i-silent users are likely to have different opinion distribution from the users who post about i. With the ground truth user opinions from the survey, we further develop and apply opinion prediction methods to i-silent users in Twitter and Facebook using their social media data and their opinions on issues other than i.
Bayesian Clustering of Player Styles for Multiplayer Games

With game play data, empirical approaches to clustering are typically based solely on game outcomes, e.g. kills, deaths, and score for each player. In this paper, we investigate a method for clustering players based on how a player’s choices relate to outcomes, or equivalently the latent player styles exhibited by players. Our approach is based on a Bayesian semi-parametric clustering method which has several advantages: the number of clusters do not need to be specified a priori; the technique can work with a very compact representation of each match (e.g. consisting primarily of indicator variables for player choices); a player can belong to multiple clusters and hence can have a hybrid style; and the resulting clusterings often have a straight-forward interpretation. To demonstrate the approach, we apply our method to multiplayer match logs from Battlefield 3 consisting of over 1200 players and 500,000 matches.
Towards holistic goal centered performance management in software development: lessons from a best practice analysis

There are strong motivating factors for more effective performance measurement practices in software development. Astute practices in this domain are lauded to improve efficiency and effectiveness. However previous studies have shown that measurement in software is intricate, complex and fraught with challenges. Consequently it is poorly managed in practice. Our research seeks to better understand performance management in a real world software development setting in order to identify the challenges and generate a roadmap for improvement. This paper presents findings from an inductive analysis of a radical measurement program in a global software organization. Our study investigates the level at which non-compliance with best practice can explain the company’s disappointing results. We found that a narrow focus on projects, rather than on organizational goals, has seriously hindered its success. We also found that the rate of change in the organization as a whole was impinging on the effective implementation of its measurement program. An analysis of the results demonstrates just how challenging software measurement is. The findings provide an evaluation of best practice relative to the literature that is informed by real industry experience.
Optimal Solitaire Game Solutions Using A* Search and Deadlock Analysis

We propose an efficient method for determining optimal solutions to such skill-based solitaire card games as Freecell. We use A* search with an admissible heuristic function based on analyzing a directed graph whose cycles represent deadlock situations in the game state. To the best of our knowledge, ours is the first algorithm that efficiently determines optimal solutions for Freecell games. We believe that the underlying ideas should be applicable not only to games but also to other classical planning problems which manifest deadlocks.
The Big Picture: A Holistic View of E-book Acquisitions

The merging of two departments into the Acquisitions and Collection Development Department afforded Loyola Marymount University an opportunity to rethink existing workflows, with the acquisition of electronic books (e-books) being identified as a critical task to review. Process mapping was used to show the complexity of different tasks being performed in the department and to provide a visualization mechanism for staff to see how their work fit into a sequence of actions as part of a larger workflow. The authors listed the types of acquisition models used at their library for e-books and constructed process maps for the following six major types: 1. Firm order e-books; 2. Firm order e-book collections; 3. Approval order e-books; 4. Demand-driven e-books; 5. Standing order e-books, and; 6. Subscription e-book database. The authors merged the individual process maps into a single visualization to view the entirety of the acquisition process as a whole and to show how the different e-book acquisition models relate and diverge from one another.
KDM security for identity-based encryption: Constructions and separations

For encryption schemes, key dependent message (KDM) security requires that ciphertexts preserve secrecy even when the messages to be encrypted depend on the secret keys. While KDM security has been extensively studied for public-key encryption (PKE), it receives much less attention in the setting of identity-based encryption (IBE). In this work, we focus on the KDM security for IBE. Our results are threefold. We first propose a generic approach to transfer the KDM security results (both positive and negative) from PKE to IBE. At the heart of our approach is a neat structure-mirroring PKE-to-IBE transformation based on indistinguishability obfuscation and puncturable PRFs, which establishes a connection between PKE and IBE in general. However, the obtained results are restricted to selective-identity sense. We then concentrate on results in adaptive-identity sense. On the positive side, we present two constructions that achieve KDM security in the adaptive-identity sense for the first time. One is built from identity-based hash proof system (IB-HPS) with homomorphic property. The other is built from indistinguishability obfuscation and a new notion named puncturable unique signature, which is bounded KDM-secure in the single-key setting. On the negative side, we separate CPA/CCA security from n-circular security (which is a prototypical case of KDM security) for IBE by giving a counterexample based on differing-inputs obfuscation and a new notion named puncturable IBE. We further propose a general framework for generating n-circular security counterexamples in identity-based setting, which might be of independent interest.
Correlation Between Homework Solution Website Use and Course Performance

Abstract The Effect of Homework Solution Website Use on Course PerformanceEarly in a Dynamics course at a Mid-Atlantic college in the Spring 2010 semester, students weresubmitting correct solutions to very challenging textbook homework problems. The solutionswere unlike any that appeared in the solution manual that is published with the textbook and alsounlike solutions posted by instructors at the school in previous years. Several students admittedto using an online homework solution site to complete their homework, even though there was astated policy against copying any type of answer key in order to complete the assigned work.Because many students argued that the online site was helpful in learning the material covered inthe assignment, data was collected for the remainder of the semester to track use of the onlinesite and corresponding performance on course exams.There are many online homework solutions sites; one is www.cramster.com, a site that describesitself as offering “homework help for math, science, engineering, and business classes byproviding resources to accelerate and strengthen the learning process.” The website providesthorough, step-by-step solutions to problems in many commonly used textbooks. Studentsdescribed the site as very useful, describing it as an online study site that helps the studentsbeing a problem with which they are struggling. This study was designed to determine the effectof online homework solution use on performance on course exams. For each student, thesubmitted solution was compared with the corresponding solution provided by the website, andonly clear copying from the website was recorded. If a student turned in no work for a givenassignment, this non-submission was also recorded. Incorrect solutions were not marked as non-submissions. Even during this short, semester-long study, significant use of the website wasidentified. Sixty students were included in the study. Of the 1740 collected assignments, 21%were non-submissions, and 15% of the last ten assignments were identified as having beencopied from the solution website. Approximately 50% of students (29 out of 60) were identifiedas having used the website at least once during the test period. Exam scores throughout thesemester and final exam grades were normalized with respect to the mean and standarddeviation.The study determined that use of the online homework website had a significant, negative effecton exam performance. Non-submission rate, however, had a greater, negative effect. Use of thewebsite significantly increased when the homework problems were more difficult. In addition,students' performance on standardized tests and a prerequisite course were compared withhomework solution website use, and no clear correlation appeared. The study found thatstudents that were well-prepared for the course were not less likely to be using the homeworksolution site.
The Siting And Design Of A Manufacturing Facility Using Hazardous Materials

A meaningful freshman engineering design experience course with an interdisciplinary environmental approach was offered at New Jersey Institute of Technology in Spring term 1997 and was taught by faculty from the Chemical and Civil Engineering Departments. The problem assigned was the Siting and Design of a Manufacturing Facility using Hazardous Materials and the process design was for a plant to manufacture aspirin. The project simulated a contract undertaken by a consulting firm to site and design the plant with the assignment given to entry level engineers. This approach does not require that the freshman students be well versed in the “traditional design concepts, background, and knowledge” required in the capstone design courses. Students were grouped into four teams of four students each to site the facility and to perform mass balance calculations for the aspirin manufacturing plant. A USGS Quadrangle map and soil information (prepared by the Soil Conservation Service, U.S. Department of Agriculture) for Somerset County, New Jersey were provided to each group. Students were asked to prepare a work schedule, which should include the following: aspirin production estimate, plant size determination, preliminary site selection, sites and surrounding area study, research on environmental restrictions, research on political considerations, economic study, cost analysis, and report preparation. Each team had to select at least three sites for their detailed study and conduct a field recon of the project areas before selecting a final site. At the end of the semester, with the completion of their study, each team submitted a written report and orally presented their recommendations regarding the selected site and the aspirin production requirements to the class and faculty.
The School Library Web Site: On the Information Highway or Stalled in the Carpark

&#x0D; &#x0D; &#x0D; Based on research conducted by the author in 1996 and 1999, this paper discusses theoretical issues and provides an overview of the purposes for which school libraries are creating and maintaining home pages or Web sites. The research has implications for those who are planning a Web page or site for their school library/media center; among other things, it provides information about what other school libraries/media centers have done and suggests some pitfalls that might be avoided It also suggests areas for further study, notably the possible development of a model that might be used for the evaluation of school library Web sites.&#x0D; &#x0D; &#x0D;
Gelfond–Zhang aggregates as propositional formulas

Answer Set Programming (ASP) has become a popular and widespread paradigm for practical Knowledge Representation thanks to its expressiveness and the available enhancements of its input language. One of such enhancements is the use of aggregates, for which different semantic proposals have been made. In this paper, we show that any ASP aggregate interpreted under Gelfond and Zhang's (GZ) semantics can be replaced (under strong equivalence) by a propositional formula. Restricted to the original GZ syntax, the resulting formula is reducible to a disjunction of conjunctions of literals but the formulation is still applicable even when the syntax is extended to allow for arbitrary formulas (including nested aggregates) in the condition. Once GZ-aggregates are represented as formulas, we establish a formal comparison (in terms of the logic of Here-and-There) to Ferraris' (F) aggregates, which are defined by a different formula translation involving nested implications. In particular, we prove that if we replace an F-aggregate by a GZ-aggregate in a rule head, we do not lose answer sets (although more can be gained). This extends the previously known result that the opposite happens in rule bodies, i.e., replacing a GZ-aggregate by an F-aggregate in the body may yield more answer sets. Finally, we characterize a class of aggregates for which GZ- and F-semantics coincide.
Playspecs: Regular Expressions for Game Play Traces

We introduce Playspecs, an application of omega-regular expressions to specifying play traces (sequences of game states or events unfolding over time). This connects the automated analysis and model checking of games to the literature on formal software verification via Bu ̈chi automata. We show how to define desirable or undesirable sequences of game events with Playspecs and how associated algorithms can find examples (or prove the impossibility) of such sequences. Playspecs have two main benefits over existing techniques for specifying the behaviors of a game over time. First, they offer a scalable commitment to formal modeling: the same Playspecs can filter existing traces gathered by telemetry, search for satisfying traces using existing game code, or drive formal verification when paired with a logical model of a game. Second, Playspecs' syntax can be customized for the game engine or game in question so designers may write specifications using their game's native vocabulary. We define Playspecs' syntax and semantics (modulo gamespecific customizations) and outline algorithms for each of the applications mentioned above, providing examples from the social simulation game Prom Week and the puzzle game engine PuzzleScript.
Dear Leader’s Happy Story Time: A Party Game Based on Automated Story Generation

Players in Dear Leader’s Happy Story Time are placed in the role of contestants in a reality TV show where they are forced to audition for roles in the upcoming film of the host, a deranged billionaire who has inexplicably been elected president. The stories are produced by a story generator that combines stock plots and characters to produce kitsch story outlines. The players then collaborate to improvise a camp performance of the outline. The game design provides a context for experimenting with automatic story generation within a narrative game, as well as an opportunity for experimenting with knowledge representation schemes for expressing the tropes of popular narrative. The story generator uses a higher-order logic for describing tropes, and an HTN planning algorithm based on Nau et al.’s SHOP.
Building Helpful Virtual Agents Using Plan Recognition and Planning

This paper presents a new model of cooperative behavior based on the interaction of plan recognition and automated planning. Based on observations of the actions of an "initiator" agent, a "supporter" agent uses plan recognition to hypothesize the plans and goals of the initiator. The supporter agent then proposes and plans for a set of subgoals it will achieve to help the initiator. The approach is demonstrated in an open-source, virtual robot platform.
Automated Decomposition of Game Maps

Video game worlds are getting increasingly large and complex. This poses challenges to the game AI for both pathfinding and strategic decisions, not least in real-time strategy games. One way to alleviate the problem is to manually pre-label the game maps with information about regions and critical choke points, which the game AI can then take advantage of. We present a method for automatically decomposing game maps into non-uniform sized regions. The method uses a flooding algorithm at its core and has the benefit, in addition to its effectiveness, to be relatively intuitive both conceptually and in implementing. Empirical evaluation on game maps shows that the automatic decomposition results in intuitive regions of a comparable standard to human-made labeling. Furthermore, we show that our automatic decomposition, when used by a pathfinding algorithm capable of taking advantage of pre-labeled regions, significantly improves search effectiveness.
Authenticated Outlier Mining for Outsourced Databases

The Data-Mining-as-a-Service (DMaS) paradigm is becoming the focus of research, as it allows the data owner (client) who lacks expertise and/or computational resources to outsource their data and mining needs to a third-party service provider (server). Outsourcing, however, raises some issues about result integrity: how could the client verify the mining results returned by the server are both sound and complete? In this paper, we focus on outlier mining, an important mining task. Previous verification techniques use an authenticated data structure (ADS) for correctness authentication, which may incur much space and communication cost. In this paper, we propose a novel solution that returns a probabilistic result integrity guarantee with much cheaper verification cost. The key idea is to insert a set of artificial records (ARs) into the dataset, from which it constructs a set of artificial outliers (AOs) and artificial non-outliers (ANOs). The AOs and ANOs are used by the client to detect any incomplete and/or incorrect mining results with a probabilistic guarantee. The main challenge that we address is how to construct ARs so that they do not change the (non-)outlierness of original records, while guaranteeing that the client can identify ANOs and AOs without executing mining. Furthermore, we build a strategic game and show that a Nash equilibrium exists only when the server returns correct outliers. Our implementation and experiments demonstrate that our verification solution is efficient and lightweight.
Strategies for Stable Merge Sorting

We introduce new stable natural merge sort algorithms, called 2-merge sort and α-merge sort. We prove upper and lower bounds for several merge sort algorithms, including Timsort, Shiver's sort, α-stack sorts, and our new 2-merge and α-merge sorts. The upper and lower bounds have the forms c · n log m and c · n log n for inputs of length n comprising m runs. For Timsort, we prove a lower bound of (1.5 – o(1))n log n. For 2-merge sort, we prove optimal upper and lower bounds of approximately (1.089 ± o(1))n log m. We state similar asymptotically matching upper and lower bounds for α-merge sort, when ϕ < α < 2, where ϕ is the golden ratio.Our bounds are in terms of merge cost; this upper bounds the number of comparisons and accurately models runtime. The merge strategies can be used for any stable merge sort, not just natural merge sorts. The new 2-merge and α-merge sorts have better worst-case merge cost upper bounds and are slightly simpler to implement than the widely-used Timsort; they also perform better in experiments.
Revocable Identity-Based Access Control for Big Data with Verifiable Outsourced Computing

To be able to leverage big data to achieve enhanced strategic insight, process optimization and make informed decision, we need to be an efficient access control mechanism for ensuring end-to-end security of such information asset. Signcryption is one of several promising techniques to simultaneously achieve big data confidentiality and authenticity. However, signcryption suffers from the limitation of not being able to revoke users from a large-scale system efficiently. We put forward, in this paper, the <i>first</i> identity-based (ID-based) signcryption scheme with efficient revocation as well as the feature to outsource unsigncryption to enable secure big data communications between data collectors and data analytical system(s). Our scheme is designed to achieve end-to-end confidentiality, authentication, non-repudiation, and integrity simultaneously, while providing scalable revocation functionality such that the overhead demanded by the private key generator (PKG) in the key-update phase only increases logarithmically based on the cardiality of users. Although in our scheme the majority of the unsigncryption tasks are outsourced to an untrusted cloud server, this approach does not affect the security of the proposed scheme. We then prove the security of our scheme, as well as demonstrating its utility using simulations.