Reviewerly/exHarmony huggingface dataset:
Solution Diversity in Planning

Diverse planning consists of generating multiple different solutions for the same planning problem. I explore solution diversity, based on quantitative (domain-independent) and qualitative (domain-dependent) distance metrics, in deterministic and nondeterministic planning domains.
Adapting Automatic Speech Recognition for Foreign Language Learners in a Serious Game

Eveil3d is a project for development of an immersive, virtual "serious game" for computer assisted foreign language learning, with which users interact verbally by means of an automatic speech recogniser. The speech of the target user group, namely adolescent low-proficiency non-native speakers, differs significantly from native adult speakers on which ASR systems are typically trained and thus on which they perform the best. As only a very small corpus of near-domain speech and text is available, the aforementioned difference becomes a development challenge. We deal with this challenge by adapting existing systems on the small data set. We adapt our language models using text selection to augment the in-domain data with similar data from out-of-domain sources. We adapt our acoustic models with MAP adaptation. Through these steps we achieve significant reductions in error.
Exploring Mixed-Initiative Interaction for Learning with Situated Instruction in Cognitive Agents

Human-agent interaction for learning with instruction canbe viewed on a continuum of instructor/agent control. At one extreme are systems that learn by instructor-driveninteractions, such as learning by demonstration, examples,or imitation. The other extreme of the continuum isoccupied by systems where instructor interaction is limited to responding to the questions posed by the agent or toproviding feedback on agent’s performance. There are advantages to an approach that explores a mixed-initiative instructional dialog. We describe an approach to mixed-initiative interaction based on collaborative discourse theory that allows Soar agents to learn from situated instruction.
Exploiting Shared Resource Dependencies in Spectrum Based Plan Diagnosis

In case of a plan failure, plan-repair is a more promising solution than replanning from scratch. The effectiveness of plan-repair depends on knowledge of which plan action failed and why. Therefore, in this paper, we propose an Extended Spectrum Based Diagnosis approach that efficiently pinpoints failed actions. Unlike Model Based Diagnosis (MBD), it does not require the fault models and behavioral descriptions of actions. Our approach first computes the likelihood of an action being faulty and subsequently proposes optimal probe locations to refine the diagnosis. We also exploit knowledge of plan steps that are instances of the same plan operator to optimize the selection of the most informative diagnostic probes. In this paper, we only focus on diagnostic aspect of plan-repair process.
Integrated Pathﬁnding and Player Analysis for Touch-Driven Games

This paper introduces a software framework, currently in prototype stage, designed to permit automatic integration of pathﬁnding navigation in isomertric camera-driven games. This framework is built with an emphasis towards touchscreen-driven gameplay on tablets and smartphones. This enables pathﬁnding to be adopted not by characters in-game, but also permits a range of traditional and experimental control schemes to utilise this feature. In addition, the framework provides for a range of metrics to be established based on user activity; enabling quality assurance to be conducted based on raw-user input and pre-processed data.
A Project Oriented, Team Based Learning Approach

This paper presents our outreach efforts in the Department of Ocean Engineering at Florida Atlantic University.The main theme of the outreach effort is "project-oriented, team-based" learning philosophy, which goes beyond the typical "cookie-cutter hands-on" ideas in that there is an overall goal for learning to take place.This is drastically different the traditional "tool-based" learning where the students have to learn all the tools first before they can solve a particular problem.By promoting project-oriented, team-based education, students can appreciate better why they are learning what they are learning, how they can work together as a team, and apply their skills to solving interesting and relevant problems.Over the past four pasts, we have hosted a Model Submarine Design Workshop for high-school students in 2004, and a teacher training workshop in 2007.In addition, we have been offering a yearly dual-enrollment summer class for high school students since 2005.The main goals of these outreach effort are to stimulate high school students' interests in pursuing science and engineering as their fields of study and careers, and to enhance the research experiences for the in-service high school teachers in science and technology areas so they can bring the knowledge and experiences back into their classrooms.
Answering Complex Queries in an Online Community Network

An online community network such as Twitter or amazon.com links entities (e.g., users, products) with various relationships (e.g., friendship, co-purchase) and make such information available for access through a web interface. The web interfaces of these networks often support features such as keyword search and "get-neighbors" — so a visitor can quickly find entities (e.g., users/products) of interest. Nonetheless, the interface is usually too restrictive to answer complex queries such as (1) find 100 Twitter users from California with at least 100 followers who talked about ICWSM last year or (2) find 100 books with at least 200 5-star reviews at amazon.com. In this paper, we introduce the novel problem of answering complex queries that involve non-searchable attributes through the web interface of an online community network. We model such a network as a heterogeneous graph with two access channels, Content Search and Local Search. We propose a unified approach that transforms the complex query into a small number of supported ones based on a strategic query-selection process. We conduct comprehensive experiments on Twitter and amazon.com which demonstrate the efficacy of our proposed algorithms.
Learning Names for RFID-Tagged Objects in Activity Videos

We describe a method for determining the names of RFID-tagged objects in activity videos using descriptions which have been parsed to provide anaphoric reference resolution and ontological categorization.
A Real-Time Model to Assess Student Engagement during Interaction with Intelligent Educational Agents

Adaptive learning is an educational method that utilizes computers as an interactive teaching device.Intelligent tutoring systems, or educational agents, use adaptive learning techniques to adapt to each student's needs and learning styles in order to individualize learning.Effective educational agents should accomplish two essential goals during the learning process -1) monitor engagement of the student during the interaction and 2) apply behavioral strategies to maintain the student's attention when engagement decreases.In this paper, we focus on the first objective of monitoring student engagement.Most educational agents do not monitor engagement explicitly, but rather assume engagement and adapt their interaction based on the student's responses to questions and tasks.A few advanced methods have begun to incorporate models of engagement through vision-based algorithms that assess behavioral cues such as eye gaze, head pose, gestures, and facial expressions.Unfortunately, these methods require a heavy computation load, memory/storage constraints, and high power consumption.In addition, these behavioral cues do not correlate well with achievement of high-cognitive tasks, as we will discuss in this paper.As an alternative, our proposed model of engagement uses physical events, such as keyboard and mouse events.This approach requires fewer resources and lower power consumption, which is also ideally suited for mobile educational agents such as handheld tablets and robotic platforms.In this paper, we discuss our engagement model which uses techniques that determine behavioral user state and correlate these findings to mouse and keyboard events.In particular, we observe three event processes: total time required to answer a question; accuracy of responses; and proper function executions.We evaluate the correctness of our model based on an investigation involving a middle-school after-school program in which a 15-question math exam that varies in cognitive difficulty is used for assessment.Eye gaze and head pose techniques are referenced for the baseline metric of engagement.We then conclude the investigation with a survey to gather the subject's perspective of their mental state throughout the exam.We found that our model of engagement is comparable to the eye gaze and head pose techniques.When high-level cognitive thinking is required, our model is more accurate than the eye gaze and head pose techniques due to the use of outside variables for assistance and non-focused gazes during questions requiring deep thought.The large time delay associated with the lack of eye contact between the student and the computer screen causes the aforementioned algorithms to incorrectly declare the subjects as being disengaged.Furthermore, speed and validity of responses can help to determine how well the student understands the material, and this is confirmed through the survey responses and video observations.This additional information will be used in the future to better integrate instructional scaffolding and adaptation with the educational agent.
Translational equivalence in Statistical Machine Translation or meaning as co-occurrence

In this paper, we will describe the current state-of-the-art of Statistical Machine Translation (SMT), and reflect on how SMT handles meaning. Statistical Machine Translation is a corpus-based approach to MT: it de-rives the required knowledge to generate new translations from corpora. General-purpose SMT systems do not use any formal semantic representa-tion. Instead, they directly extract translationally equivalent words or word sequences – expressions with the same meaning – from bilingual parallel corpora. All statistical translation models are based on the idea of word alignment, i.e., the automatic linking of corresponding words in parallel texts. The first generation SMT systems were word-based. From a linguistic point of view, the major problem with word-based systems is that the mean-ing of a word is often ambiguous, and is determined by its context. Current state-of-the-art SMT-systems try to capture the local contextual dependen-cies by using phrases instead of words as units of translation. In order to solve more complex ambiguity problems (where a broader text scope or even domain information is needed), a Word Sense Disambiguation (WSD) module is integrated in the Machine Translation environment.
Integration Of Industry Partners In Computer Science Education

The Department of Computer Science (DoCS) at Tennessee State University (TSU) has actively been involved in integrating industry into computer science education.Our main goal is to strengthen partnership among businesses and our department through participation in projectbased learning and teaching experiences with real-life business problems.In this process, business/industry partners come together with faculty members to design projects for the courses we offer.A typical project for a course is shaped with collaboration of the faculty and the corresponding industry partner for that course to fit it into the course contents and objectives.Industry partners actively participate in developing project, evaluating students' progress, guiding students, communicating with students, and assessing students' performances.This kind of active learning highly improves the student learning outcomes by providing additional motivation, professionalism, feedback from real industry partners
PEMBELAJARAN KETERAMPILAN BAHASA ARAB DALAM PERSPEKTIF GAYA BELAJAR PESERTA DIDIK

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Special issue: VI ECCOMAS thematic conference on computational vision and medical image processing (VipIMAGE)

Computational methodologies of signal processing and analyses have been commonly used in our society. For instances, fully automatic or semi-automatic Computational Vision systems have been increas...
SOCIAL MEDIAS: OPPORTUNITIES FOR LEARNING / TEACHING ENGLISH IN HIGHER EDUCATION

The greatest achievement of technology, the Internet, not only changed the lifestyles of the world population, but also created unheard of before opportunities for learning and teaching foreign languages.The development of digital technology provided the important shift from the informational Web 1.0 to the social Web 2.0, which allows involving users in active communication and collaboration with each other.The number of social media websites keeps constantly increasing, which makes them available to learners all over the world.The estimated number of social network users worldwide is 1.79 bn.Students' familiarity with online social media has been reported in this article.The opportunities for applying the Internet websites in active learning / teaching of languages depend to a great extent on what sites learners are accustomed to using and how often.The findings on the use of social media websites are obtained from the survey completed by two samples of students of Klaipeda University.The research reveals that learners use (constantly or often) Facebook, YouTube, Twitter, Google, and Wikipedia.However collaborative editing, social bookmarking, weblogs and conversational sites are never used or even not familiar.The data imply that it is essential to increase learners' training in application of social sites.Some statistical correlations between the data for both samples have been found by using the Software Package for Social Sciences (SPSS).There is either 99 % or 95 % probability that an observed Pearson's correlation coefficients are not a chance finding.It means that the findings might be applied beyond the studied samples.
ACRL 2015 Conference

ACRL), a division within the American Library Association, hosted its 75th anniversary conference in Portland, Oregon in 2015.The conference gathered together academic librarians from various fields under the theme of "Creating Sustainable Communities."The theme was echoed by the 11 program tags (which functioned as program tracks), including Teaching and Learning, Leadership and Management, and Professional and Staff Development.With such a wide variety of content represented, it wasn't difficult to find sessions relevant to the concerns of business librarians and libraries.
Creating Conversations: An Automated Dialog System

Online news sites often include a comments section where readers are allowed to leave their thoughts. These comments often contain interesting and insightful conversations between readers about the news article. However the richness of these conversations is often lost among other meaningless comments, and moreover all comments are found at the bottom of the web page. In this article, we discuss how our system inserts reader conversations into the news article to create a multimedia presentation called Shout Out. Shout Out features two virtual news anchors: one anchor reads the news and when appropriate the anchor pauses to have a conversation about the news with another anchor. This current iteration of Shout Out combines natural language techniques and reader conversations to create an engaging system.
Rhythmic analysis and quantitative measures: the essence of rhythm as temporal patterning

A comparison of Standard Italian and Southern Italian dialects is carried out using acoustic measures related to structural properties: Vowel-interval and consonantal inter-vowel-interval durations are used to obtain rhythmic measures based on a number of approach.Italian is usually considered to be 'syllabletimed'.The structural features found in the dialects offer support for a divergence from the traditional assumption of syllable-timing.Rhythm measures are calculated according to Ramus at al. 1999, Grabe-Low 2002, Barry et al. 2003, Russo-Barry to appear.In agreement with predictions derived from phonological observation, the results of the measures show a 'rhythm plot' in which the 'Pairwise Variability Indices (PVIs) place the Italian dialect speakers nearer to the stress-timed' languages than traditional typology statements would lead one to expect .
Alternative Forms of Bounded Suboptimal Search

Previous research into bounded suboptimal search has focused on the development of epsilon-admissible algorithms which are guaranteed to return solutions that are no more than a factor larger than optimal. In this paper, we consider the problem of how to construct search algorithms that satisfy alternative types of guarantees such as an additive bound. This bounding paradigm requires that the cost of any solution found is no more than the optimal cost plus gamma, which is a user-defined constant. To this end, we provide theorems that define sufficient conditions for developing algorithms for arbitrary bounding paradigms when using best-first search, iterative deepening, or focal list-based search. We then show by experimentation that these theorems can be used to construct effective additively bounded algorithms.
Motion Planning With Differential Constraints as Guided Search Over Continuous and Discrete Spaces

To compute a motion trajectory that avoids collisions, reaches a goalregion, and satisfies differential constraints imposed by robotdynamics, this paper proposes an approach that conducts a guidedsearch over the continuous space of motions and over a discrete spaceobtained by a workspace decomposition. A tree of feasible motions anda frontier of workspace regions are expanded simultaneously by firstdetermining the next region along which to expand the search and thenusing sampling-based motion planning to add trajectories to the treeto reach the selected region. When motion planning is not able toreach the selected region, its cost is increased sothat the approach has the flexibility to expand the search along newregions. Comparisons to related work show significant computationalspeedups.
Learning Actions and Action Verbs from Human-Agent Interaction

The goal of my research is to design agents that learn from human-agent interaction. Specifically, I am interested in acquisition of procedural, conceptual and linguistic knowledge related to novel actions from human-agent collaborative task execution.
Temporally Expressive Planning Based on Answer Set Programming with Constraints

Recently, a new language AC(C) was proposed to integrate answer set programming (ASP) and constraint logic programming (CLP). In this paper, we show that temporally expressive planning problems in PDDL2.1 can be translated into AC(C) and solved using AC(C) solvers. Compared with existing approaches, the new approach puts less restrictions on the planning problems and is easy to extend with new features like PDDL axioms. It can also leverage the inference engine for AC(C) which has the potential to exploit the best reasoning mechanisms developed in the ASP, SAT and CP communities.
Automatic pathology of prostate cancer in whole mount slides incorporating individual gland classification

ABSTRACTThis paper presents an automatic pathology (AutoPath) approach to detect prostatic adenocarcinoma based on morphological analysis of high resolution whole mount (WM) histopathology images o...
Understanding the Efficiency of Social Tagging Systems Using Information Theory

Given the rise in popularity of social tagging systems, it seems only natural to ask how efficient is the organically evolved tagging vocabulary in describing any underlying document objects? Does this distributed process really provide a way to circumnavigate the traditional categorization problem with ontologies? We analyze a social tagging site, namely del.icio.us, with information theory in order to evaluate the efficiency of this social tagging site for encoding navigation paths to information sources.
Are We Prepared: Issues Relating to Cybersecurity Economics

D.C., whose mission is to serve as an academic and research center dedicated to increasing the knowledge of the
(In)Visible Me? An Empirical Study of Engineering Librarian Online Profiles

Abstract (In)Visible Me? An Empirical Study of Engineering Librarian Online ProfilesThe transition of information from print to digital formats over the last two decades has had ahuge impact on academic libraries and librarians. As the volume of online information hasgrown, the perceived value of the physical library has changed. This is especially true amongengineering and science libraries, many of which have seen steady (and sometimes sharp)declines in user visits, circulation and reference transactions. In recent years a number ofengineering libraries have downsized, merged or closed in response to technological changes andshifts in the research needs and habits of users. Librarians today have fewer opportunities tointeract with faculty colleagues and students. As a result of these changes, librarians arechallenged to find new ways to connect with users. One way librarians can enhance theirvisibility and professional status is by creating online profiles on library and university websites.The purpose of this study is to explore the current development, characteristics and positioningof engineering librarian profiles. Profiles of members of the Engineering Librarians Division ofASEE will be compiled and analyzed by element, currency and location. Examples of profileelements include personal photo, contact information, education, biography, title and rank,subject expertise, research interests, video recordings, grants and awards, publications,presentations, teaching, service and professional affiliations. This study will also examinewhether there are substantial similarities or differences in the profiles of faculty-status and non-faculty status librarians, and librarians at small and large, public and private institutions.Analyzing the content and positioning of librarian profiles is the first step in developing a set ofbest practice guidelines for engineering librarian profiles.
Knowledge Transfer in Information Security Capacity Building for Community-Based Organizations

Community-based organizations (CBOs) in the health and human services sector handle very sensitive client information, such as psychiatric, HIV testing, criminal justice, and financial records. With annual revenue often in the range of $1 to $10 million, these organizations typically lack the financial, labor, and technical resources to identify and manage information security risks within their environment. Therefore, information security risk assessments were conducted at CBOs as part of a university service learning course intended to ultimately improve security within participating CBOs. Knowledge transfer between trainees and trainers is essential in order for security improvements to be realized. Therefore, this paper constructs a theoretical model of knowledge transfer that is used as a lens through which to examine initial study results of the CBO interventions as part of an exploratory study.