bluuebunny/crossref_metadata_2025 huggingface dataset:
INFLUÊNCIA DO TIPO E DA CONCENTRAÇÃO DE QUEBRADORES DE GÉIS NO PROCESSO DE FRATURAMENTO HIDRÁULICO
Authors: Cavalcante Mayra Almeida , Chaves Sinthya Gadelha , Fagundes Fabio Pereira , Santana Fagundes Keila Regina
Published: July 2017

Umas das técnicas mais utilizadas até hoje para auxiliar o aumento da produção de óleo e gás de reservatórios subterrâneos é o fraturamento hidráulico. Nesta técnica, um fluido viscoso é bombeado para o fundo do poço a uma pressão suficientemente elevada, visando à criação de uma fratura de alta condutividade na formação de interesse. O fluido de fraturamento (gel de fraturamento) transporta sólidos responsáveis pela sustentação da fratura (areia, bauxita ou cerâmica) os quais asseguram a existência de um canal efetivo e permanentemente aberto ao fluxo de hidrocarbonetos após o fim do bombeio. Normalmente, as soluções poliméricas são extensivamente utilizadas na preparação desses géis. Uma característica importante destes é ser facilmente quebrado no fim da operação, para que os seus resíduos não venham a tamponar os poros recém-criados. De acordo com a literatura, um gel completamente quebrado (Linear ou reticulado) é aquele cuja viscosidade é aproximadamente menor que 10 cP. Com isso, o objetivo deste trabalho consiste em avaliar a eficiência de diferentes tipos e concentrações (5%, 15%, 30%) dos “quebradores de gel” (Ácido Clorídrico, Persulfato de amônio e cloreto de cálcio) em função das propriedades reológicas do fluido de fraturamento. De acordo com os resultados obtidos podemos afirmar que o HCl 15% utilizado como quebrador, apesar de promover a quebra completa do gel acaba gerando alguns transtornos associados ao reservatório, podendo promover obstruções e acarretando um aumento no dano a formação. O cloreto de cálcio funcionou mais como um agente de precipitação do que propriamente como um quebrador. Assim, o persulfato de amônio, foi entre os quebradores estudados, o mais eficiente no processo de faturamento hidráulico tendo em vista os menores valores de viscosidade.
ESTUDO DE PREDIÇÃO DE PROJETOS DE RECUPERAÇÃO DE PETRÓLEO POR INJEÇÃO CONTINUA DE ÁGUA E GÁS: CAMPO DE EAST UNITY, BACIA DE MUGLAD
Authors: Pontes Amorim Nathália , Da Silva Nayra Vicente Souza , Almeida de Assis Debora Cristina
Published: July 2017

O estudo e utilização da simulação numérica na Engenharia de Reservatórios advém da necessidade de se obter uma previsão do comportamento de um campo petrolífero ao longo de sua vida útil. Essa previsão é imprescindível para a tomada de decisão e determinação da melhor estratégia de produção, a qual extrairá a maior quantidade de óleo e alcançará um melhor desempenho do campo. Nesse contexto, o presente trabalho busca utilizar-se da simulação numérica de fluxo como ferramenta para prever e analisar a performance de diversos cenários de produção para um modelo de reservatório convencional de petróleo submetido a técnica de recuperação suplementar por injeção contínua de água e injeção contínua de gás. A injeção de água é uma técnica com domínio tecnológico conhecido e é amplamente utilizada na indústria de petróleo. A técnica de injeção de gás imiscível, assim como a injeção de água, possui o comportamento essencialmente mecânico de deslocar o óleo, não ocorrendo interação de ordem química entre o fluido injetado e o óleo.  A simulação numérica de fluxo desse estudo foi realizada com o software em diferenças finitas, IMEX - Computer Modelling Group (CMG) e a análise dos resultados de cada cenário de injeção de água e de gás foi realizada a partir do estudo de variáveis, como o fator de recuperação do campo, produção acumulada de óleo e saturação de óleo. Para a definição do modelo físico, foram utilizadas as propriedades dos reservatórios observados no campo de East Unity, na Bacia de Muglad na África.
ESCOAMENTO TRANSIENTE DE ÓLEO PARAFÍNICO EM DUTO DE SEÇÃO CIRCULAR: MODELAGEM E SIMULAÇÃO
Authors: Porto Túlio Rafael Nascimento , Barbosa de Lima Antonio Gilson
Published: July 2017

A deposição de cristais estáveis de parafina nas paredes das linhas de produção, é um problema atual na indústria do petróleo. Isto impulsiona pesquisas em dutos e equipamentos, que buscam ampliar o entendimento sobre esse fenômeno e desenvolver atividades de manutenção preventiva, com maior eficiência. Este trabalho apresenta um estudo teórico do transporte de óleo parafínico em um duto horizontal de seção circular. Para descrição do fenômeno, em um sistema bidimensional, utilizou-se um modelo matemático que considera a difusão molecular como mecanismo dominante na deposição da parafina. O escoamento do óleo em regime laminar, completamente desenvolvido, é analisado a partir da consideração de que, para temperaturas superiores a temperatura de início de aparecimento dos cristais (TIAC), o petróleo (solvente) e a parafina (soluto) formam uma mistura binária e homogênea. As equações que descrevem o problema são formuladas e resolvidas, numericamente. Resultados de espessura da camada de parafina, distribuição de temperatura e pressão do óleo, ao longo do duto, no decorrer do tempo, são apresentados e analisados para diferentes condições de operação, descritas pelos valores iniciais dos números de Reynolds (Rec), Peclet (Pec) e coeficiente de solubilidade adimensional (S*). Verificou-se que a variação do Rec, em regime laminar, é irrelevante para o comportamento da camada de parafina depositada. Uma redução no Pec, promove a concentração da deposição em uma pequena região do duto, o que se evidencia em quedas bruscas na pressão do óleo, no decorrer do tempo. O parâmetro S* mostrou estar diretamente ligado a um maior alcance da espessura do depósito, em relação ao raio do tubo, sendo o mesmo, função do gradiente de temperatura entre o óleo e o ambiente externo e de propriedades físicas do depósito formado.
ARQUITETURA DE UM SISTEMA DE SOFTWARE DE SUPORTE AO PROCESSO DE ENSINO-APRENDIZAGEM
Authors: Cunha Dannilo Martins , Filgueira Aquiles Medeiros , Viana Gleiferson de Lima
Published: July 2017

Este trabalho tem o objetivo de apresentar uma arquitetura de um sistema de software que tenha a capacidade de conceder um suporte mínimo no processo de ensino-aprendizagem utilizado por cada professor do Instituto Federal de Educação, Ciência e Tecnologia. Mais especificamente, esse suporte visa realizar um mapeamento simplista do entendimento dos alunos em relação aos assuntos abordados em sala de aula de cada professor. Além de apresentar a arquitetura mencionada, este trabalho tem também o propósito de realizar a validação de tal arquitetura, mostrando e explanando sobre os resultados obtidos.
ANÁLISE DE PARTÍCULAS MISTAS EM REJEITOS DE CONCENTRAÇÃO MAGNÉTICA
Authors: Reis Jonathan Leandro Martins , Pereira Carlos Alberto , Sampaio Ney Pinheiro
Published: July 2017

Partículas mistas são partículas de diferentes minerais que estão intimamente associadas. Objetivou-se por meio deste estudo: (i) utilizar o MEV EDS na detecção de partículas mistas em rejeitos de concentração magnética úmida de alta intensidade em escala laboratorial; (ii) analisar a natureza dessas associações minerais (mineral-minério – mineral de ganga; mineral-minério – mineral-minério) e (iii) avaliar a necessidade da promoção da liberação mineral nessas partículas no sentido de aumentar a recuperação metálica. Os parâmetros experimentais foram: aumento de 250x, tensão de aceleração 20 kV e uso dos elétrons retroespalhados na obtenção das imagens. Os resultados mostraram que existem partículas mistas de mineral-minério – mineral de ganga e mineral-minério – mineral-minério, e também que a liberação dessas partículas não é viável, devido ao tamanho em que se daria maior liberação. Conclui-se que esses dados podem auxiliar na definição de alternativa para aumentar a recuperação metálica nos materiais que geraram esses rejeitos.
A QUEM INTERESSA A EXTINÇÃO DA JUSTIÇA DO TRABALHO?
Authors: Gaia Fausto Siqueira , Siqueira Natércia Sampaio
Published: July 2017

RESUMO: o presente trabalho científico pretende analisar a estrutura da Justiça do Trabalho e a necessidade de sua manutenção entre os ramos do Poder Judiciário, dentro do atual cenário macroeconômico brasileiro de recessão da economia, do aumento do número de desempregados na população economicamente ativa, de precarização das formas de trabalho e de manifestações de setores do poder econômico para a precarização dos direitos trabalhistas. A partir da perspectiva de inclusão e de tutela dos direitos fundamentais no paradigma do Estado democrático de Direito, que elevou à categoria de garantia fundamental o direito ao amplo acesso à Justiça, será procurada resposta, a partir da utilização do método de pesquisa dialético material, ao seguinte problema de pesquisa: a quem interessa a extinção da Justiça do Trabalho no Brasil?
Can Computers Create Humor?
Authors: Ritchie Graeme
Published: July 2017

Despite the fact that AI has always been adventurous in trying to elucidate complex aspects of human behavior, only recently has there been research into computational modeling of humor. One obstacle to progress is the lack of a precise and detailed theory of how humor operates. Nevertheless, since the early 1990s, there have been a number of small programs that create simple verbal humor, and more recently there have been studies of the automatic classification of the humorous status of texts. In addition, there are a number of advocates of the practical uses of computational humor: in user interfaces, in education, and in advertising. Computer‐generated humor is still quite basic, but it could be viewed as a form of exploratory creativity. For computational humor to improve, some hard problems in AI will have to be addressed.
The Second International Conference on Artificial General Intelligence (AGI‐09)
Authors: de Garis Hugo , Goertzel Ben
Published: July 2017

This article reports on AGI‐09, the Second International Conference on Artificial General Intelligence, which was held 6‐9 March 2009 in Arlington, Virginia, USA. The purpose of the conference was to exchange ideas about the creation of artificial systems with general intelligence at, and ultimately beyond, the human level.
Mixed‐Initiative Interface Personalization as a Case Study in Usable AI
Authors: Bunt Andrea , Conati Cristina , McGrenere Joanna
Published: July 2017

Interface personalization aims to streamline the process of working in a feature‐rich application by providing the user with an adapted interface tailored specifically to his or her needs. The mixed‐initiative customization assistance (MICA) system explores a middle ground between two opposing approaches to personalization: (1) an adaptable approach, where personalization is fully user controlled, and (2) and adaptive approach, where personalization is fully system controlled. We overview MICA's strategy for providing user‐adaptive recommendations to help users decide how to personalize their interfaces. In doing so, we focus primarily on how MICA handles threats to usability that are often found in adaptive interfaces including obtrusiveness and lack of understandability and control. We also describe how we evaluated MICA and highlight results from these evaluations.
Understanding and Dealing With Usability Side Effects of Intelligent Processing
Authors: Jameson Anthony
Published: July 2017

The inclusion of AI in an interactive system brings many potential benefits, but there are also potential side effects for the usability of the systems that ought to be taken into account from the very start. This article offers a systematic method for analyzing such usability side effects, the goal being to provide a solid basis for decisions about how to avoid or mitigate them. The analysis schema is applied in turn to nine classes of side effect. Many ideas that have been discussed in earlier literature are synthesized within this framework, which also brings into focus some concepts and issues that have received little attention so far.
Semantics for Digital Engineering Archives Supporting Engineering Design Education
Authors: Regli William , Kopena Joseph B. , Grauer Michael , Simpson Timothy , Stone Robert , Lewis Kemper , Bohm Matt , Wilkie David , Piecyk Martin , Osecki Jordan
Published: July 2017

This article introduces the challenge of digital preservation in the area of engineering design and manufacturing and presents a methodology to apply knowledge representation and semantic techniques to develop digital engineering archives. This work is part of an ongoing, multiuniversity effort to create cyber infrastructure‐based engineering repositories for undergraduates (CIBER‐U) to support engineering design education. The technical approach is to use knowledge representation techniques to create formal models of engineering data elements, work flows, and processes. With these techniques formal engineering knowledge and processes can be captured and preserved with some guarantee of long‐term interpretability. The article presents examples of how the techniques can be used to encode specific engineering information packages and work flows. These techniques are being integrated into a semantic wiki that supports the CIBER‐U engineering education activities across nine universities and involving more than 3500 students since 2006.
PIM: A Novel Architecture for Coordinating Behavior of Distributed Systems
Authors: Ford Kenneth M. , Allen James , Suri Niranjan , Hayes Partrick J. , Morris Robert A.
Published: July 2017

Current approaches to the problem of coordinating the activity of physically distributed systems or devices all have well‐recognized strengths and weaknesses. We propose adding to the mix a novel architecture, the process‐integrated mechanism (PIM), that enjoys the advantages of having a single controlling authority while avoiding the structural difficulties that have traditionally led to the rejection of centralized approaches in many complex settings. In many situations, PIMs improve on previous models with regard to coordination, security, ease of software development, robustness, and communication overhead. In the PIM architecture, the components are conceived as parts of a single mechanism, even when they are physically separated and operate asynchronously. The PIM model offers promise as an effective infrastructure for handling tasks that require a high degree of time‐sensitive coordination between the components, as well as a clean mechanism for coordinating the high‐level goals of loosely coupled systems. The PIM model enables coordination without the fragility and high communication overhead of centralized control, but also without the uncertainty associated with the system‐level behavior of a multiagent system (MAS). The PIM model provides an ease of programming with advantages over both multiagent systems and centralized architectures. It has the robustness of a multiagent system without the significant complexity and overhead required for interagent communication and negotiation. In contrast to centralized approaches, it does not require managing the large amounts of data that the coordinating process needs to compute a global view. In a PIM, the process moves to the data and may perform computations on the components where the data is locally available, transporting only the information needed for coordination within the PIM. While there are many remaining research issues to be addressed, we believe that PIMs offer an important and novel technique for the control of distributed systems.
Report on the AAAI 2010 Robot Exhibition
Authors: Anderson Monica D. , Chernova Sonia , Dodds Zachary , Thomaz Andrea L. , Touretzky David S.
Published: July 2017

The 19th robotics program at the annual AAAI conference was held in Atlanta, Georgia, in July 2010. In this article we give a summary of three components of the exhibition: the Small‐Scale Manipulation Challenge: Robotic Chess; the Learning by Demonstration Challenge; and the Education Track. In each section we detail the challenge task. We also describe the participating teams, highlight the research questions they tackled, and briefly describe the systems they demonstrated.
The Big Promise of Recommender Systems
Authors: Martin Francisco J. , Donaldson Justin , Ashenfelter Adam , Torrens Marc , Hangartner Rick
Published: July 2017

Recommender systems have been part of the Internet for almost two decades. Dozens of vendors have built recommendation technologies and taken them to market in two waves, roughly aligning with the web 1.0 and 2.0 revolutions. Today recommender systems are found in a multitude of online services. They have been developed using a variety of techniques and user interfaces. They have been nurtured with millions of users' explicit and implicit preferences (most often with their permission). Frequently they provide relevant recommendations that increase the revenue or user engagement of the online services that operate them. However, when we evaluate the current generation of recommender systems from the point of view of the “recommendee,” we find that most recommender systems serve the goals of the business instead of their users' interests. Thus we believe that the big promise of recommender systems has yet to be fulfilled. We foresee a third wave of recommender systems that act directly on behalf of their users across a range of domains instead of acting as a sales assistant. We also predict that such new recommender systems will better deal with information overload, take advantage of contextual clues from mobile devices, and utilize the vast information and computation stores available through cloud‐computing services to maximize users' long‐term goals.
A Taxonomy for Generating Explanations in Recommender Systems
Authors: Friedrich Gerhard , Zanker Markus
Published: July 2017

In recommender systems, explanations serve as an additional type of information that can help users to better understand the system's output and promote objectives such as trust, confidence in decision making, or utility. This article proposes a taxonomy to categorize and review the research in the area of explanations. It provides a unified view on the different recommendation paradigms, allowing similarities and differences to be clearly identified. Finally, the authors present their view on open research issues and opportunities for future work on this topic.
Introduction to the Special Issue on Dialogue with Robots
Authors: Bohus Dan , Horvitz Eric , Kanda Takayuki , Mutlu Bilge , Raux Antoine
Published: July 2017

This special issue of AI Magazine on dialogue with robots brings together a collection of articles on situated dialogue. The contributing authors have been working in interrelated fields of human‐robot interaction, dialogue systems, virtual agents, and other related areas and address core concepts in spoken dialogue with embodied robots or agents. Several of the contributors participated in the AAAI Fall Symposium on Dialog with Robots, held in November 2010, and several articles in this issue are extensions of work presented there. Others include invited contributions. The articles in this collection address diverse aspects of dialogue with robots, but are unified in addressing opportunities with spoken language interaction, physical embodiment, and enriched representations of context.
How People Talk with Robots: Designing Dialogue to Reduce User Uncertainty
Authors: Fischer Kerstin
Published: July 2017

If human‐robot interaction is mainly shaped by users' strategies to deal with their unfamiliar artificial com munication partner, as it is suggested here, robot dialogue design should orient toward reducing users' uncertainty about the affordances of the robot and the joint task. Two experiments are presented that investigate the impact of verbal robot utterances on users' behavior; results show that users react sensitively to subtle linguistic cues that may guide them into appropriate understandings of the robot. Furthermore, the role of user expectations and robot appearance are discussed in the light of the model presented.
Approaching the Symbol Grounding Problem with Probabilistic Graphical Models
Authors: Tellex Stefanie , Kollar Thomas , Dickerson Steven , Walter Matthew R. , Banerjee Ashis Gopal , Teller Seth , Roy Nicholas
Published: July 2017

In order for robots to engage in dialogue with human teammates, they must have the ability to identify correspondences between elements of language and aspects of the external world. A solution to this symbol‐grounding problem (Harnad, 1990) would enable a robot to interpret commands such as “Drive over to receiving and pick up the tire pallet.” This article describes several of our results that use probabilistic inference to address the symbol‐grounding problem. Our approach is to develop models that factor according to the linguistic structure of a command. We first describe an early result, a generative model that factors according to the sequential structure of language, and then discuss our new framework, generalized grounding graphs (G3). The G3 framework dynamically instantiates a probabilistic graphical model for a natural language input, enabling a mapping between words in language and concrete objects, places, paths, and events in the external world. We report on corpus‐based experiments in which the robot is able to learn and use word meanings in three real‐world tasks: indoor navigation, spatial language video retrieval, and mobile manipulation.
Challenges and Opportunities in Applied Machine Learning
Authors: Brodley Carla E. , Rebbapragada Umaa , Small Kevin , Wallace Byron C.
Published: July 2017

Machine‐learning research is often conducted in vitro, divorced from motivating practical applications. A researcher might develop a new method for the general task of classification, then assess its utility by comparing its performance (for example, accuracy or AUC) to that of existing classification models on publicly available data sets. In terms of advancing machine learning as an academic discipline, this approach has thus far proven quite fruitful. However, it is our view that the most interesting open problems in machine learning are those that arise during its application to real‐world problems. We illustrate this point by reviewing two of our interdisciplinary collaborations, both of which have posed unique machine‐learning problems, providing fertile ground for novel research.
Reports of the AAAI 2011 Fall Symposia
Authors: Blisard Sam , Carmichael Ted , Ding Li , Finin Tim , Frost Wende , Graesser Arthur , Hadzikadic Mirsad , Kagal Lalana , Kruijff Geert‐Jan M. , Langley Pat , Lester James , McGuinness Deborah L. , Mostow Jack , Papadakis Panagiotis , Pirri Fiora , Prasad Rashmi , Stoyanchev Svetlana , Varakantham Pradeep
Published: July 2017

The Association for the Advancement of Artificial Intelligence was pleased to present the 2011 Fall Symposium Series, held Friday through Sunday, November 4–6, at the Westin Arlington Gateway in Arlington, Virginia. The titles of the seven symposia are as follows: (1) Advances in Cognitive Systems; (2) Building Representations of Common Ground with Intelligent Agents; (3) Complex Adaptive Systems: Energy, Information, and Intelligence; (4) Multiagent Coordination under Uncertainty; (5) Open Government Knowledge: AI Opportunities and Challenges; (6) Question Generation; and (7) Robot‐Human Teamwork in Dynamic Adverse Environments. The highlights of each symposium are presented in this report.
The Best of AI in Japan — Prologue
Authors: Nishida Toyoaki
Published: July 2017

This article is the first report in the best of AI in Japan series. This series will focus not only on prominent accomplishments made in AI research and development but also on AI‐related events in society. As the first in the forthcoming series, this opening article features a historical background and outlines the contemporary AI research activities in Japan. It then highlights some recent prominent results from industry. Finally, a future perspective is given.
Design and Deployment of a Personalized News Service
Authors: Stefik Mark , Good Lance
Published: July 2017

From 2008–2010 we built an experimental personalized news system where readers subscribed to organized channels of topical information that were curated by experts. AI technology was employed to present the right information efficiently to each reader and to reduce radically the workload of curators. The system went through three implementation cycles and processed more than 20 million news stories from about 12,000 Really Simple Syndication (RSS) feeds on more than 8000 topics organized by 160 curators for more than 600 registered readers. This article describes the approach, engineering, and AI technology of the system.
The Glass Infrastructure — Using Common Sense to Create a Dynamic, Place‐Based Social‐Information System
Authors: Havasi Catherine , Borovoy Richard , Kizelshteyn Boris , Ypodimatopoulos Polychronis , Ferguson Jon , Holtzman Henry , Lippman Andrew , Schultz Dan , Blackshaw Matthew , Elliott Greg
Published: July 2017

Most organizations have a wealth of knowledge about themselves available online, but little for a visitor to interact with on‐site. At the MIT Media Lab, we have designed and deployed a novel intelligent signage system, the Glass Infrastructure (GI), that enables small groups of users to interact physically through a touch‐screen display with this data and to discover the latent connections between people, projects, and ideas. The displays are built on an adaptive, unsupervised model of the organization and its relationships developed using dimensionality reduction and commonsense knowledge that automatically classifies and organizes the information.

The GI is currently in daily use at the lab. We discuss the AI model's development, the integration of AI into a human‐computer interaction (HCI) interface, and the use of the GI during the lab's peak visitor periods. We show that the GI is used repeatedly by lab visitors and provides a window into the workings of the organization.
Distributed Problem Solving
Authors: Yeoh William , Yokoo Makoto
Published: July 2017

Distributed problem solving is a subfield within multiagent systems, where agents are assumed to be part of a team and collaborate with each other to reach a common goal. In this article, we illustrate the motivations for distributed problem solving and provide an overview of two distributed problem‐solving models, namely distributed constraint‐satisfaction problems (DCSPs) and distributed constraint‐optimization problems (DCOPs), and some of their algorithms.
PROTECT — A Deployed Game‐Theoretic System for Strategic Security Allocation for the United States Coast Guard
Authors: An Bo , Shieh Eric , Yang Rong , Tambe Milind , Baldwin Craig , DiRenzo Joseph , Maule Ben , Meyer Garrett
Published: July 2017

While three deployed applications of game theory for security have recently been reported, we as a community of agents and AI researchers remain in the early stages of these deployments; there is a continuing need to understand the core principles for innovative security applications of game theory. Toward that end, this article presents PROTECT, a game‐theoretic system deployed by the United States Coast Guard (USCG) in the Port of Boston for scheduling its patrols. USCG has termed the deployment of PROTECT in Boston a success; PROTECT is currently being tested in the Port of New York, with the potential for nationwide deployment. PROTECT is premised on an attacker‐defender Stackelberg game model and offers five key innovations. First, this system is a departure from the assumption of perfect adversary rationality noted in previous work, relying instead on a quantal response (QR) model of the adversary's behavior — to the best of our knowledge, this is the first real‐world deployment of the QR model. Second, to improve PROTECT's efficiency, we generate a compact representation of the defender's strategy space, exploiting equivalence and dominance. Third, we show how to practically model a real maritime patrolling problem as a Stackelberg game. Fourth, our experimental results illustrate that PROTECT's QR model more robustly handles real‐world uncertainties than a perfect rationality model. Finally, in evaluating PROTECT, this article for the first time provides real‐world data: comparison of human‐generated versus PROTECT security schedules, and results from an Adversarial Perspective Team's (human mock attackers) analysis.
Machine Learning for Personalized Medicine: Predicting Primary Myocardial Infarction from Electronic Health Records
Authors: Weiss Jeremy C. , Natarajan Sriraam , Peissig Peggy L. , McCarty Catherine A. , Page David
Published: July 2017

Electronic health records (EHRs) are an emerging relational domain with large potential to improve clinical outcomes. We apply two statistical relational learning (SRL) algorithms to the task of predicting primary myocardial infarction. We show that one SRL algorithm, relational functional gradient boosting, outperforms propositional learners particularly in the medically relevant high‐recall region. We observe that both SRL algorithms predict outcomes better than their propositional analogs and suggest how our methods can augment current epidemiological practices.
David L. Waltz, in Memoriam
Authors: Gabriel Richard P. , Finin Tim , Sun Ron
Published: July 2017

David L. Waltz (1943–2012), was director, Center for Computational Learning Systems (CCLS), Columbia University, and a pioneer in the field of artificial intelligence. Waltz served as Association for the Advancement of Artificial Intelligence (AAAI) president from 1997 to 1999, was a Fellow of AAAI and the Association for Computing Machinery (ACM), a senior member of the Institute for Electrical and Electronics Engineers (IEEE), and former chair of the ACM Special Interest Group on Artificial Intelligence (SIGART). Prior to joining CCLS, he was president of the NEC Research Institute in Princeton, and from 1984–1993 was director of Advanced Information Systems at Thinking Machines Corporation and a professor of computer science at Brandeis University. A celebration of his life was held in the spring of 2012, and a symposium in his honor was held September 23, 2012, at Brandeis University in Waltham, Massachusetts.
What Question Would Turing Pose Today?
Authors: Grosz Barbara J.
Published: July 2017

In 1950, when Turing proposed to replace the question “Can machines think?” with the question “Are there imaginable digital computers which would do well in the imitation game?” computer science was not yet a field of study, Shannon's theory of information had just begun to change the way people thought about communication, and psychology was only starting to look beyond behaviorism. It is stunning that so many predictions in Turing's 1950 Mind paper were right. In the decades since that paper appeared, with its inspiring challenges, research in computer science, neuroscience, and the behavioral sciences has radically changed thinking about mental processes and communication, and the ways in which people use computers has evolved even more dramatically. Turing, were he writing now, might still replace “Can machines think?” with an operational challenge, but it is likely he would propose a very different test. This paper considers what that might be in light of Turing's paper and advances in the decades since it was written.
A Real‐Time Decision Support System for High Cost Oil Well Drilling Operations
Authors: Gundersen Odd Erik , Sørmo Frode , Aamodt Agnar , Skalle Pål
Published: July 2017

In this paper we present DrillEdge — a commercial and award‐winning software system that monitors oil well drilling operations in order to reduce nonproductive time (NPT). DrillEdge utilizes case‐based reasoning with temporal representations on streaming real‐ime data, pattern matching, and agent systems to predict problems and give advice on how to mitigate the problems. We document the methods utilized, the architecture, the GUI. and the development cost in addition to two case studies.
Reports on the Workshops Held at the Sixth International AAAI Conference on Weblogs and Social Media
Authors: Archambault Daniel , Bouwmeester Ruben , Cabulea Cosmin , Daly Elizabeth M. , Di Lorenzo Giusy , de Rijke Maarten , Harrigan Martin , Kandogan Eser , Muller Michael , Naaman Mor , Quercia Daniele , Spina Damiano , Strohmaier Markus , Zubiaga Arkaitz
Published: July 2017

The workshops day at the Sixth International Conference on Weblogs and Social Media included three full‐day workshops (Real‐Time Analysis and Mining of Social Streams, Social Media Visualization, and When the City Meets the Citizen) and one half‐day workshop (The Potential of Social Media Tools and Data for Journalists in the News Media Industry). Workshops were held on June 4, 2012, the day prior to the first day of the technical conference, in Dublin, Ireland.
Interactive Narrative: An Intelligent Systems Approach
Authors: Riedl Mark O. , Bulitko Vadim
Published: July 2017

Interactive narrative is a form of digital interactive experience in which users create or influence a dramatic storyline through their actions. The goal of an interactive narrative system is to immerse users in a virtual world such that they believe that they are an integral part of an unfolding story and that their actions can significantly alter the direction or outcome of the story. In this article we review the ways in which artificial intelligence can be brought to bear on the creation of interactive narrative systems. We lay out the landscape of about 20 years of interactive narrative research and explore the successes as well as open research questions pertaining to the novel use of computational narrative intelligence in the pursuit of entertainment, education, and training.
Reports on the 2012 AAAI Fall Symposium Series
Authors: Dogan Rezarta Islamaj , Gil Yolanda , Hirsh Haym , Krishnan Narayanan C. , Lewis Michael , Mericli Cetin , Rashidi Parisa , Raskin Victor , Swarup Samarth , Sun Wei , Taylor Julia M. , Yeganova Lana
Published: July 2017

The Association for the Advancement of Artificial Intelligence was pleased to present the 2012 Fall Symposium Series, held Friday through Sunday, November 2–4, at the Westin Arlington Gateway in Arlington, Virginia. The titles of the eight symposia were as follows: AI for Gerontechnology (FS‐12‐01), Artificial Intelligence of Humor (FS‐12‐02), Discovery Informatics: The Role of AI Research in Innovating Scientific Processes (FS‐12‐03), Human Control of Bio‐Inspired Swarms (FS‐12‐04), Information Retrieval and Knowledge Discovery in Biomedical Text (FS‐12‐05), Machine Aggregation of Human Judgment (FS‐12‐06), Robots Learning Interactively from Human Teachers (FS‐12‐07), and Social Networks and Social Contagion (FS‐12‐08). The highlights of each symposium are presented in this report.
Seven Challenges in Parallel SAT Solving
Authors: Hamadi Youssef , Wintersteiger Christoph M.
Published: July 2017

This article provides a broad overview of the state of the parallel SAT solving field. A set of challenges to researchers is presented that, we believe, must be met to ensure the practical applicability of parallel SAT solvers in the future. All these challenges are described informally but put into perspective with related research results, and a (subjective) grading of difficulty for each of them is provided.
Learning Compact Visual Descriptors for Low Bit Rate Mobile Landmark Search
Authors: Duan Ling‐Yu , Chen Jie , Ji Rongrong , Huang Tiejun , Gao Wen
Published: July 2017

Along with the ever‐growing computational power of mobile devices, mobile visual search has undergone an evolution in techniques and applications. A significant trend is low bit rate visual search, where compact visual descriptors are extracted directly over a mobile and delivered as queries rather than raw images to reduce the query transmission latency. In this article, we introduce our work on low bit rate mobile landmark search, in which a compact yet discriminative landmark image descriptor is extracted by using a location context such as GPS, crowd‐sourced hotspot WLAN, and cell tower locations. The compactness originates from the bag‐of‐words image representation, with offline learning from geotagged photos from online photosharing websites including Flickr and Panoramio. The learning process involves segmenting the landmark photo collection by discrete geographical regions using a Gaussian mixture model and then boosting a ranking‐sensitive vocabulary within each region, with “entropy”‐based feedback on the compactness of the descriptor to refine both phases iteratively. In online search, when entering a geographical region, the code book in a mobile device is downstream adapted to generate extremely compact descriptors with promising discriminative ability. We have deployed landmark search apps to both HTC and iPhone mobile phones, accessing a database of a million scale images in typical areas like Beijing, New York, and Barcelona, and others. Our descriptor outperforms alternative compact descriptors (Chen et al. 2009; Chen et al., 2010; Chandrasekhar et al. 2009a; Chandrasekhar et al. 2009b) by significant margins. Beyond landmark search, this article will summarize the MPEG standarization progress of compact descriptor for visual search (CDVS) (Yuri et al. 2010; Yuri et al. 2011) toward application interoperability.
Speaking Louder than Words with Pictures Across Languages
Authors: Finch Andrew , Song Wei , Tanaka‐Ishii Kumiko , Sumita Eiichiro
Published: July 2017

In this article, we investigate the possibility of cross‐language communication using a synergy of words and pictures on mobile devices. On the one hand, communicating with only pictures is in itself a very powerful strategy, but is limited in expressiveness. On the other hand, words can express everything you could wish to say, but they are cumbersome to work with on mobile devices and need to be translated in order for their meaning to be understood. Automatic translations can contain errors that pervert the communication process, and this may undermine the users' confidence when expressing themselves across language barriers. Our idea is to create a user interface for cross‐language communication that uses pictures as the primary mode of input, and words to express the detailed meaning. This interface creates a visual process of communication that occurs on two heterogeneous channels that can support each other. We implemented this user interface as an application on the Apple iPad tablet and performed a set of experiments to determine its usefulness as a translation aid for travellers
Melomics: A Case‐Study of AI in Spain
Authors: Quintana Carlos Sánchez , Arcas Francisco Moreno , Molina David Albarracín , Rodríguez Jose David Fernández , Vico Francisco J.
Published: July 2017

Traditionally focused on good old‐fashioned AI and robotics, the Spanish AI community holds a vigorous computational intelligence substrate. Neuromorphic, evolutionary, or fuzzylike systems have been developed by many research groups in the Spanish computer sciences. It is no surprise, then, that these nature‐grounded efforts start to emerge, enriching the AI catalogue of research projects and publications and, eventually, leading to new directions of basic or applied research. In this article, we review the contribution of Melomics in computational creativity.
Recent Advances in Conversational Intelligent Tutoring Systems
Authors: Rus Vasile , D'Mello Sidney , Hu Xiangen , Graesser Arthur C.
Published: July 2017

We report recent advances in intelligent tutoring systems with conversational dialogue. We highlight progress in terms of macro‐ and microadaptivity. Macroadaptivity refers to a system's capability to select appropriate instructional tasks for the learner to work on. Microadaptivity refers to a system's capability to adapt its scaffolding while the learner is working on a particular task. The advances in macro‐ and microadaptivity that are presented here were made possible by the use of learning progressions, deeper dialogue, and natural language‐processing techniques, and by the use of affect‐enabled components. Learning progressions and deeper dialogue and natural language‐processing techniques are key features of Deep‐Tutor, the first intelligent tutoring system based on learning progressions. These improvements extend the bandwidth of possibilities for tailoring instruction to each individual student, which is needed for maximizing engagement and ultimately for learning.
Inquire Biology: A Textbook that Answers Questions
Authors: Chaudhri Vinay K. , Cheng Britte Haugan , Overholtzer Adam , Roschelle Jeremy , Spaulding Aaron , Clark Peter , Greaves Mark , Gunning Dave
Published: July 2017

Inquire Biology is a prototype of a new kind of intelligent textbook — one that answers students' questions, engages their interest, and improves their understanding. Inquire Biology provides unique capabilities through a knowledge representation that captures conceptual knowledge from the textbook and uses inference procedures to answer students' questions. Students ask questions by typing free‐form natural language queries or by selecting passages of text. The system then attempts to answer the question and also generates suggested questions related to the query or selection. The questions supported by the system were chosen to be educationally useful, for example: what is the structure of X? compare X and Y? how does X relate to Y? In user studies, students found this question‐answering capability to be extremely useful while reading and while doing problem solving. In an initial controlled experiment, community college students using the Inquire Biology prototype outperformed students using either a hard copy or conventional ebook version of the same biology textbook. While additional research is needed to fully develop Inquire Biology, the initial prototype clearly demonstrates the promise of applying knowledge representation and question‐answering technology to electronic textbooks.
The Eighth International Workshop on Planning and Scheduling for Space (IWPSS)
Authors: Morris Robert , Chien Steve
Published: July 2017

The Eighth International Workshop on Planning and Scheduling for Space (IWPSS 2013) was held on March 25–26, 2013, at the NASA Ames Research Center, Moffett Field, California. This was the eighth in a regular series that started in 1997.
A Constraint‐Based Dental School Timetabling System
Authors: Cambazard Hadrien , O'Sullivan Barry , Simonis Helmut
Published: July 2017

We describe a constraint‐based timetabling system that was developed for the dental school based at Cork University Hospital in Ireland. This system has been deployed since 2010. Dental school timetabling differs from other university course scheduling in that certain clinic sessions can be used by multiple courses at the same time, provided a limit on room capacity is satisfied. Starting from a constraint‐programming solution using a web interface, we have moved to a mixed integer programming‐based solver to deal with multiple objective functions, along with a dedicated Java application, which provides a rich user interface. Solutions for the years 2010, 2011, and 2012 have been used in the dental school, replacing a manual timetabling process, which could no longer cope with increasing student numbers and resulting resource bottlenecks. The use of the automated system allowed the dental school to increase the number of students enrolled to the maximum possible given the available resources. It also provides the school with a valuable “what‐if” analysis tool.
GRADE: Machine‐Learning Support for Graduate Admissions
Authors: Waters Austin , Miikkulainen Risto
Published: July 2017

This article describes GRADE, a statistical machine‐learning system developed to support the work of the graduate admissions committee at the University of Texas at Austin Department of Computer Science (UTCS). In recent years, the number of applications to the UTCS Ph.D. program has become too large to manage with a traditional review process. GRADE uses historical admissions data to predict how likely the committee is to admit each new applicant. It reports each prediction as a score similar to those used by human reviewers, and accompanies each by an explanation of what applicant features most influenced its prediction. GRADE makes the review process more efficient by enabling reviewers to spend most of their time on applicants near the decision boundary and by focusing their attention on parts of each applicant's file that matter the most. An evaluation over two seasons of Ph.D. admissions indicates that the system leads to dramatic time savings, reducing the total time spent on reviews by at least 74 percent.
Workshops Held at the First AAAI Conference on Human Computation and Crowdsourcing: A Report
Authors: Josephy Tatiana , Lease Matt , Paritosh Praveen , Krause Markus , Georgescu Mihai , Tjalve Michael , Braga Daniela
Published: July 2017

The first AAAI Conference on Human Computation and Crowdsourcing (HCOMP‐2013) was held November 6–9, 2013, in Palm Springs, California. Three workshops took place on Saturday, November 9: Crowdsourcing at Scale (full day), Disco: Human and Machine Learning in Games (full day), and Scaling Speech, Language Understanding, and Dialogue through Crowdsourcing (half day). This report summarizes the activities of those three events.
Reports on the 2013 AAAI Fall Symposium Series
Authors: Burns Gully APC , Gil Yolanda , Villanueva‐Rosales Natalia , Liu Yan , Risi Sebastian , Lehman Joel , Clune Jeff , Lebiere Christian , Rosenbloom Paul S. , van Harmelen Frank , Hendler James A. , Hitzler Pascal , Janowicz Krzysztof , Swarup Samarth
Published: July 2017

The Association for the Advancement of Artificial Intelligence was pleased to present the 2013 Fall Symposium Series, held Friday through Sunday, November 15–17, at the Westin Arlington Gateway in Arlington, Virginia, near Washington, D.C., USA. The titles of the five symposia were Discovery Informatics: AI Takes a Science‐Centered View on Big Data (FS‐13‐01); How Should Intelligence Be Abstracted in AI Research: MDPs, Symbolic Representations, Artificial Neural Networks, or — ? (FS‐13‐02); Integrated Cognition (FS‐13‐03); Semantics for Big Data (FS‐13‐04); and Social Networks and Social Contagion: Web Analytics and Computational Social Science (FS‐13‐05). The highlights of each symposium are presented in this report.
The Reinforcement Learning Competition 2014
Authors: Dimitrakakis Christos , Li Guangliang , Tziortziotis Nikolaos
Published: July 2017

Reinforcement learning is one of the most general problems in artificial intelligence. It has been used to model problems in automated experiment design, control, economics, game playing, scheduling, and telecommunications. The aim of the reinforcement learning competition is to encourage the development of very general learning agents for arbitrary reinforcement learning problems and to provide a test bed for the unbiased evaluation of algorithms.
Reports of the 2014 AAAI Spring Symposium Series
Authors: Jain Manish , Jiang Albert Xin , Kido Takashi , Takadama Keiki , Mercer Eric G. , Rungta Neha , Waser Mark , Wagner Alan , Burke Jennifer , Sofge Don , Lawless William , Sridharan Mohan , Hawes Nick , Hwang Tim
Published: July 2017

The Association for the Advancement of Artificial Intelligence was pleased to present the AAAI 2014 Spring Symposium Series, held Monday through Wednesday, March 24– 26, 2014. The titles of the eight symposia were Applied Computational Game Theory, Big Data Becomes Personal: Knowledge into Meaning, Formal Verification and Modeling in Human‐Machine Systems, Implementing Selves with Safe Motivational Systems and Self‐Improvement, The Intersection of Robust Intelligence and Trust in Autonomous Systems, Knowledge Representation and Reasoning in Robotics, Qualitative Representations for Robots, and Social Hacking and Cognitive Security on the Internet and New Media). This report contains summaries of the symposia, written, in most cases, by the cochairs of the symposium.