bluuebunny/crossref_metadata_2025 huggingface dataset:
Computational Sustainability
Authors: Eaton Eric , Gomes Carla , Williams Brian
Published: July 2017

Computational sustainability problems, which exist in dynamic environments with high amounts of uncertainty, provide a variety of unique challenges to artificial intelligence research and the opportunity for significant impact upon our collective future. This editorial introduction provides an overview of artificial intelligence for computational sustainability, and introduces the special issue articles that appear in this issue and the previous issue of AI Magazine.
A Review of Real‐Time Strategy Game AI
Authors: Robertson Glen , Watson Ian
Published: July 2017

This literature review covers AI techniques used for real‐time strategy video games, focusing specifically on StarCraft. It finds that the main areas of current academic research are in tactical and strategic decision making, plan recognition, and learning, and it outlines the research contributions in each of these areas. The paper then contrasts the use of game AI in academe and industry, finding the academic research heavily focused on creating game‐winning agents, while the industry aims to maximize player enjoyment. It finds that industry adoption of academic research is low because it is either inapplicable or too time‐consuming and risky to implement in a new game, which highlights an area for potential investigation: bridging the gap between academe and industry. Finally, the areas of spatial reasoning, multiscale AI, and cooperation are found to require future work, and standardized evaluation methods are proposed to produce comparable results between studies.
Power to the People: The Role of Humans in Interactive Machine Learning
Authors: Amershi Saleema , Cakmak Maya , Knox W. Bradley , Kulesza Todd
Published: July 2017

Systems that can learn interactively from their end‐users are quickly becoming widespread. Until recently, this progress has been fueled mostly by advances in machine learning; however, more and more researchers are realizing the importance of studying users of these systems. In this article we promote this approach and demonstrate how it can result in better user experiences and more effective learning systems. We present a number of case studies that demonstrate how interactivity results in a tight coupling between the system and the user, exemplify ways in which some existing systems fail to account for the user, and explore new ways for learning systems to interact with their users. After giving a glimpse of the progress that has been made thus far, we discuss some of the challenges we face in moving the field forward.
Leveraging Multiple Artificial Intelligence Techniques to Improve the Responsiveness in Operations Planning: ASPEN for Orbital Express
Authors: Knight Russell , Chouinard Caroline , Jones Grailing , Tran Daniel
Published: July 2017

The challenging timeline for DARPA's Orbital Express mission demanded a flexible, responsive, and (above all) safe approach to mission planning. Mission planning for space is challenging because of the mixture of goals and constraints. Every space mission tries to squeeze all of the capacity possible out of the spacecraft. For Orbital Express, this means performing as many experiments as possible, while still keeping the spacecraft safe. Keeping the spacecraft safe can be very challenging because we need to maintain the correct thermal environment (or batteries might freeze), we need to avoid pointing cameras and sensitive sensors at the sun, we need to keep the spacecraft batteries charged, and we need to keep the two spacecraft from colliding … made more difficult as only one of the spacecraft had thrusters.

Because the mission was a technology demonstration, pertinent planning information was learned during actual mission execution. For example, we didn't know for certain how long it would take to transfer propellant from one spacecraft to the other, although this was a primary mission goal. The only way to find out was to perform the task and monitor how long it actually took. This information led to amendments to procedures, which led to changes in the mission plan. In general, we used the ASPEN planner scheduler to generate and validate the mission plans. ASPEN is a planning system that allows us to enter all of the spacecraft constraints, the resources, the communications windows, and our objectives. ASPEN then could automatically plan our day. We enhanced ASPEN to enable it to reason about uncertainty. We also developed a model generator that would read the text of a procedure and translate it into an ASPEN model. Note that a model is the input to ASPEN that describes constraints, resources, and activities. These technologies had a significant impact on the success of the Orbital Express mission. Finally, we formulated a technique for converting procedural information to declarative information by transforming procedures into models of hierarchical task networks (HTNs). The impact of this effort on the mission was a significant reduction in (1) the execution time of the mission, (2) the daily staff required to produce plans, and (3) planning errors. Not a single misconfigured command was sent during operations.
ACTIVE‐ating Artificial Intelligence: Integrating Active Learning in an Introductory Course
Authors: desJardins Marie
Published: July 2017

This column describes my experience with using a new classroom space (the ACTIVE Center), which was designed to facilitate group‐based active learning and problem solving, to teach an introductory artificial intelligence course. By restructuring the course into a format that was roughly half lecture and half small‐group problem solving, I was able to significantly increase student engagement, their understanding and retention of difficult concepts, and my own enjoyment in teaching the class.
Truth Is a Lie: Crowd Truth and the Seven Myths of Human Annotation
Authors: Aroyo Lora , Welty Chris
Published: July 2017

Big data is having a disruptive impact across the sciences. Human annotation of semantic interpretation tasks is a critical part of big data semantics, but it is based on an antiquated ideal of a single correct truth that needs to be similarly disrupted. We expose seven myths about human annotation, most of which derive from that antiquated ideal of truth, and dispel these myths with examples from our research. We propose a new theory of truth, crowd truth, that is based on the intuition that human interpretation is subjective, and that measuring annotations on the same objects of interpretation (in our examples, sentences) across a crowd will provide a useful representation of their subjectivity and the range of reasonable interpretations.
Early Steps Toward Web‐Scale Information Extraction with LODIE
Authors: Gentile Anna Lisa , Zhang Ziqi , Ciravegna Fabio
Published: July 2017

Information extraction (IE) is the technique for transforming unstructured textual data into a structured representation that can be understood by machines. The exponential growth of the web generates an exceptional quantity of data for which automatic knowledge capture is essential. This work describes the methodology for web‐scale information extraction in the linked open data information‐extraction (LODIE) project and highlights results from the early experiments carried out in the initial phase of the project. LODIE aims to develop information‐extraction techniques able to scale at web level and adapt to user information needs. The core idea behind LODIE is the usage of linked open data, a very large‐scale information resource, as a ground‐breaking solution for IE, which provides invaluable annotated data on a growing number of domains. This article has two objectives, first, describing the LODIE project as a whole and depicting its general challenges and directions; and second, describing some initial steps taken toward the general solution, focusing on a specific IE sub‐task, wrapper induction.
Reports of the AAAI 2014 Conference Workshops
Authors: Albrecht Stefano V. , Barreto André M. S. , Braziunas Darius , Buckeridge David L. , Cuayáhuitl Heriberto , Dethlefs Nina , Endres Markus , Farahmand Amir‐massoud , Fox Mark , Frommberger Lutz , Ganzfried Sam , Guillet Sébastien , Gil Yolanda , Hunter Lawrence E. , Jhala Arnav , Kersting Kristian , Konidaris George , Lecue Freddy , McIlraith Sheila , Natarajan Sriraam , Noorian Zeinab , Poole David , Ronfard Rémi , Saffiotti Alessandro , Shaban‐Nejad Arash , Srivastava Biplav , Tesauro Gerald , Uceda‐Sosa Rosario , Van den Broeck Guy , van Otterlo Martijn , Wallace Byron C. , Weng Paul , Wiens Jenna , Zhang Jie
Published: July 2017

The AAAI‐14 Workshop program was held Sunday and Monday, July 27– 28, 2014, at the Québec City Convention Centre in Québec, Canada. The AAAI‐14 workshop program included 15 workshops covering a wide range of topics in artificial intelligence. The titles of the workshops were Artificial Intelligence and Robotics; Artificial Intelligence Applied to Assistive Technologies and Smart Environments; Cognitive Computing for Augmented Human Intelligence; Computer Poker and Imperfect Information; Discovery Informatics; Incentives and Trust in Electronic Communities; Intelligent Cinematography and Editing; Machine Learning for Interactive Systems: Bridging the Gap Between Perception, Action, and Communication; Modern Artificial Intelligence for Health Analytics; Multiagent Interaction Without Prior Coordination; Multidisciplinary Workshop on Advances in Preference Handling; Semantic Cities — Beyond Open Data to Models, Standards, and Reasoning; Sequential Decision Making with Big Data; Statistical Relational AI; and the World Wide Web and Public Health Intelligence. This article presents short summaries of those events.
Platys: From Position to Place‐Oriented Mobile Computing
Authors: Zavala Laura , Murukannaiah Pradeep K. , Poosamani Nithyananthan , Finin Tim , Joshi Anupam , Rhee Injong , Singh Munindar P.
Published: July 2017

The Platys project focuses on developing a high‐level, semantic notion of location called place. A place, unlike a geospatial position, derives its meaning from a user's actions and interactions in addition to the physical location where it occurs. Our aim is to enable the construction of a large variety of applications that take advantage of place to render relevant content and functionality and, thus, improve user experience. We consider elements of context that are particularly related to mobile computing. The main problems we have addressed to realize our place‐oriented mobile computing vision are representing places, recognizing places, and engineering place‐aware applications. We describe the approaches we have developed for addressing these problems and related subproblems. A key element of our work is the use of collaborative information sharing where users' devices share and integrate knowledge about places. Our place ontology facilitates such collaboration. Declarative privacy policies allow users to specify contextual features under which they prefer to share or not share their information.
Activity‐Based Computing: Computational Management of Activities Refecting Human Intention
Authors: Bardram Jakob E. , Jeuris Steven , Houben Steven
Published: July 2017

An important research topic in artificial intelligence is automatic sensing and inferencing of contextual information, which is used to build computer models of the user's activity. One approach to building such activity‐aware systems is the notion of activity‐based computing (ABC). ABC is a computing paradigm that has been applied in personal information‐management applications as well as in ubiquitous, multidevice, and interactive surface computing. ABC has emerged as a response to the traditional application‐and file‐centered computing paradigm, which is oblivious to a notion of a user's activity spanning heterogeneous devices, multiple applications, services, and information sources. In this article, we present ABC as an approach to contextualize information, and present our research into designing activity‐based computing technologies.
Innovative Applications of Artificial Intelligence 2014
Authors: Stracuzzi David J. , Gunning David
Published: July 2017

This issue features expanded versions of articles selected from the 2014 AAAI Conference on Innovative Applications of Artificial Intelligence (IAAI) held in Quebec City, Canada. We present a selection of four articles describing deployed applications plus two more articles that discuss work on emerging applications.
The Automated Negotiating Agents Competition, 2010–2015
Authors: Baarslag Tim , Aydoǧan Reyhan , Hindriks Koen V. , Fujita Katsuhide , Ito Takayuki , Jonker Catholijn M.
Published: July 2017

The Automated Negotiating Agents Competition is an international event that, since 2010, has contributed to the evaluation and development of new techniques and benchmarks for improving the state of the art in automated multi‐issue negotiation. A key objective of the competition has been to analyze and search the design space of negotiating agents for agents that are able to operate effectively across a variety of domains. The competition is a valuable tool for studying important aspects of negotiation including profiles and domains, opponent learning, strategies, and bilateral and multilateral protocols. Two of the challenges that remain are how to develop argumentation‐based negotiation agents that, in addition to making offers, can inform and argue to obtain an acceptable agreement for both parties; and how to create agents that can negotiate in a human fashion.
Human‐Centered Cognitive Orthoses: Artificial Intelligence for, Rather Than Instead of, the People
Authors: Neuhaus Peter , Raj Anil , Clancey William J.
Published: July 2017

This issue of AI Magazine includes six articles on cognitive orthoses, which we broadly conceive as technological approaches that amplify or enhance individual or team cognition across a wide range of goals and activities. The articles are grouped by how they relate to orthoses‐enhanced sociotechnical team intelligence at three different cognitive levels—sensorimotor physical, professional learning, and networked knowledge.
Extending the Diagnostic Capabilities of Artificial Intelligence‐Based Instructional Systems
Authors: Mathan Santosh , Yeung Nick
Published: July 2017

Active problem solving has been shown to be one of the most effective ways to acquire complex skills. Whether one is learning a programming language by implementing a computer program, or learning calculus by solving problems, context‐sensitive feedback and guidance are crucial to keeping problem‐solving efforts fruitful and efficient. This article reviews AI‐based algorithms that can diagnose student difficulties during active problem solving and serve as the basis for providing context‐sensitive and individualized guidance. The article also describes the crucial role sensor‐based estimates of cognitive resources such as working memory capacity and attention can play in enhancing the diagnostic capabilities of intelligent instructional systems
What Do You Need to Know to Use a Search Engine? Why We Still Need to Teach Research Skills
Authors: Russell Daniel M.
Published: July 2017

For the vast majority of queries (for example, navigation, simple fact lookup, and others), search engines do extremely well. Their ability to provide answers to queries quickly is a remarkable testament to the power of many of the fundamental methods of AI. They also highlight many of the issues that are common to sophisticated AI question‐answering systems. It has become clear that people think of search programs in ways that are very different from traditional information sources. Rapid and ready‐at‐hand access, depth of processing, and the way they enable people to offload some ordinary memory tasks suggest that search engines have become more of a cognitive amplifier than a simple repository or front end to the Internet. As with all sophisticated tools, people still need to learn how to use them. Although search engines are superb at finding and presenting information — up to and including extracting complex relations and making simple inferences — knowing how to frame questions and evaluate their results for accuracy and credibility remains an ongoing challenge. Some questions are still deep and complex, and still require knowledge on the part of the search user to work through to a successful answer. And the fact that the underlying information content, user interfaces, and capabilities are all in a continual state of change means that searchers need to continually update their knowledge of what these programs can (and cannot) do.
My Computer Is an Honor Student — But How Intelligent Is It? Standardized Tests as a Measure of AI
Authors: Clark Peter , Etzioni Oren
Published: July 2017

Given the well‐known limitations of the Turing test, there is a need for objective tests to both focus attention on, and measure progress toward, the goals of AI. In this paper we argue that machine performance on standardized tests should be a key component of any new measure of AI, because attaining a high level of performance requires solving significant AI problems involving language understanding and world modeling — critical skills for any machine that lays claim to intelligence. In addition, standardized tests have all the basic requirements of a practical test: they are accessible, easily comprehensible, clearly measurable, and offer a graduated progression from simple tasks to those requiring deep understanding of the world. Here we propose this task as a challenge problem for the community, summarize our state‐of‐the‐art results on math and science tests, and provide supporting data sets (www.allenai.org).
Why We Need a Physically Embodied Turing Test and What It Might Look Like
Authors: Ortiz Charles L.
Published: July 2017

The Turing test, as originally conceived, focused on language and reasoning; problems of perception and action were conspicuously absent. To serve as a benchmark for motivating and monitoring progress in AI research, this article proposes an extension to that original proposal that incorporates all four of these aspects of intelligence. Some initial suggestions are made regarding how best to structure such a test and how to measure progress. The proposed test also provides an opportunity to bring these four important areas of AI research back into sync after each has regrettably diverged into a fairly independent area of research of its own.
Qualitative Reasoning: Everyday, Pervasive, and Moving Forward — A Report on QR‐15
Authors: Friedman Scott , Lockwood Kate
Published: July 2017

The 28th International Workshop on Qualitative Reasoning (QR‐15) presented advances toward reasoning tractably with massive qualitative and quantitative models, automatically learning and reasoning about continuous processes, and representing knowledge about space, causation, and uncertainty.
Humans and Machines in the Evolution of AI in Korea
Authors: Zhang Byoung‐Tak
Published: July 2017

Artificial intelligence in Korea is currently prospering. The media are regularly reporting AI‐enabled products such as smart advisors, personal robots, autonomous cars, and human‐level intelligence machines. The IT industry is investing in deep learning and AI to maintain the global competitive edge in its services and products. The Ministry of Science, ICT, and Future Planning (MSIP) has launched new funding programs in AI and cognitive science to implement the government's newly adopted endeavor of building a creative economy and software‐centered society. However, AI did not always flourish as it now does. Similar to the history of AI worldwide, AI research and industry in Korea have faced both ups and downs in their history.
Answer Set Programming: An Introduction to the Special Issue
Authors: Brewka Gerhard , Eiter Thomas , Truszczyński Mirosław
Published: July 2017

This editorial introduces answer set programming, a vibrant research area in computational knowledge representation and declarative programming. We give a brief overview of the articles that form this special issue on answer set programming and of the main topics they discuss.
Modeling and Language Extensions
Authors: Gebser Martin , Schaub Torsten
Published: July 2017

Answer set programming (ASP) has emerged as an approach to declarative problem solving based on the stable model semantics for logic programs. The basic idea is to represent a computational problem by a logic program, formulating constraints in terms of rules, such that its answer sets correspond to problem solutions. To this end, ASP combines an expressive language for high‐level modeling with powerful low‐level reasoning capacities, provided by off‐the‐shelf tools. Compact problem representations take advantage of genuine modeling features of ASP, including (first‐order) variables, negation by default, and recursion. In this article, we demonstrate the ASP methodology on two example scenarios, illustrating basic as well as advanced modeling and solving concepts. We also discuss mechanisms to represent and implement extended kinds of preferences and optimization. An overview of further available extensions concludes the article.
First‐Order Logic with Inductive Definitions for Model‐Based Problem Solving
Authors: Bruynooghe Maurice , Denecker Marc , Truszczyński Mirosław
Published: July 2017

In answer set programming (ASP), programs can be viewed as specifications of finite Herbrand structures. Other logics can be (and, in fact, were) used toward the same end and can be taken as the basis of declarative programming systems of similar functionality as ASP. We discuss here one such logic, the logic FO(ID), and its implementation IDP3. The choice is motivated by notable similarities between ASP and FO(ID), even if both approaches trace back to different origins.
Reports of the 2016 AAAI Workshop Program
Authors: Albrecht Stefano V. , Bouchard Bruno , Brownstein John S. , Buckeridge David L. , Caragea Cornelia , Carter Kevin M. , Darwiche Adnan , Fortuna Blaz , Francillette Yannick , Gaboury Sébastien , Giles C. Lee , Grobelnik Marko , Hruschka Estevam , Kephart Jeffrey O. , Kordjamshidi Parisa , Lisy Viliam , Magazzeni Daniele , Marques‐Silva Joao , Marquis Pierre , Martinez David , Michalowski Martin , Noorian Zeinab , Pontelli Enrico , Rogers Alex , Rosenthal Stephanie , Roth Dan , Sanner Scott , Shaban‐Nejad Arash , Sinha Arunesh , Son Tran Cao , Streilein William , Thiebaux Sylvie , Wallace Byron C. , Walsh Toby , Witbroc Michael , Zhang Jie
Published: July 2017

The Workshop Program of the Association for the Advancement of Artificial Intelligence's Thirtieth AAAI Conference on Artificial Intelligence (AAAI‐16) was held at the beginning of the conference, February 12–13, 2016. Workshop participants met and discussed issues with a selected focus, and the workshop provided an informal setting for active exchange among researchers, developers, and users on topics of current interest. The AAAI‐16 workshops were an excellent forum for exploring emerging approaches and task areas, for bridging the gaps between AI and other fields or between subfields of AI, for elucidating the results of exploratory research, or for critiquing existing approaches. The 15 workshops held at AAAI‐16 were Artificial Intelligence Applied to Assistive Technologies and Smart Environments (WS‐16‐01), AI, Ethics, and Society (WS‐16‐02), Artificial Intelligence for Cyber Security (WS‐16‐03), Artificial Intelligence for Smart Grids and Smart Buildings (WS‐16‐04), Beyond NP (WS‐16‐05), Computer Poker and Imperfect Information Games (WS‐16‐06), Declarative Learning Based Programming (WS‐16‐07), Expanding the Boundaries of Health Informatics Using AI (WS‐16‐08), Incentives and Trust in Electronic Communities (WS‐16‐09), Knowledge Extraction from Text (WS‐16‐10), Multiagent Interaction Without Prior Coordination (WS‐16‐11), Planning for Hybrid Systems (WS‐16‐12), Scholarly Big Data: AI Perspectives, Challenges, and Ideas (WS‐16‐13), Symbiotic Cognitive Systems (WS‐16‐14), and World Wide Web and Population Health Intelligence (WS‐16‐15).
Hedging the Risk of Delays in Multimodal Journey Planning
Authors: Botea Adi
Published: July 2017

Traditional multimodal journey planners are deterministic. However, uncertainty in a transportation network can often lead to missed connections, causing delays and hurting the reliability level of the service. This article provides an overview of what is possibly the first multimodal journey advising system that is capable of reasoning under uncertainty and that provides more reliable journey plans.
Collaborative Language Grounding Toward Situated Human‐Robot Dialogue
Authors: Chai Joyce Y. , Fang Rui , Liu Changsong , She Lanbo
Published: July 2017

To enable situated human‐robot dialogue, techniques to support grounded language communication are essential. One particular challenge is to ground human language to a robot's internal representation of the physical world. Although copresent in a shared environment, humans and robots have mismatched capabilities in reasoning, perception, and action. Their representations of the shared environment and joint tasks are significantly misaligned. Humans and robots will need to make extra effort to bridge the gap and strive for a common ground of the shared world. Only then is the robot able to engage in language communication and joint tasks. Thus computational models for language grounding will need to take collaboration into consideration. A robot not only needs to incorporate collaborative effort from human partners to better connect human language to its own representation, but also needs to make extra collaborative effort to communicate its representation in language that humans can understand. To address these issues, the Language and Interaction Research group (LAIR) at Michigan State University has investigated multiple aspects of collaborative language grounding. This article gives a brief introduction to this research effort and discusses several collaborative approaches to grounding language to perception and action.
Reports on the 2016 IJCAI Workshop Series
Authors: Sukthankar Gita
Published: July 2017

This report summarizes the 39 workshops held as part of the 2016 International Joint Conference on Artificial Intelligence, held in New York from July 9–11.
A Short History of the RecSys Challenge
Authors: Said Alan
Published: July 2017

The RecSys Challenge is a yearly recurring competition focusing on creating the best performing recommendation approach for a specific scenario. Over the years, the competition has drawn many participants from industry and academia and has become a key part of the ACM Conference on Recommender Systems series. This article presents a brief historical overview of the RecSys Challenge from its inception in 2010 until the seventh iteration in 2016.
Robert S. Engelmore Award Article: Building AI Applications: Yesterday, Today, and Tomorrow
Authors: Smith Reid G. , Eckroth Joshua
Published: July 2017

AI applications have been deployed and used for industrial, government, and consumer purposes for many years. The experiences have been documented in IAAI conference proceedings since 1989. Over the years, the breadth of applications has expanded many times over and AI systems have become more commonplace. Indeed, AI has recently become a focal point in the industrial and consumer consciousness. This article focuses on changes in the world of computing over the last three decades that made building AI applications more feasible. We then examine lessons learned during this time and distill these lessons into succinct advice for future application builders.
Ontology Reengineering: A Case Study from the Automotive Industry
Authors: Rychtyckyj Nestor , Raman Venkatesh , Sankaranarayanan Baskaran , Kumar P. Sreenivasa , Khemani Deepak
Published: July 2017

For more than 25 years Ford Motor Company has been utilizing an AI‐based system to manage process planning for vehicle assembly at its assembly plants around the world. The scope of the AI system, known originally as the Direct Labor Management System and now as the Global Study Process Allocation System (GSPAS), has increased over the years to include additional functionality on ergonomics and powertrain assembly (engines and transmission plants). The knowledge about Ford's manufacturing processes is contained in an ontology originally developed using the KL‐ONE representation language and methodology. To preserve the viability of the GSPAS ontology and to make it easily usable for other applications within Ford, we needed to reengineer and convert the KL‐ONE ontology into a semantic web OWL/RDF format. In this article, we will discuss the process by which we reengineered the existing GSPAS KL‐ONE ontology and deployed semantic web technology in our application.
WatsonPaths: Scenario‐Based Question Answering and Inference over Unstructured Information
Authors: Lally Adam , Bagchi Sugato , Barborak Michael A. , Buchanan David W. , Chu‐Carroll Jennifer , Ferrucci David A. , Glass Michael R. , Kalyanpur Aditya , Mueller Erik T. , Murdock J. William , Patwardhan Siddharth , Prager John M.
Published: July 2017

We present WatsonPaths, a novel system that can answer scenario‐based questions. These include medical questions that present a patient summary and ask for the most likely diagnosis or most appropriate treatment. Watson‐Paths builds on the IBM Watson question‐answering system. WatsonPaths breaks down the input scenario into individual pieces of information, asks relevant subquestions of Watson to conclude new information, and represents these results in a graphic model. Probabilistic inference is performed over the graph to conclude the answer. On a set of medical test preparation questions, WatsonPaths shows a significant improvement in accuracy over multiple baselines.
Artificial Intelligence Education
Authors: Wollowski Michael , Neller Todd , Boerkoel James
Published: July 2017

This issue of AI Magazine includes five articles that cover subjects of current concern to the AI education community. This editorial introduces those five articles.
Ask Me Anything About MOOCs
Authors: Fisher Douglas H. , Isbell Charles L. , Littman Michael L. , Neller Todd , Boerkoel James
Published: July 2017

In this article, 10 questions about MOOCs (crowdsourced from the recipients of the AAAI and SIGCSE mailing lists) were posed by editors Michael Wollowski, Todd Neller, and James Boerkoel to educators Douglas H. Fisher, Charles Isbell, and Michael Littman.
Keeping It Real: Using Real‐World Problems to Teach AI to Diverse Audiences
Authors: Sintov Nicole , Kar Debarun , Nguyen Thanh , Fang Fei , Hoffman Kevin , Lyet Arnaud , Tambe Milind
Published: July 2017

In recent years, AI‐based applications have increasingly been used in real‐world domains. For example, game theory–based decision aids have been successfully deployed in various security settings to protect ports, airports, and wildlife. This article describes our unique problem‐to‐project educational approach that used games rooted in real‐world issues to teach AI concepts to diverse audiences. Specifically, our educational program began by presenting real‐world security issues, and progressively introduced complex AI concepts using lectures, interactive exercises, and ultimately hands‐on games to promote learning. We describe our experience in applying this approach to several audiences, including students of an urban public high school, university undergraduates, and security domain experts who protect wildlife. We evaluated our approach based on results from the games and participant surveys.
Veterinary Anthelmintics and Anthelmintic Drug Resistance
Authors: Dyary Hiewa
Published: July 2017

Helminths are a diverse group of parasitic worms in the body of animals andhuman. Infection of livestock with parasitic worms poses a great burden on thehealth of animals that eventually leads to great losses in the productivity of theseanimals and economic losses to the farmers. The control of helminthiasis isdependent almost solely on the use of anthelmintic drugs, due to the ease ofimplementation and low cost of therapy, compared to other methods of control.However, chemotherapy of parasitic worms is burdened with such problems as thedevelopment of anthelmintic resistance (AR). Many of the currently availableanthelmintic drugs have been in use for quite a long time and reports exhibiting thedevelopment of AR against them are increasing.Improving livestock management and, hence, productivity is a requirement in orderto compensate for the increasing world population, which will eventually lead toincreased demands for animal products. The tackling of AR needs to implementsuch methods as: (i) the systematic use of the currently available drugs, (ii) controlof animal pasture, (iii) promoting the breeding of animals that are naturallyresistant to certain types of helminths and (iv) development of new anthelminticdrugs by the pharmaceutical industry that have novel modes of action. Althougheach of these methods plays a part in the control program, chemotherapy willremain the cornerstone in the control program of helminth infections. Hence, thecontinuous supply of new antiparasitic compounds to the currently availableanthelmintic pool is the best strategy to be implemented in the fight againsthelminth infections.
Indication of calcareous tempestite inside the Qulqula Group in the Zagros Suture Zone, KRI
Authors: Baziany Mushir
Published: July 2017

This sedimentological study focuses on carbonate storm deposits (calcareous tempestites) have been recognized for Qulqula platform in the Zagros Suture Zone outcropping at Sharbazher area in the northeastern Sulaimani City. This deposits are recorded between the oolitic limestone and calcareous turbidities in the Qulqula Group for the first time. These offer the first indication of event sedimentation in the Qulqula domain. Calcareous tempestites deposited on subsided eastern Arabian continental margin at initial stage of continental rifting, most possibly during Early Late Triassic to Early Jurassic. It is mostly encompasscalcarenite beds and indicating by some storm generated criteria such as: hummocky cross-stratification, parallel lamination, symmetrical wave-ripples, normally graded flat pebble conglomerate, and sole mark (flute caste, load cast, groove mark). Moreover, found Cruziana and Skolithos trace fossils with these calcarenite beds. Finally, for paleogeographic configuration of Qulqula carbonate platform, facies-depth connections on carbonate ramp model build up as shallowing-upward cycles from calcareous turbidities which deposited in distal part of outer ramp and carbonate distally steepened ramp to calcareous tempestites in mid ramp to oolitic limestone were formed in high-energy inner carbonate ramp.
Alzheimer’s Disease: Dawn of a New Era?
Authors: Amirrad Farideh , Bousoik Emira , Shamloo Kiumars , Al-Shiyab Hassan , Nguyen Viet-Huong V. , Montazeri Aliabadi Hamidreza
Published: July 2017

Alzheimer’s disease (AD) is an irreversible neurodegenerative disease characterized by a progressive decline in cognition and memory, leading to significant impairment in daily activities and ultimately death. It is the most common cause of dementia, the prevalence of which increases with age; however, age is not the only predisposing factor. The pathology of this cognitive impairing disease is still not completely understood, which has limited the development of valid therapeutic options. Recent years have witnessed a wide range of novel approaches to combat this disease, so that they greatly increased our understanding of the disease and of the unique drug development issues associated with this disease. In this paper, we provide a brief overview of the history, the clinical presentation and diagnosis, and we undertake a comprehensive review of the various approaches that have been brought to clinical trials in recent years, including immunotherapeutic approaches, tau-targeted strategies, neurotransmitter-based therapies, neurotropic and hematopoietic growth factors, and antioxidant therapies, trying to highlight the lessons learned from these approaches. This article is open to POST-PUBLICATION REVIEW. Registered readers (see “For Readers”) may comment by clicking on ABSTRACT on the issue’s contents page.
Kangaroo Mother Care 1: Alleviation of Physiological Problems in Premature Infants
Authors: Bear Rebecca J. , Mellor David J.
Published: July 2017

Kangaroo mother care (KMC) involves placing the newborn infant into prolonged and continuous skin-to-skin contact with the mother as soon as possible after birth, exclusive breastfeeding, early discharge from the health facility, and supportive follow-up at home. Claimed benefits of KMC as an aid to the clinical mitigation of some detrimental features of prematurity need to be evidence based. This article, the first of two, provides an overview of the impact of prematurity on those features of neonates to which KMC may be directed. Specifically, the mitigation of some cardiorespiratory, neurophysiological, sensory, gastrointestinal, musculoskeletal, renal, metabolic, and immunological impacts are outlined. Relevant neurobehavioral, psychosocial, sociocultural, and economic perspectives are briefly reviewed in the companion article. These two articles provide scientific support for a wider upscaling of KMC education and its cautious use in physiologically stable preterm infants.
Effect of R Ratio on Performance of Injection-Pressure-Operated Gas Lift Valves
Authors: Decker (retired) K. L.
Published: July 2017

An injection-pressure-operated (IPO) gas lift valve's closing force is supplied by a nitrogen charge, acting on the effective area of the bellows (Ab), or a spring force. Traditionally, the opening force is the production pressure acting on the area of the port (Ap) plus the injection pressure acting on the bellows effective area minus the area of the port (Ab − Ap). Traditionally, the ratio Ap/Ab is referred to as the R ratio, and has been considered constant for every valve of the same make, model, and port size. The actual R ratio is not a constant and neither is it equal to the published value. The published R ratios are embedded in all gas lift design programs, and are an integral part of the gas lift design process. This paper describes the consequences of using an assumed R ratio in a gas lift design that is not the same as the actual R ratio of the valve that will be installed in the well.
Shallow groundwater quality assessment: use of the improved Nemerow pollution index, wavelet transform and neural networks
Authors: Yang Q. , Zhang J. , Hou Z. , Lei X. , Tai W. , Chen W. , Chen T.
Published: July 2017

Shallow groundwater is generally of great interest to the community due to its easy availability. However, it is very sensitive to external stimulus. In this paper, shallow groundwater quality is assessed and classified with improved Nemerow pollution index, multi-layer perceptron artificial neural network (MLP-ANN) optimized with a back-propagation algorithm and wavelet neural network (WNN) methods in a coastal aquifer, Fujian Province, South China. The data used in three models were collected during the pre-monsoon over the period 2004–2011. The eight parameters, total dissolved solids, total hardness, chemical oxygen demand, chloride, sulphate, nitrate, nitrite and fluorides, were selected to characterize groundwater quality classification based on the National Quality Standard for Groundwater (GB/T 14848-93). The results of MLP-ANN and WNN are interpreted by mean absolute error, root mean square error and R2 (determination coefficient) criteria. The results obtained from three methods demonstrate that WNN has a higher accuracy compared with the other two methods. The study reveals that these methods are efficient tools for assessing groundwater quality.
Phosphorus fractions and its summer flux from sediments of deep reservoirs located at a phosphate-rock watershed, Central China
Authors: Bao Yufei , Wang Yuchun , Hu Mingming , Wang Qiwen
Published: July 2017

Huangbai River, including four enchained reservoirs, is located in a phosphate-rock watershed in Yichang City, Central China. Previous studies showed that pollution levels due to activities of phosphate mining (PM) were extremely high and the water quality of reservoirs was severely affected by sedimentation. Yet, detailed knowledge of the sediment is lacking at that high phosphorus (P) concentration basin. Therefore, the different P fractions and its diffusion fluxes at the water-sediment interface of four deep reservoirs have been investigated for the first time to understand the internal P loading. The results indicated that the concentrations of total P , ranging from 9,631.5 to 581.6 mg kg−1, exhibited an apparent spatial trend from the upstream to the downstream reservoirs, which corresponded with the activities of P mining in this basin. The P-fraction concentrations obtained from the sites were mainly ranked in this order: P associated with calcium (Ca-Pi) > organic P (Po) > P bound to aluminum (Al), ferrum (Fe) and manganese (Mn) oxides and hydroxides (Fe/Al-Pi). The orthophosphate diffusion fluxes ranged from −0.40 ± 0.09 to 0.95 ± 0.14 mg m−2 d−1 which were positively related to P fraction concentrations while negatively related to oxidation–reduction potential and dissolved oxygen values. These results implied the dynamics role of internal P loading. The principle component analysis suggested that PM activities and internal P loading were the most reactive factors in this river system.
Behavior of Steel Welded Tapered Beam-column
Authors: Dogariu A.I. , Crișan A. , Cristuțiu M. , Nunes D.L. , Juca A.
Published: July 2017

Steel structural elements with variable cross-section, made of welded plates, are largely used in the construction industry for both beams and columns in accordance with the stress and stiffness demand in the structure. These types of elements are mainly used for the design of single storey frames with pitched roof rafters and pinned column base. Rafters and columns can be designed as tapered members made of steel welded plates, respecting the bending moment diagrams for gravitational load combination. This paper deals with experimental tests performed on tapered beam-columns elements, subjected to both bending moment and compressive axial force together with analytical investigation.
Influence of Shear Connection Distributions on the Behaviour of Continuous Steel-concrete Composite Beams
Authors: Zona Alessandro , Leoni Graziano , Dall’Asta Andrea
Published: July 2017

Background:

In this work the behaviour of continuous steel-concrete composite beams with different shear connection distributions obtained from two design methods,i.e. Eurocode 4 and a proposed alternative approach, is analysed.

Objective:

For this purpose a finite element model specifically developed for the nonlinear analysis of steel-concrete composite beams is adopted. This finite element model includes material nonlinearity of slab concrete, reinforcement steel, beam steel as well as slab-beam nonlinear partial interaction due to the deformable shear connection. The inclusion of the partial interaction in the composite beam model provides information on the slab-beam interface slip and shear force and enables to model the failure of the shear connectors.

Results and Conclusion:

In this way it is possible to analyse and quantify the effect of shear connector distributions on the global and local response of continuous steel-concrete composite beams, both under service load levels and at collapse. Particular attention is focused on the ductility requirements on the shear connectors when varying the connection design approach and distribution.
How Can a Steel Structure Survive to Impact Loading?
Authors: Jean-François Demonceau , Ludivine Comeliau , Van Long Hoang , Jean-Pierre Jaspart
Published: July 2017

Recent events such as natural catastrophes or terrorism attacks have highlighted the necessity to ensure the structural integrity of buildings under exceptional events. For more than 10 years, the University of Liege is strongly involved in researches further investigating the response of structures to such exceptional events [1, 2]. The present paper gives a global overview on recent or on-going developments performed at the University of Liege in the field of robustness of steel building structures subjected to impact loading leading to the loss of a column. The conducted studies are founded on a combination of experimental, numerical and analytical approaches with the final aim to propose simplified procedures useful for practitioners and allowing ensuring an appropriate level of robustness to structures for the considered scenario.
On the European Norms of Design of Buckling Restrained Braced Frames
Authors: Zsarnóczay Ádám , Balogh Tamás , Vigh László Gergely
Published: July 2017

The application of buckling restrained braced frames is hindered in Europe by the absence of a standardized design procedure in Eurocode 8, the European seismic design standard. The presented research aims to develop a robust design procedure for buckling restrained braced frames. A design procedure is proposed by the authors. Its performance has been evaluated for buckling restrained braced frames with two-bay X-brace type brace configurations using a state-of-the-art methodology based on the recommendations in the FEMA P695 document. A special numerical material model was developed within the scope of this research to represent the behavior of buckling restrained braces more appropriately in a numerical environment. A total of 24 archetype designs were prepared and their nonlinear dynamic response was calculated using real ground motion records in incremental dynamic analyses. Evaluation of archetype collapse probabilities confirms that the proposed design procedure can utilize the advantageous behavior of buckling restrained braces. Resulting reliability indices suggest a need for additional regulations in the Eurocodes that introduce reasonable structural reliability index limits for seismic design.
Frailty Screening Tools for Elderly Patients Incident to Dialysis
Authors: van Loon Ismay N. , Goto Namiko A. , Boereboom Franciscus T.J. , Bots Michiel L. , Verhaar Marianne C. , Hamaker Marije E.
Published: July 2017

Background and objectives

A geriatric assessment is an appropriate method for identifying frail elderly patients. In CKD, it may contribute to optimize personalized care. However, a geriatric assessment is time consuming. The purpose of our study was to compare easy to apply frailty screening tools with the geriatric assessment in patients eligible for dialysis.

Design, setting, participants, & measurements

A total of 123 patients on incident dialysis ≥65 years old were included <3 weeks before to ≤2 weeks after dialysis initiation, and all underwent a geriatric assessment. Patients with impairment in two or more geriatric domains on the geriatric assessment were considered frail. The diagnostic abilities of six frailty screening tools were compared with the geriatric assessment: the Fried Frailty Index, the Groningen Frailty Indicator, Geriatric8, the Identification of Seniors at Risk, the Hospital Safety Program, and the clinical judgment of the nephrologist. Outcome measures were sensitivity, specificity, positive predictive value, and negative predictive value.

Results

In total, 75% of patients were frail according to the geriatric assessment. Sensitivity of frailty screening tools ranged from 48% (Fried Frailty Index) to 88% (Geriatric8). The discriminating features of the clinical judgment were comparable with the other screening tools. The Identification of Seniors at Risk screening tool had the best discriminating abilities, with a sensitivity of 74%, a specificity of 80%, a positive predictive value of 91%, and a negative predictive value of 52%. The negative predictive value was poor for all tools, which means that almost one half of the patients screened as fit (nonfrail) had two or more geriatric impairments on the geriatric assessment.

Conclusions

All frailty screening tools are able to detect geriatric impairment in elderly patients eligible for dialysis. However, all applied screening tools, including the judgment of the nephrologist, lack the discriminating abilities to adequately rule out frailty compared with a geriatric assessment.