Mobility assistance system for an electric wheelchair using annotated maps

An electric wheelchair is very useful for physically challenged or elderly people. A electric wheelchair can be equipped with a computer and sensors such as cameras and LIDARs to make it a robotic wheelchair. This opens the possibility to reduce the burden and increase the comfort of the users with use of robotics technology. In this paper, we begin with a dynamic shared control and propose to use a map with annotations to increase the user’s comfort while keeping safety. We provide a system with localization, which can relate the current position of the wheelchair to the annotations. Both quantitative evaluation and subjective survey demonstrate the effectiveness of the proposed method.     

An Infrastructure for Argumentative Agents

Multiagent systems are suitable for providing a framework that allows agents to perform collaborative processes in a social context. Furthermore, argumentation is a natural way of reaching agreements between several parties. However, it is difficult to find infrastructures of argumentation offering support for agent societies and their social context. Offering support for agent societies allows representation of more realistic environments to have argumentation dialogues. We propose an infrastructure to develop and execute argumentative agents in an open multiagent system. It offers tools to develop agents with argumentation capabilities. It also offers support for agent societies and their social context. The infrastructure is publicly available. Also, it has been implemented in an application scenario where argumentative agents try to reach an agreement about the best solution to solve a problem reported to the system.     

Case‐based curve behaviour prediction

Case‐based reasoning (CBR) is the area of artificial intelligence where problems are solved by adapting solutions that worked for similar problems from the past. This technique can be applied in different domains and with different problem representations. In this paper, a system curve base generator (CuBaGe) is presented. This framework is designed to be a domain‐independent prediction system for the analysis and prediction of curves and time‐series trends, based on the CBR technology. CuBaGe employs a novel curve representation method based on splines and a corresponding similarity function based on definite integrals. This combination of curve representation and similarity measure showed excellent results with sparse and non‐equidistant time series, which is demonstrated through a set of experiments. Copyright © 2008 John Wiley & Sons, Ltd.     

Worst‐case execution time analysis for a Java processor

In this paper, we propose a solution for a worst‐case execution time (WCET) analyzable Java system: a combination of a time‐predictable Java processor and a tool that performs WCET analysis at Java bytecode level. We present a Java processor, called JOP, designed for time‐predictable execution of real‐time tasks. The execution time of bytecodes, the instructions of the Java virtual machine, is known to cycle accuracy for JOP. Therefore, JOP simplifies the low‐level WCET analysis. A method cache, which fills whole Java methods into the cache, simplifies cache analysis. The WCET analysis tool is based on integer linear programming. The tool performs the low‐level analysis at the bytecode level and integrates the method cache analysis. An integrated data‐flow analysis performs receiver‐type analysis for dynamic method dispatches and loop‐bound analysis. Furthermore, a model checking approach to WCET analysis is presented where the method cache can be exactly simulated. The combination of the time‐predictable Java processor and the WCET analysis tool is evaluated with standard WCET benchmarks and three real‐time applications. The WCET friendly architecture of JOP and the integrated method cache analysis yield tight WCET bounds. Comparing the exact, but expensive, model checking‐based analysis of the method cache with the static approach demonstrates that the static approximation of the method cache is sufficiently tight for practical purposes. Copyright © 2010 John Wiley & Sons, Ltd.     

Image interpolation for virtual sports scenarios

View interpolation has been explored in the scientific community as a means to avoid the complexity of full 3D in the construction of photo-realistic interactive scenarios. EVENTS project attempts to apply state of the art view interpolation to the field of professional sports. The aim is to populate a wide scenario such as a stadium with a number of cameras and, via computer vision, to produce photo-realistic moving or static images from virtual viewpoints, i.e where there is no physical camera. EVENTS proposes an innovative view interpolation scheme based on the Joint View Triangulation algorithm developed by the project participants. Joint View Triangulation is combined within the EVENTS framework with new initiatives in the field of multiple view layered representation, automatic seed matching, image-based rendering, tracking occluding layers and constrained scene analysis. The computer vision software has been implemented on top of a novel high performance computing platform with the aim to achieve real-time interpolation.     

AGATHA: Using heuristic search to automate the construction of case law theories

In this paper we describe AGATHA, a program designed to automate the process of theory construction in case based domains. Given a seed case and a number of precedent cases, the program uses a set of argument moves to generate a search space for a dialogue between the parties to the dispute. Each move is associated with a set of theory constructors, and thus each point in the space can be associated with a theory intended to explain the seed case and the other cases in the domain. The space is large and so an heuristic search method is needed. This paper describes two methods based on A* and alpha/beta pruning and also a series of experiments designed to explore the appropriateness of different evaluation functions, the most useful precedents to use as seed cases and the quality of the resulting theories.     

基于卷积的时态CBR快速检索算法及应用

探讨了如何增强CBR对一种常见的时态信息,即时间序列数据的检索能力;分析了已有的基于傅里叶频谱分析的时间序列检索算法应用于CBR时遇到的问题,并根据时态CBR检索的需要,提出了一种新的基于循环卷积和傅里叶变换时间序列检索算法.理论分析和数值实验结果都证明,提出的算法在检索效率上有一定的优势.将采取这种检索方法的时态CBR应用于时间序列的预测问题中,取得了较好的预测效果且具有较高的预测效率.     

An association model based reasoning method for individualized service recommender

Recommender systems have been widely accepted across a broad range of application areas. Their key task is to estimate the user's need as accurately as possible. To do so, conventional recommender systems have focused on how to more accurately determine similar users or similar products. However, individuals often have unique preferences, or they do not always prefer to use the same service. Typically, an individual's association from his own experience will be preferable, that is more accurate, compared with common interests he may have with other users. However, recommendation methods based on association, versus common interests, have been very few. Hence, the purpose of this paper is to propose an association model based reasoning methodology that estimates users’ associative strength from self‐experiences based on association theories. In particular, we adopt the Rescorla–Wagner model, the Galton free association test, and Russell's circumflex model for mood positivity to estimate associative strength. We perform an experimental study with actual experience data to verify the hypotheses, which validates the association model based algorithm in finding the best service with a good elapsed time.     

Case‐based approach for supporting strategy decision making

The practice of strategy decision making proves that when the management board is strongly limited in its capacity to take rational actions, specifically in the context of great decision complexity and uncertainty, it is considered good practice to refer to experience through reasoning by analogy. In this paper, we would like to concentrate on supporting strategic decisions in small and medium enterprises (SMEs). The complexity of analogy‐based reasoning has its roots in an attempt to solve new problems based on past cases from a different domain, while we will focus on case‐based approach for a single domain. Additionally, we have chosen case‐based reasoning as a suitable decision‐making paradigm because it is corresponds to managers’ decision‐making behaviour. We present the STRATEGOS case‐based reasoning system for supporting strategic decision making by SMEs management boards and then the system evaluation by the dozens of chief executive officers (CEOs) from SMEs is presented. The results of the survey are promising and show the remarkable correspondence of the proposed solution with expectations and strategic behaviour of CEOs.     

Composing and scheduling service‐oriented applications in time‐triggered distributed real‐time Java environments

During the last decade, the number of distributed application domains with temporal requirements has significantly augmented, arising the necessity of exploring new concepts and paradigms that allow, on the one hand, the development of dynamic and flexible distributed applications and, on the other hand, the reusability of code. Service‐oriented paradigms have been successfully applied to distributed environments, increasing their flexibility and allowing the reusability of their components. Besides, distributed real‐time Java technologies have shown to be a good candidate to deploy real‐time distributed applications. This paper presents a model for service‐oriented applications on a time‐triggered distributed real‐time Java environment, focusing on the definition of the temporal model of an application and its schedulability, applying and evaluating this model in real‐time service‐oriented composition algorithms. Copyright © 2012 John Wiley & Sons, Ltd.     

Generic reflective feedback: An effective approach to developing clinical reasoning skills

Problem‐based learning can be an effective tool to develop clinical reasoning skills. However, it traditionally takes place in tutorial groups, giving students little flexibility in how and when they learn. This pilot study compared the effectiveness of generic reflective feedback (GRF) with tutorial‐based reflective feedback on the development of students' clinical reasoning skills. Case studies were placed in an interactive software package, with GRF for the nine patient cases (36 GRF forms in total). The GRF contained information about common mistakes and omissions made by students in previous years. By design, the GRF left some clinical questions unanswered in order to prompt student reflection, enhance the development of their clinical reasoning skills and give the 2010 students (n = 53) greater control over the way in which they engaged with the unit. Clinical reasoning skills development, assessed by responses to the 36 parts across the 9 cases and in the relevant section of the final exam, was compared with the 2009 tutorial cohort (n = 47 students). GRF enabled student progression through each of the nine online cases with minimal tutor intervention. The cohort receiving GRF performed as well as those students engaging in tutorials with individualized feedback. GRF was associated with a significant increase in student satisfaction and flexibility in how and when they learned. We conclude that GRF enabled online enhancement of a case‐based clinical reasoning unit. Further research on how GRF can optimize learning in different online settings is warranted.     

DRAMA MANAGEMENT AND PLAYER MODELING FOR INTERACTIVE FICTION GAMES

A growing research community is working toward employing drama management components in story‐based games. These components gently guide the story toward a narrative arc that improves the player's gaming experience. In this article we evaluate a novel drama management approach deployed in an interactive fiction game called Anchorhead. This approach uses player's feedback as the basis for guiding the personalization of the interaction. The results indicate that adding our Case‐based Drama manaGer (C‐DraGer) to the game guides the players through the interaction and provides a better overall player experience. Unlike previous approaches to drama management, this article focuses on exhibiting the success of our approach by evaluating results using human players in a real game implementation. Based on this work, we report several insights on drama management which were possible only due to an evaluation with real players.     

A hybrid approach for selecting service‐based real‐time composition algorithms in heterogeneous environments

Service‐based approach has been successfully applied to distributed environments, modelling them as pieces of functionality that exchange information by means of messages in order to achieve a common goal. The advantages of this approach can be also be applied to distributed real‐time systems, increasing their flexibility and allowing the creation of new brand applications from existing services in the system. If this is an online process, then time‐bounded composition algorithms are needed to not jeopardize the performance of the whole system. Different composition algorithms are studied and proposed, two of them optimal and another two based on heuristics. This paper presents an analytical solution that selects, depending on the structure of the application and on the load of the whole system, the most suitable composition algorithm to be executed in order to obtain a composed application in bounded time. Copyright © 2011 John Wiley & Sons, Ltd.     

基于实例的多推理机合作变型设计系统

产品变型设计的基本思想就是通过改进已有的系列产品或模块来适应新的设计需求.针对变型设计的基本特点,提出了以基于实例的推理为基础,综合运用规则推理和约束满足方法来完成产品的变型设计活动.结合所开发的“细纱机模块化变型设计系统”,从知识表达模式、推理流程等方面详细讨论了以基于实例的推理为核心方法的多推理机合作变型设计系统的实现.     

基于改进型模糊ARTMAP网络的CBR遥感图像分类系统研究

针对难以及时地获取充足而准确的遥感样本、缺乏积累和管理遥感样本的有效手段是制约遥感图像分类技术发展的瓶颈问题。构建了基于改进型模糊ARTMAP网络的CBR(case-based reasoning范例推理)遥感图像分类系统。系统将改进型模糊ARTMAP网络作为范例的知识提取器和图像分类器,运用CBR求解策略实现遥感样本知识的合理储备、优化组合和重复利用。分别应用本文所建系统、最大似然法、BP网络和改进型模糊ARTMAP网络对向海自然保护区TM遥感图像进行分类操作,实验结果表明,本文建立的系统与其他分类方法相比,能够更好地提高遥感样本数据的利用效率和遥感图像的分类精度,而且一定程度上解决了在样本有限的条件下如何高效利用已有数据进行遥感图像分类的问题。     

An adaptive clinical decision support system for serving the elderly with chronic diseases in healthcare industry

With the increasing ageing population worldwide, providing effective nursing care planning in nursing homes is important in meeting the expectations of elderly patients and in streamlining the healthcare information process, hence maintaining high‐quality services. Instead of the traditional manual nursing care planning formulation based on expert experience and subjective judgement, this paper describes an adaptive decision support system, namely, the cloud‐based nursing care planning system, to enable decision making in formulating nursing care strategies. By integrating cloud computing technology and the case‐based reasoning (CBR) technique, medical records and documents pertaining to the elderly can be captured in real time, whereas appropriate treatment plans based on past similar treatment records can be formulated. However, the current case adaptation processes in CBR rely on domain experts to modify retrieved cases, which may not satisfy the needs of the elderly. Therefore, text mining is integrated in the case adaptation process of CBR for extracting up‐to‐date medical information from the Internet so that its efficiency can be improved. By conducting a pilot study in a nursing home, it was shown that the time for formulating applicable treatment plans for elderly patients can be reduced, and the service satisfaction level can be enhanced.     

Occlusion Textures for Plausible Soft Shadows*

This paper presents a new approach to compute plausible soft shadows for complex dynamic scenes and rectangular light sources. We estimate the occlusion at each point of the scene using prefiltered occlusion textures, which dynamically approximate the scene geometry. The algorithm is fast and its performance independent of the light's size. Being image‐based, it is mostly independent of the scene complexity and type. No a priori information is needed, and there is no caster/receiver separation. This makes the method appealing and easy to use.     

SIMILARITY‐BASED RETRIEVAL WITH STRUCTURE‐SENSITIVE SPARSE BINARY DISTRIBUTED REPRESENTATIONS

We present an approach to similarity‐based retrieval from knowledge bases that takes into account both the structure and semantics of knowledge base fragments. Those fragments, or analogues, are represented as sparse binary vectors that allow a computationally efficient estimation of structural and semantic similarity by the vector dot product. We present the representation scheme and experimental results for the knowledge base that was previously used for testing of leading analogical retrieval models MAC/FAC and ARCS. The experiments show that the proposed single‐stage approach provides results compatible with or better than the results of two‐stage models MAC/FAC and ARCS in terms of recall and precision. We argue that the proposed representation scheme is useful for large‐scale knowledge bases and free‐structured database applications.     

Volumetric Billboards

We introduce an image‐based representation, called volumetric billboards, allowing for the real‐time rendering of semi‐transparent and visually complex objects arbitrarily distributed in a 3D scene. Our representation offers full parallax effect from any viewing direction and improved anti‐aliasing of distant objects. It correctly handles transparency between multiple and possibly overlapping objects without requiring any primitive sorting. Furthermore, volumetric billboards can be easily integrated into common rasterization‐based renderers, which allows for their concurrent use with polygonal models and standard rendering techniques such as shadow‐mapping. The representation is based on volumetric images of the objects and on a dedicated real‐time volume rendering algorithm that takes advantage of the GPU geometry shader. Our examples demonstrate the applicability of the method in many cases including levels‐of‐detail representation for multiple intersecting complex objects, volumetric textures, animated objects and construction of high‐resolution objects by assembling instances of low‐resolution volumetric billboards.