Managing Conversation Uncertainty in TutorJ

Uncertainty in natural language dialogue is often treated through stochastic models. Some of the authors already presented TutorJ mat is an Intelligent Tutoring System, whose interaction with the user is very intensive, and makes use of both dialogic and graphical modality. When managing the interaction, the system needs to cope with uncertainty due to the understanding of the user's needs and wishes. In this paper we present the extended version of TutorJ, focusing on the new features added to its chatbot module. These features allow to merge deterministic and probabilistic reasoning in dialogue management, and in writing the rules of the system's procedural memory

Improving Assessment of Students through Semantic Space Construction

Assessment is one of the hardest tasks an Intel- ligent Tutoring System has to perform. It involves different and sometimes uncorrelated sub-tasks: building a student model to define her needs, defining tools and procedures to perform tests, understanding students’ replies to system prompts, defining suitable procedures to evaluate the correctness of students’ replies, and strategies to improve students’ abilities after the assessment session. In this work we present an improvement of our system, TutorJ, with particular attention to the assessment phase. Many tutoring systems offer only a limited set of assessment options like multiple-choice questions, fill-in-the-blanks tests or other types of predefined replies obtained through graphical widgets (radio-buttons, text-areas). This limited set of solutions makes interaction poor and unable to satisfy the users’ needs. Our interest is to enrich interaction with dialog in natural language. In this respect, the assessment problem is strictly connected to natural language understanding. The preliminary step is indeed to understand questions and replies of the student. We have reviewed the system design in the framework of a cognitive architecture with the aim to reach a double result: the reduction of the effort for the construction of the knowledge base and the improvement of the system capabilities in the assessment process. To this aim a new common semantic space has been defined and implemented. The entire architecture is oriented to intuitive and natural interaction

A Map-Based Visualization Tool To Support Tutors In E-Learning 2.0

Web 2.0 regards essentially the social issues about the new usage of web applications, but participative web and user generated contents induce a new way to think about the design of the web applications themselves. This is particularly true in the field educational systems that are all web based applications. Many researchers are now devoted to study what is called e-learning 2.0 both as regards the technological issues in the field of computer science, and in relation to the impact of the web 2.0 social and psychological issues on the education process itself. One of the most crucial topics in e-learning 2.0 is the way to provide support to the teacher/tutor to avoid cog- nitive overload when he/she is monitoring the evolution group dynamics inside the class, and decides the proper strategies to ensure the pursuit of the learning goals. Map visualization is a good way to present information without cognitive overload. We present a map-based tool in support of the tutor that is an extension of our ITS called TutorJ. The tool allows a human tutor to have multiple map visualizations about the domain of the course, the social (forum-based) interaction between the students, and the amount of topics faced by each student. The paper reports a detailed description of the architecture of the tool, and a discussion about its relevance in the field of e- learning 2.0

A meta-cognitive architecture for planning in uncertain environments

Abstract The behavior of an artificial agent performing in a natural environment is influenced by many different pressures and needs coming from both external world and internal factors, which sometimes drive the agent to reach conflicting goals. At the same time, the interaction between an artificial agent and the environment is deeply affected by uncertainty due to the imprecision in the description of the world, and the unpredictability of the effects of the agent's actions. Such an agent needs meta-cognition in terms of both self-awareness and control. Self-awareness is related to the internal conditions that may possibly influence the completion of the task, while control is oriented to performing actions that maintain the internal model of the world and the perceptions aligned. In this work, a general meta-cognitive architecture is presented, which is aimed at overcoming these problems. The proposed architecture describes an artificial agent, which is capable to combine cognition and meta-cognition to solve problems in an uncertain world, while reconciling opposing requirements and goals. While executing a plan, such an agent reflects upon its actions and how they can be affected by its internal conditions, and starts a new goal setting process to cope with unforeseen changes. The work defines the concept of "believability" as a generic uncertain quantity, the operators to manage believability, and provides the reader with the u-MDP that is a novel MDP able to deal with uncertain quantities expressed as possibility, probability, and fuzziness. A couple u-MDPs are used to implement the agent's cognitive and meta-cognitive module. The last one is used to perceive both the physical resources of the agent's embodiment and the actions performed by the cognitive module in order to issue goal setting and re-planning actions

GAIML: A New Language for Verbal and Graphical Interaction in Chatbots

Natural and intuitive interaction between users and complex systems is a crucial research topic in human-computer interaction. A major direction is the definition and implementation of systems with natural language understanding capabilities. The interaction in natural language is often performed by means of systems called chatbots. A chatbot is a conversational agent with a proper knowledge base able to interact with users. Chatbots appearance can be very sophisticated with 3D avatars and speech processing modules. However the interaction between the system and the user is only performed through textual areas for inputs and replies. An interaction able to add to natural language also graphical widgets could be more effective. On the other side, a graphical interaction involving also the natural language can increase the comfort of the user instead of using only graphical widgets. In many applications multi-modal communication must be preferred when the user and the system have a tight and complex interaction. Typical examples are cultural heritages applications (intelligent museum guides, picture browsing) or systems providing the user with integrated information taken from different and heterogenous sources as in the case of the iGoogle™ interface. We propose to mix the two modalities (verbal and graphical) to build systems with a reconfigurable interface, which is able to change with respect to the particular application context. The result of this proposal is the Graphical Artificial Intelligence Markup Language (GAIML) an extension of AIML allowing merging both interaction modalities. In this context a suitable chatbot system called Graphbot is presented to support this language. With this language is possible to define personalized interface patterns that are the most suitable ones in relation to the data types exchanged between the user and the system according to the context of the dialogue

Automatic generation of user interfaces using the set description language

We present a paradigm to generate automatically graphical user interfaces from a formal description of the data model following the well-known model-view-control paradigm. This paradigm provide complete separation between data model and interface description, setting the programmer free from the low-level aspects of programming interfaces, letting him take care of higher level aspects. The interface along with the data model is described by means of a formal language, the Set Description Language. We also describe the infrastructure based on this paradigm we implemented to generate graphical user interfaces for generic applications. Moreover, it can adapt the user interface of a program to the needs derived from the type of data managed by the user from time to time

Breast dynamic contrast-enhanced-magnetic resonance imaging and radiomics: State of art

Breast cancer represents the most common malignancy in women, being one of the most frequent cause of cancer-related mortality. Ultrasound, mammography, and magnetic resonance imaging (MRI) play a pivotal role in the diagnosis of breast lesions, with different levels of accuracy. Particularly, dynamic contrast-enhanced MRI has shown high diagnostic value in detecting multifocal, multicentric, or contralateral breast cancers. Radiomics is emerging as a promising tool for quantitative tumor evaluation, allowing the extraction of additional quantitative data from radiological imaging acquired with different modalities. Radiomics analysis may provide novel information through the quantification of lesions heterogeneity, that may be relevant in clinical practice for the characterization of breast lesions, prediction of tumor response to systemic therapies and evaluation of prognosis in patients with breast cancers. Several published studies have explored the value of radiomics with good-to-excellent diagnostic and prognostic performances for the evaluation of breast lesions. Particularly, the integrations of radiomics data with other clinical and histopathological parameters have demonstrated to improve the prediction of tumor aggressiveness with high accuracy and provided precise models that will help to guide clinical decisions and patients management. The purpose of this article in to describe the current application of radiomics in breast dynamic contrast-enhanced MRI

New microvascular ultrasound techniques: abdominal applications

Microvascular ultrasound (MVUS) is a new ultrasound technique that allows the detection of slow-velocity flow, providing the visualization of the blood flow in small vessels without the need of intravenous contrast agent administration. This technology has been integrated in the most recent ultrasound equipment and applied for the assessment of vascularization. Compared to conventional color Doppler and power Doppler imaging, MVUS provides higher capability to detect intralesional flow. A growing number of studies explored the potential applications in hepatobiliary, genitourinary, and vascular pathologies. Different flow patterns can be observed in hepatic and renal focal lesions providing information on tumor vascularity and improving the differential diagnosis. This article aims to provide a detailed review on the current evidences and applications of MVUS in abdominal imaging

Advances in liver US, CT, and MRI: moving toward the future

Over the past two decades, the epidemiology of chronic liver disease has changed with an increase in the prevalence of nonalcoholic fatty liver disease in parallel to the advent of curative treatments for hepatitis C. Recent developments provided new tools for diagnosis and monitoring of liver diseases based on ultrasound (US), computed tomography (CT), and magnetic resonance imaging (MRI), as applied for assessing steatosis, fibrosis, and focal lesions. This narrative review aims to discuss the emerging approaches for qualitative and quantitative liver imaging, focusing on those expected to become adopted in clinical practice in the next 5 to 10 years. While radiomics is an emerging tool for many of these applications, dedicated techniques have been investigated for US (controlled attenuation parameter, backscatter coefficient, elastography methods such as point shear wave elastography [pSWE] and transient elastography [TE], novel Doppler techniques, and three-dimensional contrast-enhanced ultrasound [3D-CEUS]), CT (dual-energy, spectral photon counting, extracellular volume fraction, perfusion, and surface nodularity), and MRI (proton density fat fraction [PDFF], elastography [MRE], contrast enhancement index, relative enhancement, T1 mapping on the hepatobiliary phase, perfusion). Concurrently, the advent of abbreviated MRI protocols will help fulfill an increasing number of examination requests in an era of healthcare resource constraints