A novel Big Data analytics and intelligent technique to predict driver's intent

Modern age offers a great potential for automatically predicting the driver's intent through the increasing miniaturization of computing technologies, rapid advancements in communication technologies and continuous connectivity of heterogeneous smart objects. Inside the cabin and engine of modern cars, dedicated computer systems need to possess the ability to exploit the wealth of information generated by heterogeneous data sources with different contextual and conceptual representations. Processing and utilizing this diverse and voluminous data, involves many challenges concerning the design of the computational technique used to perform this task. In this paper, we investigate the various data sources available in the car and the surrounding environment, which can be utilized as inputs in order to predict driver's intent and behavior. As part of investigating these potential data sources, we conducted experiments on e-calendars for a large number of employees, and have reviewed a number of available geo referencing systems. Through the results of a statistical analysis and by computing location recognition accuracy results, we explored in detail the potential utilization of calendar location data to detect the driver's intentions. In order to exploit the numerous diverse data inputs available in modern vehicles, we investigate the suitability of different Computational Intelligence (CI) techniques, and propose a novel fuzzy computational modelling methodology. Finally, we outline the impact of applying advanced CI and Big Data analytics techniques in modern vehicles on the driver and society in general, and discuss ethical and legal issues arising from the deployment of intelligent self-learning cars

Towards responsive Sensitive Artificial Listeners

This paper describes work in the recently started project SEMAINE, which aims to build a set of Sensitive Artificial Listeners – conversational agents designed to sustain an interaction with a human user despite limited verbal skills, through robust recognition and generation of non-verbal behaviour in real-time, both when the agent is speaking and listening. We report on data collection and on the design of a system architecture in view of real-time responsiveness

An Innovative, Multidisciplinary Educational Program in Interactive Information Storage and Retrieval

There exists a large number of large-scale bibliographic Information Storage and Retrieval Systems containing large amounts of valuable data of interest in a wide variety of research applications. These systems are not used to capacity because the end users, i.e., the researchers, have not been trained in the techniques of accessing such systems. This thesis describes the development of a transportable, university-level course in methods of querying on-line interactive Information Storage and Retrieval systems as a solution to this problem. This course was designed to instruct upper division science and engineering students to enable these end users to directly access such systems. The course is designed to be taught by instructors who are not specialists in either computer science or research skills. It is independent of any particular IS and R system or computer hardware. The project is sponsored by NASA and conducted by the University of Southwestern Louisiana and Southern University

Artificial Intelligence-Enabled Intelligent Assistant for Personalized and Adaptive Learning in Higher Education

This paper presents a novel framework, Artificial Intelligence-Enabled Intelligent Assistant (AIIA), for personalized and adaptive learning in higher education. The AIIA system leverages advanced AI and Natural Language Processing (NLP) techniques to create an interactive and engaging learning platform. This platform is engineered to reduce cognitive load on learners by providing easy access to information, facilitating knowledge assessment, and delivering personalized learning support tailored to individual needs and learning styles. The AIIA's capabilities include understanding and responding to student inquiries, generating quizzes and flashcards, and offering personalized learning pathways. The research findings have the potential to significantly impact the design, implementation, and evaluation of AI-enabled Virtual Teaching Assistants (VTAs) in higher education, informing the development of innovative educational tools that can enhance student learning outcomes, engagement, and satisfaction. The paper presents the methodology, system architecture, intelligent services, and integration with Learning Management Systems (LMSs) while discussing the challenges, limitations, and future directions for the development of AI-enabled intelligent assistants in education.Comment: 29 pages, 10 figures, 9659 word

Visualization of database structures for information retrieval

This paper describes the Book House system, which is designed to support children's information retrieval in libraries as part of their education. It is a shareware program available on CD‐ROM or floppy disks, and comprises functionality for database searching as well as for classifying and storing book information in the database. The system concept is based on an understanding of children's domain structures and their capabilities for categorization of information needs in connection with their activities in schools, in school libraries or in public libraries. These structures are visualized in the interface by using metaphors and multimedia technology. Through the use of text, images and animation, the Book House encourages children ‐ even at a very early age ‐ to learn by doing in an enjoyable way, which plays on their previous experiences with computer games. Both words and pictures can be used for searching; this makes the system suitable for all age groups. Even children who have not yet learned to read properly can, by selecting pictures, search for and find those books they would like to have read aloud. Thus, at the very beginning of their school life, they can learn to search for books on their own. For the library community, such a system will provide an extended service which will increase the number of children's own searches and also improve the relevance, quality and utilization of the book collections in the libraries. A market research report on the need for an annual indexing service for books in the Book House format is in preparation by the Danish Library Centre A/S

Factors shaping the evolution of electronic documentation systems

The main goal is to prepare the space station technical and managerial structure for likely changes in the creation, capture, transfer, and utilization of knowledge. By anticipating advances, the design of Space Station Project (SSP) information systems can be tailored to facilitate a progression of increasingly sophisticated strategies as the space station evolves. Future generations of advanced information systems will use increases in power to deliver environmentally meaningful, contextually targeted, interconnected data (knowledge). The concept of a Knowledge Base Management System is emerging when the problem is focused on how information systems can perform such a conversion of raw data. Such a system would include traditional management functions for large space databases. Added artificial intelligence features might encompass co-existing knowledge representation schemes; effective control structures for deductive, plausible, and inductive reasoning; means for knowledge acquisition, refinement, and validation; explanation facilities; and dynamic human intervention. The major areas covered include: alternative knowledge representation approaches; advanced user interface capabilities; computer-supported cooperative work; the evolution of information system hardware; standardization, compatibility, and connectivity; and organizational impacts of information intensive environments

Milestones for Teaching the Spreadsheet Program

There are different manners of teaching a spreadsheet program. In any case, it is intended that the teacher settles the objectives of the course and adapts them to the particular audience he/she has to deal with. This paper aims at providing any teacher whatever his/her specific objectives and his/her audience with elements to help him/her building a course. It focuses mainly on two important issues: 1 - select in all that may be said about such complex tools, what is prior to know and to teach, i.e. what leads to autonomy in using but also to autonomy in learning (because everything cannot be taught) and 2 - show how concepts are closely related to good formatting considerations. A method based on the "invariants of information processing" is outlined, partially illustrated and an implementation is described throughout a course designed for students preparing a master in Education Sciences.Comment: 11 Page