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Ontologies for Agents : Theory and Experiences
On the other hand, ontologies have established themselves as a powerful tool to enable kno- edge sharing, and a growing number of applications have bene?ted from the use of ontologies as a means to achieve semantic interoperability among heterogeneous, distributed systems. In principle ontologies and agents are a match made in heaven, that has failed to happen. What makes a simple piece of software an agent is its ability to communicate in a ”social” environment, to make autonomous decisions, and to be proactive on behalf of its user. Communication ultimately depends on und- standing the goals, preferences, and constraints posed by the user. Autonomy is theabilitytoperformataskwithlittleornouserintervention,whileproactiveness involves acting autonomously with no need for user prompting. Communication, but also autonomy and proactiveness, depend on knowledge. The ability to c- municate depends on understanding the syntax (terms and structure) and the semantics of a language. Ontologies provide the terms used to describe a domain and the semantics associated with them. In addition, ontologies are often comp- mented by some logical rules that constrain the meaning assigned to the terms. These constraints are represented by inference rules that can be used by agents to perform the reasoning on which autonomy and proactiveness are based.
Metalearning : Applications to Automated Machine Learning and Data Mining
This book as one of the fastest-growing areas of research in machine learning, metalearning studies principled methods to obtain efficient models and solutions by adapting machine learning and data mining processes. This adaptation usually exploits information from past experience on other tasks and the adaptive processes can involve machine learning approaches. As a related area to metalearning and a hot topic currently, automated machine learning (AutoML) is concerned with automating the machine learning processes. Metalearning and AutoML can help AI learn to control the application of different learning methods and acquire new solutions faster without unnecessary interventions from the user.
Medical Imaging and Augmented Reality ; 4th International Workshop Tokyo, Japan, August 1-2, 2008 Proceedings
Constitutes the refereed proceedings of the 4th International Workshop on Medical Imaging and Augmented Reality, MIAR 2008, held in Tokyo, Japan, in August 2008.The 44 revised full papers presented together with 3 invited papers were carefully reviewed and selected from 90 submissions. The papers are organized in topical sections on surgical planning and simulation, medical image computing, image analysis, shape modeling and morphometry, image-guided robotics, image-guided intervention, interventional imaging, image registration, augmented reality, and image segmentation.
Medical Imaging and Augmented Reality ; 3rd International Workshop, Shanghai, China, August 17-18, 2006, Proceedings
The Third International Workshop on Medical Imaging and Augmented Reality, MIAR 2006, was held in Shanghai, China at the Regal International East Asia Hotel during August 17-18, 2006. The goal of MIAR 2006 was to bring together researchers in medical image computing and intervention to present the state-of-the-art devel- ments in this ever-growing research area.
Medical Image Computing and Computer-Assisted Intervention - MICCAI 2008 ; 11th International Conference, New York, NY, USA, September 6-10, 2008, Proceedings, Part II
The program committee carefully selected 258 revised papers from numerous submissions for presentation in two volumes, based on rigorous peer reviews. The first volume includes 127 papers related to medical image computing, segmentation, shape and statistics analysis, modeling, motion tracking and compensation, as well as registration. The second volume contains 131 contributions related to robotics and interventions, statistical analysis, segmentation, intervention, modeling, and registration.
Medical Image Computing and Computer-Assisted Intervention - MICCAI 2008 ; 11th International Conference, New York, NY, USA, September 6-10, 2008, Proceedings, Part I
The program committee carefully selected 258 revised papers from numerous submissions for presentation in two volumes, based on rigorous peer reviews. The first volume includes 127 papers related to medical image computing, segmentation, shape and statistics analysis, modeling, motion tracking and compensation, as well as registration. The second volume contains 131 contributions related to robotics and interventions, statistical analysis, segmentation, intervention, modeling, and registration.
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007; 10th International Conference, Brisbane, Australia, October 29 - November 2, 2007, Proceedings, Part II
The 10th International Conference on Medical Imaging and Computer Assisted Intervention, MICCAI2007, washeldattheBrisbaneConventionandExhibition Centre, South Bank, Brisbane, Australia from 29th October to 2nd November 2007. MICCAI has become a premier international conference in this domain, with in-depth papers on the multidisciplinary ?elds of biomedical image computing, computer assisted intervention and medical robotics.
Medical image computing and computer-assisted intervention – MICCAI 2007 ; 10th International Conference, Brisbane, Australia, October 29 - November 2, 2007, Proceedings, Part I
This title is part of a two-volume set that constitute the refereed proceedings of the 10th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2007.
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006 ; Vol. 4191; 9th International Conference, Copenhagen, Denmark, October 1-6, 2006, Proceedings, Part II
T MICCAI papers are of high standard and have a long lifetime. In this v- ume as well as in the latest journal issues of Medical Image Analysis and IEEE Transactions on Medical Imaging papers cite previous MICCAIs including the ?rst MICCAI conference in Cambridge, Massachusetts, 1998. It is obvious that the community requires the MICCAI papers as archive material. Therefore the proceedingsofMICCAIarefrom2005andhenceforthbeing indexedbyMedline. Acarefulreviewandselectionprocesswasexecutedinordertosecurethebest possible program for the MICCAI 2006 conference. We received 578 scienti?c papers from which 39 papers were selected for the oral program and 193 papers for the poster program.
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006 ; Vol. 4190 ; 9th International Conference, Copenhagen, Denmark, October 1-6, 2006, Proceedings, Part I
MICCAI papers are of high standard and have a long lifetime. In this v- ume as well as in the latest journal issues of Medical Image Analysis and IEEE Transactions on Medical Imaging papers cite previous MICCAIs including the ?rst MICCAI conference in Cambridge, Massachusetts, 1998. It is obvious that the community requires the MICCAI papers as archive material. Therefore the proceedingsofMICCAIarefrom2005andhenceforthbeing indexedbyMedline. Acarefulreviewandselectionprocesswasexecutedinordertosecurethebest possible program for the MICCAI 2006 conference. We received 578 scienti?c papers from which 39 papers were selected for the oral program and 193 papers for the poster program.
Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2005 ; 8th International Conference, Palm Springs, CA, USA, October 26-29, 2005, Proceedings, Part II
Robotics, Image-Guided Surgery and Interventions -- Image Registration II -- Medical Image Computing -- Atlases -- Shape I -- Structural and Functional Brain Analysis -- Model-Based Image Analysis -- Image-Guided Intervention: Simulation, Modeling and Display -- Simulation and Modeling II -- Medical Image Computing -- Shape II -- Image Segmentation and Analysis II -- Image Registration III --
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2005 ; 8th International Conference, Palm Springs, CA, USA, October 26-29, 2005, Proceedings, Part I
This paper presents a method for classification of medical images, using machine learning and deformation-based morphometry. A morphological representation of the anatomy of interest is first obtained using highdimensional template warping, from which regions that display strong correlations between morphological measurements and the classification (clinical) variable are extracted using a watershed segmentation, taking into account the regional smoothness of the correlation map which is estimated by a crossvalidation strategy in order to achieve robustness to outliers. A Support Vector Machine-Recursive Feature Elimination (SVM-RFE) technique is then used to rank computed features from the extracted regions, according to their effect on the leave-one-out error bound. Finally, SVM classification is applied using the best set of features, and it is tested using leave-one-out. The results from a group of 61 brain images of female normal controls and schizophrenia patients demonstrate not only high classification accuracy (91.8%) and steep ROC curves, but also exceptional stability with respect to the number of selected features and the SVM kernel size
IOT control and surveillance system
An automated system is a combination of both software and hardware which is designed and programmed to work automatically without the need of any human operator to provide inputs and instructions for each operation. The Internet of Things (IoT) is a network of connected things. These ‘things’ (devices) communicate with each other using machine to machine communication (M2M). Information is traversed between devices so that processes can be automated, without the need for human intervention. By reducing the number of people involved in a business process, several advantages arise, including improved accuracy and up-time. We will build an IoT automated system to control access of humans and vehicles to a warehouse based on biometrics and image recognition techniques.
Introduction to development engineering
Introduces the emerging field of development engineering and its constituent theories, methods, and applications. It is both an instructional text for students and a resource for researchers and practitioners involved in the design and scaling of technologies for low-resource communities. The scope is broad, ranging from the development of mobile applications for low-literacy users to hardware and software solutions for providing electricity and water in remote environments. It is also highly interdisciplinary, drawing on methods and theories from the social sciences as well as engineering and the natural sciences.
Intelligent tutoring systems ; 9th International Conference, ITS 2008, Montreal, Canada, June 23-27, 2008 Proceedings
This book constitutes the refereed proceedings of the 9th International Conference on Intelligent Tutoring Systems, ITS 2008, held in Montreal, Canada, in June 2008.The 63 revised full papers and 61 poster papers presented together with abstracts of 5 keynote talks were carefully reviewed and selected from 207 submissions. The papers are organized in topical sections on emotion and affect, tutor evaluation, student modeling, machine learning, authoring tools , tutor feedback and intervention, data mining, e-learning and Web-based ITS, natural language techniques and dialogue, narrative tutors and games, semantic Web and ontology, cognitive models, and collaboration.
Exploring Resilience : A Scientific Journey from Practice to Theory
Resilience has become an important topic on the safety research agenda and in organizational practice. Most empirical work on resilience has been descriptive, identifying characteristics of work and organizing activity which allow organizations to cope with unexpected situations. Fewer studies have developed testable models and theories that can be used to support interventions aiming to increase resilience and improve safety. In addition, the absent integration of different system levels from individuals, teams, organizations, regulatory bodies, and policy level in theory and practice imply that mechanisms through which resilience is linked across complex systems are not yet well understood. Scientific efforts have been made to develop constructs and models that present relationships; however, these cannot be characterized as sufficient for theory building. There is a need for taking a broader look at resilience practices as a foundation for developing a theoretical framework that can help improve safety in complex systems.
Engineering self-organising systems ; Vol. 3464 : Methodologies and applications
Self-organisation, self-regulation, self-repair, and self-maintenance are promising conceptual approaches to deal with the ever increasing complexity of distributed interacting software and information handling systems. Self-organising applications are able to dynamically change their functionality and structure without direct user intervention to respond to changes in requirements and the environment. This book comprises revised and extended papers presented at the International Workshop on Engineering Self-Organising Applications, ESOA 2004, held in New York, NY, USA in July 2004 at AAMAS as well as invited papers from leading researchers. The papers are organized in topical sections on state of the art, synthesis and design methods, self-assembly and robots, stigmergy and related topics, and industrial applications.
Diabetes genetic finder & predictor = أداة البحث والتنبؤ الجيني لمرض السكري
The diabetes genetic finder & predictor app is a comprehensive, user-friendly solution that revolutionizes diabetes care. This powerful app integrates a wide array of features designed to empower diabetes patients and enhance their overall well-being. A standout feature of the app is its ability to predict the risk of hereditary diabetes diseases, offering users early detection and intervention opportunities. It also predicts general diabetes risk, diabetic foot complications, and retinopathy. Users can monitor their blood sugar levels, heart rate, and oxygenation either manually or through smart watch integration. Additionally, users can enter their diabetes type and HbA1c levels.The app's medication management feature simplifies the complex task of tracking and organizing medications, providing timely reminders to ensure adherence to treatment plans. Users can scan QR codes on products to check their sugar content and suitability, schedule their medications, generate reports for specific periods, and access a comprehensive list of frequently asked questions about diabetes..
Machine learning in healthcare : Fundamentals and recent applications
Discusses how to build various ML algorithms and how they can be applied to improve healthcare systems. Healthcare applications of AI are innumerable: medical data analysis, early detection and diagnosis of disease, providing objective-based evidence to reduce human errors, curtailing inter- and intra-observer errors, risk identification and interventions for healthcare management, real-time health monitoring, assisting clinicians and patients for selecting appropriate medications, and evaluating drug responses. Extensive demonstrations and discussion on the various principles of machine learning and its application in healthcare is provided, along with solved examples and exercises.
Machine learning and big data : Concepts, algorithms, tools and applications
Showcase novel use-cases and applications, present empirical research results from user-centered qualitative and quantitative experiments of these new applications, and facilitate a discussion forum to explore the latest trends in big data and machine learning by providing algorithms which can be trained to perform interdisciplinary techniques such as statistics, linear algebra, and optimization and also create automated systems that can sift through large volumes of data at high speed to make predictions or decisions without human intervention
