Practical Computing with Pattern Structures in FCART Environment

International audienceA new general and efficient architecture for working with pattern structures, an extension of FCA for dealing with "complex" descriptions, is introduced and implemented in a subsystem of Formal Concept Analysis Research Toolbox (FCART). The architecture is universal in terms of possible dataset structures and formats, techniques of pattern structure manipulation

Proceedings of the International Workshop "What can FCA do for Artificial Intelligence?" (FCA4AI 2014)

International audienceThis is the third edition of the FCA4AI workshop, whose first edition was organized at ECAI 2012 Conference (Montpellier, August 2012) and second edition was organized at IJCAI 2013 Conference (Beijing, August 2013, see http://www.fca4ai.hse.ru/). Formal Concept Analysis (FCA) is a mathematically well-founded theory aimed at data analysis and classification that can be used for many purposes, especially for Artificial Intelligence (AI) needs. The objective of the workshop is to investigate two main main issues: how can FCA support various AI activities (knowledge discovery, knowledge representation and reasoning, learning, data mining, NLP, information retrieval), and how can FCA be extended in order to help AI researchers to solve new and complex problems in their domain

International Workshop "What can FCA do for Artificial Intelligence?" (FCA4AI at IJCAI 2013, Beijing, China, August 4 2013)

International audienceThis second edition of the FCA4AI workshop (the first edition was associated to the ECAI 2012 Conference, see http://www.fca4ai.hse.ru/), shows again that there are many AI researchers interested in FCA. Formal Concept Analysis (FCA) is a mathematically well-founded theory aimed at data analysis and classification. FCA allows one to build a concept lattice and a system of dependencies (implications) which can be used for many AI needs, e.g. knowledge processing involving learning, knowledge discovery, knowledge representation and reasoning, ontology engineering, as well as information retrieval and text processing. Thus, there exist many natural links between FCA and AI. Accordingly, the focus in this workshop was on how can FCA support AI activities (knowledge processing) and how can FCA be extended in order to help AI researchers to solve new and complex problems in their domains

FCAIR 2012 Formal Concept Analysis Meets Information Retrieval Workshop co-located with the 35th European Conference on Information Retrieval (ECIR 2013) March 24, 2013, Moscow, Russia

International audienceFormal Concept Analysis (FCA) is a mathematically well-founded theory aimed at data analysis and classifiation. The area came into being in the early 1980s and has since then spawned over 10000 scientific publications and a variety of practically deployed tools. FCA allows one to build from a data table with objects in rows and attributes in columns a taxonomic data structure called concept lattice, which can be used for many purposes, especially for Knowledge Discovery and Information Retrieval. The Formal Concept Analysis Meets Information Retrieval (FCAIR) workshop collocated with the 35th European Conference on Information Retrieval (ECIR 2013) was intended, on the one hand, to attract researchers from FCA community to a broad discussion of FCA-based research on information retrieval, and, on the other hand, to promote ideas, models, and methods of FCA in the community of Information Retrieval

Ontology reuse and synthesis for modelling and simulation

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonThe proliferation and ubiquity of SemanticWeb technologies have transformed the way computer society reshapes its technology through knowledge integration, knowledge reuse and knowledge sharing. Ontology, one of the Semantic Web components, is a way to represent domain knowledge into a human-understandable and machine-readable format. Ontology in simulation has been seen as a conceptual model of a system in an explicit and unambiguous manner, where it can be applied to better capture the modeler’s perspective of the domain. Regarding an ontology for simulation modeling, by reusing ontologies, it helps to reduce time and effort in attaining the domain knowledge, and at the same time assist in domain understanding. For a semantically-richer simulation ontology, it is useful to engage with real data and existing ontologies. This research contributes a rigorous method that extracts domain knowledge, synthesizes processes performed within the domain, and builds a minimal and viable ontology for simulation modeling, knownas aMinimal Viable Simulation Ontology (MVSimO). The research method initially applies ontology selection techniques in Ontology Reuse Framework (ORF) to obtain suitable existing ontologies for reuse. ORF incorporates a module extraction technique during the domain conceptualization phase, where the modules will represent domain knowledge as sub-ontologies. Formal Concept Analysis is later applied to the real-world data to reveal the process details of the domain. Finally, the development of MVSimO is completed by the derivation of event semantic of the processes. The effectiveness of ontology selection and synthesizing methods, is reviewed by evaluating the selected ontology knowledge extracted, and the detailed ontological model of MVSimO. The evaluation of,MVSimO is performed to determine its agreement to the established simulation model of the domain. The evaluation results are encouraging, providing concrete outcomes of the new technique of ontology reuse and new development to the research area

Knee joint biomechanics after anterior cruciate ligament reconstruction

Anterior cruciate ligament (ACL) is an important stabilizer of the knee joint. After ACL rupture, the knee joint has difficulty maintaining its stability; thus the patient often has to receive an ACL-reconstructive surgery to regain the knee joint functions. Unfortunately, traditional transtibial surgical techniques could not fully restore the normal knee joint kinematics during daily activities. Moreover, a higher rate of osteoarthritis was found from the ACL-reconstructed knees compared to the knees without a history of ACL-injuries. The reason for the increased risk of knee osteoarthritis is still unclear, and the pathologies due to abnormal knee joint kinematics remain controversial. The dissertation was to delineate the knee joint motion and loading after ACL-reconstruction. Thirty patients who received ACL-reconstructive surgeries using the traditional transtibial technique and 14 using the recently developed anteromedial portal technique were recruited from the same center (OrthoCarolina). Twenty healthy subjects without history of knee injuries were recruited as the control group. Human motion data and ground reaction force data were collected during level walking and downstairs pivoting using an optical motion capture system. Three-dimensional (3D) knee joint motions were determined from redundant markers using an optimization approach. The 3D knee joint moments and forces were calculated from motion data, ground reaction data by using an inverse dynamics model of the lower extremity. A finite element model was created, and the distributions of stress/strain within articular cartilage under physiological loading were estimated. The results from two groups of patients using different reconstruction techniques were compared. In the transtibial group, excessive internal tibial rotation (2° on average during stance phase), varus rotation and anterior femur translation (swing phase) were observed in the ACL-reconstructed knees when compared to the control group during level walking. The 3D knee joint motion following ACL-reconstruction was found to be influenced by the leg dominance. The motion and load in the uninjured contralateral knee were also affected. During downstairs pivoting, the normal varus rotation and adduction moment were not fully restored by the transtibial technique. Overall, the anteromedial portal technique improved the postsurgical knee joint kinematics by reducing the offsets in the internal tibial rotation, varus rotation and anterior femur translation during level walking. It also improved the adduction moment during downstairs pivoting. At the same time, the anteromedial portal technique may cause a flexion/extension deficit during the stance phase of walking. Results of finite element analysis demonstrated higher pressures within the medial femoral cartilage during the stance phase of walking; it also demonstrated that there is an increased knee joint laxity after ACL-reconstruction. The anteromedial portal technique was overall better than the traditional transtibial technique in respect to postsurgical knee joint compressive loading and contact pressure. The study provides evidence of the possibility by using anatomical single-bundle ACL-reconstruction technique to fight the knee joint osteoarthritis after ligament injury

Satellite broadcasting system study

The study to develop a system model and computer program representative of broadcasting satellite systems employing community-type receiving terminals is reported. The program provides a user-oriented tool for evaluating performance/cost tradeoffs, synthesizing minimum cost systems for a given set of system requirements, and performing sensitivity analyses to identify critical parameters and technology. The performance/ costing philosophy and what is meant by a minimum cost system is shown graphically. Topics discussed include: main line control program, ground segment model, space segment model, cost models and launch vehicle selection. Several examples of minimum cost systems resulting from the computer program are presented. A listing of the computer program is also included

Development and Validation of a Kinematically-Driven Computational Model of the Patellofemoral Joint

The patellofemoral joint represents one of the most challenging musculoskeletal systems to understand and manage. Disruption in the normal tracking of the patellofemoral joint can lead to elevated stress and microtrauma to the articular cartilage, cascading to the development of osteoarthritis. To develop effective treatment therapies, relationships between altered patellar motion and subsequent changes in articular cartilage loading must be measured. Computational modeling provides joint-specific changes in contact mechanics, but current techniques are limited by force-based assumptions and lack validation. The objective of this work was to develop a subject-specific modeling framework driven by highly accurate knee joint kinematics as a tool to estimate knee joint contact stress in vivo. First, a repeatable knee joint testing system for simultaneous measurement of patellofemoral joint kinematics and joint contact pressures was established. Measurements of patellofemoral and tibiofemoral translations and rotations were highly repeatable with intraclass correlation coefficients greater than 0.98/0.90 and 0.80/0.97, respectively. Measurements of joint contact pressure were repeatable within 5.3% - 6.8%. Second, a unique patellofemoral modeling framework employing the discrete element method combined with accurate knee joint kinematics was developed using two cadaveric knee joint specimens. Model-generated stresses were validated using experimentally measured pressures. The model predicted the experimental data well, with percent error (%) differences in contact stress distribution being less than 13%, validating the model’s ability to predict the experimental changes in joint contact. Lastly, this validated model was implemented in a group of individuals with patellofemoral osteoarthritis (n=5) and a control group (n=6) during a downhill walking task. The model predicted unique patellofemoral joint stress patterns between the two groups such that individuals with patellofemoral osteoarthritis experienced greater (58%) lateral facet joint contact stress early within the loading phase of the gait cycle compared to the control group (38%). This dissertation has validated and implemented a novel modeling technique driven by highly accurate, subject-specific kinematics to estimate patellofemoral joint contact stress during a downhill walking task. Future use of these models can provide quantitative evidence of the effectiveness of current patellofemoral treatment solutions and allow for the development of improved rehabilitation strategies