Distributed Formal Concept Analysis Algorithms Based on an Iterative MapReduce Framework

While many existing formal concept analysis algorithms are efficient, they are typically unsuitable for distributed implementation. Taking the MapReduce (MR) framework as our inspiration we introduce a distributed approach for performing formal concept mining. Our method has its novelty in that we use a light-weight MapReduce runtime called Twister which is better suited to iterative algorithms than recent distributed approaches. First, we describe the theoretical foundations underpinning our distributed formal concept analysis approach. Second, we provide a representative exemplar of how a classic centralized algorithm can be implemented in a distributed fashion using our methodology: we modify Ganter's classic algorithm by introducing a family of MR* algorithms, namely MRGanter and MRGanter+ where the prefix denotes the algorithm's lineage. To evaluate the factors that impact distributed algorithm performance, we compare our MR* algorithms with the state-of-the-art. Experiments conducted on real datasets demonstrate that MRGanter+ is efficient, scalable and an appealing algorithm for distributed problems.Comment: 17 pages, ICFCA 201, Formal Concept Analysis 201

Isolated patellofemoral osteoarthritis: A systematic review of treatment options using the GRADE approach

Background and purpose The optimal treatment for isolated patellofemoral osteoarthritis is unclear at present. We systematically reviewed the highest level of available evidence on the nonoperative and operative treatment of isolated patellofemoral osteoarthritis to develop an evidenced-based discussion of treatment options

Formal Concept Analysis via Atomic Priming

Formal Concept Analysis (FCA) looks to decompose a matrix of objects-attributes into a set of sparse matrices capturing the underlying structure of a formal context. We propose a Rank Reduction (RR) method to prime approximate FCAs, namely RRFCA. While many existing FCA algorithms are complete, lectic ordering of the lattice may not minimize search/decomposition time. Initially, RRFCA decompositions are not unique or complete; however, a set of good closures with high support is learned quickly, and then, made complete. RRFCA has its novelty in that we propose a new multiplicative two-stage method. First, we describe the theoretical foundations underpinning our RR approach. Second, we provide a representative exemplar, showing how RRFCA can be implemented. Further experiments demonstrate that RRFCA methods are efficient, scalable and yield time-savings. We demonstrate the resulting methods lend themselves to parallelization

Results of self-centering patellofemoral prosthesis: A retrospective study of 57 implants

PURPOSE OF THE STUDY: The aim of this retrospective analysis was to report results obtained with a self-centering patellofemoral prosthesis. We wanted to determine whether self-centering still has indications for the treatment of patellofemoral osteoarthritis. MATERIAL AND METHODS: This was a continuous series of 57 knees operated on since 1986 in the same center for implantation of a self-centering patellofemoral prosthesis (Medinov then Depuy). Eight patients died and four were lost to follow-up. Two knees were excluded from the analysis after revision with a PFP. We report here the outcome of 43 prostheses at mean follow-up of six years two months (range 78 months to 15 years). The IKS score (200 points) and the ADL scale (in %) were recorded. The position of the prosthesis was assessed on plain X-rays. Mean age at implantation was 67.2 years. The main reasons for surgery were osteoarthritis secondary to dysplasia (60%) and primary disease (31.1%). RESULTS: At last follow-up, the IKS score was 157.2 points (range 76-195). The mean ADL score was 74.1/100 (48.8-96.3). The IKS evaluation showed good outcome in 66.7% of knees. The ADL scale gave a less satisfactory outcome: 57.7% good outcome for this scale which takes into account all knee functions for activities of daily life. Outcome was better among patients with trochlear dysplasia. Eleven patients (24.4%) had had revision surgery for total knee arthroplasty. Preoperatively, the trochlear angle was smaller in revision cases (p=0.023). In these patients, the first prosthesis was more anterior (p=0.004) with a greater horizontal axis (p=0.015). DISCUSSION: Our outcomes were less satisfactory than the average results in the literature. It must be noted however, that the concept of a good outcome depends on the scale used for assessment. We found in our series a 10% difference between the ADL scale and the IKS score. Independently of the assessment scale used, outcome was better in knees with osteoarthritis secondary to dysplasia. An analysis of the X-ray findings disclosed technical errors leading to failure. The outcome of patellofemoral prosthesis depends essentially on two factors: technical precision and patient selection. CONCLUSION: In light of these findings, we have come to limit still further the rare indications for patellofemoral prostheses. The typical indication is isolated advanced patellofemoral osteoarthritis secondary to patellofemoral dysplasia unresponsive to medical treatment in patients aged 50-70 years. Revision with a total knee arthroplasty required changing the patellar insert if worn. We have not had any particular problem with revision total knee arthroplasty after patellofemoral prosthesis