Relationship based Entity Recommendation System

With the increase in usage of the internet as a place to search for information, the importance of the level of relevance of the results returned by search engines have increased by many folds in recent years. In this paper, we propose techniques to improve the relevance of results shown by a search engine, by using the kinds of relationships between entities a user is interested in. We propose a technique that uses relationships between entities to recommend related entities from a knowledge base which is a collection of entities and the relationships with which they are connected to other entities. These relationships depict more real world relationships between entities, rather than just simple “is-a” or “has-a” relationships. The system keeps track of relationships on which user is clicking and uses this click count as a preference indicator to recommend future entities. This approach is very useful in modern day semantic web searches for recommending entities of user’s interests

Closing the window for compressed Dark Sectors with disappearing charged tracks

We investigate the sensitivity at current and future hadron colliders to a heavy electrically-charged particle with a proper decay length below a centimetre, whose decay products are invisible due to below-threshold energies and/or small couplings to the Standard Model. A cosmologically-motivated example of a framework that contains such a particle is the Minimal Supersymmetric Standard Model in the limit of pure Higgsinos. The current hadron-collider search strategy has no sensitivity to the upper range of pure Higgsino masses that are consistent with the thermal relic density, even at a future collider with 100 TeV centre-of-mass energy. We show that performing a disappearing track search within the inner 10 cm of detector volume would improve the reach in lifetime by a factor of 3 at the 14 TeV LHC and a further factor of 5 at a 100 TeV collider, resulting in around 10 events for 1.1 TeV thermal Higgsinos. In order to include the particles with the largest boost in the analysis, we furthermore propose a purely track-based search in both the central and forward regions, each of which would increase the number of events by another factor of 5, improving our reach at small lifetimes. This would allow us to definitively discover or exclude the experimentally-elusive pure-Higgsino thermal relic at a 100 TeV collider.Comment: 20 pages, 11 figure

Re-interpreting the Oxbridge stransverse mass variable MT2 in general cases

We extend the range of possible applications of MT2 type analyses to decay chains with multiple invisible particles, as well as to asymmetric event topologies with different parent and/or different children particles. We advocate two possible approaches. In the first, we introduce suitably defined 3+1-dimensional analogues of the MT2 variable, which take into account all relevant on-shell kinematic constraints in a given event topology. The second approach utilizes the conventional MT2 variable, but its kinematic endpoint is suitably reinterpreted on a case by case basis, depending on the specific event topology at hand. We provide the general prescription for this reinterpretation, including the formulas relating the measured MT2 endpoint (as a function of the test masses of all the invisible particles) to the underlying physical mass spectrum. We also provide analytical formulas for the shape of the differential distribution of the doubly projected MT2(perp) variable for the ten possible event topologies with one visible particle and up to two invisible particles per decay chain. We illustrate our results with the example of leptonic chargino decays, (chargino to lepton, neutrino and LSP) in supersymmetry.Comment: 36 pages, 9 figures, Preprint typeset in JHEP styl

Observations on Factors Affecting Performance of MapReduce based Apriori on Hadoop Cluster

Designing fast and scalable algorithm for mining frequent itemsets is always being a most eminent and promising problem of data mining. Apriori is one of the most broadly used and popular algorithm of frequent itemset mining. Designing efficient algorithms on MapReduce framework to process and analyze big datasets is contemporary research nowadays. In this paper, we have focused on the performance of MapReduce based Apriori on homogeneous as well as on heterogeneous Hadoop cluster. We have investigated a number of factors that significantly affects the execution time of MapReduce based Apriori running on homogeneous and heterogeneous Hadoop Cluster. Factors are specific to both algorithmic and non-algorithmic improvements. Considered factors specific to algorithmic improvements are filtered transactions and data structures. Experimental results show that how an appropriate data structure and filtered transactions technique drastically reduce the execution time. The non-algorithmic factors include speculative execution, nodes with poor performance, data locality & distribution of data blocks, and parallelism control with input split size. We have applied strategies against these factors and fine tuned the relevant parameters in our particular application. Experimental results show that if cluster specific parameters are taken care of then there is a significant reduction in execution time. Also we have discussed the issues regarding MapReduce implementation of Apriori which may significantly influence the performance.Comment: 8 pages, 8 figures, International Conference on Computing, Communication and Automation (ICCCA2016

Right Atrial Metastatic Melanoma with Unknown Primaries

A 54-year-old male with history of anemia and rheumatoid arthritis presented with a three-month history of dyspnea on exertion and lower extremity edema. Patient was referred for a transthoracic echocardiogram that revealed a large right atrial mass with reduced ejection fraction of 40% and an incidental large liver mass. Subsequent cardiac MRI revealed a lobulated right atrial mass measuring 5.4 cm * 5.3 cm with inferior vena cava compression and adjacent multiple large liver lesions confirmed to be malignant melanoma through biopsy. Interestingly, no primaries were found in the patient. PET/CT imaging displayed hypermetabolic masses within the right atrium and liver that likely represent metastases, as well as bilateral pleural effusions, most likely due to heart failure. Preoperative coronary angiogram demonstrated perfusion to the mass by a dense network of neovasculature arising from the mid right coronary artery. The cardiac melanoma was surgically removed, and the right atrium was reconstructed with a pericardial patch. After surgery, all cardiac chambers appeared normal in size and function with associated moderate tricuspid regurgitation. The patient is currently being administered ipilimumab for systemic therapy of metastatic melanoma