Preference programming and inconsistent interval matrices

The problem of derivation of the weights of altematives from pairwise comparison matrices is long standing. In this paper,Lexicographic Goal Programming (LGP) has been used to find out weights from pairwise inconsistent interval judgment matrices. A number of properties and advantages of LGP as a weight determination technique have been explored. An algorithm for identification and modification of inconsistent bounds is also provided. The proposed technique has been illustrated by means of numerical examples.Analytic hierarchy process; Interval judgment; Preferente programming

Evaluating surgical skills from kinematic data using convolutional neural networks

The need for automatic surgical skills assessment is increasing, especially because manual feedback from senior surgeons observing junior surgeons is prone to subjectivity and time consuming. Thus, automating surgical skills evaluation is a very important step towards improving surgical practice. In this paper, we designed a Convolutional Neural Network (CNN) to evaluate surgeon skills by extracting patterns in the surgeon motions performed in robotic surgery. The proposed method is validated on the JIGSAWS dataset and achieved very competitive results with 100% accuracy on the suturing and needle passing tasks. While we leveraged from the CNNs efficiency, we also managed to mitigate its black-box effect using class activation map. This feature allows our method to automatically highlight which parts of the surgical task influenced the skill prediction and can be used to explain the classification and to provide personalized feedback to the trainee.Comment: Accepted at MICCAI 201

Coherent Dependence Cluster

This thesis introduces coherent dependence clusters and shows their relevance in areas of software engineering such as program comprehension and mainte- nance. All statements in a coherent dependence cluster depend upon the same set of statements and affect the same set of statements; a coherent cluster’s statements have ‘coherent’ shared backward and forward dependence. We introduce an approximation to efficiently locate coherent clusters and show that its precision significantly improves over previous approximations. Our empirical study also finds that, despite their tight coherence constraints, coherent dependence clusters are to be found in abundance in production code. Studying patterns of clustering in several open-source and industrial programs reveal that most contain multiple significant coherent clusters. A series of case studies reveal that large clusters map to logical functionality and pro- gram structure. Cluster visualisation also reveals subtle deficiencies of program structure and identify potential candidates for refactoring efforts. Supplemen- tary studies of inter-cluster dependence is presented where identification of coherent clusters can help in deriving hierarchical system decomposition for reverse engineering purposes. Furthermore, studies of program faults find no link between existence of coherent clusters and software bugs. Rather, a longi- tudinal study of several systems find that coherent clusters represent the core architecture of programs during system evolution. Due to the inherent conservativeness of static analysis, it is possible for unreachable code and code implementing cross-cutting concerns such as error- handling and debugging to link clusters together. This thesis studies their effect on dependence clusters by using coverage information to remove unexecuted and rarely executed code. Empirical evaluation reveals that code reduction yields smaller slices and clusters

Isoflavones-Based Liposome Formulations as Anti-Aging for Skincare

Isoflavones commonly found in plants such as soya and red clover express many health benefits including skin healing and anti-aging properties. The capacity to counteract aging is due to isoflavones being both anti-oxidants as well as phytoestrogens, hence preventing both extrinsic as well as intrinsic aging processes. In skincare formulations their effects could be enhanced with the aid of advanced delivery systems. Isoflavones from soya bean source has successfully been incorporated into liposomes and further used in commercially available anti-aging creams. However different plants vary in isoflavone composition. Red clover isoflavones express less affinity for the estrogen receptor whilst simultaneously containing isoflavone structures that should be easier to encapsulate in liposome vehicles compared to soya bean derived isoflavones. If liposome entrapped isoflavones could successfully be obtained, the novel liposome could have a visible effect on the skin and reduce the visible adverse outcomes of aging and moreover be advantageous in terms of endocrinological safety and/or have a higher efficiency of delivering active when compared to the currently available products on the market

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

Application of probiotics and prebiotics for promoting growth of Tiger shrimp (Penaeus monodon): an approach to eco-friendly shrimp aquaculture

The current study has been conducted to evaluate the growth performance of shrimp (Penaeus monodon) by applying eco-friendly culture mechanism like prebiotics and probiotics. The experiment was carried out for 95 days in different shrimp farms at coastal district of Bagerhat, Bangladesh. Three different treatments viz., probiotic treated as T1, prebiotics treated as T2 and both probiotics and prebiotics as T3 with a control group were designed to conduct the experiment. The size of the experimental ponds was five acre and the stocking density was 4/m2 in each treatment. CP NASA shrimp feed (32% protein) was given thrice in a day during the study period. After 95 days of culture period, the maximum weight gain was observed at T3 (33.78±0.18 g) whereas the minimum weight gain was observed at control group (25.69±0.10 g). The survival rate was the highest in T3 (89.01%) followed by T2 (75.51%) and T1 (53.44%) and the lowest rate was observed in control group (50.88%). Overall production was higher in T3 (833.78 kg ha-1) compared to T2 (553.40 kg ha-1), T1 (447.84 kg ha-1) and Control group (310.57 kg ha-1). pH value was found to maximum in T3 (7.71±0.08) and it was minimum in T1 (7.41±0.10). In addition, the maximum TAN value was found to be 2.22±0.19 mg L-1 in C pond and it was minimum in T3 (0.32±0.06 mg L-1). Therefore, it could be concluded that combine application of probiotics and prebiotics might be the reliable media to enhance production of shrimp by maintaining eco-friendly environment in aquaculture. Int. J. Agril. Res. Innov. Tech. 10(2): 15-20, December 202

Developing a forecasting model for cholera incidence in Dhaka megacity through time series climate data.

Cholera, an acute diarrheal disease spread by lack of hygiene and contaminated water, is a major public health risk in many countries. As cholera is triggered by environmental conditions influenced by climatic variables, establishing a correlation between cholera incidence and climatic variables would provide an opportunity to develop a cholera forecasting model. Considering the auto-regressive nature and the seasonal behavioral patterns of cholera, a seasonal-auto-regressive-integrated-moving-average (SARIMA) model was used for time-series analysis during 2000-2013. As both rainfall (r = 0.43) and maximum temperature (r = 0.56) have the strongest influence on the occurrence of cholera incidence, single-variable (SVMs) and multi-variable SARIMA models (MVMs) were developed, compared and tested for evaluating their relationship with cholera incidence. A low relationship was found with relative humidity (r = 0.28), ENSO (r = 0.21) and SOI (r = -0.23). Using SVM for a 1 °C increase in maximum temperature at one-month lead time showed a 7% increase of cholera incidence (p < 0.001). However, MVM (AIC = 15, BIC = 36) showed better performance than SVM (AIC = 21, BIC = 39). An MVM using rainfall and monthly mean daily maximum temperature with a one-month lead time showed a better fit (RMSE = 14.7, MAE = 11) than the MVM with no lead time (RMSE = 16.2, MAE = 13.2) in forecasting. This result will assist in predicting cholera risks and better preparedness for public health management in the future

Preference programming and inconsistent interval matrices

The problem of derivation of the weights of altematives from pairwise comparison matrices is long standing. In this paper,Lexicographic Goal Programming (LGP) has been used to find out weights from pairwise inconsistent interval judgment matrices. A number of properties and advantages of LGP as a weight determination technique have been explored. An algorithm for identification and modification of inconsistent bounds is also provided. The proposed technique has been illustrated by means of numerical examples

Preference programming and inconsistent interval matrices

The problem of derivation of the weights of altematives from pairwise comparison matrices is long standing. In this paper,Lexicographic Goal Programming (LGP) has been used to find out weights from pairwise inconsistent interval judgment matrices. A number of properties and advantages of LGP as a weight determination technique have been explored. An algorithm for identification and modification of inconsistent bounds is also provided. The proposed technique has been illustrated by means of numerical examples