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

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

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

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

Socio-Demographic and Oral Health Related Risk Factors for Periodontal Disease in Inner North East London (INEL) Adults: A Secondary Analysis of the INEL Data.

Introduction: Periodontal disease is a serious collection of diseases which can lead to chronic inflammation, the destruction of tooth supporting structures and ultimately; tooth loss. It is also one of the most common diseases of the oral cavity and the major cause of tooth loss in adults and may have a major impact on the quality of life off those who suffer with the condition. Objectives: To determine the socio-demographic and oral-health-related risk factors for periodontal disease in a sample of adults living in Inner North East London (INEL), UK. Methods: A secondary analysis was conducted on data from the 2008 survey on ‘The Oral Health of Adults in INEL.’ Data were entered into the Statistical Package for Social Sciences (SPSS v19, IBM UK Ltd, Portsmouth, UK) and analysed using descriptive analysis, chi-squared tests (P ≤ 0.05), together with multivariate regression analysis. The original survey employed a multi-stage sampling procedure and the final sample size was 361. All of the participants were selected from the London Boroughs of Tower Hamlets, City and Hackney and Newham. Periodontal disease indicators, such as the loss of clinical attachment and periodontal pocket depths were cross-matched with socio-demographic and oral health-related behaviours. Associations between the two were ascertained using chi-squared statistics and multivariate regression analysis. The case-definition adopted to indicate the presence of periodontal disease was “a clinical loss of attachment and periodontal pocketing of four millimetres or more, in at-least one tooth respectively”. Results: The prevalence of periodontal disease in the original INEL sample was 39.3%. Age and gender were the variables most commonly associated with periodontal disease. The prevalence of disease demonstrated an increase with age, and in terms of gender, 48.7% of males were observed to have periodontal disease compared to 32.2% of females. Ethnicity (p=0.005) and area of residence (p=0.005) were more directly associated with periodontal pocket depth ≥ 4 mm. Dental attendance (p=0.04) and education (p=0.02) were more directly associated with clinical loss of attachment. When assessing the combined outcomes, multivariate regression analysis showed that after controlling for age and gender, subjects without a work-related qualification were more likely to have periodontal disease (OR=1.780, 95% C.I. 1.066-2.973). Dental attendance was identified as another significant predictor of periodontal disease for example subjects who never visited a dentist were at more risk than the regular attenders (OR=3.700, 95% C.I. 1.448-9.458). Conclusion: The overall prevalence of periodontal disease in an Inner North East London sample was observed to be slightly higher but generally comparable with respect to the national average, as determined by the UK Adult Dental Health Survey (1998). Of the various socio-demographic and oral-health-related risk factors analysed in the present study, age, gender, work-related qualification and dental attendance were observed to increase the likelihood of periodontal disease. Furthermore, epidemiological studies should be implemented in order to develop prevention strategies which should focus on improving access to dental services in the local community in order to reduce periodontal disease rates

A dimensioning and tolerancing methodology for concurrent engineering applications I: problem representation

This paper is the first of two which present a methodology for determining the dimensional specifications of all the component parts and sub-assemblies of a product according to their dimensional requirements. To achieve this goal, two major steps are followed, each of which is described in a paper. In the first paper, all relationships necessary for finding the values of dimensions and tolerances are represented in a matrix form, known as a Dimensional Requirements/Dimensions (DR/D) matrix. In the second paper, the values of individual dimensions and tolerances are determined by applying a comprehensive solution strategy to satisfy all the relationships represented in the DR/D matrix. The methodology is interactive and suitable for use in a concurrent engineering (CE) environment. The graphical tool presented in this paper will assist a CE team in visualizing the overall D&T problem and foreseeing the ramifications of decisions regarding the selection of dimensions and tolerances. This will assist the CE team to systematically determine all the controllable variables, such as dimensions, tolerances, and manufacturing processes