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This paper utilizes data mining to study the effect of Problem Based Learning (PBL), an innovative pedagogical approach that has been implemented in undergraduate education at a private university in India for teaching Statistics and Operations Research (OR) to techno-management students.

The study follows the assumptions of an in-situ experiment. It employs BBA (IT) and BCA student(s) as a subject and their end of semester GPA as a performance indicator. The pedagogical approach to this study is integrating PBL with classroom teaching. The paper uses a combination of statistics and data mining to analyze the impact of PBL and establish research conclusions.

The study concludes that the introduction of PBL positively results in an improved GPA for students with a math background. PBL is more effective for BBA (IT) male students. Female students seem to be performing equally well irrespective of the inclusion of PBL. Pattern analysis of shape parameters evidences the impact of PBL, and the results are established through the decision tree and test of proportions.

The study is limited to students from a single institute.

This Pattern analysis, as applied in this paper, can be scaled to evaluate the impact of any innovative pedagogical approach agnostic of the field of study. Facilitators can use the process defined in the paper to implement PBL for teaching Statistics and Operations research. Shape parameters of the batch in the previous semester can be utilized by facilitators to plan remedial action for the next semester by classifying students as desirable/non-desirable. Techno-management institutes can alleviate the dread and fear of mathematical subjects by integrating PBL with classroom teaching.

The study utilizes an innovative analytical approach of combining shape parameters with classification. It further provides uniqueness in arriving at a classification of batch performance as desirable/non-desirable and utilizes data mining to emphasize a delineating impact of PBL across both critical parameters of the batch and the student. The study also defines a framework for the implementation of PBL for a techno-management program in Statistics and Operations Research.

This paper reports two experiments that investigated the semantic distance model (SDM) of relevance assessment. In the first experiment graduate students of mathematics and economics assessed the relevance relationships between bibliographic records and hierarchies of terms composed of classification headings or help‐menu terms. The relevance assessments of the classification headings, but not the help‐menu terms, exhibited both a semantic distance effect and a semantic direction effect as predicted by the sdm. Topical subject expertise enhanced both these effects. The second experiment investigated whether the poor performance of the help‐menu terms was an experimental design artifact reflecting the comparison of terse help terms with verbose classification headings. In the second experiment the help‐menu terms were compared to a hierarchy of single‐word terms where they exhibited both a semantic distance and semantic direction effect.

Calculating the exact top event probability of fault trees is an important analysis in quantitative risk assessments. However, it is a difficult problem for the trees with complex structure. Therefore, the paper aims to provide an efficient calculation method to obtain an exact top event probability of a fault tree with many repeated events when the minimal cut sets of the tree model are given.

The method is based on the inclusion‐exclusion method. Generally, the inclusion‐exclusion method tends to get into computational difficulties for a large‐scale fault tree. The computation time has been reduced by enumerating only non‐canceling terms.

The method enables the calculation of the probability more quickly than the conventional method. The effect increases as the number of repeated events increases, namely the tree structure becomes complex. This method also can be applied to obtain the lower and upper bounds of the top event probability easily.

The paper expresses the top event probability by using only non‐canceling terms. This is the first application in fault tree analysis.

This paper aims to present a method for calculating the top event probability of a fault tree with priority AND gates.

The paper makes use of Merle's temporal operators for obtaining the minimal cut sequence set of a dynamic fault tree. Although Merle's expression is based on the occurrence time of an event sequence, the paper treats the expression as an event containing the order of events. This enables the authors to treat the minimal cut sequence set by using the static fault tree techniques. The proposed method is based on the sum of disjoint products. The method for a static FT is extended to a more applicable one that can deal with the order operators proposed by Merle et al.

First, an algorithm to obtain the minimal cut sequence set of dynamic fault trees is proposed. This algorithm enables the authors to analyze reasonably large scale dynamic fault trees. Second, the proposed method of obtaining the top event probability of a dynamic fault tree is efficient compared with an inclusion‐exclusion based method proposed by Merle et al. and a conventional Markov chain approach. Furthermore, the paper shows the top event probability is derived easily when all the basic events have exponential failure rates.

The methodology presented shows a new solution for calculating the top event probability of dynamic fault trees.

The purpose of this paper is to study the slime mould Physarum polycephalum

The paper proceeds by representing major urban areas of China by oat flakes, inoculating the slime mould in Beijing, waiting till the slime mould colonises all urban areas, or colonises some and cease further propagation, and analysing the protoplasmic networks formed and comparing with man-made motorway network and planar proximity graphs. Findings

Laboratory experiments found that P. polycephalum

The paper demonstrated the strong component of transport system built by slime mould of P. polycephalum

For the solution of equations with sparse matrices, the problem of bandwidth reduction is an important issue. Though graph theoretical algorithms are available, the purpose of this paper is to examine the feasibility of ant systems (AS).

For band optimization an ant colony algorithm based on AS is utilized. In this algorithm a local search procedure is also included to improve the solution.

AS algorithms are found to be suitable for bandwidth optimization.

Application of AS to the bandwidth reduction is the main purpose of this paper, which is successfully performed. The results are compared to those of a graph theoretical bandwidth optimization algorithm.

Breast cancer (BC) is one of the leading cancer in the world, BC risk has been there for women of the middle age also, it is the malignant tumor. However, identifying BC in the early stage will save most of the women’s life. As there is an advancement in the technology research used Machine Learning (ML) algorithm Random Forest for ranking the feature, Support Vector Machine (SVM), and Naïve Bayes (NB) supervised classifiers for selection of best optimized features and prediction of BC accuracy. The estimation of prediction accuracy has been done by using the dataset Wisconsin Breast Cancer Data from University of California Irvine (UCI) ML repository. To perform all these operation, Anaconda one of the open source distribution of Python has been used. The proposed work resulted in extemporize improvement in the NB and SVM classifier accuracy. The performance evaluation of the proposed model is estimated by using classification accuracy, confusion matrix, mean, standard deviation, variance, and root mean-squared error.

The experimental results shows that 70-30 data split will result in best accuracy. SVM acts as a feature optimizer of 12 best features with the result of 97.66% accuracy and improvement of 1.17% after feature reduction. NB results with feature optimizer 17 of best features with the result of 96.49% accuracy and improvement of 1.17% after feature reduction.

The study shows that proposal model works very effectively as compare to the existing models with respect to accuracy measures.

Cybernetics is a powerful unifying concept. It can break down the barriers existing within technology itself, as well as those dividing science from technology. But these barriers are ultimately symbols of general cultural attitudes and consequently a general change of attitude will also be needed. This general change must be achieved through education and the development of the interdisciplinary science of cybernetics.

The purpose of this paper is to discuss Dr Rose's paper which presented his views of the cybernetic revolution; education and the environmental barrier; and the purpose of education.

This paper introduces the concepts held by systemists and cyberneticians in the late 1960s. Sections of the original publication by Dr Rose are included.

Places in an historical context the concepts of the cyberneticians and systemists – of that time and re‐emphasizes their role in forming present day thinking.

Forms part of the tributes paid to the role of Dr Rose and his contribution to these areas of research and development. The original paper discussed was republished in 1991 as a 20th Anniversary tribute to the founding editor of the journal Kybernetes.