Identifying hazardousness of sewer pipeline gas mixture using classification methods: a comparative study

In this work, we formulated a real-world problem related to sewer pipeline gas detection using the classification-based approaches. The primary goal of this work was to identify the hazardousness of sewer pipeline to offer safe and non-hazardous access to sewer pipeline workers so that the human fatalities, which occurs due to the toxic exposure of sewer gas components, can be avoided. The dataset acquired through laboratory tests, experiments, and various literature sources was organized to design a predictive model that was able to identify/classify hazardous and non-hazardous situation of sewer pipeline. To design such prediction model, several classification algorithms were used and their performances were evaluated and compared, both empirically and statistically, over the collected dataset. In addition, the performances of several ensemble methods were analyzed to understand the extent of improvement offered by these methods. The result of this comprehensive study showed that the instance-based learning algorithm performed better than many other algorithms such as multilayer perceptron, radial basis function network, support vector machine, reduced pruning tree. Similarly, it was observed that multi-scheme ensemble approach enhanced the performance of base predictors

A NEW PARADIGM IN FAST BCD DIVISION USING ANCIENT INDIAN VEDIC MATHEMATICS SUTRAS

For decades, division is the most time consuming and expensive procedure in the Arithmetic and Logic Unit of the processors. This paper proposes a novel division algorithm based on Ancient Indian Vedic Mathematics Sutras which is much faster compared to conventional division algorithms. Also large value for the dividend and the divisor do not adversely affect the speed as time estimation of the algorithm depends on the number of normalizations of the remainder rather than on the number of bits in the dividend and the divisor. The algorithm has exhibited remarkable results for conventional midrange processors with numbers of size around 50 bits(15 digit numbers), the upper ceiling of computable numbers for conventional algorithms and the algorithm can divide numbers having size up to 38 digits (127 bits) with conventional processor in the present form, if modified it can divide even bigger numbers