PurposeTo represent the effect of ‘human factors in total quality management (TQM) environment’ in terms of a single numerical index by considering their inheritances and interactions.Design/methodology/approachVarious human factors affecting the TQM culture in an organization are identified and discussed for the sub factors affecting them. These factors are interacting with each other and their overall effect helps an organization in attaining TQM enabled needs. The paper attempts to represent the overall effect of human factors quantitatively by developing a mathematical model using graph theoretic approach. In this approach, interaction among identified human factors is represented through digraph, matrix model and a multinomial.FindingsThe extent of human aspects present in an organization, conducive to TQM culture is represented in terms of the “human index”. It provides an insight into the human factors at system and subsystem level. The developed procedure may be useful for self‐analysis and comparison among organizations.Research limitations/implicationsSince, human behaviour is difficult to predict, so are the human factors. The paper considers general factors, which may vary depending on type of organization, size of organization and geographical location. There is a scope of research in factor specific organizations.Practical implicationsIt provides a useful methodology for organizations to assess human aspects and improve upon therein. Procedure for stepwise application of methodology is given with example that may help an industry to implement it.Originality/valueThe paper attempts to quantify the intangibles through systematic approach and is of value to industries to improve upon their work environment.

Fault diagnosis and condition monitoring are important to increase the efficiency and reliability of photovoltaic modules. This paper reviews the challenges and limitations associated with fault diagnosis of solar modules. A thorough analysis of various faults responsible for failure of solar modules has been discussed. After reviewing relevant work, a monitoring tool is designed using thermography and artificial intelligent systems that allows the detection of various types of faults in PV modules and at the same time the designed tool aims to filter the nonsignificant anomalies. A neural network (NN) classifier is applied to the transfer characteristics (I‐V data) of the faulty PV module for the diagnosis which adapts multilayer perceptron (MLP) networks to identify the type and location of occurring faults. The Discrete wavelet transform (DWT) based signal processing technique is utilized in the feature extraction process to reduce the NN input size. The developed detection algorithm is adapted for 24/7 automated surveillance. For a given fault condition, the average fault detection time is observed to be <9 seconds, which is lower than the previous work done. The developed algorithm achieved 100% accuracy when tested on a predetermined fault data set.

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Plague is one of mankind's greatest scourges, which has swept away millions of people over the centuries. The first available record of the occurrence of this calamity, in humans, is from the Bible, in 1000 bc, in the city of Ashdod. The first definitely identified pandemic originated in Egypt in ad 542 (the Justinian Plague) and is estimated to have caused 100 million deaths. The second one, lasting for three centuries and claiming over 25 million lives appeared in 1334 in China spreading to many spots on the globe. The third pandemic occurred in Europe from the fifteenth to eighteenth century. The current pandemic began around 1860, in the Chinese province Yunnan; it reached Hong Kong in 1894 killing 100 000 individuals. Within 20 years the disease spread from southern Chinese ports throughout the world resulting in more than 10 million deaths. Since the discovery of the causative agent in 1894, there have been remarkable advancements in immunoprophylaxis and chemoprophylaxis. However, the disease is still active in Africa, in Asia and in Americas and has been classified as a currently re-emerging disease. A 'Plague-free World' will probably remain a dream for an indefinite period.

An enzyme-linked immunosorbent assay was done for the detection of immunoglobulin G and M (IgG and IgM) antibodies to Echinococcus granulosus in surgically proved cases of hydatidosis, especially pulmonary hydatidosis, by use of human hydatid cyst fluid antigen and soluble scolex antigen. This assay was compared with the following standardized techniques: the indirect hemagglutination test, the indirect immunofluorescent antibody test, and Casoni's intradermal test. The enzyme-linked immunosorbent assay, with either of the antigens (human hydatid cyst fluid or soluble scolex antigen), was more sensitive and specific than the other techniques in diagnosing cases of hydatidosis, especially hydatid disease of the lung.