For the construction company, tendering is the most popular way of acquiring contracts. The decision to participate in the tender needs to be made carefully, as it affects the condition of the company and is an important aspect in its quest for success. The bid/no bid decision making is a complex process involving a number of factors. The research carried out so far has mainly concerned the identification of the various kinds of influences on contractors’ bidding decisions. The researchers, on the basis of contractors’ opinions, created rank lists in an attempt to categorize the factors. In this paper the author employs factor analysis which belongs to basic methods of multi-dimensional data analysis. The paper’s aim is first to depict an output set of observed variables, that is bid/no bid factors, in terms of a smaller set of latent variables which cannot be directly observed and then to interpret the dependencies between them.
A speaker recognition system based on joint factor analysis (JFA) is proposed to improve whispering speakers’ recognition rate under channel mismatch. The system estimated separately the eigenvoice and the eigenchannel before calculating the corresponding speaker and the channel factors. Finally, a channel-free speaker model was built to describe accurately a speaker using model compensation. The test results from the whispered speech databases obtained under eight different channels showed that the correct recognition rate of a recognition system based on JFA was higher than that of the Gaussian Mixture Model-Universal Background Model. In particular, the recognition rate in cellphone channel tests increased significantly.
The selection of the formwork system for high rise building affects the entire construction project duration and cost. The study reports the factors influencing the selection of different formwork system in the construction of high rise buildings through structural questionnaire survey from the client, contractor, consultant, and interviews with expert members. Total of 40 technical factors was identified from the literature and 220 filled questionnaires were received from the respondent. Relative Importance Index method is used to find the topmost factors affecting the selection of formwork system. Additionally, from factor analysis 22 factors were identified to have a correlation with one another. Regression analysis reveals that duration of the project, maintenance cost, adaptability, and safety have impact on formwork selection across time, cost and quality. These findings could potentially increase the construction company’s existing knowledge in relation to formwork selection.
In the study, environmetric methods were successfully performed a) to explore natural and anthropogenic controls on reservoir water quality, b) to investigate spatial and temporal differences in quality, and c) to determine quality variables discriminating three reservoirs in Izmir, Turkey. Results showed that overall water quality was mainly governed by “natural factors” in the whole region. A parameter that was the most important in contributing to water quality variation for one reservoir was not important for another. Between summer and winter periods, difference in arsenic concentrations were statistically significant in the Tahtalı, Ürkmez and iron concentrations were in the Balçova reservoirs. Observation of high/low levels in two seasons was explained by different processes as for instance, dilution from runoff at times of high flow seeped through soil and entered the river along with the rainwater run-off and adsorption. Three variables “boron, arsenic and sulphate” discriminated quality among Balçova & Tahtalı, Balçova & Ürkmez and two variables “zinc and arsenic” among the Tahtalı & Ürkmez reservoirs. The results illustrated the usefulness of multivariate statistical techniques to fingerprint pollution sources and investigate temporal/spatial variations in water quality.
The aim of this article is to evaluate the quality of the Danube River in its course through Serbia as well as to demonstrate the possibilities for using three statistical methods: Principal Component Analysis (PCA), Factor Analysis (FA) and Cluster Analysis (CA) in the surface water quality management. Given that the Danube is an important trans-boundary river, thorough water quality monitoring by sampling at different distances during shorter and longer periods of time is not only ecological, but also a political issue. Monitoring was carried out at monthly intervals from January to December 2011, at 17 sampling sites. The obtained data set was treated by multivariate techniques in order, firstly, to identify the similarities and differences between sampling periods and locations, secondly, to recognize variables that affect the temporal and spatial water quality changes and thirdly, to present the anthropogenic impact on water quality parameters.
Indian SMEs are going to play pivotal role in transforming Indian economy and achieving
double digit growth rate in near future. Performance of Indian SMEs is vital in making
India as a most preferred manufacturing destination worldwide under India’s “Make in India
Policy”. Current research was based on Indian automotive SMEs. Indian automotive SMEs
must develop significant agile capability in order to remain competitive in highly uncertain
global environment. One of the objectives of the research was to find various enablers of
agility through literature survey. Thereafter questionnaire administered exploratory factor
analysis was performed to extract various factors of agility relevant in Indian automotive
SMEs environment. Multiple regression analysis was applied to assess the relative importance
of these extracted factors. “Responsiveness” was the most important factor followed by
“Ability to reconfigure”, “Ability to collaborate”, and “Competency”. Thereafter fuzzy logic
bases algorithm was applied to assess the current level of agility of Indian automotive SMEs.
It was found as “Slightly Agile”, which was the deviation from the targeted level of agility.
Fuzzy ranking methodology facilitated the identification & criticalities of various barriers
to agility, so that necessary measures can be taken to improve the current agility level of
Indian automotive SMEs. The current research may helpful in finding; key enablers of agility,
assessing the level of agility, and ranking of the various enablers of agility to point out the
weak zone of agility so that subsequent corrective action may be taken in any industrial
environment similar to India automotive SMEs.
The Shatt Al Arab River (SAAR) is a major source of raw water for most water treatment plants (WTP’s) located along with it in Basrah province. This study aims to determine the effects of different variables on water quality of the SAAR, using multivariate statistical analysis. Seventeen variables were measured in nine WTP’s during 2017, these sites are Al Hussain (1), Awaissan (2), Al Abass (3), Al Garma (4), Mhaigran (5), Al Asmaee (6), Al Jubaila (7), Al Baradia (8), Al Lebani (9). The dataset is treated using principal component analysis (PCA) / factor analysis (FA), cluster analysis (CA) to the most important factors affecting water quality, sources of contamination and the suitability of water for drinking and irrigation. Three factors are responsible for the data structure representing 88.86% of the total variance in the dataset. CA shows three different groups of similarity between the sampling stations, in which station 5 (Mhaigran) is more contami-nated than others, while station 3 (Al Abass) and 6 (Al Asmaee) are less contaminated. Electrical conductivity (EC) and sodium adsorption ratio (SAR) are plotted on Richard diagram. It is shown that the samples of water of Mhaigran are locat-ed in the class of C4-S3 of very high salinity and sodium, water samples of Al Abass station, are located in the class of C3-S1 of high salinity and low sodium, and others are located in the class of C4-S2 of high salinity and medium sodium. Generally, the results of most water quality parameters reveal that SAAR is not within the permissible levels of drinking and irrigation.