Threshold value estimation of journey-distance using generalized polynomial function

The present work demonstrates an experience in estimating the threshold value of journey distances travelled by transit passengers using generalized polynomial function. The threshold value of journey distances may be defined as that distance beyond which passengers might no more be interested to travel by their reported mode. A knowledge on this threshold value is realized to be useful to limit the upper-most slab of transit fare, while preparing of a length-based fare matrix table. Theoretically, the threshold value can be obtained at that point on the cumulative frequency distribution (CFD) curve of journey distances at which the maximum rate of change of the slope of curve occurs. In this work, the CFD curve of the journey distance values is empirically modelled using Newton’s Polynomial Interpolation method, which helps to overcome various challenges usually encountered while an assumption of a theoretical probability distribution is considered a priori for the CFD.

A Framework for the Improvement of Frugal Design Practices

Current frugal design practice is focused on the cost reduction of the product. Despite advancements in the domain of frugal Innovation, it is not systematized to develop products for all sets of users, including marginalized society. Many design researchers and engineers now dedicate time and knowledge to producing practical solutions to enhance the quality of life of the marginal community. The approach currently being adopted restricts the development of products intended for all segments of the users. In this paper, cumulative frequency distribution analysis and the Relative Importance Index is used to identify the essential attributes, which contribute to delivering actual frugal products in terms of functionality, usability, performance, affordability, accessibility, aesthetics, and robustness. The framework is beneficial to eradicate the discriminatory effect of being labeled as “Jugaad” users.

Percentile-based grain size distribution analysis tools (GSDtools) – estimating confidence limits and hypothesis tests for comparing two samples

Most studies of gravel bed rivers present at least one bed surface grain size distribution, but there is almost never any information provided about the uncertainty in the percentile estimates. We present a simple method for estimating the grain size confidence intervals about sample percentiles derived from standard Wolman or pebble count samples of bed surface texture. The width of a grain size confidence interval depends on the confidence level selected by the user (e.g., 95 %), the number of stones sampled to generate the cumulative frequency distribution, and the shape of the frequency distribution itself. For a 95 % confidence level, the computed confidence interval would include the true grain size parameter in 95 out of 100 trials, on average. The method presented here uses binomial theory to calculate a percentile confidence interval for each percentile of interest, then maps that confidence interval onto the cumulative frequency distribution of the sample in order to calculate the more useful grain size confidence interval. The validity of this approach is confirmed by comparing the predictions using binomial theory with estimates of the grain size confidence interval based on repeated sampling from a known population. We also developed a two-sample test of the equality of a given grain size percentile (e.g., D50), which can be used to compare different sites, sampling methods, or operators. The test can be applied with either individual or binned grain size data. These analyses are implemented in the freely available GSDtools package, written in the R language. A solution using the normal approximation to the binomial distribution is implemented in a spreadsheet that accompanies this paper. Applying our approach to various samples of grain size distributions in the field, we find that the standard sample size of 100 observations is typically associated with uncertainty estimates ranging from about ±15 % to ±30 %, which may be unacceptably large for many applications. In comparison, a sample of 500 stones produces uncertainty estimates ranging from about ±9 % to ±18 %. In order to help workers develop appropriate sampling approaches that produce the desired level of precision, we present simple equations that approximate the proportional uncertainty associated with the 50th and 84th percentiles of the distribution as a function of sample size and sorting coefficient; the true uncertainty in any sample depends on the shape of the sample distribution and can only be accurately estimated once the sample has been collected.

Techno-economic assessment of establishment of wind farms in different provinces of Saudi Arabia to mitigate future energy challenges

In the present study, the techno-economic feasibility of development of 15 MW wind power plants (wind farms) in the Kingdom of Saudi Arabia has been investigated by analyzing long-term wind speed data. To achieve this aim, two geographically distinct sites covering different non-coastal locations of the Kingdom of Saudi Arabia have been selected. Long-term data indicates that the yearly average wind speed of Kingdom of Saudi Arabia varies from 3.0-4.5 m/s at 10 m height. The wind farms simulated consist of different combinations of 600 kW commercial wind machines (50 m hub-height). The NREL?s (HOMER Energy?s) HOMER software has been employed to perform the analysis. The study presents the monthly variations of wind speed, cumulative frequency distribution profiles of wind speed, monthly and yearly amount of energy generated from the proposed 15 MW wind farms (50 m hub-height) at different non-coastal locations of Kingdom of Saudi Arabia, cost of generating energy ($/kWh), capacity factor (%), etc. The cumulative frequency distribution indicates that the wind speeds are less than 3 m/s for 48% and 59% of the time during the year at Badanah (Northern province) and Khamis-Mashayt (Southern province), respectively. This implies that wind electric conversion systems or wind farms will not produce energy for 48% of the time during the year at Badanah and for 59% at Khamis-Mashayt. The annual energy produced by 15 MW wind farms (50 m hub-height) has been found to be 18778 and 11314 MWh at Northern and Southern provinces, respectively. The cost of wind-based electricity by using 600 kW (50 m hub-height) commercial wind electric conversion systems has been found to be 0.0612 and 0.1016 US$/kWh for Badanah and Khamis-Mushayt, respectively. Also, the capacity factor of the wind-based power plant has been found to vary from 9 to 15% for the considered locations.

Seasonal indoor radon studies in buildings of Accra Metropolis of Greater Accra region of Ghana

Indoor radon concentration for annual, rainy and dry season have been studied in 228 buildings which includes bedroom, kitchen, sitting room, laboratories and offices in Accra metropolis of Greater Accra of Ghana. The passive radon CR-39 SSNTD was used for this study. The cumulative frequency distribution, normalizing Q-Q plots, Kolmogorov-Smirnov and Shapiro-Wilk statistical test showed that the result of both workplaces and dwellings are not normally distributed. The strong positive correlation between the two seasons occurred at 95% confidence level with 2 tailed. The rainy season recorded highest coefficient variation of r2 = 0.982. Statistical analysis of median (39.3), AM (103.4), GM (57.9) and GSD (3.2) for rainy season were greater than that of the dry season of median (26.9), AM (88.2), GM (49.2) and GSD (2.8) respectively. Rainy season was found to contain high radon concentrations than the dry season for all the studied locations. In general, workplace had radon concentration far greater than dwellings. The results obtained from this study ranged between 13.6 to 533.7 Bq/m3, out of which 9.6%, 12.7% and 3.5% were found to be greater than action levels proposed by WHO, EC and ICRP.