Basic geotechnical properties,chemistry and mineralogy of some laterite soils from S.W. Nigeria

Laterite soils derived from four basement complex rocks and a sedimentary formation from Southwestern Nigeria are analysed for their basic geotechnical properties, chemistry and mineralogy. Results obtained show that the granite gneiss derived and the sedimentary laterite soils are good engineering materials. The amphibolite derived laterite soil has a linear shrinkage of 10% and contains SO ₄ ^2? ions. The quartz schist derived and the micaschist derived laterite soils contain rather high amounts of muscovite ?30% and 25% respectively. The usability of the laterite soils and the implications of the presence of SO ₄ ^2? ions and mica and the high linear shrinkage are discussed.     

A multi-server perishable inventory system with negative customer

In this paper, we consider a continuous review perishable inventory system with multi-server service facility. In such systems the demanded item is delivered to the customer only after performing some service, such as assembly of parts or installation, etc. Compared to many inventory models in which the inventory is depleted at the demand rate, however in this model, it is depleted, at the rate at which the service is completed. We assume that the arrivals of customers are according to a Markovian arrival process (MAP) and that the service time has exponential distribution. The ordering policy is based on (s, S) policy. The lead time is assumed to have exponential distribution. The customer who finds either all servers are busy or no item (excluding those in service) is in the stock, enters into an orbit of infinite size. These orbiting customers send requests at random time points for possible selection of their demands for service. The interval time between two successive request-time points is assumed to have exponential distribution. In addition to the regular customers, a second flow of negative customers following an independent MAP is also considered so that a negative customer will remove one of the customers from the orbit. The joint probability distribution of the number of busy servers, the inventory level and the number of customers in the orbit is obtained in the steady state. Various measures of stationary system performance are computed and the total expected cost per unit time is calculated. The results are illustrated numerically.     

Weighted dynamic time warping for time series classification

Dynamic time warping (DTW), which finds the minimum path by providing non-linear alignments between two time series, has been widely used as a distance measure for time series classification and clustering. However, DTW does not account for the relative importance regarding the phase difference between a reference point and a testing point. This may lead to misclassification especially in applications where the shape similarity between two sequences is a major consideration for an accurate recognition. Therefore, we propose a novel distance measure, called a weighted DTW (WDTW), which is a penalty-based DTW. Our approach penalizes points with higher phase difference between a reference point and a testing point in order to prevent minimum distance distortion caused by outliers. The rationale underlying the proposed distance measure is demonstrated with some illustrative examples. A new weight function, called the modified logistic weight function (MLWF), is also proposed to systematically assign weights as a function of the phase difference between a reference point and a testing point. By applying different weights to adjacent points, the proposed algorithm can enhance the detection of similarity between two time series. We show that some popular distance measures such as DTW and Euclidean distance are special cases of our proposed WDTW measure. We extend the proposed idea to other variants of DTW such as derivative dynamic time warping (DDTW) and propose the weighted version of DDTW. We have compared the performances of our proposed procedures with other popular approaches using public data sets available through the UCR Time Series Data Mining Archive for both time series classification and clustering problems. The experimental results indicate that the proposed approaches can achieve improved accuracy for time series classification and clustering problems.     

Emission of pollutants from wood waste incineration at sawmills in Abeokuta metropolis,Nigeria

This paper reports an assessment of the effects of wood waste burning on air quality and the perceived human health in an urban setting. The concentrations of particulates and selected gases were monitored within the vicinity of sawmills in Abeokuta metropolis. The levels of CO, CO₂, SO₂, NO_x, NO₂, H₂S, CH₄ and particulates at distances from sawmill dumps were measured using portable samplers. Additionally, information on sawmill operations and health problems encountered by the exposed population were collected from a community survey. From the data analyses, between 60 and 100% of wood waste generated by sawmills were burned openly, leading to pollutants emission. The mean concentrations of PM_0.3–0.5 (32 523–40 284 μg/m³), NO₂ (1.0 ppm), SO₂ (3.3 ppm), CO (759 ppm) and CO₂ (4.9%) were higher than the permissible limits at 0–15 m from the dump sites. Almost all sampled parameters showed positive association (R = 0.90–0.98; p < 0.05) at sample sites. Moreover, distance of sites to the dumps explained 51–93% of the variation in parameters levels. Both respiratory and dermal diseases were frequently experienced by the exposed population. Strict land-use zoning, pollution abatement measures, environmental quality monitoring and waste-to-energy interventions are urgently required in the study area.     

Magnetic resonance diffusion imaging of ovarian masses: a first experience with 12 cases

Objective: The objective of the study was to determine the feasibility of using apparent diffusion coefficient (ADC) measurement for the differential diagnosis of malignancy in ovarian masses. Materials and methods: Twelve cases involving ovarian masses were imaged using spin echo diffusion magnetic resonance imaging (MRI). Five cases involved malignant ovarian masses, on the basis of postoperative histologic examination, and the rest involved benign masses. The ovarian masses were imaged in vivo (10 cases) before surgery and ex vivo (8 cases) after surgical resection. Diffusion-weighted data were corrected for motion using the phase data from unweighted data in nine cases. Multifactorial analysis of variance was used to evaluate the effects of malignancy, location (in vivo versus ex vivo), and motion correction on the measurement of ADC intensity and texture. Results: Motion correction caused an undesirable spatial smoothing of the ADC maps and a significant interaction ( ) was found between location and motion correction. ADC value ( ) and texture ( ) differences were found between malignant and nonmalignant ovarian masses. Conclusion: Measurement of ADC intensity and texture has the potential to differentially diagnose malignancy in individual ovarian masses if the problem of image motion artifact can be eliminated through the use of faster imaging sequences.Acknowledgements. The cooperation of Dr. Vance Chow in the acquisition of the in vivo diffusion MRI data is gratefully acknowledged. Thanks to Ron Borowsky for discussions on the statistical data analysis. Data management, final data analysis, and figure preparation was completed by Jennifer Hadley. This work was supported by the Canadian Institutes for Health Research (CIHR) and the Saskatchewan Health Services Utilization and Research Commission (HSURC).     

Influence of schistosity on the strength and wave velocity characteristics of a mica schist saprolite

Anisotropy in a mica schist saprolite is investigated by consideration of its unconfined compressive strength and wave velocity characteristics for different inclinations of the planes of schistosity. In each locality, the differences for each characteristic with respect to the inclinations of schistosity planes were significant. Microfabric studies aided the explanation for the differences obtained. The pertinence of this anisotropy in soil grouping as well as in site investigation and engineering construction is discussed.     

OPERATING REGIME DECOMPOSITION USING NEURAL NETWORKS

This article addresses the problem of identification of a nonlinear process operating over a wide range of conditions. The global space is divided into multiple local regimes, a nonlinear model is developed for each regime, and a quadratic programming-based algorithm is used to ensure smooth transition between the regimes on-line. The use of nonlinear models as opposed to linear models reduces the number of local regimes needed. Neural networks are used to model these regimes because of their strong ability to capture nonlinearity, and their combination with the switching algorithm improves transient performance. The performance of the method is demonstrated on an exothermic CSTR and a pH neutralization process.     

Some properties of A sedimentary laterite soil as engineering construction material

A sedimentary laterite soil is examined for its suitability as a construction material by the consideration of its mineralogy and basic geotechnical properties as well as its consolidation and permeability in the compacted state. Three compaction energy levels are utilised. Mineralogically, the soil contains virtually nothing undesirable while its basic geotechnical properties are those generally ascribed to non-problematic soils. The compressibility of the soil varies from moderate to low depending on the energy of compaction. It is however impervious for all the compaction energy levels. The sedimentary laterite soil constitute a good engineering construction material as it has already been successfully used as base and sub-base material in road construction. Results obtained in this study show that this laterite soil is also suitable for use as fill materials in embankment and dam construction.     

One-pot room temperature synthesis of biopolymer-capped ZnSe nanoparticles

The synthesis of monodispersed, starch-capped ZnSe nanoparticles via a facile, “green” and environmentally benign route at room temperature is being reported. The nanoparticles exhibited strong quantum confinement effect with respect to the bulk ZnSe. The transmission electron microscopy (TEM) image indicated that the particles were well dispersed and spherical in shape. The X-ray diffraction (XRD) analysis showed that the ZnSe nanoparticles were of the wurtzite structure, with average particle diameter of about 3.50 nm. The Fourier transform infrared (FT-IR) spectrum confirmed the presence of starch as passivating agent.