Gas Flaring in the Niger Delta Nigeria: An Act of Inhumanity to Man and His Environment

The Niger Delta Region of Nigeria is home to about 20 million people and 40 different ethnic groups. The region has an area of seventy thousand square kilometers (70,000 KM2) of wetlands, formed primarily by sediments deposition and makes up 7.5 percent of Nigeria's total landmass. The notable ecological zones in this region includes: coastal barrier islands; mangrove swamp forests; fresh water swamps; and lowland rainforests. This incredibly naturally-endowed ecosystem region, which contains one of the highest concentrations of biodiversity on the planet, in addition to supporting abundant flora and fauna, is threatened by the inhuman act known as gas flaring. Gas flaring is the combustion of natural gas that is associated with crude oil when it is pumped up from the ground. In petroleum-producing areas such as the Niger Delta region of Nigeria where insufficient investment was made in infrastructure to utilize natural gas, flaring is employed to dispose of this associated gas. This practice has impoverished the communities where it is practiced, with attendant environmental, economic and health challenges. This paper discusses the adverse environmental and health implication associated with the practice, the role of Government, Policy makers, Oil companies and the Local communities aimed at bring this inhuman practice to a prompt end.

Numerical Prediction of NOX in the Exhaust of a Compression Ignition Engine

For numerical prediction of the NOX in the exhaust of a compression ignition engine a model was developed by considering the parameter equivalence ratio. This model was validated by comparing the predicted results of NOX with experimental ones. The ultimate aim of the work was to access the applicability, robustness and performance of the improved NOX model against other NOX models.

In silico Simulations for DNA Shuffling Experiments

DNA shuffling is a powerful method used for in vitro evolute molecules with specific functions and has application in areas such as, for example, pharmaceutical, medical and agricultural research. The success of such experiments is dependent on a variety of parameters and conditions that, sometimes, can not be properly pre-established. Here, two computational models predicting DNA shuffling results is presented and their use and results are evaluated against an empirical experiment. The in silico and in vitro results show agreement indicating the importance of these two models and motivating the study and development of new models.

Multiple Power Flow Solutions Using Particle Swarm Optimization with Embedded Local Search Technique

Particle Swarm Optimization (PSO) with elite PSO parameters has been developed for power flow analysis under practical constrained situations. Multiple solutions of the power flow problem are useful in voltage stability assessment of power system. A method of determination of multiple power flow solutions is presented using a hybrid of Particle Swarm Optimization (PSO) and local search technique. The unique and innovative learning factors of the PSO algorithm are formulated depending upon the node power mismatch values to be highly adaptive with the power flow problems. The local search is applied on the pbest solution obtained by the PSO algorithm in each iteration. The proposed algorithm performs reliably and provides multiple solutions when applied on standard and illconditioned systems. The test results show that the performances of the proposed algorithm under critical conditions are better than the conventional methods.

Gasifier System Identification for Biomass Power Plants using Neural Network

The use of renewable energy sources becomes more necessary and interesting. As wider applications of renewable energy devices at domestic, commercial and industrial levels has not only resulted in greater awareness, but also significantly installed capacities. In addition, biomass principally is in the form of woods, which is a form of energy by humans for a long time. Gasification is a process of conversion of solid carbonaceous fuel into combustible gas by partial combustion. Many gasifier models have various operating conditions; the parameters kept in each model are different. This study applied experimental data, which has three inputs, which are; biomass consumption, temperature at combustion zone and ash discharge rate. One output is gas flow rate. For this paper, neural network was used to identify the gasifier system suitable for the experimental data. In the result,neural networkis usable to attain the answer.

Optimal Design for SARMA(P,Q)L Process of EWMA Control Chart

The main goal of this paper is to study Statistical Process Control (SPC) with Exponentially Weighted Moving Average (EWMA) control chart when observations are serially-correlated. The characteristic of control chart is Average Run Length (ARL) which is the average number of samples taken before an action signal is given. Ideally, an acceptable ARL of in-control process should be enough large, so-called (ARL0). Otherwise it should be small when the process is out-of-control, so-called Average of Delay Time (ARL1) or a mean of true alarm. We find explicit formulas of ARL for EWMA control chart for Seasonal Autoregressive and Moving Average processes (SARMA) with Exponential white noise. The results of ARL obtained from explicit formula and Integral equation are in good agreement. In particular, this formulas for evaluating (ARL0) and (ARL1) be able to get a set of optimal parameters which depend on smoothing parameter (λ) and width of control limit (H) for designing EWMA chart with minimum of (ARL1).

Air Quality in Sports Venues with Distinct Characteristics

In July 2012, an indoor/outdoor monitoring programme was undertaken in two university sports facilities: a fronton and a gymnasium. Comfort parameters (temperature, relative humidity, CO and CO2) and total volatile organic compounds (VOCs) were continuously monitored. Concentrations of NO2, carbonyl compounds and individual VOCs were obtained. Low volume samplers were used to collect particulate matter (PM10). The minimum ventilation rates stipulated for acceptable indoor air quality were observed in both sports facilities. It was found that cleaning activities may have a large influence on the VOC levels. Acrolein was one of the most abundant carbonyl compounds, showing concentrations above the recommended limit. Formaldehyde was detected at levels lower than those commonly reported for other indoor environments. The PM10 concentrations obtained during the occupancy periods ranged between 38 and 43μgm-3 in the fronton and from 154 to 198μgm-3 in the gymnasium.

Evolutionary of Prostate Cancer Stem Cells in Prostate Duct

A systems approach model for prostate cancer in prostate duct, as a sub-system of the organism is developed. It is accomplished in two steps. First this research work starts with a nonlinear system of coupled Fokker-Plank equations which models continuous process of the system like motion of cells. Then extended to PDEs that include discontinuous processes like cell mutations, proliferation and deaths. The discontinuous processes is modeled by using intensity poisson processes. The model incorporates the features of the prostate duct. The system of PDEs spatial coordinate is along the proximal distal axis. Its parameters depend on features of the prostate duct. The movement of cells is biased towards distal region and mutations of prostate cancer cells is localized in the proximal region. Numerical solutions of the full system of equations are provided, and are exhibit traveling wave fronts phenomena. This motivates the use of the standard transformation to derive a canonically related system of ODEs for traveling wave solutions. The results obtained show persistence of prostate cancer by showing that the non-negative cone for the traveling wave system is time invariant. The traveling waves have a unique global attractor is proved also. Biologically, the global attractor verifies that evolution of prostate cancer stem cells exhibit the avascular tumor growth. These numerical solutions show that altering prostate stem cell movement or mutation of prostate cancer cells lead to avascular tumor. Conclusion with comments on clinical implications of the model is discussed.

The Determination of Cellulose Spiral Angle by Small-Angle X-Ray Scattering from Structurally Characterized Acacia mangium Cell Wall

The spiral angle of the elementary cellulose fibril in the wood cell wall, often called microfibril angle, (MFA). Microfibril angle in hardwood is one of the key determinants of solid timber performance due to its strong influence on the stiffness, strength, shrinkage, swelling, thermal-dynamics mechanical properties and dimensional stability of wood. Variation of MFA (degree) in the S2 layer of the cell walls among Acacia mangium trees was determined using small-angle X-ray scattering (SAXS). The length and orientation of the microfibrils of the cell walls in the irradiated volume of the thin samples are measured using SAXS and optical microscope for 3D surface measurement. The undetermined parameters in the analysis are the MFA, (M) and the standard deviation (σФ) of the intensity distribution arising from the wandering of the fibril orientation about the mean value. Nine separate pairs of values are determined for nine different values of the angle of the incidence of the X-ray beam relative to the normal to the radial direction in the sample. The results show good agreement. The curve distribution of scattered intensity for the real cell wall structure is compared with that calculated with that assembly of rectangular cells with the same ratio of transverse to radial cell wall length. It is demonstrated that for β = 45°, the peaks in the curve intensity distribution for the real and the rectangular cells coincide. If this peak position is Ф45, then the MFA can be determined from the relation M = tan-1 (tan Ф45 / cos 45°), which is precise for rectangular cells. It was found that 92.93% of the variation of MFA can be attributed to the distance from pith to bark. Here we shall present our results of the MFA in the cell wall with respect to its shape, structure and the distance from pith to park as an important fast check and yet accurate towards the quality of wood, its uses and application.

Comparison of Neural Network and Logistic Regression Methods to Predict Xerostomia after Radiotherapy

To evaluate the ability to predict xerostomia after radiotherapy, we constructed and compared neural network and logistic regression models. In this study, 61 patients who completed a questionnaire about their quality of life (QoL) before and after a full course of radiation therapy were included. Based on this questionnaire, some statistical data about the condition of the patients’ salivary glands were obtained, and these subjects were included as the inputs of the neural network and logistic regression models in order to predict the probability of xerostomia. Seven variables were then selected from the statistical data according to Cramer’s V and point-biserial correlation values and were trained by each model to obtain the respective outputs which were 0.88 and 0.89 for AUC, 9.20 and 7.65 for SSE, and 13.7% and 19.0% for MAPE, respectively. These parameters demonstrate that both neural network and logistic regression methods are effective for predicting conditions of parotid glands.

Beneficial Use of Coal Combustion By-products in the Rehabilitation of Failed Asphalt Pavements

This study demonstrates the use of Class F fly ash in combination with lime or lime kiln dust in the full depth reclamation (FDR) of asphalt pavements. FDR, in the context of this paper, is a process of pulverizing a predetermined amount of flexible pavement that is structurally deficient, blending it with chemical additives and water, and compacting it in place to construct a new stabilized base course. Test sections of two structurally deficient asphalt pavements were reclaimed using Class F fly ash in combination with lime and lime kiln dust. In addition, control sections were constructed using cement, cement and emulsion, lime kiln dust and emulsion, and mill and fill. The service performance and structural behavior of the FDR pavement test sections were monitored to determine how the fly ash sections compared to other more traditional pavement rehabilitation techniques. Service performance and structural behavior were determined with the use of sensors embedded in the road and Falling Weight Deflectometer (FWD) tests. Monitoring results of the FWD tests conducted up to 2 years after reclamation show that the cement, fly ash+LKD, and fly ash+lime sections exhibited two year resilient modulus values comparable to open graded cement stabilized aggregates (more than 750 ksi). The cement treatment resulted in a significant increase in resilient modulus within 3 weeks of construction and beyond this curing time, the stiffness increase was slow. On the other hand, the fly ash+LKD and fly ash+lime test sections indicated slower shorter-term increase in stiffness. The fly ash+LKD and fly ash+lime section average resilient modulus values at two years after construction were in excess of 800 ksi. Additional longer-term testing data will be available from ongoing pavement performance and environmental condition data collection at the two pavement sites.

Active Tendons for Seismic Control of Buildings

In this study, active tendons with Proportional Integral Derivation type controllers were applied to a SDOF and a MDOF building model. Physical models of buildings were constituted with virtual springs, dampers and rigid masses. After that, equations of motion of all degrees of freedoms were obtained. Matlab Simulink was utilized to obtain the block diagrams for these equations of motion. Parameters for controller actions were found by using a trial method. After earthquake acceleration data were applied to the systems, building characteristics such as displacements, velocities, accelerations and transfer functions were analyzed for all degrees of freedoms. Comparisons on displacement vs. time, velocity vs. time, acceleration vs. time and transfer function (Db) vs. frequency (Hz) were made for uncontrolled and controlled buildings. The results show that the method seems feasible.

Thermodynamic Performance of a Combined Power and Ejector Refrigeration Cycle

In this study thermodynamic performance analysis of a combined organic Rankine cycle and ejector refrigeration cycle is carried out for use of low-grade heat source in the form of sensible energy. Special attention is paid to the effects of system parameters including the turbine inlet temperature and turbine inlet pressure on the characteristics of the system such as ratios of mass flow rate, net work production, and refrigeration capacity as well as the coefficient of performance and exergy efficiency of the system. Results show that for a given source the coefficient of performance increases with increasing of the turbine inlet pressure. However, the exergy efficiency has an optimal condition with respect to the turbine inlet pressure.

An Evaluation of Sputum Smear Conversion and Haematological Parameter Alteration in Early Detection Period of New Pulmonary Tuberculosis (PTB) Patients

Sputum smear conversion after one month of antituberculosis therapy in new smear positive pulmonary tuberculosis patients (PTB+) is a vital indicator towards treatment success. The objective of this study is to determine the rate of sputum smear conversion in new PTB+ patients after one month under treatment of National Institute of Diseases of the Chest and Hospital (NIDCH). Analysis of sputum smear conversion was done by re-clinical examination with sputum smear microscopic test after one month. Socio-demographic and hematological parameters were evaluated to perceive the correlation with the disease status. Among all enrolled patients only 33.33% were available for follow up diagnosis and of them only 42.86% patients turned to smear negative. Probably this consequence is due to non-coherence to the proper disease management. 66.67% and 78.78% patients reported low haemoglobin and packed cell volume level respectively whereas 80% and 93.33% patients accounted accelerated platelet count and erythrocyte sedimentation rate correspondingly.

Automated Knowledge Engineering

This article outlines conceptualization and implementation of an intelligent system capable of extracting knowledge from databases. Use of hybridized features of both the Rough and Fuzzy Set theory render the developed system flexibility in dealing with discreet as well as continuous datasets. A raw data set provided to the system, is initially transformed in a computer legible format followed by pruning of the data set. The refined data set is then processed through various Rough Set operators which enable discovery of parameter relationships and interdependencies. The discovered knowledge is automatically transformed into a rule base expressed in Fuzzy terms. Two exemplary cancer repository datasets (for Breast and Lung Cancer) have been used to test and implement the proposed framework.

Robust Camera Calibration using Discrete Optimization

Camera calibration is an indispensable step for augmented reality or image guided applications where quantitative information should be derived from the images. Usually, a camera calibration is obtained by taking images of a special calibration object and extracting the image coordinates of projected calibration marks enabling the calculation of the projection from the 3d world coordinates to the 2d image coordinates. Thus such a procedure exhibits typical steps, including feature point localization in the acquired images, camera model fitting, correction of distortion introduced by the optics and finally an optimization of the model-s parameters. In this paper we propose to extend this list by further step concerning the identification of the optimal subset of images yielding the smallest overall calibration error. For this, we present a Monte Carlo based algorithm along with a deterministic extension that automatically determines the images yielding an optimal calibration. Finally, we present results proving that the calibration can be significantly improved by automated image selection.

Conceptual Design of Aeroelastic Demonstrator for Whirl Flutter Simulation

This paper deals with the conceptual design of the new aeroelastic demonstrator for the whirl flutter simulation. The paper gives a theoretical background of the whirl flutter phenomenon and describes the events of the whirl flutter occurrence in the aerospace practice. The second part is focused on the experimental research of the whirl flutter on aeroelastic similar models. Finally the concept of the new aeroelastic demonstrator is described. The demonstrator represents the wing and engine of the twin turboprop commuter aircraft including a driven propeller. It allows the changes of the main structural parameters influencing the whirl flutter stability characteristics. It is intended for the experimental investigation of the whirl flutter in the wind tunnel. The results will be utilized for validation of analytical methods and software tools.

Drying of Papaya (Carica papaya L.) Using a Microwave-vacuum Dryer

In present work, drying characteristics of fresh papaya (Carica papaya L.) was studied to understand the dehydration process and its behavior. Drying experiments were carried out by a laboratory scaled microwave-vacuum oven. The parameters affecting drying characteristics including operating modes (continuous, pulsed), microwave power (400 and 800 W), and vacuum pressure (20, 30, and 40 cmHg) were investigated. For pulsed mode, two levels of power-off time (60 and 120 s) were used while the power-on time was fixed at 60 s and the vacuum pressure was fixed at 40 cmHg. For both operating modes, the effects of drying conditions on drying time, drying rate, and effective diffusivity were investigated. The results showed high microwave power, high vacuum, and pulsed mode of 60 s-on/60 s-off favored drying rate as shown by the shorten drying time and increased effective diffusivity. The drying characteristics were then described by Page-s model, which showed a good agreement with experimental data.

Dispenser Longitudinal Movement ControlDesign Based on Auto - Disturbances –Rejection - Controller

Based on the feature of model disturbances and uncertainty being compensated dynamically in auto – disturbances-rejection-controller (ADRC), a new method using ADRC is proposed for the decoupling control of dispenser longitudinal movement in big flight envelope. Developed from nonlinear model directly, ADRC is especially suitable for dynamic model that has big disturbances. Furthermore, without changing the structure and parameters of the controller in big flight envelope, this scheme can simplify the design of flight control system. The simulation results in big flight envelope show that the system achieves high dynamic performance, steady state performance and the controller has strong robustness.

Block Homotopy Perturbation Method for Solving Fuzzy Linear Systems

In this paper, we present an efficient numerical algorithm, namely block homotopy perturbation method, for solving fuzzy linear systems based on homotopy perturbation method. Some numerical examples are given to show the efficiency of the algorithm.