Abstract: This study investigated street begging and its psychosocial effect in Ibadan Metropolis, Oyo State, Nigeria. In carrying out this study, four research questions were used. The instrument used for data collection was a face-to-face and self-developed questionnaire. The results revealed there is high awareness level on the causes of street begging among the respondents, who also mentioned several factors contributing to street begging. However, respondents disagreed that lack of education is a factor contributing to street begging in Nigeria. The psycho-social effects of street begging, as identified by the respondents, are development of inferiority complex, lack of social interaction, loss of self-respect and dignity, increased mindset of poverty and loss of self-confident. Solution to street begging as identified by the respondents also includes provision of rehabilitation centers, provision of food for students in Islamic schools and monthly survival allowance. Specific policies and other legislative frameworks are needed in terms of age, sex, disability, and family-related issues, to effectively address the begging problem. Therefore, it is recommended that policy planners must adopt multi-faceted, multi-targeted, and multi-tiered approaches if they are to have any impact on the lives of street beggars in all four categories. In this regard, both preventative and responsive interventions are needed instead of rehabilitative solutions for each category of street beggars.
Abstract: System identification of an Unmanned Aerial Vehicle (UAV), to acquire its mathematical model, is a significant step in the process of aircraft flight automation. The need for reliable mathematical model is an established requirement for autopilot design, flight simulator development, aircraft performance appraisal, analysis of aircraft modifications, preflight testing of prototype aircraft and investigation of fatigue life and stress distribution etc. This research is aimed at system identification of a fixed wing UAV by means of specifically designed flight experiment. The purposely designed flight maneuvers were performed on the UAV and aircraft states were recorded during these flights. Acquired data were preprocessed for noise filtering and bias removal followed by parameter estimation of longitudinal dynamics transfer functions using MATLAB system identification toolbox. Black box identification based transfer function models, in response to elevator and throttle inputs, were estimated using least square error technique. The identification results show a high confidence level and goodness of fit between the estimated model and actual aircraft response.
Abstract: In the present study, a design of the suspended polymeric microfluidic platform is introduced that is fabricated with three polymeric layers. Changing the microchannel plane to be perpendicular to microcantilever plane, drastically decreases moment of inertia in that direction. In addition, the platform is made of polymer (around five orders of magnitude less compared to silicon). It causes significant increase in the sensitivity of the cantilever deflection. Next, although the dimensions of this platform are constant, by misaligning the embedded microchannels laterally in the suspended microfluidic platform, the sensitivity can be highly increased. The investigation is studied on four fluids including water, seawater, milk, and blood for flow ranges from low rate of 5 to 70 µl/min to obtain the best design with the highest sensitivity. The best design in this study shows the sensitivity increases around 50% for water, seawater, milk, and blood at the flow rate of 70 µl/min by just misaligning the embedded microchannels in the suspended polymeric microfluidic platform.
Abstract: In contrast to existing methods which do not take into account
multiconnectivity in a broad sense of this term, we develop
mathematical models and highly effective combination (BIEM
and FDM) numerical methods of calculation of stationary and
quasi-stationary temperature field of a profile part of a blade
with convective cooling (from the point of view of realization
on PC). The theoretical substantiation of these methods is
proved by appropriate theorems. For it, converging quadrature
processes have been developed and the estimations of errors in
the terms of A.Ziqmound continuity modules have been
received. For visualization of profiles are used: the method of the least
squares with automatic conjecture, device spline, smooth
replenishment and neural nets. Boundary conditions of heat
exchange are determined from the solution of the
corresponding integral equations and empirical relationships.
The reliability of designed methods is proved by calculation
and experimental investigations heat and hydraulic
characteristics of the gas turbine first stage nozzle blade.
Abstract: Statement of the automatic speech recognition
problem, the assignment of speech recognition and the application
fields are shown in the paper. At the same time as Azerbaijan speech,
the establishment principles of speech recognition system and the
problems arising in the system are investigated. The computing algorithms of speech features, being the main part
of speech recognition system, are analyzed. From this point of view,
the determination algorithms of Mel Frequency Cepstral Coefficients
(MFCC) and Linear Predictive Coding (LPC) coefficients expressing
the basic speech features are developed. Combined use of cepstrals of
MFCC and LPC in speech recognition system is suggested to
improve the reliability of speech recognition system. To this end, the
recognition system is divided into MFCC and LPC-based recognition
subsystems. The training and recognition processes are realized in
both subsystems separately, and recognition system gets the decision
being the same results of each subsystems. This results in decrease of
error rate during recognition. The training and recognition processes are realized by artificial
neural networks in the automatic speech recognition system. The
neural networks are trained by the conjugate gradient method. In the
paper the problems observed by the number of speech features at
training the neural networks of MFCC and LPC-based speech
recognition subsystems are investigated. The variety of results of neural networks trained from different
initial points in training process is analyzed. Methodology of
combined use of neural networks trained from different initial points
in speech recognition system is suggested to improve the reliability
of recognition system and increase the recognition quality, and
obtained practical results are shown.
Abstract: Hardly any neat biodiesel satisfies the European EN14214 standard for compression ignition engine application. To satisfy the EN14214 standard, various additives are doped into biodiesel; however, biodiesel additives might cause other problems such as increase in the particular emission and increased specific fuel consumption. In addition, the additives could be expensive. Considering the increasing level of greenhouse gas GHG emissions and fossil fuel depletion, it is forecasted that the use of biodiesel will be higher in the near future. Hence, the negative aspects of the biodiesel additives will likely to gain much more importance and need to be replaced with better solutions. This study aims to satisfy the European standard EN14214 by blending the biodiesels derived from sustainable feedstocks. Waste Cooking Oil (WCO) and Animal Fat Oil (AFO) are two sustainable feedstocks in the EU (including the UK) for producing biodiesels. In the first stage of the study, these oils were transesterified separately and neat biodiesels (W100 & A100) were produced. Secondly, the biodiesels were blended together in various ratios: 80% WCO biodiesel and 20% AFO biodiesel (W80A20), 60% WCO biodiesel and 40% AFO biodiesel (W60A40), 50% WCO biodiesel and 50% AFO biodiesel (W50A50), 30% WCO biodiesel and 70% AFO biodiesel (W30A70), 10% WCO biodiesel and 90% AFO biodiesel (W10A90). The prepared samples were analysed using Thermo Scientific Trace 1300 Gas Chromatograph and ISQ LT Mass Spectrometer (GC-MS). The GS-MS analysis gave Fatty Acid Methyl Ester (FAME) breakdowns of the fuel samples. It was found that total saturation degree of the samples was linearly increasing (from 15% for W100 to 54% for A100) as the percentage of the AFO biodiesel was increased. Furthermore, it was found that WCO biodiesel was mainly (82%) composed of polyunsaturated FAMEs. Cetane numbers, iodine numbers, calorific values, lower heating values and the densities (at 15 oC) of the samples were estimated by using the mass percentages data of the FAMEs. Besides, kinematic viscosities (at 40 °C and 20 °C), densities (at 15 °C), heating values and flash point temperatures of the biomixture samples were measured in the lab. It was found that estimated and measured characterisation results were comparable. The current study concluded that biomixture fuel samples W60A40 and W50A50 were perfectly satisfying the European EN 14214 norms without any need of additives. Investigation on engine performance, exhaust emission and combustion characteristics will be conducted to assess the full feasibility of the proposed biomixture fuels.
Abstract: Dual-phase high carbon steels (DHCS) are commonly known for their improved strength, hardness, and abrasive resistance properties due to co-presence of retained austenite and martensite at the same time. Retained austenite is a meta-stable phase at room temperature, and stability of this phase governs the response of DHCS at different conditions. This research paper studies the effect of RA stability on corrosion behaviour of high carbon steels after they have been immersed into 1.0 M NaCl solution for various times. For this purpose, two different steels with different RA stabilities have been investigated. The surface morphology of the samples before and after corrosion attack was observed by secondary electron microscopy (SEM) and atomic force microscopy (AFM), along with the weight loss and Vickers hardness analysis. Microstructural investigations proved the preferential attack to retained austenite phase during corrosion. Hence, increase in the stability of retained austenite in dual-phase steels led to decreasing the weight loss rate.
Abstract: In this paper, the performance and emission characteristics of a Single Cylinder Spark Ignition engine have been investigated. The research is based on micro emulsion application as fuel in a gasoline engine. We have analyzed many micro emulsion compositions in various proportions, for predicting the performance of the Spark Ignition engine. This new technology of fuel modifications is emerging very rapidly as lot of research is going on in the field of micro emulsion fuels in Compression Ignition engines, but the micro emulsion fuel used in a Gasoline engine is very rare. The use of micro emulsion as fuel in a Spark Ignition engine is virtually unexplored. So, our main goal is to see the performance and emission characteristics of micro emulsions as fuel, in Spark Ignition engines, and finding which composition is more efficient. In this research, we have used various micro emulsion fuels whose composition varies for all the three blends, and their performance and emission characteristic were predicted in AVL Boost software. Conventional Gasoline fuel 90%, 80% and 85% were blended with co-surfactant Ethanol in different compositions, and water was used as an additive for making it crystal clear transparent micro emulsion fuel, which is thermodynamically stable. By comparing the performances of engines, the power has shown similarity for micro emulsion fuel and conventional Gasoline fuel. On the other hand, Torque and BMEP shows increase for all the micro emulsion fuels. Micro emulsion fuel shows higher thermal efficiency and lower Specific Fuel Consumption for all the compositions as compared to the Gasoline fuel. Carbon monoxide and Hydro carbon emissions were also measured. The result shows that emissions decrease for all the composition of micro emulsion fuels, and proved to be the most efficient fuel both in terms of performance and emission characteristics.
Abstract: The antifungal potential of ethanolic leaf extracts of Vernonia amygdalina in the biological control of some common tomato wilt fungi was investigated. The experiment was set up in Completely Randomized Design (CRD) with eight treatments and three replicates. 5 mm diameter agar discs of 7 days old cultures of Fusarium oxysporum and Sclerotium rolfsii were obtained using a sterile 5 mm diameter cork borer and cultured on Potato Dextrose Agar (PDA) inoculated with 5 ml of various concentrations of V. amygdalina ethanolic leaf extracts in petri dishes, and incubated for 10 days at 28 0C. The highest radial growth inhibitions of F. oxysporum (34.98%) and S. rolfsii (31.05%) were recorded 48 hours post-inoculation, both at 75% extract concentration. The leaf extracts of V. amygdalina used in the study exhibited significant inhibition of radial growth of the test organisms (P ≤ 0.05) and could be applied in the biological control of fungal wilt pathogens of tomato as a means of enhancing tomato yield and productivity.
Abstract: A thermodynamic analysis of a partial evaporating Rankine cycle with regeneration using zeotropic ammonia-water mixture as a working fluid is presented in this paper. The thermodynamic laws were applied to evaluate the system performance. Based on the thermodynamic model, the effects of the vapor quality and the ammonia mass fraction on the system performance were extensively investigated. The results showed that thermal efficiency has a peak value with respect to the vapor quality as well as the ammonia mass fraction. The partial evaporating ammonia based Rankine cycle has a potential to improve recovery of low-grade finite heat source.
Abstract: Elastic performances, as an essential property of nanowires (NWs), play a significant role in the design and fabrication of modern nanodevices. In this paper, our interest is focused on ZnO NWs to investigate wire diameter (Dwire ≤ 400 nm) effects on elastic properties. The plotted data reveal that a strong size dependence of the elastic constants exists when the wire diameter is smaller than ~ 100 nm. For larger diameters (Dwire > 100 nm), these ones approach their corresponding bulk values. To enrich this study, we make use of the scanning acoustic microscopy simulation technique. The calculation methodology consists of several steps: determination of longitudinal and transverse wave velocities, calculation of refection coefficients, calculation of acoustic signatures and Rayleigh velocity determination. Quantitatively, it was found that changes in ZnO diameters over the ranges 1 nm ≤ Dwire ≤ 100 nm lead to similar exponential variations, for all elastic parameters, of the from: A = a + b exp(-Dwire/c) where a, b, and c are characteristic constants of a given parameter. The developed relation can be used to predict elastic properties of such NW by just knowing its diameter and vice versa.
Abstract: This paper aims to evaluate the effectiveness of different crystalline coating materials concerning of chloride ions penetration. The concrete ages at the coating installation and its moisture conditions were addressed; where, these two factors may play a dominant role for the effectiveness of the used materials. Rapid chloride ions penetration test (RCPT) was conducted at different ages and moisture conditions according to the relevant standard. In addition, the contaminated area and the penetration depth of the chloride ions were investigated immediately after the RCPT test using chemical identifier, 0.1 M silver nitrate AgNO3 solution. Results have shown that, the very low chloride ions penetrability, for the studied crystallization materials, were investigated only with the old age concrete (G1). The significant reduction in chloride ions’ penetrability was illustrated after 7 days of installing the crystalline coating layers. Using imageJ is more reliable to describe the contaminated area of chloride ions, where the distribution of aggregate and heterogeneous of cement mortar was considered in the images analysis.
Abstract: Mathematical and computational modellings are the necessary tools for reviewing, analysing, and predicting processes and events in the wide spectrum range of scientific fields. Therefore, in a field as rapidly developing as neuroscience, the combination of these two modellings can have a significant role in helping to guide the direction the field takes. The paper combined mathematical and computational modelling to prove a weakness in a very precious model in neuroscience. This paper is intended to analyse all-or-none principle in Hodgkin-Huxley mathematical model. By implementation the computational model of Hodgkin-Huxley model and applying the concept of all-or-none principle, an investigation on this mathematical model has been performed. The results clearly showed that the mathematical model of Hodgkin-Huxley does not observe this fundamental law in neurophysiology to generating action potentials. This study shows that further mathematical studies on the Hodgkin-Huxley model are needed in order to create a model without this weakness.
Abstract: The study of microbial ecology and their function in anaerobic digestion processes are essential to control the biological processes. This is to know the symbiotic relationship between the microorganisms that are involved in the conversion of complex organic matter in the industrial wastewater to simple molecules. In this study, diversity and quantity of bacterial community in the granular sludge taken from the different compartments of a full-scale upflow anaerobic sludge blanket (UASB) reactor treating brewery wastewater was investigated using polymerase chain reaction (PCR) and real-time quantitative PCR (qPCR). The phylogenetic analysis showed three major eubacteria phyla that belong to Proteobacteria, Firmicutes and Chloroflexi in the full-scale UASB reactor, with different groups populating different compartment. The result of qPCR assay showed high amount of eubacteria with increase in concentration along the reactor’s compartment. This study extends our understanding on the diverse, topological distribution and shifts in concentration of microbial communities in the different compartments of a full-scale UASB reactor treating brewery wastewater. The colonization and the trophic interactions among these microbial populations in reducing and transforming complex organic matter within the UASB reactors were established.
Abstract: This study presents new gait representations for improving gait recognition accuracy on cross gait appearances, such as normal walking, wearing a coat and carrying a bag. Based on the Gait Energy Image (GEI), two ideas are implemented to generate new gait representations. One is to append lower knee regions to the original GEI, and the other is to apply convolutional operations to the GEI and its variants. A set of new gait representations are created and used for training multi-class Support Vector Machines (SVMs). Tests are conducted on the CASIA dataset B. Various combinations of the gait representations with different convolutional kernel size and different numbers of kernels used in the convolutional processes are examined. Both the entire images as features and reduced dimensional features by Principal Component Analysis (PCA) are tested in gait recognition. Interestingly, both new techniques, appending the lower knee regions to the original GEI and convolutional GEI, can significantly contribute to the performance improvement in the gait recognition. The experimental results have shown that the average recognition rate can be improved from 75.65% to 87.50%.
Abstract: Numerical investigation of hammershock propagation in the S-bend intake caused by engine surge has been conducted by using Improved Delayed Detach-Eddy Simulation (IDDES). The effects of surge signatures on hammershock characteristics are obtained. It was shown that once the hammershock is produced, it moves upward to the intake entrance quickly with constant speed, however, the strength of hammershock keeps increasing. Meanwhile, being influenced by the centrifugal force, the hammershock strength on the larger radius side is much larger. Hammershock propagation speed and strength are sensitive to the ramp upgradient of surge signature. A larger ramp up gradient results in higher propagation speed and greater strength. Nevertheless, ramp down profile of surge signature have no obvious effect on the propagation speed and strength of hammershock. Increasing the maximum value of surge signature leads to enhance in the intensity of hammershock, they approximately match quadratic function distribution law.
Abstract: In this work, a three-dimensional finite element model was developed to investigate the crack breathing behavior at different crack locations considering the effect of unbalance force. A two-disk rotor with a crack is simulated using ABAQUS. The duration of each crack status (open, closed and partially open/closed) during a full shaft rotation was examined to analyse the crack breathing behavior. Unbalanced shaft crack breathing behavior was found to be different at different crack locations. The breathing behavior of crack along the shaft length is divided into different regions depending on the unbalance force and crack location. The simulated results in this work can be further utilised to obtain the time-varying stiffness matrix of the cracked shaft element under the influence of unbalance force.
Abstract: In general, state-of-the-art Data Acquisition Systems
(DAQ) in high energy physics experiments must satisfy high
requirements in terms of reliability, efficiency and data rate capability.
This paper presents the development and deployment of a debugging
tool named DAQ Debugger for the intelligent, FPGA-based Data
Acquisition System (iFDAQ) of the COMPASS experiment at CERN.
Utilizing a hardware event builder, the iFDAQ is designed to be
able to readout data at the average maximum rate of 1.5 GB/s of
the experiment. In complex softwares, such as the iFDAQ, having
thousands of lines of code, the debugging process is absolutely
essential to reveal all software issues. Unfortunately, conventional
debugging of the iFDAQ is not possible during the real data taking.
The DAQ Debugger is a tool for identifying a problem, isolating
the source of the problem, and then either correcting the problem
or determining a way to work around it. It provides the layer
for an easy integration to any process and has no impact on the
process performance. Based on handling of system signals, the
DAQ Debugger represents an alternative to conventional debuggers
provided by most integrated development environments. Whenever
problem occurs, it generates reports containing all necessary
information important for a deeper investigation and analysis. The
DAQ Debugger was fully incorporated to all processes in the iFDAQ
during the run 2016. It helped to reveal remaining software issues
and improved significantly the stability of the system in comparison
with the previous run. In the paper, we present the DAQ Debugger
from several insights and discuss it in a detailed way.
Abstract: Medical images are important to help identifying different diseases, for example, Magnetic resonance imaging (MRI) can be used to investigate the brain, spinal cord, bones, joints, breasts, blood vessels, and heart. Image segmentation, in medical image analysis, is usually the first step to find out some characteristics with similar color, intensity or texture so that the diagnosis could be further carried out based on these features. This paper introduces an improved C-means model to segment the MRI images. The model is based on information entropy to evaluate the segmentation results by achieving global optimization. Several contributions are significant. Firstly, Genetic Algorithm (GA) is used for achieving global optimization in this model where fuzzy C-means clustering algorithm (FCMA) is not capable of doing that. Secondly, the information entropy after segmentation is used for measuring the effectiveness of MRI image processing. Experimental results show the outperformance of the proposed model by comparing with traditional approaches.
Abstract: In the last years, the crashworthiness of an automotive body structure can be improved, since the beginning of the design stage, thanks to the development of specific optimization tools. It is well known how the finite element codes can help the designer to investigate the crashing performance of structures under dynamic impact. Therefore, by coupling nonlinear mathematical programming procedure and statistical techniques with FE simulations, it is possible to optimize the design with reduced number of analytical evaluations. In engineering applications, many optimization methods which are based on statistical techniques and utilize estimated models, called meta-models, are quickly spreading. A meta-model is an approximation of a detailed simulation model based on a dataset of input, identified by the design of experiments (DOE); the number of simulations needed to build it depends on the number of variables. Among the various types of meta-modeling techniques, Kriging method seems to be excellent in accuracy, robustness and efficiency compared to other ones when applied to crashworthiness optimization. Therefore the application of such meta-model was used in this work, in order to improve the structural optimization of a bumper for a racing car in composite material subjected to frontal impact. The specific energy absorption represents the objective function to maximize and the geometrical parameters subjected to some design constraints are the design variables. LS-DYNA codes were interfaced with LS-OPT tool in order to find the optimized solution, through the use of a domain reduction strategy. With the use of the Kriging meta-model the crashworthiness characteristic of the composite bumper was improved.