Abstract: Blood pulse is an important human physiological signal commonly used for the understanding of the individual physical health. Current methods of non-invasive blood pulse sensing require direct contact or access to the human skin. As such, the performances of these devices tend to vary with time and are subjective to human body fluids (e.g. blood, perspiration and skin-oil) and environmental contaminants (e.g. mud, water, etc). This paper proposes a simulation model for the novel method of non-invasive acquisition of blood pulse using the disturbance created by blood flowing through a localized magnetic field. The simulation model geometry represents a blood vessel, a permanent magnet, a magnetic sensor, surrounding tissues and air in 2-dimensional. In this model, the velocity and pressure fields in the blood stream are described based on Navier-Stroke equations and the walls of the blood vessel are assumed to have no-slip condition. The blood assumes a parabolic profile considering a laminar flow for blood in major artery near the skin. And the inlet velocity follows a sinusoidal equation. This will allow the computational software to compute the interactions between the magnetic vector potential generated by the permanent magnet and the magnetic nanoparticles in the blood. These interactions are simulated based on Maxwell equations at the location where the magnetic sensor is placed. The simulated magnetic field at the sensor location is found to assume similar sinusoidal waveform characteristics as the inlet velocity of the blood. The amplitude of the simulated waveforms at the sensor location are compared with physical measurements on human subjects and found to be highly correlated.
Abstract: Heterogeneity of solid waste characteristics as well as the complex processes taking place within the landfill ecosystem motivated the implementation of soft computing methodologies such as artificial neural networks (ANN), fuzzy logic (FL), and their combination. The present work uses a hybrid ANN-FL model that employs knowledge-based FL to describe the process qualitatively and implements the learning algorithm of ANN to optimize model parameters. The model was developed to simulate and predict the landfill gas production at a given time based on operational parameters. The experimental data used were compiled from lab-scale experiment that involved various operating scenarios. The developed model was validated and statistically analyzed using F-test, linear regression between actual and predicted data, and mean squared error measures. Overall, the simulated landfill gas production rates demonstrated reasonable agreement with actual data. The discussion focused on the effect of the size of training datasets and number of training epochs.
Abstract: The aim of the present study is to analyze the generation of osteoporotic vertebral bone induced by lack of calcium during growth period and analyze its effects for disc degeneration, based on biomechanical and histomorphometrical study. Mechanical and histomorphological characteristics of lumbar vertebral bones and discs of rats with calcium free diet (CFD) were detected and tracked by using high resolution in-vivo micro-computed tomography (in-vivo micro-CT), finite element (FE) and histological analysis. Twenty female Sprague-Dawley rats (6 weeks old, approximate weight 170g) were randomly divided into two groups (CFD group: 10, NOR group: 10). The CFD group was maintained on a refmed calcium-controlled semisynthetic diet without added calcium, to induce osteoporosis. All lumbar (L 1-L6) were scanned by using in vivo micro-CT with 35i.un resolution at 0, 4, 8 weeks to track the effects of CFD on the generation of osteoporosis. The fmdings of the present study indicated that calcium insufficiency was the main factor in the generation of osteoporosis and it induced lumbar vertebral disc degeneration. This study is a valuable experiment to firstly evaluate osteoporotic vertebral bone and disc degeneration induced by lack of calcium during growth period from a biomechanical and histomorphometrical point of view.
Abstract: Environmental pollution problems have been globally
main concern in all fields including economy, society and culture into
the 21st century. Beginning with the Kyoto Protocol, the reduction on
the emissions of greenhouse gas such as CO2 and SOX has been a
principal challenge of our day. As most buildings unlike durable goods
in other industries have a characteristic and long life cycle, they
consume energy in quantity and emit much CO2. Thus, for green
building construction, more research is needed to reduce the CO2
emissions at each stage in the life cycle. However, recent studies are
focused on the use and maintenance phase. Also, there is a lack of
research on the initial design stage, especially the structure design.
Therefore, in this study, we propose an optimal design plan
considering CO2 emissions and cost in composite buildings
simultaneously by applying to the structural design of actual building.
Abstract: The waverider is proved to be a remarkably useful
configuration for hypersonic glide vehicle (HGV) in terms of the high
lift-to-drag ratio. Due to the severe aerodynamic heating and the
processing technical restriction, the sharp leading edge of waverider
should be blunted, and then the flow characteristics and the
aerodynamic performance along the trajectory will change. In this
paper, the flow characteristics of a HGV, including the rarefied gas
effect and transition phenomenon, were studied based on a reference
trajectory. A numerical simulation was carried out to study the
performance of the HGV under a typical condition.
Abstract: This paper presents a computer simulation model based on system dynamics methodology for analyzing the dynamic characteristics of input energy structure in agriculture and Bangladesh is used here as a case study for model validation. The model provides an input energy structure linking the major energy flows with human energy and draft energy from cattle as well as tractors and/or power tillers, irrigation, chemical fertilizer and pesticide. The evaluation is made in terms of different energy dependent indicators. During the simulation period, the energy input to agriculture increased from 6.1 to 19.15 GJ/ha i.e. 2.14 fold corresponding to energy output in terms of food, fodder and fuel increase from 71.55 to 163.58 GJ/ha i.e. 1.28 fold from the base year. This result indicates that the energy input in Bangladeshi agricultural production is increasing faster than the energy output. Problems such as global warming, nutrient loading and pesticide pollution can associate with this increasing input. For an assessment, a comparative statement of input energy use in agriculture of developed countries (DCs) and least developed countries (LDCs) including Bangladesh has been made. The performance of the model is found satisfactory to analyze the agricultural energy system for LDCs
Abstract: With the advent of social web initiatives, some argued
that these new emerging tools might be useful in tacit knowledge
sharing through providing interactive and collaborative technologies.
However, there is still a poverty of literature to understand how and
what might be the contributions of social media in facilitating tacit
knowledge sharing. Therefore, this paper is intended to theoretically
investigate and map social media concepts and characteristics with
tacit knowledge creation and sharing requirements. By conducting a
systematic literature review, five major requirements found that need
to be present in an environment that involves tacit knowledge
sharing. These requirements have been analyzed against social media
concepts and characteristics to see how they map together. The
results showed that social media have abilities to comply some of the
main requirements of tacit knowledge sharing. The relationships have
been illustrated in a conceptual framework, suggesting further
empirical studies to acknowledge findings of this study.
Abstract: This paper reports the fatigue crack growth behaviour
of gas tungsten arc, electron beam and laser beam welded Ti-6Al-4V
titanium alloy. Centre cracked tensile specimens were prepared to
evaluate the fatigue crack growth behaviour. A 100kN servo
hydraulic controlled fatigue testing machine was used under constant
amplitude uniaxial tensile load (stress ratio of 0.1 and frequency of
10 Hz). Crack growth curves were plotted and crack growth
parameters (exponent and intercept) were evaluated. Critical and
threshold stress intensity factor ranges were also evaluated. Fatigue
crack growth behaviour of welds was correlated with mechanical
properties and microstructural characteristics of welds. Of the three
joints, the joint fabricated by laser beam welding exhibited higher
fatigue crack growth resistance due to the presence of fine lamellar
microstructure in the weld metal.
Abstract: Land degradation is of concern in many countries. People more and more must address the problems associated with the degradation of soil properties due to man. Increasingly, organic soil amendments, such as compost are being examined for their potential use in soil restoration and for preventing soil erosion. In the Czech Republic, compost is the most used to improve soil structure and increase the content of soil organic matter. Land reclamation / restoration is one of the ways to evaluate industrially produced compost because Czech farmers are not willing to use compost as organic fertilizer. The most common use of reclamation substrates in the Czech Republic is for the rehabilitation of landfills and contaminated sites.
This paper deals with the influence of reclamation substrates (RS) with different proportions of compost and sand on selected soil properties–chemical characteristics, nitrogen bioavailability, leaching of mineral nitrogen, respiration activity and plant biomass production. Chemical properties vary proportionally with addition of compost and sand to the control variant (topsoil). The highest differences between the variants were recorded in leaching of mineral nitrogen (varies from 1.36mg dm-3 in C to 9.09mg dm-3). Addition of compost to soil improves conditions for plant growth in comparison with soil alone. However, too high addition of compost may have adverse effects on plant growth. In addition, high proportion of compost increases leaching of mineral N. Therefore, mixture of 70% of soil with 10% of compost and 20% of sand may be recommended as optimal composition of RS.
Abstract: Luxury is an identity, a philosophy and a culture
which requires understanding before the adoption of e-business
practices because of its intricacies and output are essentially different
from other types of goods. Factors such as culture, personal
characteristics, website quality, and vendor characteristics influence
the online purchasing behavior of consumers thus making it a
complex area of study. This paper explores the scope of e-retail for
luxury consumption in the U.A.E. by identifying what motivates and
de-motivates online purchase behavior of U.A.E. consumers and
necessary hypotheses have been drawn to reflect behavior between
online luxury preference consumers and non-online luxury preference
consumers.
Abstract: The aim of this study was to screen for
microorganism that able to utilize 3-N-trimethylamino-1-propanol
(homocholine) as a sole source of carbon and nitrogen. The aerobic
degradation of homocholine has been found by a gram-positive
Rhodococcus sp. bacterium isolated from soil. The isolate was
identified as Rhodococcus sp. strain A4 based on the phenotypic
features, physiologic and biochemical characteristics, and
phylogenetic analysis. The cells of the isolated strain grown on both
basal-TMAP and nutrient agar medium displayed elementary
branching mycelia fragmented into irregular rod and coccoid
elements. Comparative 16S rDNA sequencing studies indicated that
the strain A4 falls into the Rhodococcus erythropolis subclade and
forms a monophyletic group with the type-strains of R. opacus, and
R. wratislaviensis. Metabolites analysis by capillary electrophoresis,
fast atom bombardment-mass spectrometry, and gas
chromatography- mass spectrometry, showed trimethylamine (TMA)
as the major metabolite beside β-alanine betaine and
trimethylaminopropionaldehyde. Therefore, the possible degradation
pathway of trimethylamino propanol in the isolated strain is through
consequence oxidation of alcohol group (-OH) to aldehyde (-CHO)
and acid (-COOH), and thereafter the cleavage of β-alanine betaine
C-N bonds yielded trimethylamine and alkyl chain.
Abstract: It is important to predict yield in semiconductor test process in order to increase yield. In this study, yield prediction means finding out defective die, wafer or lot effectively. Semiconductor test process consists of some test steps and each test includes various test items. In other world, test data has a big and complicated characteristic. It also is disproportionably distributed as the number of data belonging to FAIL class is extremely low. For yield prediction, general data mining techniques have a limitation without any data preprocessing due to eigen properties of test data. Therefore, this study proposes an under-sampling method using support vector machine (SVM) to eliminate an imbalanced characteristic. For evaluating a performance, randomly under-sampling method is compared with the proposed method using actual semiconductor test data. As a result, sampling method using SVM is effective in generating robust model for yield prediction.
Abstract: Distant-talking voice-based HCI system suffers from
performance degradation due to mismatch between the acoustic
speech (runtime) and the acoustic model (training). Mismatch is
caused by the change in the power of the speech signal as observed at
the microphones. This change is greatly influenced by the change in
distance, affecting speech dynamics inside the room before reaching
the microphones. Moreover, as the speech signal is reflected, its
acoustical characteristic is also altered by the room properties. In
general, power mismatch due to distance is a complex problem. This
paper presents a novel approach in dealing with distance-induced
mismatch by intelligently sensing instantaneous voice power variation
and compensating model parameters. First, the distant-talking speech
signal is processed through microphone array processing, and the
corresponding distance information is extracted. Distance-sensitive
Gaussian Mixture Models (GMMs), pre-trained to capture both
speech power and room property are used to predict the optimal
distance of the speech source. Consequently, pre-computed statistic
priors corresponding to the optimal distance is selected to correct
the statistics of the generic model which was frozen during training.
Thus, model combinatorics are post-conditioned to match the power
of instantaneous speech acoustics at runtime. This results to an
improved likelihood in predicting the correct speech command at
farther distances. We experiment using real data recorded inside two
rooms. Experimental evaluation shows voice recognition performance
using our method is more robust to the change in distance compared
to the conventional approach. In our experiment, under the most
acoustically challenging environment (i.e., Room 2: 2.5 meters), our
method achieved 24.2% improvement in recognition performance
against the best-performing conventional method.
Abstract: The main objective of this study is to test the
relationship between numbers of variables representing the firm
characteristics (market-related variables) and the extent of voluntary
disclosure levels (forward-looking disclosure) in the annual reports of
Egyptian firms listed on the Egyptian Stock Exchange. The results
show that audit firm size is significantly positively correlated (in all
the three years) with the level of forward-looking disclosure.
However, industry type variable (which divided to: industries,
cement, construction, petrochemicals and services), is found being
insignificantly association with the level of forward-looking
information disclosed in the annual reports for all the three years.
Abstract: Transesterified vegetable oils (biodiesel) are promising alternative fuel for diesel engines. Used vegetable oils are disposed from restaurants in large quantities. But higher viscosity restricts their direct use in diesel engines. In this study, used cooking oil was dehydrated and then transesterified using an alkaline catalyst. The combustion, performance and emission characteristics of Used Cooking oil Methyl Ester (UCME) and its blends with diesel oil are analysed in a direct injection C.I. engine. The fuel properties and the combustion characteristics of UCME are found to be similar to those of diesel. A minor decrease in thermal efficiency with significant improvement in reduction of particulates, carbon monoxide and unburnt hydrocarbons is observed compared to diesel. The use of transesterified used cooking oil and its blends as fuel for diesel engines will reduce dependence on fossil fuels and also decrease considerably the environmental pollution.
Abstract: Several works regarding facial recognition have dealt with methods which identify isolated characteristics of the face or with templates which encompass several regions of it. In this paper a new technique which approaches the problem holistically dispensing with the need to identify geometrical characteristics or regions of the face is introduced. The characterization of a face is achieved by randomly sampling selected attributes of the pixels of its image. From this information we construct a set of data, which correspond to the values of low frequencies, gradient, entropy and another several characteristics of pixel of the image. Generating a set of “p" variables. The multivariate data set with different polynomials minimizing the data fitness error in the minimax sense (L∞ - Norm) is approximated. With the use of a Genetic Algorithm (GA) it is able to circumvent the problem of dimensionality inherent to higher degree polynomial approximations. The GA yields the degree and values of a set of coefficients of the polynomials approximating of the image of a face. By finding a family of characteristic polynomials from several variables (pixel characteristics) for each face (say Fi ) in the data base through a resampling process the system in use, is trained. A face (say F ) is recognized by finding its characteristic polynomials and using an AdaBoost Classifier from F -s polynomials to each of the Fi -s polynomials. The winner is the polynomial family closer to F -s corresponding to target face in data base.
Abstract: This work describes the aerodynamic characteristic for
aircraft wing model with and without bird feather like winglet. The
aerofoil used to construct the whole structure is NACA 653-218
Rectangular wing and this aerofoil has been used to compare the
result with previous research using winglet. The model of the
rectangular wing with bird feather like winglet has been fabricated
using polystyrene before design using CATIA P3 V5R13 software
and finally fabricated in wood. The experimental analysis for the
aerodynamic characteristic for rectangular wing without winglet,
wing with horizontal winglet and wing with 60 degree inclination
winglet for Reynolds number 1.66×105, 2.08×105 and 2.50×105 have
been carried out in open loop low speed wind tunnel at the
Aerodynamics laboratory in Universiti Putra Malaysia. The
experimental result shows 25-30 % reduction in drag coefficient and
10-20 % increase in lift coefficient by using bird feather like winglet
for angle of attack of 8 degree.
Abstract: Main Memory Database systems (MMDB) store their
data in main physical memory and provide very high-speed access.
Conventional database systems are optimized for the particular
characteristics of disk storage mechanisms. Memory resident
systems, on the other hand, use different optimizations to structure
and organize data, as well as to make it reliable.
This paper provides a brief overview on MMDBs and one of the
memory resident systems named FastDB and compares the
processing time of this system with a typical disc resident database
based on the results of the implementation of TPC benchmarks
environment on both.
Abstract: This paper proposes a new method for analyzing textual data. The method deals with items of textual data, where each item is described based on various viewpoints. The method acquires 2- class classification models of the viewpoints by applying an inductive learning method to items with multiple viewpoints. The method infers whether the viewpoints are assigned to the new items or not by using the models. The method extracts expressions from the new items classified into the viewpoints and extracts characteristic expressions corresponding to the viewpoints by comparing the frequency of expressions among the viewpoints. This paper also applies the method to questionnaire data given by guests at a hotel and verifies its effect through numerical experiments.
Abstract: The characterisation of agro-wastes fibres for composite applications from Nigeria using X-ray diffraction (XRD) and Scanning Electron Microscopy (SEM) has been done. Fibres extracted from groundnut shell, coconut husk, rice husk, palm fruit bunch and palm fruit stalk are processed using two novel cellulose fibre production methods developed by the authors. Cellulose apparent crystallinity calculated using the deconvolution of the diffractometer trace shows that the amorphous portion of cellulose was permeable to hydrolysis yielding high crystallinity after treatment. All diffratograms show typical cellulose structure with well-defined 110, 200 and 040 peaks. Palm fruit fibres had the highest 200 crystalline cellulose peaks compared to others and it is an indication of rich cellulose content. Surface examination of the resulting fibres using SEM indicates the presence of regular cellulose network structure with some agglomerated laminated layer of thin leaves of cellulose microfibrils. The surfaces were relatively smooth indicating the removal of hemicellulose, lignin and pectin.