Abstract: This study assessed fish marketing as panacea towards
sustainable agriculture in Ogun State, Nigeria. Multi-stage sampling
technique was used in the selection of 150 fish marketers for this
study. Descriptive statistics were used for the objectives while
Product Pearson Moment Correlation was used to test the hypothesis.
Result of the findings revealed that the mean age of the respondents
was 38.60 years. Majority (93.33%) of the respondents had
acceptable levels of formal education. Many (44.00%) of the
respondents had spent 1-5 years in fish marketing. The average
quantity of fish sold in a day was 94.10kg. However, efficient fish
marketing were hindered by inadequate processing equipment,
storage rooms and ice holding facilities (86.67%). There was a
significant relationship between socio-economic characteristics and
profit realized from fish marketing (p < 0.05). It was recommended
that storage and warehousing facilities should be provided to the fish
marketers in the study area.
Abstract: The Stokes equation connected with the fluid flow
over the axisymmetric bodies in a cylindrical area is considered. The
equation is studied in a moving coordinate system with the
appropriate boundary conditions. Effective formulas for the velocity
components are obtained. The graphs of the velocity components and
velocity profile are plotted.
Abstract: In this paper we propose a Particle Swarm heuristic
optimized Multi-Antenna (MA) system. Efficient MA systems
detection is performed using a robust stochastic evolutionary
computation algorithm based on movement and intelligence of
swarms. This iterative particle swarm optimized (PSO) detector
significantly reduces the computational complexity of conventional
Maximum Likelihood (ML) detection technique. The simulation
results achieved with this proposed MA-PSO detection algorithm
show near optimal performance when compared with ML-MA
receiver. The performance of proposed detector is convincingly
better for higher order modulation schemes and large number of
antennas where conventional ML detector becomes non-practical.
Abstract: This paper is proposed the dynamic simulation of
small power induction motor based on Mathematical modeling. The
dynamic simulation is one of the key steps in the validation of the
design process of the motor drive systems and it is needed for
eliminating inadvertent design mistakes and the resulting error in the
prototype construction and testing. This paper demonstrates the
simulation of steady-state performance of induction motor by
MATLAB Program Three phase 3 hp induction motor is modeled
and simulated with SIMULINK model.
Abstract: Simulation model is an easy way to build up models
to represent real life scenarios, to identify bottlenecks and to enhance
system performance. Using a valid simulation model may give
several advantages in creating better manufacturing design in order to
improve the system performances. This paper presents result of
implementing a simulation model to design hard disk drive
manufacturing process by applying line balancing to improve both
productivity and quality of hard disk drive process. The line balance
efficiency showed 86% decrease in work in process, output was
increased by an average of 80%, average time in the system was
decreased 86% and waiting time was decreased 90%.
Abstract: The objective of this study is to determine the thermal comfort among worker at Malaysian automotive industry. One critical manual assembly workstation had been chosen as a subject for the study. The human subjects for the study constitute operators at Body Assembly Station of the factory. The environment examined was the Relative Humidity (%), Airflow (m/s), Air Temperature (°C) and Radiant Temperature (°C) of the surrounding workstation area. The environmental factors were measured using Babuc apparatus, which is capable to measure simultaneously those mentioned environmental factors. The time series data of fluctuating level of factors were plotted to identify the significant changes of factors. Then thermal comfort of the workers were assessed by using ISO Standard 7730 Thermal sensation scale by using Predicted Mean Vote (PMV). Further Predicted percentage dissatisfied (PPD) is used to estimate the thermal comfort satisfaction of the occupant. Finally the PPD versus PMV were plotted to present the thermal comfort scenario of workers involved in related workstation. The result of PMV at the related industry is between 1.8 and 2.3, where PPD at that building is between 60% to 84%. The survey result indicated that the temperature more influenced comfort to the occupants
Abstract: This paper investigates how the use of machine learning techniques can significantly predict the three major dimensions of learner-s emotions (pleasure, arousal and dominance) from brainwaves. This study has adopted an experimentation in which participants were exposed to a set of pictures from the International Affective Picture System (IAPS) while their electrical brain activity was recorded with an electroencephalogram (EEG). The pictures were already rated in a previous study via the affective rating system Self-Assessment Manikin (SAM) to assess the three dimensions of pleasure, arousal, and dominance. For each picture, we took the mean of these values for all subjects used in this previous study and associated them to the recorded brainwaves of the participants in our study. Correlation and regression analyses confirmed the hypothesis that brainwave measures could significantly predict emotional dimensions. This can be very useful in the case of impassive, taciturn or disabled learners. Standard classification techniques were used to assess the reliability of the automatic detection of learners- three major dimensions from the brainwaves. We discuss the results and the pertinence of such a method to assess learner-s emotions and integrate it into a brainwavesensing Intelligent Tutoring System.
Abstract: In this study we focus on improvement performance
of a cue based Motor Imagery Brain Computer Interface (BCI). For
this purpose, data fusion approach is used on results of different
classifiers to make the best decision. At first step Distinction
Sensitive Learning Vector Quantization method is used as a feature
selection method to determine most informative frequencies in
recorded signals and its performance is evaluated by frequency
search method. Then informative features are extracted by packet
wavelet transform. In next step 5 different types of classification
methods are applied. The methodologies are tested on BCI
Competition II dataset III, the best obtained accuracy is 85% and the
best kappa value is 0.8. At final step ordered weighted averaging
(OWA) method is used to provide a proper aggregation classifiers
outputs. Using OWA enhanced system accuracy to 95% and kappa
value to 0.9. Applying OWA just uses 50 milliseconds for
performing calculation.
Abstract: Sugarcane bagasses are one of the most extensively used agricultural residues. Using acid hydrolysis and fermentation, conversion of sugarcane bagasses to lactic acid was technically and economically feasible. This research was concerned with the solubility of lignin in ammonium hydroxide, acid hydrolysis and lactic acid fermentation by Lactococcus lactis, Lactobacillus delbrueckii, Lactobacillus plantarum, and Lactobacillus casei. The lignin extraction results for different ammonium hydroxide concentrations showed that 10 % (v/v) NH4OH was favorable to lignin dissolution. Acid hydrolysis can be enhanced with increasing acid concentration and reaction temperature. The optimum glucose and xylose concentrations occurred at 121 ○C for 1 hour hydrolysis time in 10% sulphuric acid solution were 32 and 11 g/l, respectively. In order to investigate the significance of medium composition on lactic acid production, experiments were undertaken whereby a culture of Lactococcus lactis was grown under various glucose, peptone, yeast extract and xylose concentrations. The optimum medium was composed of 5 g/l glucose, 2.5 g/l xylose, 10 g/l peptone and 5 g/l yeast extract. Lactococcus lactis represents the most efficient for lactic acid production amongst those considered. The lactic acid fermentation by Lactococcus lactis after 72 hours gave the highest yield of 1.4 (g lactic acid per g reducing sugar).
Abstract: The overall objective of this paper is to retrieve soil
surfaces parameters namely, roughness and soil moisture related to
the dielectric constant by inverting the radar backscattered signal
from natural soil surfaces.
Because the classical description of roughness using statistical
parameters like the correlation length doesn't lead to satisfactory
results to predict radar backscattering, we used a multi-scale
roughness description using the wavelet transform and the Mallat
algorithm. In this description, the surface is considered as a
superposition of a finite number of one-dimensional Gaussian
processes each having a spatial scale. A second step in this study
consisted in adapting a direct model simulating radar backscattering
namely the small perturbation model to this multi-scale surface
description. We investigated the impact of this description on radar
backscattering through a sensitivity analysis of backscattering
coefficient to the multi-scale roughness parameters.
To perform the inversion of the small perturbation multi-scale
scattering model (MLS SPM) we used a multi-layer neural network
architecture trained by backpropagation learning rule. The inversion
leads to satisfactory results with a relative uncertainty of 8%.
Abstract: This article presents the development of a neural
network cognitive model for the classification and detection of
different frequency signals. The basic structure of the implemented
neural network was inspired on the perception process that humans
generally make in order to visually distinguish between high and low
frequency signals. It is based on the dynamic neural network concept,
with delays. A special two-layer feedforward neural net structure was
successfully implemented, trained and validated, to achieve
minimum target error. Training confirmed that this neural net
structure descents and converges to a human perception classification
solution, even when far away from the target.
Abstract: A sensitive and specific method for quantitative
determination of aflatoxins(B1, B2, G1,G2), deoxynivalenol,
fumonisin(B1,B2), ochratoxin A, zearalenone, T-2 and HT-2 in
roasted and ground grains using liquid chromatography combined
with tandem mass spectrometry. A double extraction using a
phosphate buffer solution followed by methanol was applied to
achieve effective co extraction of 11 mycotoxins. A multitoxin
immunoaffinity column for all these mycotoxins was used to clean up
the extract. The LODs of mycotoxins were 0.1~6.1 μg/kg, LOQs were
0.3~18.4 μg/kg. Forty seven samples collected from Seoul (Korea) for
mycotoxin contamination monitoring. The results showed that the
occurrence of zearalenone and deoxynivalenol were frequent.
Zearalenone was detected in all samples and deoxynivalenol was
detected in 80.9 % samples in the range 0.626 ~ 29.264 μg/kg and N.D
~ 48.332 μg/kg respectively. Fumonisins and ochratoxin A were
detected in 46.8% samples and 17 % samples respectively, aflatoxins
and T-2/HT-2 toxins were not detected all samples.
Abstract: In data mining, the association rules are used to find
for the associations between the different items of the transactions
database. As the data collected and stored, rules of value can be found
through association rules, which can be applied to help managers
execute marketing strategies and establish sound market frameworks.
This paper aims to use Fuzzy Frequent Pattern growth (FFP-growth)
to derive from fuzzy association rules. At first, we apply fuzzy
partition methods and decide a membership function of quantitative
value for each transaction item. Next, we implement FFP-growth
to deal with the process of data mining. In addition, in order to
understand the impact of Apriori algorithm and FFP-growth algorithm
on the execution time and the number of generated association
rules, the experiment will be performed by using different sizes of
databases and thresholds. Lastly, the experiment results show FFPgrowth
algorithm is more efficient than other existing methods.
Abstract: This paper describes a 2.4 GHz passive switch mixer
and a 5/2.5 GHz voltage-controlled negative Gm oscillator (VCO)
with an inversion-mode MOS varactor. Both circuits are implemented
using a 1P8M 0.13 μm process. The switch mixer has an input
referred 1 dB compression point of -3.89 dBm and a conversion
gain of -0.96 dB when the local oscillator power is +2.5 dBm.
The VCO consumes only 1.75 mW, while drawing 1.45 mA from a
1.2 V supply voltage. In order to reduce the passives size, the VCO
natural oscillation frequency is 5 GHz. A clocked CMOS divideby-
two circuit is used for frequency division and quadrature phase
generation. The VCO has a -109 dBc/Hz phase noise at 1 MHz
frequency offset and a 2.35-2.5 GHz tuning range (after the frequency
division), thus complying with ZigBee requirements.
Abstract: Interactive web-based computer simulations are
needed by the medical community to replicate the experience of
surgical procedures as closely and realistically as possible without
the need to practice on corpses, animals and/or plastic models. In this
paper, we offer a review on current state of the research on
simulations of surgical threads, identify future needs and present our
proposed plans to meet them. Our goal is to create a physics-based
simulator, which will predict the behavior of surgical thread when
subjected to conditions commonly encountered during surgery. To
that end, we will i) develop three dimensional finite element models
based on the Cosserat theory of elasticity ii) test and feedback results
with the medical community and iii) develop a web-based user
interface to run/command our simulator and visualize the results. The
impacts of our research are that i) it will contribute to the
development of a new generation of training for medical school
students and ii) the simulator will be useful to expert surgeons in
developing new, better and less risky procedures.
Abstract: A local wastewater treatment plant (WWTP)
experiencing poor nitrification tracked down high level of
surfactants in the plant-s influent and effluent. The aims of this project were to assess the potential inhibitory effect of surfactants on activated sludge processes. The effect of the
presence of TergitolNP-9, TrigetolNP-7, Trigetol15-S-9,
dodecylbenzene sulphonate (SDBS) and sodium dodecyl
sulfate (SDS) on activated sludge oxygen uptake rate (OUR) and nitrification were assessed. The average concentration of non-ionic and anionic
surfactants in the influent to the local WWTP were 7 and 8.7 mg/L, respectively. Removal of 67% to 90% of the non-ionic and 93-99% of the anionic surfactants tested were measured. All surfactants tested showed inhibitory effects both on OUR
and nitrification. SDS incurred the lowest inhibition whereas
SDBS and NP-9 caused severe inhibition to OUR and
Nitrification. Activated sludge flocs sizes slightly decreased
after 3 hours contact with the surfactant present in the test.
The results obtained indicated that high concentrations of
surfactants are likely to have an adverse effect on the
performance of WWTPs utilizing activated sludge processes.
Abstract: Skip cycle is a working strategy for spark ignition
engines, which allows changing the effective stroke of an engine
through skipping some of the four stroke cycles. This study proposes
a new mechanism to achieve the desired skip-cycle strategy for
internal combustion engines. The air and fuel leakage, which occurs
through the gas exchange, negatively affects the efficiency of the
engine at high speeds and loads. An absolute sealing is assured by
direct use of poppet valves, which are kept in fully closed position
during the skipped mode. All the components of the mechanism were
designed according to the real dimensions of the Anadolu Motor's
gasoline engine and modeled in 3D by means of CAD software. As
the mechanism operates in two modes, two dynamically equivalent
models are established to obtain the force and strength analysis for
critical components.
Abstract: In this paper a new cost function for blind equalization
is proposed. The proposed cost function, referred to as the modified
maximum normalized cumulant criterion (MMNC), is an extension
of the previously proposed maximum normalized cumulant criterion
(MNC). While the MNC requires a separate phase recovery system
after blind equalization, the MMNC performs joint blind equalization
and phase recovery. To achieve this, the proposed algorithm
maximizes a cost function that considers both amplitude and phase of
the equalizer output. The simulation results show that the proposed
algorithm has an improved channel equalization effect than the MNC
algorithm and simultaneously can correct the phase error that the
MNC algorithm is unable to do. The simulation results also show that
the MMNC algorithm has lower complexity than the MNC algorithm.
Moreover, the MMNC algorithm outperforms the MNC algorithm
particularly when the symbols block size is small.
Abstract: Currently in many major cities, public transit schedules
are disseminated through lists of routes, grids of stop times and
static maps. This paper describes a web based geographic information
system which disseminates the same schedule information through
intuitive GIS techniques. Using data from Calgary, Canada, an map
based interface has been created to allow users to see routes, stops and
moving buses all at once. Zoom and pan controls as well as satellite
imagery allows users to apply their personal knowledge about the
local geography to achieve faster, and more pertinent transit results.
Using asynchronous requests to web services, users are immersed
in an application where buses and stops can be added and removed
interactively, without the need to wait for responses to HTTP requests.
Abstract: Three-phase induction machines are today a standard
for industrial electrical drives. Cost, reliability, robustness and maintenance free operation are among the reasons these machines are
replacing dc drive systems. The development of power electronics
and signal processing systems has eliminated one of the greatest
disadvantages of such ac systems, which is the issue of control. With
modern techniques of field oriented vector control, the task of
variable speed control of induction machines is no longer a
disadvantage. The need to increase system performance, particularly
when facing limits on the power ratings of power supplies and
semiconductors, motivates the use of phase number other than three,
In this paper a novel scheme of connecting two, three phase
induction motors in parallel fed by two inverters; viz. VSI and CSI
and their vector control is presented.