Abstract: This paper demonstrates the bus location system for
the route bus through the experiment in the real environment. A
bus location system is a system that provides information such as
the bus delay and positions. This system uses actual services and
positions data of buses, and those information should match data
on the database. The system has two possible problems. One, the
system could cost high in preparing devices to get bus positions.
Two, it could be difficult to match services data of buses. To avoid
these problems, we have developed this system at low cost and short
time by using the smart phone with GPS and the bus route system.
This system realizes the path planning considering bus delay and
displaying position of buses on the map. The bus location system
was demonstrated on route buses with smart phones for two months.
Abstract: In this paper, an analytical modeling is presentated to
describe the channel noise in GME SGT/CGT MOSFET, based on
explicit functions of MOSFETs geometry and biasing conditions for
all channel length down to deep submicron and is verified with the
experimental data. Results shows the impact of various parameters
such as gate bias, drain bias, channel length ,device diameter and gate
material work function difference on drain current noise spectral
density of the device reflecting its applicability for circuit design
applications.
Abstract: Biological Ammonia removal (nitrification), the
oxidation of ammonia to nitrate catalyzed by bacteria, is a key part of
global nitrogen cycling. In the first step of nitrification,
chemolithoautotrophic ammonia oxidizer transform ammonia to
nitrite, this subsequently oxidized to nitrate by nitrite oxidizing
bacteria. This process can be affected by several factors. In this study
the effect of influent COD on biological ammonia removal in a
bench-scale biological reactor was investigated. Experiments were
carried out using synthetic wastewater. The initial ammonium
concentration was 25mgNH4
+-N L-1. The effect of COD between
247.55±1.8 and 601.08±3.24mgL-1 on biological ammonia removal
was investigated by varying the COD loading supplied to reactor.
From the results obtained in this study it could be concluded in the
range of 247.55±1.8 to 351.35±2.05mgL-1, there is a direct
relationship between amount of COD and ammonia removal.
However more than 351.35±2.05 up to 601.08±3.24mgL-1 were
found an indirect relationship between them.
Abstract: A numerical simulation of micro Poiseuille flow has
performed for rarefied and compressible flow at slip flow regimes.
The wall roughness is simulated in two cases with triangular
microelements and random micro peaks distributed on wall surfaces
to study the effects of roughness shape and distribution on flow field.
Two values of Mach and Knudsen numbers have used to investigate
the effects of rarefaction as well as compressibility. The numerical
results have also checked with available theoretical and experimental
relations and good agreements has achieved. High influence of
roughness shape can be seen for both compressible and
incompressible rarefied flows. In addition it is found that rarefaction
has more significant effect on flow field in microchannels with
higher relative roughness. It is also found that compressibility has
more significant effects on Poiseuille number when relative
roughness increases.
Abstract: At the present, auto part industries have become higher challenge in strategy market. As this consequence, manufacturers need to have better response to customers in terms of quality, cost, and delivery time. Moreover, they need to have a good management in factory to comply with international standard maximum capacity and lower cost. This would lead companies to have to order standard part from aboard and become the major cost of inventory. The development of auto part research by recycling materials experiment is to compare the auto parts from recycle materials to international auto parts (CKD). Factors studied in this research were the recycle material ratios of PU-foam, felt, and fabric. Results of recycling materials were considered in terms of qualities and properties on the parameters such as weight, sound absorption, water absorption, tensile strength, elongation, and heat resistance with the CKD. The results were showed that recycling materials would be used to replace for the CKD.
Abstract: This paper presents a dynamic adaptation scheme for
the frequency of inter-deme migration in distributed genetic algorithms
(GA), and its VLSI hardware design. Distributed GA,
or multi-deme-based GA, uses multiple populations which evolve
concurrently. The purpose of dynamic adaptation is to improve
convergence performance so as to obtain better solutions. Through
simulation experiments, we proved that our scheme achieves better
performance than fixed frequency migration schemes.
Abstract: Undular hydraulic jumps are illustrated by a smooth
rise of the free surface followed by a train of stationary waves. They
are sometimes experienced in natural waterways and rivers. The
characteristics of undular hydraulic jumps are studied here. The
height, amplitude and the main characteristics of undular jump is
depended on the upstream Froude number and aspect ratio. The
experiments were done on the smooth bed flume. These results
compared with other researches and the main characteristics of the
undular hydraulic jump were studied in this article.
Abstract: Ramadan requires individuals to abstain from food and fluid intake between sunrise and sunset; physiological considerations predict that poorer mood, physical performance and mental performance will result. In addition, any difficulties will be worsened because preparations for fasting and recovery from it often mean that nocturnal sleep is decreased in length, and this independently affects mood and performance.
A difficulty of interpretation in many studies is that the observed changes could be due to fasting but also to the decreased length of sleep and altered food and fluid intakes before and after the daytime fasting. These factors were separated in this study, which took place over three separate days and compared the effects of different durations of fasting (4, 8 or 16h) upon a wide variety of measures (including subjective and objective assessments of performance, body composition, dehydration and responses to a short bout of exercise) - but with an unchanged amount of nocturnal sleep, controlled supper the previous evening, controlled intakes at breakfast and daytime naps not being allowed. Many of the negative effects of fasting observed in previous studies were present in this experiment also. These findings indicate that fasting was responsible for many of the changes previously observed, though some effect of sleep loss, particularly if occurring on successive days (as would occur in Ramadan) cannot be excluded.
Abstract: The performance and the plasma created by a pulsed
magnetoplasmadynamic thruster for small satellite application is
studied to understand better the ablation and plasma propagation
processes occurring during the short-time discharge. The results can
be applied to improve the quality of the thruster in terms of efficiency,
and to tune the propulsion system to the needs required by the satellite
mission. Therefore, plasma measurements with a high-speed camera
and induction probes, and performance measurements of mass bit
and impulse bit were conducted. Values for current sheet propagation
speed, mean exhaust velocity and thrust efficiency were derived from
these experimental data. A maximum in current sheet propagation
was found by the high-speed camera measurements for a medium
energy input and confirmed by the induction probes. A quasilinear
tendency between the mass bit and the energy input, the current
action integral respectively, was found, as well as a linear tendency
between the created impulse and the discharge energy. The highest
mean exhaust velocity and thrust efficiency was found for the highest
energy input.
Abstract: Pharmaceutical industries and effluents of sewage treatment plants are the main sources of residual pharmaceuticals in water resources. These emergent pollutants may adversely impact the biophysical environment. Pharmaceutical industries often generate wastewater that changes in characteristics and quantity depending on the used manufacturing processes. Carbamazepine (CBZ), {5Hdibenzo [b,f]azepine-5-carboxamide, (C15H12N2O)}, is a significant non-biodegradable pharmaceutical contaminant in the Jordanian pharmaceutical wastewater, which is not removed by the activated sludge processes in treatment plants. Activated carbon may potentially remove that pollutant from effluents, but the high cost involved suggests that more attention should be given to the potential use of low-cost materials in order to reduce cost and environmental contamination. Powders of Jordanian non-metallic raw materials namely, Azraq Bentonite (AB), Kaolinite (K), and Zeolite (Zeo) were activated (acid and thermal treatment) and evaluated by removing CBZ. The results of batch and column techniques experiments showed around 46% and 67% removal of CBZ respectively.
Abstract: An accurate and proficient artificial neural network
(ANN) based genetic algorithm (GA) is developed for predicting of
nanofluids viscosity. A genetic algorithm (GA) is used to optimize
the neural network parameters for minimizing the error between the
predictive viscosity and the experimental one. The experimental
viscosity in two nanofluids Al2O3-H2O and CuO-H2O from 278.15
to 343.15 K and volume fraction up to 15% were used from
literature. The result of this study reveals that GA-NN model is
outperform to the conventional neural nets in predicting the viscosity
of nanofluids with mean absolute relative error of 1.22% and 1.77%
for Al2O3-H2O and CuO-H2O, respectively. Furthermore, the results
of this work have also been compared with others models. The
findings of this work demonstrate that the GA-NN model is an
effective method for prediction viscosity of nanofluids and have
better accuracy and simplicity compared with the others models.
Abstract: The belief K-modes method (BKM) approach is a new
clustering technique handling uncertainty in the attribute values of
objects in both the cluster construction task and the classification one.
Like the standard version of this method, the BKM results depend on
the chosen initial modes. So, one selection method of initial modes
is developed, in this paper, aiming at improving the performances of
the BKM approach. Experiments with several sets of real data show
that by considered the developed selection initial modes method, the
clustering algorithm produces more accurate results.
Abstract: The performance of schedules released to a shop floor may greatly be affected by unexpected disruptions. Thus, this paper considers the flexible job shop scheduling problem when processing times of some operations are represented by a uniform distribution with given lower and upper bounds. The objective is to find a predictive schedule that can deal with this uncertainty. The paper compares two genetic approaches to obtain predictive schedule. To determine the performance of the predictive schedules obtained by both approaches, an experimental study is conducted on a number of benchmark problems.
Abstract: For more than 120 years, gold mining formed the
backbone the South Africa-s economy. The consequence of mine
closure was observed in large-scale land degradation and widespread
pollution of surface water and groundwater. This paper investigates
the feasibility of using natural zeolite in removing heavy metals
contaminating the Wonderfonteinspruit Catchment Area (WCA), a
water stream with high levels of heavy metals and radionuclide
pollution. Batch experiments were conducted to study the adsorption
behavior of natural zeolite with respect to Fe2+, Mn2+, Ni2+, and Zn2+.
The data was analysed using the Langmuir and Freudlich isotherms.
Langmuir was found to correlate the adsorption of Fe2+, Mn2+, Ni2+,
and Zn2+ better, with the adsorption capacity of 11.9 mg/g, 1.2 mg/g,
1.3 mg/g, and 14.7 mg/g, respectively. Two kinetic models namely,
pseudo-first order and pseudo second order were also tested to fit the
data. Pseudo-second order equation was found to be the best fit for
the adsorption of heavy metals by natural zeolite. Zeolite
functionalization with humic acid increased its uptake ability.
Abstract: Due to the stringent legislation for emission of diesel
engines and also increasing demand on fuel consumption, the
importance of detailed 3D simulation of fuel injection, mixing and
combustion have been increased in the recent years. In the present
work, FIRE code has been used to study the detailed modeling of
spray and mixture formation in a Caterpillar heavy-duty diesel
engine. The paper provides an overview of the submodels
implemented, which account for liquid spray atomization, droplet
secondary break-up, droplet collision, impingement, turbulent
dispersion and evaporation. The simulation was performed from
intake valve closing (IVC) to exhaust valve opening (EVO). The
predicted in-cylinder pressure is validated by comparing with
existing experimental data. A good agreement between the predicted
and experimental values ensures the accuracy of the numerical
predictions collected with the present work. Predictions of engine
emissions were also performed and a good quantitative agreement
between measured and predicted NOx and soot emission data were
obtained with the use of the present Zeldowich mechanism and
Hiroyasu model. In addition, the results reported in this paper
illustrate that the numerical simulation can be one of the most
powerful and beneficial tools for the internal combustion engine
design, optimization and performance analysis.
Abstract: This paper is a continuation of our daily energy peak load forecasting approach using our modified network which is part of the recurrent networks family and is called feed forward and feed back multi context artificial neural network (FFFB-MCANN). The inputs to the network were exogenous variables such as the previous and current change in the weather components, the previous and current status of the day and endogenous variables such as the past change in the loads. Endogenous variable such as the current change in the loads were used on the network output. Experiment shows that using endogenous and exogenous variables as inputs to the FFFBMCANN rather than either exogenous or endogenous variables as inputs to the same network produces better results. Experiments show that using the change in variables such as weather components and the change in the past load as inputs to the FFFB-MCANN rather than the absolute values for the weather components and past load as inputs to the same network has a dramatic impact and produce better accuracy.
Abstract: Clustering in high dimensional space is a difficult
problem which is recurrent in many fields of science and
engineering, e.g., bioinformatics, image processing, pattern
reorganization and data mining. In high dimensional space some of
the dimensions are likely to be irrelevant, thus hiding the possible
clustering. In very high dimensions it is common for all the objects in
a dataset to be nearly equidistant from each other, completely
masking the clusters. Hence, performance of the clustering algorithm
decreases.
In this paper, we propose an algorithmic framework which
combines the (reduct) concept of rough set theory with the k-means
algorithm to remove the irrelevant dimensions in a high dimensional
space and obtain appropriate clusters. Our experiment on test data
shows that this framework increases efficiency of the clustering
process and accuracy of the results.
Abstract: Quantum computation using qubits made of two component Bose-Einstein condensates (BECs) is analyzed. We construct a general framework for quantum algorithms to be executed using the collective states of the BECs. The use of BECs allows for an increase of energy scales via bosonic enhancement, resulting in two qubit gate operations that can be performed at a time reduced by a factor of N, where N is the number of bosons per qubit. We illustrate the scheme by an application to Deutsch-s and Grover-s algorithms, and discuss possible experimental implementations. Decoherence effects are analyzed under both general conditions and for the experimental implementation proposed.
Abstract: Modeling of the dynamic behavior and motion are
renewed interest in the improved tractive performance of an
intelligent air-cushion tracked vehicle (IACTV). This paper presents
a new dynamical model for the forces on the developed small scale
intelligent air-cushion tracked vehicle moving over swamp peat. The
air cushion system partially supports the 25 % of vehicle total weight
in order to make the vehicle ground contact pressure 7 kN/m2. As the
air-cushion support system can adjust automatically on the terrain, so
the vehicle can move over the terrain without any risks. The springdamper
system is used with the vehicle body to control the aircushion
support system on any undulating terrain by making the
system sinusoidal form. Experiments have been carried out to
investigate the relationships among tractive efficiency, slippage,
traction coefficient, load distribution ratio, tractive effort, motion
resistance and power consumption in given terrain conditions.
Experiment and simulation results show that air-cushion system
improves the vehicle performance by keeping traction coefficient of
71% and tractive efficiency of 62% and the developed model can
meet the demand of transport efficiency with the optimal power
consumption.
Abstract: In this paper a stochastic scenario-based model predictive control applied to molten salt storage systems in concentrated solar tower power plant is presented. The main goal of this study is to build up a tool to analyze current and expected future resources for evaluating the weekly power to be advertised on electricity secondary market. This tool will allow plant operator to maximize profits while hedging the impact on the system of stochastic variables such as resources or sunlight shortage.
Solving the problem first requires a mixed logic dynamic modeling of the plant. The two stochastic variables, respectively the sunlight incoming energy and electricity demands from secondary market, are modeled by least square regression. Robustness is achieved by drawing a certain number of random variables realizations and applying the most restrictive one to the system. This scenario approach control technique provides the plant operator a confidence interval containing a given percentage of possible stochastic variable realizations in such a way that robust control is always achieved within its bounds. The results obtained from many trajectory simulations show the existence of a ‘’reliable’’ interval, which experimentally confirms the algorithm robustness.