Abstract: In this paper, based on the work in [1], we further give
a general model for acquiring knowledge, which first focuses on the
research of how and when things involved in problems are made
then describes the goals, the energy and the time to give an optimum
model to decide how many related things are supposed to be involved
in. Finally, we acquire knowledge from this model in which there are
the attributes, actions and connections of the things involved at the
time when they are born and the time in their life. This model not
only improves AI theories, but also surely brings the effectiveness
and accuracy for AI system because systems are given more
knowledge when reasoning or computing is used to bring about
results.
Abstract: Healthcare providers sometimes use the power of
humor as a treatment and therapy for buffering mental health or easing
mental disorders because humor can provide relief from distress and
conflict. Humor is also very suitable for advertising because of similar
benefits. This study carefully examines humor's widespread use in
advertising and identifies relationships among humor mechanisms,
female depictions, and product types. The purpose is to conceptualize
how humor theories can be used not only to successfully define a
product as fitting within one of four color categories of the product
color matrix, but also to identify compelling contemporary female
depictions through humor in ads. The results can offer an idealization
for marketing managers and consumers to help them understand how
female role depictions can be effectively used with humor in ads. The
four propositions developed herein are derived from related literature,
through the identification of marketing strategy formulations that
achieve product memory enhancement by adopting humor
mechanisms properly matched with female role depictions.
Abstract: Nowadays, obtaining traditional statistics and reports
is not adequate for the needs of organizational managers. The
managers need to analyze and to transform the raw data into
knowledge in the world filled with information. Therefore in this
regard various processes have been developed. In the meantime the
artificial intelligence-based processes are used and the new topics
such as business intelligence and knowledge discovery have
emerged. In the current paper it is sought to study the business
intelligence and its applications in the organizations.
Abstract: Information on weed distribution within the field is
necessary to implement spatially variable herbicide application.
Since hand labor is costly, an automated weed control system could be
feasible. This paper deals with the development of an algorithm for
real time specific weed recognition system based on Histogram
Analysis of an image that is used for the weed classification. This
algorithm is specifically developed to classify images into broad and
narrow class for real-time selective herbicide application. The
developed system has been tested on weeds in the lab, which have
shown that the system to be very effectiveness in weed identification.
Further the results show a very reliable performance on images of
weeds taken under varying field conditions. The analysis of the results
shows over 95 percent classification accuracy over 140 sample images
(broad and narrow) with 70 samples from each category of weeds.
Abstract: Shippers are concentrating on the core competency to
stay competitive and outsourcing the logistic activities to the third
party who is expert in this field. This third party logistics (3PL) is
drawing the due attention at government, industrial, academicians
and practitioner-s levels. If the logistics cost in India can be brought
down from the current level of 13% of GDP to 9% (level in the U.S.),
the savings would be around Rs 3 lakh crore approximately per
annum. But the problem with the shippers is to select the suitable
3PL provider. Various criteria for selection of 3PL have been listed
in the literature which are discussed in the present literature review.
Every shipper will select the criteria suitable to its own requirement
which have to be dynamically reviewed time to time so as to fit in the
ever changing environment.
Abstract: The mitigation of crop loss due to damaging freezes
requires accurate air temperature prediction models. Previous work
established that the Ward-style artificial neural network (ANN) is a
suitable tool for developing such models. The current research
focused on developing ANN models with reduced average prediction
error by increasing the number of distinct observations used in
training, adding additional input terms that describe the date of an
observation, increasing the duration of prior weather data included in
each observation, and reexamining the number of hidden nodes used
in the network. Models were created to predict air temperature at
hourly intervals from one to 12 hours ahead. Each ANN model,
consisting of a network architecture and set of associated parameters,
was evaluated by instantiating and training 30 networks and
calculating the mean absolute error (MAE) of the resulting networks
for some set of input patterns. The inclusion of seasonal input terms,
up to 24 hours of prior weather information, and a larger number of
processing nodes were some of the improvements that reduced
average prediction error compared to previous research across all
horizons. For example, the four-hour MAE of 1.40°C was 0.20°C, or
12.5%, less than the previous model. Prediction MAEs eight and 12
hours ahead improved by 0.17°C and 0.16°C, respectively,
improvements of 7.4% and 5.9% over the existing model at these
horizons. Networks instantiating the same model but with different
initial random weights often led to different prediction errors. These
results strongly suggest that ANN model developers should consider
instantiating and training multiple networks with different initial
weights to establish preferred model parameters.
Abstract: In this paper, we establish several oscillation criteria for the nonlinear second-order damped delay dynamic equation r(t)|xΔ(t)|β-1xΔ(t)Δ + p(t)|xΔσ(t)|β-1xΔσ(t) + q(t)f(x(τ (t))) = 0 on an arbitrary time scale T, where β > 0 is a constant. Our results generalize and improve some known results in which β > 0 is a quotient of odd positive integers. Some examples are given to illustrate our main results.
Abstract: Truncated multiplier is a good candidate for digital
signal processing (DSP) applications including finite impulse
response (FIR) and discrete cosine transform (DCT). Through
truncated multiplier a significant reduction in Field Programmable
Gate Array (FPGA) resources can be achieved. This paper presents
for the first time a comparison of resource utilization of Spartan-3AN
and Virtex-5 implementation of standard and truncated multipliers
using Very High Speed Integrated Circuit Hardware Description
Language (VHDL). The Virtex-5 FPGA shows significant
improvement as compared to Spartan-3AN FPGA device. The
Virtex-5 FPGA device shows better performance with a percentage
ratio of number of occupied slices for standard to truncated
multipliers is increased from 40% to 73.86% as compared to Spartan-
3AN is decreased from 68.75% to 58.78%. Results show that the
anomaly in Spartan-3AN FPGA device average connection and
maximum pin delay have been efficiently reduced in Virtex-5 FPGA
device.
Abstract: More and more natural disasters are happening every
year: floods, earthquakes, volcanic eruptions, etc. In order to reduce
the risk of possible damages, governments all around the world are
investing into development of Early Warning Systems (EWS) for
environmental applications. The most important task of the EWS is
identification of the onset of critical situations affecting environment
and population, early enough to inform the authorities and general
public. This paper describes an approach for monitoring of flood
protections systems based on machine learning methods. An
Artificial Intelligence (AI) component has been developed for
detection of abnormal dike behaviour. The AI module has been
integrated into an EWS platform of the UrbanFlood project (EU
Seventh Framework Programme) and validated on real-time
measurements from the sensors installed in a dike.
Abstract: During last decades, worldwide researchers dedicated
efforts to develop machine-based seismic Early Warning systems,
aiming at reducing the huge human losses and economic damages.
The elaboration time of seismic waveforms is to be reduced in order
to increase the time interval available for the activation of safety
measures. This paper suggests a Data Mining model able to correctly
and quickly estimate dangerousness of the running seismic event.
Several thousand seismic recordings of Japanese and Italian
earthquakes were analyzed and a model was obtained by means of a
Bayesian Network (BN), which was tested just over the first
recordings of seismic events in order to reduce the decision time and
the test results were very satisfactory.
The model was integrated within an Early Warning System
prototype able to collect and elaborate data from a seismic sensor
network, estimate the dangerousness of the running earthquake and
take the decision of activating the warning promptly.
Abstract: Super resolution (SR) technologies are now being
applied to video to improve resolution. Some TV sets are now
equipped with SR functions. However, it is not known if super
resolution image reconstruction (SRR) for TV really works or not.
Super resolution with non-linear signal processing (SRNL) has
recently been proposed. SRR and SRNL are the only methods for
processing video signals in real time. The results from subjective
assessments of SSR and SRNL are described in this paper. SRR video
was produced in simulations with quarter precision motion vectors and
100 iterations. These are ideal conditions for SRR. We found that the
image quality of SRNL is better than that of SRR even though SRR
was processed under ideal conditions.
Abstract: Air infiltration in mass scale industrial applications of
bio char production is inevitable. The presence of oxygen during the
carbonization process is detrimental to the production of biochar yield
and properties. The experiment was carried out on several wood
species in a fixed-bed pyrolyser under various fractions of oxygen
ranging from 0% to 11% by varying nitrogen and oxygen composition
in the pyrolysing gas mixtures at desired compositions. The bed
temperature and holding time were also varied. Process optimization
was carried out by Response Surface Methodology (RSM) by
employing Central Composite Design (CCD) using Design Expert 6.0
Software. The effect of oxygen ratio and holding time on biochar yield
within the range studied were statistically significant. From the
analysis result, optimum condition of 15.2% biochar yield of
mangrove wood was predicted at pyrolysis temperature of 403 oC,
oxygen percentage of 2.3% and holding time of two hours. This
prediction agreed well with the experiment finding of 15.1% biochar
yield.
Abstract: This paper proposes an application of the differential
evolution (DE) algorithm for solving the economic dispatch problem
(ED). Furthermore, the regenerating population procedure added to
the conventional DE in order to improve escaping the local minimum
solution. To test performance of DE algorithm, three thermal
generating units with valve-point loading effects is used for testing.
Moreover, investigating the DE parameters is presented. The
simulation results show that the DE algorithm, which had been
adjusted parameters, is better convergent time than other optimization
methods.
Abstract: This research presents the development of simulation
modeling for WIP management in semiconductor fabrication.
Manufacturing simulation modeling is needed for productivity
optimization analysis due to the complex process flows involved
more than 35 percent re-entrance processing steps more than 15 times
at same equipment. Furthermore, semiconductor fabrication required
to produce high product mixed with total processing steps varies from
300 to 800 steps and cycle time between 30 to 70 days. Besides the
complexity, expansive wafer cost that potentially impact the
company profits margin once miss due date is another motivation to
explore options to experiment any analysis using simulation
modeling. In this paper, the simulation model is developed using
existing commercial software platform AutoSched AP, with
customized integration with Manufacturing Execution Systems
(MES) and Advanced Productivity Family (APF) for data collections
used to configure the model parameters and data source. Model
parameters such as processing steps cycle time, equipment
performance, handling time, efficiency of operator are collected
through this customization. Once the parameters are validated, few
customizations are made to ensure the prior model is executed. The
accuracy for the simulation model is validated with the actual output
per day for all equipments. The comparison analysis from result of
the simulation model compared to actual for achieved 95 percent
accuracy for 30 days. This model later was used to perform various
what if analysis to understand impacts on cycle time and overall
output. By using this simulation model, complex manufacturing
environment like semiconductor fabrication (fab) now have
alternative source of validation for any new requirements impact
analysis.
Abstract: In this study, the kinetic of biogas production was studied by performing a series laboratory experiment using rumen fluid of animal ruminant as inoculums. Cattle manure as substrate was inoculated by rumen fluid to the anaerobic biodigester. Laboratory experiments using 400 ml biodigester were performed in batch operation mode. Given 100 grams of fresh cattle manure was fed to each biodigester and mixed with rumen fluid by manure : rumen weight ratio of 1:1 (MR11). The operating temperatures were varied at room temperature and 38.5 oC. The cumulative volume of biogas produced was used to measure the biodigester performance. The research showed that the rumen fluid inoculated to biodigester gave significant effect to biogas production (P
Abstract: Usually, the solid-fuel flow of an iron ore sinter plant
consists of different types of the solid-fuels, which differ from each
other. Information about the composition of the solid-fuel flow
usually comes every 8-24 hours. It can be clearly seen that this
information cannot be used to control the sintering process in real
time. Due to this, we propose an expert system which uses indirect
measurements from the process in order to obtain the composition of
the solid-fuel flow by solving an optimization task. Then this
information can be used to control the sintering process. The
proposed technique can be successfully used to improve sinter
quality and reduce the amount of solid-fuel used by the process.
Abstract: To compress, improve bit error performance and also enhance 2D images, a new scheme, called Iterative Cellular-Turbo System (IC-TS) is introduced. In IC-TS, the original image is partitioned into 2N quantization levels, where N is denoted as bit planes. Then each of the N-bit-plane is coded by Turbo encoder and transmitted over Additive White Gaussian Noise (AWGN) channel. At the receiver side, bit-planes are re-assembled taking into consideration of neighborhood relationship of pixels in 2-D images. Each of the noisy bit-plane values of the image is evaluated iteratively using IC-TS structure, which is composed of equalization block; Iterative Cellular Image Processing Algorithm (ICIPA) and Turbo decoder. In IC-TS, there is an iterative feedback link between ICIPA and Turbo decoder. ICIPA uses mean and standard deviation of estimated values of each pixel neighborhood. It has extra-ordinary satisfactory results of both Bit Error Rate (BER) and image enhancement performance for less than -1 dB Signal-to-Noise Ratio (SNR) values, compared to traditional turbo coding scheme and 2-D filtering, applied separately. Also, compression can be achieved by using IC-TS systems. In compression, less memory storage is used and data rate is increased up to N-1 times by simply choosing any number of bit slices, sacrificing resolution. Hence, it is concluded that IC-TS system will be a compromising approach in 2-D image transmission, recovery of noisy signals and image compression.
Abstract: A dual-reciprocity boundary element method is presented
for the numerical solution of a class of axisymmetric elastodynamic
problems. The domain integrals that arise in the integrodifferential
formulation are converted to line integrals by using the
dual-reciprocity method together suitably constructed interpolating
functions. The second order time derivatives of the displacement
in the governing partial differential equations are suppressed by
using Laplace transformation. In the Laplace transform domain, the
problem under consideration is eventually reduced to solving a system
of linear algebraic equations. Once the linear algebraic equations are
solved, the displacement and stress fields in the physical domain can
be recovered by using a numerical technique for inverting Laplace
transforms.
Abstract: The main purpose of the study was to determine whether students- interpretation achievement differed with the use of various multimedia presentation types. Four groups of students, text only (T), audio only (A), text and audio (TA), text and image (TI), were arranged and they were presented the same story via different types of multimedia presentations. Inference achievement was measured by a critical thinking inference test. Higher mean scores for the TA group compared to the other three groups were found. Also when compared pairwise, interpretation achievement of the TA group differed significantly from scores of the T and TI groups. These differences were interpreted with the increased cognitive load. Increased cognitive load for the TA group may have invited students to put more effort into comprehending the text, thus resulting in better test scores. Findings of the study can be seen as a sign of the importance of learning situations and learning outcomes in multimedia-supported learning environments and may have practical benefits for instructional designers.
Abstract: Protective coatings that resist oxide scale growth and
decrease chromium evaporation are necessary to make stainless steel
interconnect materials for long-term durable operation of solid oxide
fuel cells (SOFCs). In this study a layer of cobalt was electroplated
on the surface of AISI 441 ferritic stainless steel which is used in
solid oxide fuel cells for interconnect applications. The oxidation
behavior of coated substrates was studied as a function of time at
operating conditions of SOFCs. Cyclic oxidation has been also tested
at 800ºC for 100 cycles. Cobalt coating during isothermal oxidation
caused to the oxide growth resistance by limiting the outward
diffusion of Cr cation and the inward diffusion of oxygen anion.
Results of cyclic oxidation exhibited that coated substrates
demonstrate an excellent resistance against the spallation and
cracking.