Abstract: The paper proposes a unified model for multimedia data retrieval which includes data representatives, content representatives, index structure, and search algorithms. The multimedia data are defined as k-dimensional signals indexed in a multidimensional k-tree structure. The benefits of using the k-tree unified model were demonstrated by running the data retrieval application on a six networked nodes test bed cluster. The tests were performed with two retrieval algorithms, one that allows parallel searching using a single feature, the second that performs a weighted cascade search for multiple features querying. The experiments show a significant reduction of retrieval time while maintaining the quality of results.
Abstract: The assessment of the efficacy of devised Mobile-
Assisted Instructional Modes in Mobile Learning was the focus of
this research. The study adopted pre-test, post-test, control group
quasi-experimental design. Research instruments were developed,
validated and used for collecting data. Findings revealed that the
students exposed to Mobile Task Based Learning Mode (MTBLM) in
using Mobile-Assisted Instruction (MAI) performed significantly
better. The implication of these findings is that, the Audio tutorial
and Practice Mode (ATPM) (Stimulus instruments) of MAI had been
found better over the other modes used in the study.
Abstract: CO2 is the primary anthropogenic greenhouse gas,
accounting for 77% of the human contribution to the greenhouse
effect in 2004. In the recent years, global concentration of CO2 in the
atmosphere is increasing rapidly. CO2 emissions have an impact on
global climate change. Anthropogenic CO2 is emitted primarily from
fossil fuel combustion. Carbon capture and storage (CCS) is one
option for reducing CO2 emissions. There are three major approaches
for CCS: post-combustion capture, pre-combustion capture and
oxyfuel process. Post-combustion capture offers some advantages as
existing combustion technologies can still be used without radical
changes on them.
There are several post combustion gas separation and capture
technologies being investigated, namely; (a) absorption, (b)
cryogenic separation, (c) membrane separation (d) micro algal biofixation
and (e) adsorption. Apart from establishing new techniques,
the exploration of capture materials with high separation performance
and low capital cost are paramount importance. However, the
application of adsorption from either technology, require easily
regenerable and durable adsorbents with a high CO2 adsorption
capacity. It has recently been reported that the cost of the CO2
capture can be reduced by using this technology. In this paper, the
research progress (from experimental results) in adsorbents for CO2
adsorption, storage, and separations were reviewed and future
research directions were suggested as well.
Abstract: Duplicated region detection is a technical method to
expose copy-paste forgeries on digital images. Copy-paste is one
of the common types of forgeries to clone portion of an image
in order to conceal or duplicate special object. In this type of
forgery detection, extracting robust block feature and also high
time complexity of matching step are two main open problems.
This paper concentrates on computational time and proposes a local
block matching algorithm based on block clustering to enhance time
complexity. Time complexity of the proposed algorithm is formulated
and effects of two parameter, block size and number of cluster, on
efficiency of this algorithm are considered. The experimental results
and mathematical analysis demonstrate this algorithm is more costeffective
than lexicographically algorithms in time complexity issue
when the image is complex.
Abstract: A novel robust audio watermarking scheme is
proposed in this paper. In the proposed scheme, the host audio signals
are segmented into frames. Two consecutive frames are assessed if
they are suitable to represent a watermark bit. If so, frequency
transform is performed on these two frames. The compressionexpansion
technique is adopted to generate distortion over the two
frames. The distortion is used to represent one watermark bit.
Psychoacoustic model is applied to calculate local auditory mask to
ensure that the distortion is not audible. The watermarking schemes
using mono and stereo audio signals are designed differently. The
correlation-based detection method is used to detect the distortion
and extract embedded watermark bits. The experimental results show
that the quality degradation caused by the embedded watermarks is
perceptually transparent and the proposed schemes are very robust
against different types of attacks.
Abstract: In order to study the effects of supplemental irrigation, different levels of nitrogen chemical fertilizer and inoculation with rhizobium bacteria on the grain yield of chickpea, an experiment was carried out using split plot arrangement in randomize complete block design with three replication in agricultural researches station of Zanjan, Iran during 2009-2010 cropping season. The factors of experiment consisted of irritation (without irrigation (I1), irrigation at flowering stage (I2), irrigation at flowering and grain filling stages (I3) and full irrigation (I4)) and different levels of nitrogen fertilizer (without using of nitrogen fertilizer (N0), 75 kg.ha-1 (N75), 150 kg.ha-1 (N150) and inoculation with rhizobium bacteria (N4). The results of the analysis of variance showed that the effects of irrigation, nitrogen fertilizer levels and bacterial inoculation, were significant affect on number of pods per plant, number grains per plant, grain weight, grain yield, biological yield and harvest index at 1% probability level. Also Results showed that the grain yield in full irrigation treatment and inoculated with rhizobium bacteria was significantly higher than the other treatments.
Abstract: The aim of current research was to investigate ASLT method suitability for accelerated beer shelf-life determination. The research was accomplished on popular Latvian beer: light filtrated and unfiltered pasteurized beer with alcohol content 5.2%; dark filtrated pasteurized beer with alcohol content 4.2% with shelf-life five months. Bottled in dark glass bottles beer samples were storage during 20 weeks at several temperature regimes: +10±1 °C, +20±1 °C, +30±1 °C, +40±1 °C. Samples quality parameters as physically-chemical and microbiological was tested every two weeks using standard methods. It is possible to determine beer shelf-life rapidly during storage at +30±1 °C for filtered pasteurized light beer by 2.5 times, unfiltered pasteurized light beer by 1.4 times and for filtered pasteurized dark beer by 1.7 times. During preset experiments it was proved, that it is possible to determine beer shelf-life rapidly using ASLT method if beer storage temperature could be increased by +10±1 °C.
Abstract: This paper presents a physics-based model for the
high-voltage fast recovery diodes. The model provides a good
trade-off between reverse recovery time and forward voltage drop
realized through a combination of lifetime control and emitter
efficiency reduction techniques. The minority carrier lifetime can be
extracted from the reverse recovery transient response and forward
characteristics. This paper also shows that decreasing the amount of
the excess carriers stored in the drift region will result in softer
characteristics which can be achieved using a lower doping level. The
developed model is verified by experiment and the measurement data
agrees well with the model.
Abstract: Supersonic open and closed cavity flows are investigated experimentally and computationally. Free stream Mach number of two is set. Schlieren imaging is used to visualise the flow behaviour showing stark differences between open and closed. Computational Fluid Dynamics (CFD) is used to simulate open cavity of flow with aspect ratio of 4. A rear wall treatment is implemented in order to pursue a simple passive control approach. Good qualitative agreement is achieved between the experimental flow visualisation and the CFD in terms of the expansion-shock waves system. The cavity oscillations are shown to be dominated by the first and third Rossister modes combining to high fluctuations of non-linear nature above the cavity rear edge. A simple rear wall treatment in terms of a hole shows mixed effect on the flow oscillations, RMS contours, and time history density fluctuations are given and analysed.
Abstract: Determining how many virtual machines a Linux host
could run can be a challenge. One of tough missions is to find the
balance among performance, density and usability. Now KVM
hypervisor has become the most popular open source full
virtualization solution. It supports several ways of running guests with
more memory than host really has. Due to large differences between
minimum and maximum guest memory requirements, this paper
presents initial results on same-page merging, ballooning and live
migration techniques that aims at optimum memory usage on
KVM-based cloud platform. Given the design of initial experiments,
the results data is worth reference for system administrators. The
results from these experiments concluded that each method offers
different reliability tradeoff.
Abstract: Phaseolus coccineus L. is the third most important
cultivated Phaseolus species in the world. It is widely grown in
Latvia due to its earliness, good taste and uniform and qualitative
yield. Experiments were carried out in the laboratories of Department
of Food Technology and Agronomical Analysis Scientific Laboratory
at Latvia Universityof Agriculture. Beans (Phaseolus coccineus L.)
crude protein, crude ash content as well as colour measurements were
analyzed. Results show, that brown coloured beans have less crude
protein content than others, and ash content have significant
differences.
Abstract: Classification of electroencephalogram (EEG) signals
extracted during mental tasks is a technique that is actively pursued
for Brain Computer Interfaces (BCI) designs. In this paper, we
compared the classification performances of univariateautoregressive
(AR) and multivariate autoregressive (MAR) models
for representing EEG signals that were extracted during different
mental tasks. Multilayer Perceptron (MLP) neural network (NN)
trained by the backpropagation (BP) algorithm was used to classify
these features into the different categories representing the mental
tasks. Classification performances were also compared across
different mental task combinations and 2 sets of hidden units (HU): 2
to 10 HU in steps of 2 and 20 to 100 HU in steps of 20. Five different
mental tasks from 4 subjects were used in the experimental study and
combinations of 2 different mental tasks were studied for each
subject. Three different feature extraction methods with 6th order
were used to extract features from these EEG signals: AR
coefficients computed with Burg-s algorithm (ARBG), AR
coefficients computed with stepwise least square algorithm (ARLS)
and MAR coefficients computed with stepwise least square
algorithm. The best results were obtained with 20 to 100 HU using
ARBG. It is concluded that i) it is important to choose the suitable
mental tasks for different individuals for a successful BCI design, ii)
higher HU are more suitable and iii) ARBG is the most suitable
feature extraction method.
Abstract: In this paper, we propose a new method to distinguish
between arousal and relaxation states by using multiple features
acquired from a photoplethysmogram (PPG) and support vector
machine (SVM). To induce arousal and relaxation states in subjects, 2
kinds of sound stimuli are used, and their corresponding biosignals are
obtained using the PPG sensor. Two features–pulse to pulse interval
(PPI) and pulse amplitude (PA)–are extracted from acquired PPG
data, and a nonlinear classification between arousal and relaxation is
performed using SVM.
This methodology has several advantages when compared with
previous similar studies. Firstly, we extracted 2 separate features from
PPG, i.e., PPI and PA. Secondly, in order to improve the classification
accuracy, SVM-based nonlinear classification was performed.
Thirdly, to solve classification problems caused by generalized
features of whole subjects, we defined each threshold according to
individual features.
Experimental results showed that the average classification
accuracy was 74.67%. Also, the proposed method showed the better
identification performance than the single feature based methods.
From this result, we confirmed that arousal and relaxation can be
classified using SVM and PPG features.
Abstract: This paper presents results of measurements campaign
carried out at a carrier frequency of 24GHz with the help of TPLINK
router in indoor line-of-sight (LOS) scenarios. Firstly, the
radio wave propagation strategies are analyzed in some rooms with
router of point to point Ad hoc network. Then floor attenuation is
defined for 3 floors in experimental region. The free space model and
dual slope models are modified by considering the influence of
corridor conditions on each floor. Using these models, indoor signal
attenuation can be estimated in modeling of indoor radio wave
propagation. These results and modified models can also be used in
planning the networks of future personal communications services.
Abstract: Organic farmers across Saskatchewan face soil
phosphorus (P) shortages. Due to the restriction on inputs in organic
systems, farmers rely on crop rotation and naturally-occurring
arbuscular mycorrhizal fungi (AMF) for plant P supply. Crop rotation
is important for disease, pest, and weed management. Crops that are
not colonized by AMF (non-mycorrhizal) can decrease colonization
of a following crop. An experiment was performed to quantify soil P
cycling in four cropping sequences under organic management and
determine if mustard (non-mycorrhizal) was delaying the
colonization of subsequent wheat. Soils from the four cropping
sequences were measured for inorganic soil P (Pi), AMF spore
density (SD), phospholipid fatty acid analysis (PLFA, for AMF
biomarker counts), and alkaline phosphatase activity (ALPase,
related to AMF metabolic activity). Plants were measured for AMF
colonization and P content and uptake of above-ground biomass. A
lack of difference in AMF activity indicated that mustard was not
depressing colonization. Instead, AMF colonization was largely
determined by crop type and crop rotation.
Abstract: This paper presents a multiband CPW-fed slot antenna
with L-slot bowtie tuning stub. The proposed antenna has been
designed for PCS 1900, UMTS, WLAN 802.11 a/b/g and bluetooth
applications, with a cost-effective FR4 substrate. The proposed
antenna still radiate as omni-directional in azimuth plane and
sufficient bandwidth for all above mentions. The proposed antenna
works as dual-wideband, bandwidth at low frequency band and high
frequency are about 45.49 % and 22.39 % respectively. The
experimental results of the constructed prototype are presented and
also compared with simulation results using a commercial software
tool.
Abstract: In this paper, a direct torque control - space vector
modulation (DTC-SVM) scheme is presented for a six-phase speed
and voltage sensorless induction motor (IM) drive. The decoupled
torque and stator flux control is achieved based on IM stator flux field orientation. The rotor speed is detected by on-line estimating of
the rotor angular slip speed and stator vector flux speed. In addition, a simple method is introduced to estimate the stator resistance.
Moreover in this control scheme the voltage sensors are eliminated
and actual motor phase voltages are approximated by using PWM
inverter switching times and the dc link voltage. Finally, some simulation and experimental results are presented to verify the
effectiveness and capability of the proposed control scheme.
Abstract: In a metal forming process, the friction between the
material and the tools influences the process by modifying the stress
distribution of the workpiece. This frictional behaviour is often taken
into account by using a constant coefficient of friction in the finite
element simulations of sheet metal forming processes. However,
friction coefficient varies in time and space with many parameters.
The Stribeck friction model is investigated in this study to predict
springback behaviour of AA6061-T4 sheets during V-bending
process. The coefficient of friction in Stribeck curve depends on
sliding velocity and contact pressure. The plane-strain bending
process is simulated in ABAQUS/Standard. We compared the
computed punch load-stroke curves and springback related to the
constant coefficient of friction with the defined friction model. The
results clearly showed that the new friction model provides better
agreement between experiments and results of numerical simulations.
The influence of friction models on stress distribution in the
workpiece is also studied numerically
Abstract: This paper presents an approach for the determination of the optimal cutting parameters (spindle speed, feed rate, depth of cut and engagement) leading to minimum surface roughness in face milling of high silicon stainless steel by coupling neural network (NN) and Electromagnetism-like Algorithm (EM). In this regard, the advantages of statistical experimental design technique, experimental measurements, artificial neural network, and Electromagnetism-like optimization method are exploited in an integrated manner. To this end, numerous experiments on this stainless steel were conducted to obtain surface roughness values. A predictive model for surface roughness is created by using a back propogation neural network, then the optimization problem was solved by using EM optimization. Additional experiments were performed to validate optimum surface roughness value predicted by EM algorithm. It is clearly seen that a good agreement is observed between the predicted values by EM coupled with feed forward neural network and experimental measurements. The obtained results show that the EM algorithm coupled with back propogation neural network is an efficient and accurate method in approaching the global minimum of surface roughness in face milling.
Abstract: We present an Electronic Nose (ENose), which is
aimed at identifying the presence of one out of two gases, possibly
detecting the presence of a mixture of the two. Estimation of the
concentrations of the components is also performed for a volatile
organic compound (VOC) constituted by methanol and acetone, for
the ranges 40-400 and 22-220 ppm (parts-per-million), respectively.
Our system contains 8 sensors, 5 of them being gas sensors (of the
class TGS from FIGARO USA, INC., whose sensing element is a tin
dioxide (SnO2) semiconductor), the remaining being a temperature
sensor (LM35 from National Semiconductor Corporation), a
humidity sensor (HIH–3610 from Honeywell), and a pressure sensor
(XFAM from Fujikura Ltd.).
Our integrated hardware–software system uses some machine
learning principles and least square regression principle to identify at
first a new gas sample, or a mixture, and then to estimate the
concentrations. In particular we adopt a training model using the
Support Vector Machine (SVM) approach with linear kernel to teach
the system how discriminate among different gases. Then we apply
another training model using the least square regression, to predict
the concentrations.
The experimental results demonstrate that the proposed
multiclassification and regression scheme is effective in the
identification of the tested VOCs of methanol and acetone with
96.61% correctness. The concentration prediction is obtained with
0.979 and 0.964 correlation coefficient for the predicted versus real
concentrations of methanol and acetone, respectively.