Abstract: The need in cognitive radio system for a simple, fast, and independent technique to sense the spectrum occupancy has led to the energy detection approach. Energy detector is known by its dependency on noise variation in the system which is one of its major drawbacks. In this paper, we are aiming to improve its performance by utilizing a weighted collaborative spectrum sensing, it is similar to the collaborative spectrum sensing methods introduced previously in the literature. These weighting methods give more improvement for collaborative spectrum sensing as compared to no weighting case. There is two method proposed in this paper: the first one depends on the channel status between each sensor and the primary user while the second depends on the value of the energy measured in each sensor.
Abstract: The regulatory competence of blood glucose homeostasis might determine the degree of academic performance. The aim of this study was to produce a model of students' alcohol use based on glucose homeostasis control and cognitive functions that might define the pathogenetic mechanism of alcohol's effect on academic performance. The study took six hours and thirty minutes on fasting, involving thirteen male students. Disturbances in cognitive functions, precisely a decrease in the effectiveness of active attention and a faster development of fatigue after four to six hours of mental work in alcohol users, compared to abstainers was statistically proven. These disturbances in alcohol users were retained even after seven to ten days of moderate alcohol use and might be the reason for the low academic performances among students who use alcoholic beverages.
Abstract: Iron ore and coal are the two major important raw
materials being used in Iron making industries. Usually ore fines
containing around 5% Alumina are rejected due to higher proportion
of alumina. Therefore, a technology or process which may reduce
the alumina content by 2% by beneficiation process will be highly
attractive . In addition fine coals with ash content is used nearly 12%
is directly injected in blast furnace. Fast fluidization is a technology
by using dry beneficiation of coal and iron ore can be done. During
the fluidization process the iron ore band coal is fluidized at high
velocity in the riser of a fast fluidized bed, the heavier and coarse
particles is generally settled at the bottom in a dense zone of the riser
while the finer and lighter particle are entrained to the top dilute zone
and then via a cyclone is fed back to the bottom of the riser column.
Most of the alumina and low ash fine size coals being lighter are
expected to move up to the riser and by a natural beneficiation of
ores is expected to take place in the riser. Therefore in this study an
attempt has been made for dry beneficiation of iron ore and coal in a
fluidized bed and its hydrodynamic characterization.
Abstract: Nowadays, the earth is countered with serious problem
of air pollution. This problem has been started from the industrial
revolution and has been faster in recent years, so that leads the earth
to ecological and environmental disaster. One of its results is the
global warming problem and its related increase in global
temperature. The most important factors in air pollution especially in
urban environments are Automobiles and residential buildings that are
the biggest consumers of the fossil energies, so that if the residential
buildings as a big part of the consumers of such energies reduce their
consumption rate, the air pollution will be decreased. Since
Metropolises are the main centers of air pollution in the world,
assessment and analysis of efficient strategies in decreasing air
pollution in such cities, can lead to the desirable and suitable results
and can solve the problem at least in critical level. Tabriz city is one
of the most important metropolises in North west of Iran that about
two million people are living there. for its situation in cold dry
climate, has a high rate of fossil energies consumption that make air
pollution in its urban environment. These two factors, being both
metropolis and in cold dry climate, make this article try to analyze the
strategies of climatic design in old districts of the city and use them in
new districts of the future. These strategies can be used in this city
and other similar cities and pave the way to reduce energy
consumption and related air pollution to save whole world.
Abstract: This paper proposes a novel solution for optimizing
the size and communication overhead of a distributed multiagent
system without compromising the performance. The proposed approach
addresses the challenges of scalability especially when the
multiagent system is large. A modified spectral clustering technique
is used to partition a large network into logically related clusters.
Agents are assigned to monitor dedicated clusters rather than monitor
each device or node. The proposed scalable multiagent system is
implemented using JADE (Java Agent Development Environment)
for a large power system. The performance of the proposed topologyindependent
decentralized multiagent system and the scalable multiagent
system is compared by comprehensively simulating different
fault scenarios. The time taken for reconfiguration, the overall computational
complexity, and the communication overhead incurred are
computed. The results of these simulations show that the proposed
scalable multiagent system uses fewer agents efficiently, makes faster
decisions to reconfigure when a fault occurs, and incurs significantly
less communication overhead.
Abstract: Data stream analysis is the process of computing
various summaries and derived values from large amounts of data
which are continuously generated at a rapid rate. The nature of a
stream does not allow a revisit on each data element. Furthermore,
data processing must be fast to produce timely analysis results. These
requirements impose constraints on the design of the algorithms to
balance correctness against timely responses. Several techniques
have been proposed over the past few years to address these
challenges. These techniques can be categorized as either dataoriented
or task-oriented. The data-oriented approach analyzes a
subset of data or a smaller transformed representation, whereas taskoriented
scheme solves the problem directly via approximation
techniques. We propose a hybrid approach to tackle the data stream
analysis problem. The data stream has been both statistically
transformed to a smaller size and computationally approximated its
characteristics. We adopt a Monte Carlo method in the approximation
step. The data reduction has been performed horizontally and
vertically through our EMR sampling method. The proposed method
is analyzed by a series of experiments. We apply our algorithm on
clustering and classification tasks to evaluate the utility of our
approach.
Abstract: The spectral action balance equation is an equation that
used to simulate short-crested wind-generated waves in shallow water
areas such as coastal regions and inland waters. This equation consists
of two spatial dimensions, wave direction, and wave frequency which
can be solved by finite difference method. When this equation with
dominating propagation velocity terms are discretized using central
differences, stability problems occur when the grid spacing is chosen
too coarse. In this paper, we introduce the splitting modified donorcell
scheme for avoiding stability problems and prove that it is
consistent to the modified donor-cell scheme with same accuracy. The
splitting modified donor-cell scheme was adopted to split the wave
spectral action balance equation into four one-dimensional problems,
which for each small problem obtains the independently tridiagonal
linear systems. For each smaller system can be solved by direct or
iterative methods at the same time which is very fast when performed
by a multi-cores computer.
Abstract: To successfully provide a fast FIR filter with FTT algorithms, overlapped-save algorithms can be used to lower the computational complexity and achieve the desired real-time processing. As the length of the input block increases in order to improve the efficiency, a larger volume of zero padding will greatly increase the computation length of the FFT. In this paper, we use the overlapped block digital filtering to construct a parallel structure. As long as the down-sampling (or up-sampling) factor is an exact multiple lengths of the impulse response of a FIR filter, we can process the input block by using a parallel structure and thus achieve a low-complex fast FIR filter with overlapped-save algorithms. With a long filter length, the performance and the throughput of the digital filtering system will also be greatly enhanced.
Abstract: Recently, a growing interest has emerged on the
development of new and efficient energy sources, due to the inevitable extinction of the nonrenewable energy reserves. One of
these alternative sources which has a great potential and sustainability to meet up the energy demand is biomass energy. This
significant energy source can be utilized with various energy
conversion technologies, one of which is biomass gasification in
supercritical water.
Water, being the most important solvent in nature, has very important characteristics as a reaction solvent under supercritical
circumstances. At temperatures above its critical point (374.8oC and
22.1 MPa), water becomes more acidic and its diffusivity increases.
Working with water at high temperatures increases the thermal
reaction rate, which in consequence leads to a better dissolving of the
organic matters and a fast reaction with oxygen. Hence, supercritical water offers a control mechanism depending on solubility, excellent
transport properties based on its high diffusion ability and new reaction possibilities for hydrolysis or oxidation.
In this study the gasification of a real biomass, namely olive mill
wastewater (OMW), in supercritical water is investigated with the
use of Pt/Al2O3 and Ni/Al2O3 catalysts. OMW is a by-product
obtained during olive oil production, which has a complex nature
characterized by a high content of organic compounds and
polyphenols. These properties impose OMW a significant pollution
potential, but at the same time, the high content of organics makes
OMW a desirable biomass candidate for energy production.
All of the catalytic gasification experiments were made with five
different reaction temperatures (400, 450, 500, 550 and 600°C),
under a constant pressure of 25 MPa. For the experiments conducted
with Ni/Al2O3 catalyst, the effect of five reaction times (30, 60, 90,
120 and 150 s) was investigated. However, procuring that similar
gasification efficiencies could be obtained at shorter times, the experiments were made by using different reaction times (10, 15, 20,
25 and 30 s) for the case of Pt/Al2O3 catalyst. Through these experiments, the effects of temperature, time and catalyst type on the
gasification yields and treatment efficiencies were investigated.
Abstract: Histogram plays an important statistical role in digital
image processing. However, the existing quantum image models are
deficient to do this kind of image statistical processing because
different gray scales are not distinguishable. In this paper, a novel
quantum image representation model is proposed firstly in which the
pixels with different gray scales can be distinguished and operated
simultaneously. Based on the new model, a fast quantum algorithm of
constructing histogram for quantum image is designed. Performance
comparison reveals that the new quantum algorithm could achieve an
approximately quadratic speedup than the classical counterpart. The
proposed quantum model and algorithm have significant meanings for
the future researches of quantum image processing.
Abstract: In this study, we used a two-stage process and
potassium hydroxide (KOH) to transform waste biomass (rice straw)
into activated carbon and then evaluated the adsorption capacity of the
waste for removing carbofuran from an aqueous solution. Activated
carbon was fast and effective for the removal of carbofuran because of
its high surface area. The native and carbofuran-loaded adsorbents
were characterized by elemental analysis. Different adsorption
parameters, such as the initial carbofuran concentration, contact time,
temperature and pH for carbofuran adsorption, were studied using a
batch system. This study demonstrates that rice straw can be very
effective in the adsorption of carbofuran from bodies of water.
Abstract: In this paper, a new reverse converter for the moduli set {2n, 2n–1, 2n–1–1} is presented. We improved a previously introduced conversion algorithm for deriving an efficient hardware design for reverse converter. Hardware architecture of the proposed converter is based on carry-save adders and regular binary adders, without the requirement for modular adders. The presented design is faster than the latest introduced reverse converter for moduli set {2n, 2n–1, 2n–1–1}. Also, it has better performance than the reverse converters for the recently introduced moduli set {2n+1–1, 2n, 2n–1}
Abstract: An efficient parallel form in digital signal processor can improve the algorithm performance. The butterfly structure is an important role in fast Fourier transform (FFT), because its symmetry form is suitable for hardware implementation. Although it can perform a symmetric structure, the performance will be reduced under the data-dependent flow characteristic. Even though recent research which call as novel memory reference reduction methods (NMRRM) for FFT focus on reduce memory reference in twiddle factor, the data-dependent property still exists. In this paper, we propose a parallel-computing approach for FFT implementation on digital signal processor (DSP) which is based on data-independent property and still hold the property of low-memory reference. The proposed method combines final two steps in NMRRM FFT to perform a novel data-independent structure, besides it is very suitable for multi-operation-unit digital signal processor and dual-core system. We have applied the proposed method of radix-2 FFT algorithm in low memory reference on TI TMSC320C64x DSP. Experimental results show the method can reduce 33.8% clock cycles comparing with the NMRRM FFT implementation and keep the low-memory reference property.
Abstract: There are many researches to detect collision between real object and virtual object in 3D space. In general, these techniques are need to huge computing power. So, many research and study are constructed by using cloud computing, network computing, and distribute computing. As a reason of these, this paper proposed a novel fast 3D collision detection algorithm between real and virtual object using 2D intersection area. Proposed algorithm uses 4 multiple cameras and coarse-and-fine method to improve accuracy and speed performance of collision detection. In the coarse step, this system examines the intersection area between real and virtual object silhouettes from all camera views. The result of this step is the index of virtual sensors which has a possibility of collision in 3D space. To decide collision accurately, at the fine step, this system examines the collision detection in 3D space by using the visual hull algorithm. Performance of the algorithm is verified by comparing with existing algorithm. We believe proposed algorithm help many other research, study and application fields such as HCI, augmented reality, intelligent space, and so on.
Abstract: Many algorithms are available for sorting the unordered elements. Most important of them are Bubble sort, Heap sort, Insertion sort and Shell sort. These algorithms have their own pros and cons. Shell Sort which is an enhanced version of insertion sort, reduces the number of swaps of the elements being sorted to minimize the complexity and time as compared to insertion sort. Shell sort improves the efficiency of insertion sort by quickly shifting values to their destination. Average sort time is O(n1.25), while worst-case time is O(n1.5). It performs certain iterations. In each iteration it swaps some elements of the array in such a way that in last iteration when the value of h is one, the number of swaps will be reduced. Donald L. Shell invented a formula to calculate the value of ?h?. this work focuses to identify some improvement in the conventional Shell sort algorithm. ''Enhanced Shell Sort algorithm'' is an improvement in the algorithm to calculate the value of 'h'. It has been observed that by applying this algorithm, number of swaps can be reduced up to 60 percent as compared to the existing algorithm. In some other cases this enhancement was found faster than the existing algorithms available.
Abstract: In this paper, we propose an improved 3D star skeleton
technique, which is a suitable skeletonization for human posture representation
and reflects the 3D information of human posture.
Moreover, the proposed technique is simple and then can be performed
in real-time. The existing skeleton construction techniques, such as
distance transformation, Voronoi diagram, and thinning, focus on the
precision of skeleton information. Therefore, those techniques are not
applicable to real-time posture recognition since they are computationally
expensive and highly susceptible to noise of boundary. Although
a 2D star skeleton was proposed to complement these problems,
it also has some limitations to describe the 3D information of the
posture. To represent human posture effectively, the constructed skeleton
should consider the 3D information of posture. The proposed 3D
star skeleton contains 3D data of human, and focuses on human action
and posture recognition. Our 3D star skeleton uses the 8 projection
maps which have 2D silhouette information and depth data of human
surface. And the extremal points can be extracted as the features of 3D
star skeleton, without searching whole boundary of object. Therefore,
on execution time, our 3D star skeleton is faster than the “greedy" 3D
star skeleton using the whole boundary points on the surface. Moreover,
our method can offer more accurate skeleton of posture than the
existing star skeleton since the 3D data for the object is concerned.
Additionally, we make a codebook, a collection of representative 3D
star skeletons about 7 postures, to recognize what posture of constructed
skeleton is.
Abstract: Deployment of pneumatic muscles in various
industrial applications is still in its early days, considering the relative
newness of these components. The field of robotics holds particular
future potential for pneumatic muscles, especially in view of their
specific behaviour known as compliance. The paper presents and
discusses an innovative constructive solution for a gripper system
mountable on an industrial robot, based on actuation by a linear
pneumatic muscle and transmission of motion by gear and rack
mechanism. The structural, operational and constructive models of
the new gripper are presented, along with some of the experimental
results obtained subsequently to the testing of a prototype. Further
presented are two control variants of the gripper system, one by
means of a 3/2-way fast-switching solenoid valve, the other by means
of a proportional pressure regulator. Advantages and disadvantages
are discussed for both variants.
Abstract: In this paper, we present a new method for
incorporating global shift invariance in support vector machines.
Unlike other approaches which incorporate a feature extraction stage,
we first scale the image and then classify it by using the modified
support vector machines classifier. Shift invariance is achieved by
replacing dot products between patterns used by the SVM classifier
with the maximum cross-correlation value between them. Unlike the
normal approach, in which the patterns are treated as vectors, in our
approach the patterns are treated as matrices (or images). Crosscorrelation
is computed by using computationally efficient
techniques such as the fast Fourier transform. The method has been
tested on the ORL face database. The tests indicate that this method
can improve the recognition rate of an SVM classifier.
Abstract: Ants are fascinating creatures that demonstrate the
ability to find food and bring it back to their nest. Their ability as a
colony, to find paths to food sources has inspired the development of
algorithms known as Ant Colony Systems (ACS). The principle of
cooperation forms the backbone of such algorithms, commonly used
to find solutions to problems such as the Traveling Salesman
Problem (TSP). Ants communicate to each other through chemical
substances called pheromones. Modeling individual ants- ability to
manipulate this substance can help an ACS find the best solution.
This paper introduces a Dynamic Ant Colony System with threelevel
updates (DACS3) that enhance an existing ACS. Experiments
were conducted to observe single ant behavior in a colony of
Malaysian House Red Ants. Such behavior was incorporated into the
DACS3 algorithm. We benchmark the performance of DACS3 versus
DACS on TSP instances ranging from 14 to 100 cities. The result
shows that the DACS3 algorithm can achieve shorter distance in
most cases and also performs considerably faster than DACS.
Abstract: Text Mining is around applying knowledge discovery techniques to unstructured text is termed knowledge discovery in text (KDT), or Text data mining or Text Mining. In Neural Network that address classification problems, training set, testing set, learning rate are considered as key tasks. That is collection of input/output patterns that are used to train the network and used to assess the network performance, set the rate of adjustments. This paper describes a proposed back propagation neural net classifier that performs cross validation for original Neural Network. In order to reduce the optimization of classification accuracy, training time. The feasibility the benefits of the proposed approach are demonstrated by means of five data sets like contact-lenses, cpu, weather symbolic, Weather, labor-nega-data. It is shown that , compared to exiting neural network, the training time is reduced by more than 10 times faster when the dataset is larger than CPU or the network has many hidden units while accuracy ('percent correct') was the same for all datasets but contact-lences, which is the only one with missing attributes. For contact-lences the accuracy with Proposed Neural Network was in average around 0.3 % less than with the original Neural Network. This algorithm is independent of specify data sets so that many ideas and solutions can be transferred to other classifier paradigms.