Abstract: Land use change, if not based on proper scientific
investigation affects other physical, chemical, and biological
properties of soil and leading to increased destruction and erosion. It
was imperative to study the effects of changing rangelands to
farmlands on some Soil quality indexes. Undisturbed soil samples
were collected from the depths of 0-10 and 10-30 centimeter in
pasture with good vegetation cover(GP), pasture with medium
vegetation cover(MP), abandoned dry land farming(ADF) and
degraded dry land farming(DDF) land uses in Ghareh Aghaj
watershed of Isfahan province. The results revealed that organic
matter(OM), cation exchange capacity(CEC) and available
potassium(AK) decreasing in the depth of 0-10 centimeter were 66.6,
38.8 and 70 percent and in the depth of 10-30 centimeter were 58,
61.4 and 83.5 percent respectively in DDF comparison with GP.
Concerning to the results, it seems that land use change can decrease
soil quality and increase soil degradation and lead in undesirable
consequences.
Abstract: These In this work, a regular unit speed curve in six
dimensional Euclidean space, whose Frenet curvatures are constant,
is considered. Thereafter, a method to calculate Frenet apparatus of
this curve is presented.
Abstract: In this paper, the Tabu search algorithm is used to
solve a transportation problem which consists of determining the
shortest routes with the appropriate vehicle capacity to facilitate the
travel of the students attending the University of Mauritius. The aim
of this work is to minimize the total cost of the distance travelled by
the vehicles in serving all the customers. An initial solution is
obtained by the TOUR algorithm which basically constructs a giant
tour containing all the customers and partitions it in an optimal way
so as to produce a set of feasible routes. The Tabu search algorithm
then makes use of a search procedure, a swapping procedure and the
intensification and diversification mechanism to find the best set of
feasible routes.
Abstract: The radio frequency identification (RFID) is a
technology for automatic identification of items, particularly in
supply chain, but it is becoming increasingly important for industrial
applications. Unlike barcode technology that detects the optical
signals reflected from barcode labels, RFID uses radio waves to
transmit the information from an RFID tag affixed to the physical
object. In contrast to today most often use of this technology in
warehouse inventory and supply chain, the focus of this paper is an
overview of the structure of RFID systems used by RFID technology
and it also presents a solution based on the application of RFID for
brand authentication, traceability and tracking, by implementing a
production management system and extending its use to traders.
Abstract: A new method for low complexity image coding is presented, that permits different settings and great scalability in the generation of the final bit stream. This coding presents a continuoustone still image compression system that groups loss and lossless compression making use of finite arithmetic reversible transforms. Both transformation in the space of color and wavelet transformation are reversible. The transformed coefficients are coded by means of a coding system in depending on a subdivision into smaller components (CFDS) similar to the bit importance codification. The subcomponents so obtained are reordered by means of a highly configure alignment system depending on the application that makes possible the re-configure of the elements of the image and obtaining different levels of importance from which the bit stream will be generated. The subcomponents of each level of importance are coded using a variable length entropy coding system (VBLm) that permits the generation of an embedded bit stream. This bit stream supposes itself a bit stream that codes a compressed still image. However, the use of a packing system on the bit stream after the VBLm allows the realization of a final highly scalable bit stream from a basic image level and one or several enhance levels.
Abstract: In this study, we examine multiple algebras and
algebraic structures derived from them and by stating a theory on
multiple algebras; we will show that the theory of multiple algebras
is a natural extension of the theory of universal algebras. Also, we
will treat equivalence relations on multiple algebras, for which the
quotient constructed modulo them is a universal algebra and will
study the basic relation and the fundamental algebra in question.
In this study, by stating the characteristic theorem of multiple
algebras, we show that the theory of multiple algebras is a natural
extension of the theory of universal algebras.
Abstract: WLAN Positioning has been presented by many
approaches in literatures using the characteristics of Received Signal
Strength (RSS), Time of Arrival (TOA) or Time Difference of
Arrival (TDOA), Angle of Arrival (AOA) and cell ID. Among these,
RSS approach is the simplest method to implement because there is
no need of modification on both access points and client devices
whereas its accuracy is terrible due to physical environments. For
TOA or TDOA approach, the accuracy is quite acceptable but most
researches have to modify either software or hardware on existing
WLAN infrastructure. The scales of modifications are made on only
access card up to the changes in protocol of WLAN. Hence, it is an
unattractive approach to use TOA or TDOA for positioning system.
In this paper, the new concept of merging both RSS and TOA
positioning techniques is proposed. In addition, the method to
achieve TOA characteristic for positioning WLAN user without any
extra modification necessarily appended in the existing system is
presented. The measurement results confirm that the proposed
technique using both RSS and TOA characteristics provides better
accuracy than using only either RSS or TOA approach.
Abstract: A systematic and exhaustive method based on the group
structure of a unitary Lie algebra is proposed to generate an enormous
number of quantum codes. With respect to the algebraic structure,
the orthogonality condition, which is the central rule of generating
quantum codes, is proved to be fully equivalent to the distinguishability
of the elements in this structure. In addition, four types of
quantum codes are classified according to the relation of the codeword
operators and some initial quantum state. By linking the unitary Lie
algebra with the additive group, the classical correspondences of some
of these quantum codes can be rendered.
Abstract: We estimate snow velocity and snow drift density on hilly terrain under the assumption that the drifting snow mass can be represented using a micro-continuum approach (i.e. using a nonclassical mechanics approach assuming a class of fluids for which basic equations of mass, momentum and energy have been derived). In our model, the theory of coupled stress fluids proposed by Stokes [1] has been employed for the computation of flow parameters. Analyses of bulk drift velocity, drift density, drift transport and mass transport of snow particles have been carried out and computations made, considering various parametric effects. Results are compared with those of classical mechanics (logarithmic wind profile). The results indicate that particle size affects the flow characteristics significantly.
Abstract: Image data holds a large amount of different context
information. However, as of today, these resources remain largely
untouched. It is thus the aim of this paper to present a basic technical
framework which allows for a quick and easy exploitation of context
information from image data especially by non-expert users.
Furthermore, the proposed framework is discussed in detail
concerning important social and ethical issues which demand special
requirements in system design. Finally, a first sensor prototype is
presented which meets the identified requirements. Additionally,
necessary implications for the software and hardware design of the
system are discussed, rendering a sensor system which could be
regarded as a good, acceptable and justifiable technical and thereby
enabling the extraction of context information from image data.
Abstract: High Speed PM Generators driven by micro-turbines
are widely used in Smart Grid System. So, this paper proposes
comparative study among six classical, optimized and genetic
analytical design cases for 400 kW output power at tip speed 200
m/s. These six design trials of High Speed Permanent Magnet
Synchronous Generators (HSPMSGs) are: Classical Sizing;
Unconstrained optimization for total losses and its minimization;
Constrained optimized total mass with bounded constraints are
introduced in the problem formulation. Then a genetic algorithm is
formulated for obtaining maximum efficiency and minimizing
machine size. In the second genetic problem formulation, we attempt
to obtain minimum mass, the machine sizing that is constrained by
the non-linear constraint function of machine losses. Finally, an
optimum torque per ampere genetic sizing is predicted. All results are
simulated with MATLAB, Optimization Toolbox and its Genetic
Algorithm. Finally, six analytical design examples comparisons are
introduced with study of machines waveforms, THD and rotor losses.
Abstract: Support Vector Machine (SVM) is a recent class of statistical classification and regression techniques playing an increasing role in applications to detection problems in various engineering problems, notably in statistical signal processing, pattern recognition, image analysis, and communication systems. In this paper, SVM is applied to an infrared (IR) binary communication system with different types of channel models including Ricean multipath fading and partially developed scattering channel with additive white Gaussian noise (AWGN) at the receiver. The structure and performance of SVM in terms of the bit error rate (BER) metric is derived and simulated for these channel stochastic models and the computational complexity of the implementation, in terms of average computational time per bit, is also presented. The performance of SVM is then compared to classical binary signal maximum likelihood detection using a matched filter driven by On-Off keying (OOK) modulation. We found that the performance of SVM is superior to that of the traditional optimal detection schemes used in statistical communication, especially for very low signal-to-noise ratio (SNR) ranges. For large SNR, the performance of the SVM is similar to that of the classical detectors. The implication of these results is that SVM can prove very beneficial to IR communication systems that notoriously suffer from low SNR at the cost of increased computational complexity.
Abstract: In the context of sensor networks, where every few
dB saving counts, the novel node cooperation schemes are reviewed
where MIMO techniques play a leading role. These methods could be
treated as joint approach for designing physical layer of their
communication scenarios. Then we analyzed the BER performance
of transmission diversity schemes under a general fading channel
model and proposed a power allocation strategy to the transmitting
sensor nodes. This approach is then compared to an equal-power
assignment method and its performance enhancement is verified by
the simulation. Another key point of the contribution lies in the
combination of optimal power allocation and sensor nodes-
cooperation in a transmission diversity regime (MISO). Numerical
results are given through figures to demonstrate the optimality and
efficiency of proposed combined approach.
Abstract: The paper introduces and discusses definitions and concepts from the supplier relationship management area. This review has the goal to provide readers with the basic conditions to understand the market mechanisms and the technological developments of the SRM market. Further on, the work gives a picture of the actual business environment in which the SRM vendors are in, and the main trends in the field, based on the main SRM functionalities i.e. e-Procurement, e-Sourcing and Supplier Enablement, which indicates users and software providers the future technological developments and practises that will take place in this area in the next couple of years.
Abstract: Training neural networks to capture an intrinsic
property of a large volume of high dimensional data is a difficult
task, as the training process is computationally expensive. Input
attributes should be carefully selected to keep the dimensionality of
input vectors relatively small.
Technical indexes commonly used for stock market prediction
using neural networks are investigated to determine its effectiveness
as inputs. The feed forward neural network of Levenberg-Marquardt
algorithm is applied to perform one step ahead forecasting of
NASDAQ and Dow stock prices.
Abstract: Air emissions from waste treatment plants often
consist of a combination of Volatile Organic Compounds (VOCs)
and odors. Hydrogen sulfide is one of the major odorous gases
present in the waste emissions coming from municipal wastewater
treatment facilities. Hydrogen sulfide (H2S) is odorous, highly toxic
and flammable. Exposure to lower concentrations can result in eye
irritation, a sore throat and cough, shortness of breath, and fluid in
the lungs. Biofiltration has become a widely accepted technology for
treating air streams containing H2S. When compared with other nonbiological
technologies, biofilter is more cost-effective for treating large
volumes of air containing low concentrations of biodegradable compounds.
Optimization of biofilter media is essential for many reasons such as:
providing a higher surface area for biofilm growth, low pressure drop,
physical stability, and good moisture retention. In this work, a novel
biofilter media is developed and tested at a pumping station of a
municipality located in the United Arab Emirates (UAE). The
media is found to be very effective (>99%) in removing H2S
concentrations that are expected in pumping stations under steady
state and shock loading conditions.
Abstract: In this paper a new method for increasing the speed of
SAGCM-APD is proposed. Utilizing carrier rate equations in
different regions of the structure, a circuit model for the structure is
obtained. In this research, in addition to frequency response, the
effect of added new charge layer on some transient parameters like
slew-rate, rising and falling times have been considered. Finally, by
trading-off among some physical parameters such as different layers
widths and droppings, a noticeable decrease in breakdown voltage
has been achieved. The results of simulation, illustrate some features
of proposed structure improvement in comparison with conventional
SAGCM-APD structures.
Abstract: The present paper presents a finite element model and
analysis for the interaction between a piezoresistive tactile sensor and
biological tissues. The tactile sensor is proposed for use in minimally
invasive surgery to deliver tactile information of biological tissues to
surgeons. The proposed sensor measures the relative hardness of soft
contact objects as well as the contact force. Silicone rubbers were
used as the phantom of biological tissues. Finite element analysis of
the silicone rubbers and the mechanical structure of the sensor were
performed using COMSOL Multiphysics (v3.4) environment. The
simulation results verify the capability of the sensor to be used to
differentiate between different kinds of silicone rubber materials.
Abstract: Complexity, as a theoretical background has made it
easier to understand and explain the features and dynamic behavior
of various complex systems. As the common theoretical background
has confirmed, borrowing the terminology for design from the
natural sciences has helped to control and understand urban
complexity. Phenomena like self-organization, evolution and
adaptation are appropriate to describe the formerly inaccessible
characteristics of the complex environment in unpredictable bottomup
systems. Increased computing capacity has been a key element in
capturing the chaotic nature of these systems.
A paradigm shift in urban planning and architectural design has
forced us to give up the illusion of total control in urban
environment, and consequently to seek for novel methods for
steering the development. New methods using dynamic modeling
have offered a real option for more thorough understanding of
complexity and urban processes. At best new approaches may renew
the design processes so that we get a better grip on the complex
world via more flexible processes, support urban environmental
diversity and respond to our needs beyond basic welfare by liberating
ourselves from the standardized minimalism.
A complex system and its features are as such beyond human
ethics. Self-organization or evolution is either good or bad. Their
mechanisms are by nature devoid of reason. They are common in
urban dynamics in both natural processes and gas. They are features
of a complex system, and they cannot be prevented. Yet their
dynamics can be studied and supported.
The paradigm of complexity and new design approaches has been
criticized for a lack of humanity and morality, but the ethical
implications of scientific or computational design processes have not
been much discussed. It is important to distinguish the (unexciting)
ethics of the theory and tools from the ethics of computer aided
processes based on ethical decisions. Urban planning and architecture
cannot be based on the survival of the fittest; however, the natural
dynamics of the system cannot be impeded on grounds of being
“non-human".
In this paper the ethical challenges of using the dynamic models
are contemplated in light of a few examples of new architecture and
dynamic urban models and literature. It is suggested that ethical
challenges in computational design processes could be reframed
under the concepts of responsibility and transparency.
Abstract: The segmentation of endovascular tools in fluoroscopy images can be accurately performed automatically or by minimum user intervention, using known modern techniques. It has been proven in literature, but no clinical implementation exists so far because the computational time requirements of such technology have not yet been met. A classical segmentation scheme is composed of edge enhancement filtering, line detection, and segmentation. A new method is presented that consists of a vector that propagates in the image to track an edge as it advances. The filtering is performed progressively in the projected path of the vector, whose orientation allows for oriented edge detection, and a minimal image area is globally filtered. Such an algorithm is rapidly computed and can be implemented in real-time applications. It was tested on medical fluoroscopy images from an endovascular cerebral intervention. Ex- periments showed that the 2D tracking was limited to guidewires without intersection crosspoints, while the 3D implementation was able to cope with such planar difficulties.