Abstract: This paper addresses the analysis of the interference between complementary ground component (CGC) base station and mobile earth station (MES). In the frequency sharing scenario between CGC base station and MES, the interference from the adjacent beams must be considered. In this paper, we estimated the interference to MES of an integrated satellite system and the result is presented as the carrier to interference ratio(C/I) with respect to the number of CGC base station in the adjacent beam and the ratio of satellite beam center radius to the total beam radius (R1/R). By using these results, we can determine the minimum separation distance between the CGC base stations of adjacent beam and MES for compatibility. This result can be applied to the CGC base station of an integrated satellite system for the effective frequency sharing.
Abstract: This study presents a new method for detecting the
cutting tool wear based on the measured cutting force signals using
the regression model and I-kaz method. The detection of tool wear
was done automatically using the in-house developed regression
model and 3D graphic presentation of I-kaz 3D coefficient during
machining process. The machining tests were carried out on a CNC
turning machine Colchester Master Tornado T4 in dry cutting
condition, and Kistler 9255B dynamometer was used to measure the
cutting force signals, which then stored and displayed in the DasyLab
software. The progression of the cutting tool flank wear land (VB)
was indicated by the amount of the cutting force generated. Later, the
I-kaz was used to analyze all the cutting force signals from beginning
of the cut until the rejection stage of the cutting tool. Results of the IKaz
analysis were represented by various characteristic of I-kaz 3D
coefficient and 3D graphic presentation. The I-kaz 3D coefficient
number decreases when the tool wear increases. This method can be
used for real time tool wear monitoring.
Abstract: In this paper, we present a comparative study of the
genetic algorithms and Hessian-s methods for optimal research of the
active powers in an electric network of power. The objective function
which is the performance index of production of electrical energy is
minimized by satisfying the constraints of the equality type and
inequality type initially by the Hessian-s methods and in the second
time by the genetic Algorithms. The results found by the application
of AG for the minimization of the electric production costs of power
are very encouraging. The algorithms seem to be an effective
technique to solve a great number of problems and which are in
constant evolution. Nevertheless it should be specified that the
traditional binary representation used for the genetic algorithms
creates problems of optimization of management of the large-sized
networks with high numerical precision.
Abstract: The electrical power systems of aircrafts have made
serious progress in recent years because the aircrafts depend more
and more on the electricity. There is a trend in the aircraft industry to
replace hydraulic and pneumatic systems with electrical systems,
achieving more comfort and monitoring features and enlarging the
energetic efficiency. Thus, was born the concept More Electric
Aircraft. In this paper is analyzed the integration of a fuel cell into
the existing electrical generation and distribution systems of an
aircraft. The dynamic characteristics of fuel cell systems necessitate
an adaptation of the electrical power system. The architecture studied
in this paper consists of a 50kW fuel cell, a dc to dc converter and
several loads. The dc to dc converter is used to step down the fuel
cell voltage from about 625Vdc to 28Vdc.
Abstract: Learning the gradient of neuron's activity function
like the weight of links causes a new specification which is
flexibility. In flexible neural networks because of supervising and
controlling the operation of neurons, all the burden of the learning is
not dedicated to the weight of links, therefore in each period of
learning of each neuron, in fact the gradient of their activity function,
cooperate in order to achieve the goal of learning thus the number of
learning will be decreased considerably.
Furthermore, learning neurons parameters immunes them against
changing in their inputs and factors which cause such changing.
Likewise initial selecting of weights, type of activity function,
selecting the initial gradient of activity function and selecting a fixed
amount which is multiplied by gradient of error to calculate the
weight changes and gradient of activity function, has a direct affect
in convergence of network for learning.
Abstract: We have investigated statistical properties of the defect turbulence in 1D CGLE wherein many body interaction is involved between local depressing wave (LDW) and local standing wave (LSW). It is shown that the counting number fluctuation of LDW is subject to the sub-Poisson statistics (SUBP). The physical origin of the SUBP can be ascribed to pair extinction of LDWs based on the master equation approach. It is also shown that the probability density function (pdf) of inter-LDW distance can be identified by the hyper gamma distribution. Assuming a superstatistics of the exponential distribution (Poisson configuration), a plausible explanation is given. It is shown further that the pdf of amplitude of LDW has a fattail. The underlying mechanism of its fluctuation is examined by introducing a generalized fractional Poisson configuration.
Abstract: The adsorption of bovine serum albumin (BSA), immunoglobulin G (IgG) and fibrinogen (Fgn) on fluorinated selfassembled monolayers have been studied using time of flight secondary ion mass spectrometry (ToF-SIMS) and Spectroscopic Ellipsometry (SE). The objective of the work has to establish the utility of ToF-SIMS for the determination of the amount of protein adsorbed on the surface. Quantification of surface adsorbed proteins was carried out using SE and a good correlation between ToF-SIMS results and SE was achieved. The surface distribution of proteins were also analysed using Atomic Force Microscopy (AFM). We show that the surface distribution of proteins strongly affect the ToFSIMS results.
Abstract: This paper focuses on a critical component of the situational awareness (SA), the control of autonomous vertical flight for vectored thrust aerial vehicle (VTAV). With the SA strategy, we proposed a flight control procedure to address the dynamics variation and performance requirement difference of flight trajectory for an unmanned helicopter model with vectored thrust configuration. This control strategy for chosen model of VTAV has been verified by simulation of take-off and forward maneuvers using software package Simulink and demonstrated good performance for fast stabilization of motors, consequently, fast SA with economy in energy can be asserted during search-and-rescue operations.
Abstract: MOSCAPs of various combinations of Hafnium
oxide and Titanium oxide of varying thickness with Aluminum as gate electrode have been fabricated and electrically characterized.
The effects of voltage stress on the I-V characteristics for prolonged time durations have been studied and compared. Results showed
hard breakdown and negligible degradation of reliability under stress.
Abstract: In this paper, the existence, multiplicity and
noexistence of positive solutions for a class of semipositone
discrete boundary value problems with two parameters is
studied by applying nonsmooth critical point theory and
sub-super solutions method.
Abstract: In order to integrate knowledge in heterogeneous
case-based reasoning (CBR) systems, ontology-based CBR system
has become a hot topic. To solve the facing problems of
ontology-based CBR system, for example, its architecture is
nonstandard, reusing knowledge in legacy CBR is deficient, ontology
construction is difficult, etc, we propose a novel approach for
semi-automatically construct ontology-based CBR system whose
architecture is based on two-layer ontology. Domain knowledge
implied in legacy case bases can be mapped from relational database
schema and knowledge items to relevant OWL local ontology
automatically by a mapping algorithm with low time-complexity. By
concept clustering based on formal concept analysis, computing
concept equation measure and concept inclusion measure, some
suggestions about enriching or amending concept hierarchy of OWL
local ontologies are made automatically that can aid designers to
achieve semi-automatic construction of OWL domain ontology.
Validation of the approach is done by an application example.
Abstract: This paper presents a customized deformable model
for the segmentation of abdominal and thoracic aortic aneurysms in
CTA datasets. An important challenge in reliably detecting aortic
aneurysm is the need to overcome problems associated with intensity
inhomogeneities and image noise. Level sets are part of an important
class of methods that utilize partial differential equations (PDEs) and
have been extensively applied in image segmentation. A Gaussian
kernel function in the level set formulation, which extracts the local
intensity information, aids the suppression of noise in the extracted
regions of interest and then guides the motion of the evolving contour
for the detection of weak boundaries. The speed of curve evolution
has been significantly improved with a resulting decrease in
segmentation time compared with previous implementations of level
sets. The results indicate the method is more effective than other
approaches in coping with intensity inhomogeneities.
Abstract: Thermite welding is mainly used in world. The
reasons why the thermite welding method is widely used are
that the equipment has good mobility and total working time
of that is shorter than that of the enclosed arc welding method
on site. Moreover, the operating skill, which required for
thermite welding, is less than that of for enclosed arc welding.
In the present research work, heat treatment and combined
'expulsion and heat treatment' techniques were used improve
the mechanical properties and weldment structure. The
specimens were cut in the transverse direction from expulsion
with Heat treated and heat treated Thermite Welded rails.
Specimens were prepared according to AWS standard and
subjected to tensile test, Impact test and hardness and their
results were tabulated. Microstructural analysis was carried
out with the help of SEM. Then analyze to effect of heat
treated and 'expulsion with heat treated' with the properties of
their thermite welded rails. Compare the mechanical and
microstructural properties of thermite welded rails between
heat expulsion with heat treated and heat treated. Mechanical
and microstructural response expulsion with heat treated
thermite welded rail is higher value as compared to heat
treatment.
Abstract: the research was accomplished on fresh in Latvia wild
growing cranberries and cranberry cultivars. The aim of the study
was to evaluate effect of pretreatment method and drying conditions
on the volatile compounds composition in cranberries. Berries
pre-treatment methods were: perforation, halving and
steam-blanching. The berries before drying in a cabinet drier were
pre-treated using all three methods, in microwave vacuum
drier – using a steam-blanching and halving. Volatile compounds in
cranberries were analysed using GC-MS of extracts obtained by
SPME. During present research 21 various volatile compounds were
detected in fresh cranberries: the cultivar 'Steven' - 15, 'Bergman'
and 'Early black' – 13, 'Ben Lear' and 'Pilgrim' – 11 and wild
cranberries – 14 volatile compounds. In dried cranberries 20 volatile
compounds were detected. Mathematical data processing allows
drawing a conclusion that there exists the significant influence of
cranberry cultivar, pre-treatment method and drying condition on
volatile compounds in berries and new volatile compound formation.
Abstract: Different approaches for heating\cooling of stirred tanks, coils and jackets, are investigated using computational fluid dynamics (CFD).A time-dependant sliding mesh approach is applied to simulate the flow in both conditions. The investigations are carried out under the turbulent flow conditions for a Rushton impeller and heating elements are considered isothermal. The flow behavior and temperature distribution are studied for each case and heat transfer coefficient is calculated. Results show different velocity profiles for each case. Unsteady temperature distribution is not similar for different cases .In the case of the coiled stirred vessel more uniform temperature and higher heat transfer coefficient is resulted.
Abstract: This paper outlines the application of Knowledge Management (KM) principles in the context of Educational institutions. The paper caters to the needs of the engineering institutions for imparting quality education by delineating the instruction delivery process in a highly structured, controlled and quantified manner. This is done using a software tool EDULOGIC+. The central idea has been based on the engineering education pattern in Indian Universities/ Institutions. The data, contents and results produced over contiguous years build the necessary ground for managing the related accumulated knowledge. Application of KM has been explained using certain examples of data analysis and knowledge extraction.
Abstract: Part IV of the Civil Code of the Russian Federation dedicated to legal regulation of Intellectual property rights came into force in 2008. It is a first attempt of codification in Intellectual property sphere in Russia. That is why a lot of new norms appeared. The main problem of the Russian Civil Code (part IV) is that many rules (norms of Law) contradict the norms of International Intellectual property Law (i.e. protection of inventions, creations, ideas, know-how, trade secrets, innovations). Intellectual property rights protect innovations and creations and reward innovative and creative activity. Intellectual property rights are international in character and in that respect they fit in rather well with the economic reality of the global economy. Inventors prefer not to take out a patent for inventions because it is a very difficult procedure, it takes a lot of time and is very expensive. That-s why they try to protect their inventions as ideas, know-how, confidential information. An idea is the main element of any object of Intellectual property (creation, invention, innovation, know-how, etc.). But ideas are not protected by Civil Code of Russian Federation. The aim of the paper is to reveal the main problems of legal regulation of Intellectual property in Russia and to suggest possible solutions. The authors of this paper have raised these essential issues through different activities. Through the panel survey, questionnaires which were spread among the participants of intellectual activities the main problems of implementation of innovations, protecting of the ideas and know-how were identified. The implementation of research results will help to solve economic and legal problems of innovations, transfer of innovations and intellectual property.1
Abstract: A case study of the generation scheduling optimization
of the multi-hydroplants on the Yuan River Basin in China is reported
in this paper. Concerning the uncertainty of the inflows, the
long/mid-term generation scheduling (LMTGS) problem is solved by
a stochastic model in which the inflows are considered as stochastic
variables. For the short-term generation scheduling (STGS) problem, a
constraint violation priority is defined in case not all constraints are
satisfied. Provided the stage-wise separable condition and low
dimensions, the hydroplant-based operational region schedules
(HBORS) problem is solved by dynamic programming (DP). The
coordination of LMTGS and STGS is presented as well. The
feasibility and the effectiveness of the models and solution methods
are verified by the numerical results.
Abstract: In order to Study the efficacy application of green
manure as chickpea pre plant, field experiments were carried out in
2007 and 2008 growing seasons. In this research the effects of
different strategies for soil fertilization were investigated on grain
yield and yield component, minerals, organic compounds and
cooking time of chickpea. Experimental units were arranged in splitsplit
plots based on randomized complete blocks with three
replications. Main plots consisted of (G1): establishing a mixed
vegetation of Vicia panunica and Hordeum vulgare and (G2):
control, as green manure levels. Also, five strategies for obtaining the
base fertilizer requirement including (N1): 20 t.ha-1 farmyard manure;
(N2): 10 t.ha-1 compost; (N3): 75 kg.ha-1 triple super phosphate;
(N4): 10 t.ha-1 farmyard manure + 5 t.ha-1 compost and (N5): 10 t.ha-1
farmyard manure + 5 t.ha-1 compost + 50 kg.ha-1 triple super
phosphate were considered in sub plots. Furthermoree four levels of
biofertilizers consisted of (B1): Bacillus lentus + Pseudomonas
putida; (B2): Trichoderma harzianum; (B3): Bacillus lentus +
Pseudomonas putida + Trichoderma harzianum; and (B4): control
(without biofertilizers) were arranged in sub-sub plots. Results
showed that integrating biofertilizers (B3) and green manure (G1)
produced the highest grain yield. The highest amounts of yield were
obtained in G1×N5 interaction. Comparison of all 2-way and 3-way
interactions showed that G1N5B3 was determined as the superior
treatment. Significant increasing of N, P2O5, K2O, Fe and Mg content
in leaves and grains emphasized on superiority of mentioned
treatment because each one of these nutrients has an approved role in
chlorophyll synthesis and photosynthesis abilities of the crops. The
combined application of compost, farmyard manure and chemical
phosphorus (N5) in addition to having the highest yield, had the best
grain quality due to high protein, starch and total sugar contents, low
crude fiber and reduced cooking time.
Abstract: In this paper, an extreme learning machine with an automatic segmentation algorithm is applied to heart disorder classification by heart sound signals. From continuous heart sound signals, the starting points of the first (S1) and the second heart pulses (S2) are extracted and corrected by utilizing an inter-pulse histogram. From the corrected pulse positions, a single period of heart sound signals is extracted and converted to a feature vector including the mel-scaled filter bank energy coefficients and the envelope coefficients of uniform-sized sub-segments. An extreme learning machine is used to classify the feature vector. In our cardiac disorder classification and detection experiments with 9 cardiac disorder categories, the proposed method shows significantly better performance than multi-layer perceptron, support vector machine, and hidden Markov model; it achieves the classification accuracy of 81.6% and the detection accuracy of 96.9%.