Abstract: Multicast Network Technology has pervaded our
lives-a few examples of the Networking Techniques and also for the
improvement of various routing devices we use. As we know the
Multicast Data is a technology offers many applications to the user
such as high speed voice, high speed data services, which is presently
dominated by the Normal networking and the cable system and
digital subscriber line (DSL) technologies. Advantages of Multi cast
Broadcast such as over other routing techniques. Usually QoS
(Quality of Service) Guarantees are required in most of Multicast
applications. The bandwidth-delay constrained optimization and we
use a multi objective model and routing approach based on genetic
algorithm that optimizes multiple QoS parameters simultaneously.
The proposed approach is non-dominated routes and the performance
with high efficiency of GA. Its betterment and high optimization has
been verified. We have also introduced and correlate the result of
multicast GA with the Broadband wireless to minimize the delay in
the path.
Abstract: The paper presents the influence of the conventional
ploughing tillage technology in comparison with the minimum
tillage, upon the soil properties, weed control and yield in the case of
maize (Zea mays L.), soya-bean (Glycine hispida L.) and winter
wheat (Triticum aestivum L.) in a three years crop rotation. A
research has been conducted at the University of Agricultural
Sciences and Veterinary Medicine Cluj-Napoca, Romania. The use of
minimum soil tillage systems within a three years rotation: maize,
soya-bean, wheat favorites the rise of the aggregates hydro stability
with 5.6-7.5% on a 0-20 cm depth and 5-11% on 20-30 cm depth.
The minimum soil tillage systems – paraplow, chisel or rotary grape
– are polyvalent alternatives for basic preparation, germination bed
preparation and sowing, for fields and crops with moderate loose
requirements being optimized technologies for: soil natural fertility
activation and rationalization, reduction of erosion, increasing the
accumulation capacity for water and realization of sowing in the
optimal period. The soil tillage system influences the productivity
elements of cultivated species and finally the productions thus
obtained. Thus, related to conventional working system, the
productions registered in minimum tillage working represented 89-
97% in maize, 103-112% in soya-bean, 93-99% in winter-wheat. The
results of investigations showed that the yield is a conclusion soil
tillage systems influence on soil properties, plant density assurance
and on weed control. Under minimum tillage systems in the case of
winter weat as an option for replacing classic ploughing, the best
results in terms of quality indices were obtained from version worked
with paraplow, followed by rotary harrow and chisel. At variants
worked with paraplow were obtained quality indices close to those of
the variant worked with plow, and protein and gluten content was
even higher. At Ariesan variety, highest protein content, 12.50% and
gluten, 28.6% was obtained for the variant paraplow.
Abstract: The customary practice of identifying industrial sickness is a set traditional techniques which rely upon a range of manual monitoring and compilation of financial records. It makes the process tedious, time consuming and often are susceptible to manipulation. Therefore, certain readily available tools are required which can deal with such uncertain situations arising out of industrial sickness. It is more significant for a country like India where the fruits of development are rarely equally distributed. In this paper, we propose an approach based on Artificial Neural Network (ANN) to deal with industrial sickness with specific focus on a few such units taken from a less developed north-east (NE) Indian state like Assam. The proposed system provides decision regarding industrial sickness using eight different parameters which are directly related to the stages of sickness of such units. The mechanism primarily uses certain signals and symptoms of industrial health to decide upon the state of a unit. Specifically, we formulate an ANN based block with data obtained from a few selected units of Assam so that required decisions related to industrial health could be taken. The system thus formulated could become an important part of planning and development. It can also contribute towards computerization of decision support systems related to industrial health and help in better management.
Abstract: Because of importance of energy, optimization of
power generation systems is necessary. Gas turbine cycles are
suitable manner for fast power generation, but their efficiency is
partly low. In order to achieving higher efficiencies, some
propositions are preferred such as recovery of heat from exhaust
gases in a regenerator, utilization of intercooler in a multistage
compressor, steam injection to combustion chamber and etc.
However thermodynamic optimization of gas turbine cycle, even
with above components, is necessary. In this article multi-objective
genetic algorithms are employed for Pareto approach optimization of
Regenerative-Intercooling-Gas Turbine (RIGT) cycle. In the multiobjective
optimization a number of conflicting objective functions
are to be optimized simultaneously. The important objective
functions that have been considered for optimization are entropy
generation of RIGT cycle (Ns) derives using Exergy Analysis and
Gouy-Stodola theorem, thermal efficiency and the net output power
of RIGT Cycle. These objectives are usually conflicting with each
other. The design variables consist of thermodynamic parameters
such as compressor pressure ratio (Rp), excess air in combustion
(EA), turbine inlet temperature (TIT) and inlet air temperature (T0).
At the first stage single objective optimization has been investigated
and the method of Non-dominated Sorting Genetic Algorithm
(NSGA-II) has been used for multi-objective optimization.
Optimization procedures are performed for two and three objective
functions and the results are compared for RIGT Cycle. In order to
investigate the optimal thermodynamic behavior of two objectives,
different set, each including two objectives of output parameters, are
considered individually. For each set Pareto front are depicted. The
sets of selected decision variables based on this Pareto front, will
cause the best possible combination of corresponding objective
functions. There is no superiority for the points on the Pareto front
figure, but they are superior to any other point. In the case of three
objective optimization the results are given in tables.
Abstract: Phrases has a long history in information retrieval, particularly in commercial systems. Implicit semantic relationship between words in a form of BaseNP have shown significant improvement in term of precision in many IR studies. Our research focuses on linguistic phrases which is language dependent. Our results show that using BaseNP can improve performance although above 62% of words formation in Malay Language based on derivational affixes and suffixes.
Abstract: In this paper is shown that the probability-statistic methods application, especially at the early stage of the aviation gas turbine engine (GTE) technical condition diagnosing, when the flight information has property of the fuzzy, limitation and uncertainty is unfounded. Hence is considered the efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the Fuzzy Logic and Neural Networks methods. Training with high accuracy of fuzzy multiple linear and non-linear models (fuzzy regression equations) which received on the statistical fuzzy data basis is made. Thus for GTE technical condition more adequate model making are analysed dynamics of skewness and kurtosis coefficients' changes. Researches of skewness and kurtosis coefficients values- changes show that, distributions of GTE work parameters have fuzzy character. Hence consideration of fuzzy skewness and kurtosis coefficients is expedient. Investigation of the basic characteristics changes- dynamics of GTE work parameters allows to draw conclusion on necessity of the Fuzzy Statistical Analysis at preliminary identification of the engines' technical condition. Researches of correlation coefficients values- changes shows also on their fuzzy character. Therefore for models choice the application of the Fuzzy Correlation Analysis results is offered. For checking of models adequacy is considered the Fuzzy Multiple Correlation Coefficient of Fuzzy Multiple Regression. At the information sufficiency is offered to use recurrent algorithm of aviation GTE technical condition identification (Hard Computing technology is used) on measurements of input and output parameters of the multiple linear and non-linear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The developed GTE condition monitoring system provides stage-bystage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine temperature condition was made.
Abstract: Environmental awareness and the recent
environmental policies have forced many electric utilities to
restructure their operational practices to account for their emission
impacts. One way to accomplish this is by reformulating the
traditional economic dispatch problem such that emission effects are
included in the mathematical model. This paper presents a Particle
Swarm Optimization (PSO) algorithm to solve the Economic-
Emission Dispatch problem (EED) which gained recent attention due
to the deregulation of the power industry and strict environmental
regulations. The problem is formulated as a multi-objective one with
two competing functions, namely economic cost and emission
functions, subject to different constraints. The inequality constraints
considered are the generating unit capacity limits while the equality
constraint is generation-demand balance. A novel equality constraint
handling mechanism is proposed in this paper. PSO algorithm is
tested on a 30-bus standard test system. Results obtained show that
PSO algorithm has a great potential in handling multi-objective
optimization problems and is capable of capturing Pareto optimal
solution set under different loading conditions.
Abstract: Product Data Management (PDM) systems for Computer
Aided Design (CAD) file management are widely established
in design processes. This management system is indispensable for
design collaboration or when design task distribution is present. It is
thus surprising that engineering design curricula has not paid much
attention in the education of PDM systems. This is also the case
for eduction of ecodesign and environmental evaluation of products.
With the rise of sustainability as a strategic aspect in companies,
environmental concerns are becoming a key issue in design. This
paper discusses the establishment of a PDM platform to be used
among technical and vocational schools in Austria. The PDM system
facilitates design collaboration among these schools. Further, it will
be discussed how the PDM system has been prepared in order to
facilitate environmental evaluation of parts, components and subassemblies
of a product. By integrating a Business Intelligence
solution, environmental Life Cycle Assessment and communication
of results is enabled.
Abstract: To explore pipelines is one of various bio-mimetic
robot applications. The robot may work in common buildings such as
between ceilings and ducts, in addition to complicated and massive
pipeline systems of large industrial plants. The bio-mimetic robot finds
any troubled area or malfunction and then reports its data. Importantly,
it can not only prepare for but also react to any abnormal routes in the
pipeline. The pipeline monitoring tasks require special types of mobile
robots. For an effective movement along a pipeline, the movement of
the robot will be similar to that of insects or crawling animals. During
its movement along the pipelines, a pipeline monitoring robot has an
important task of finding the shapes of the approaching path on the
pipes. In this paper we propose an effective solution to the pipeline
pattern recognition, based on the fuzzy classification rules for the
measured IR distance data.
Abstract: Cell formation is the first step in the design of cellular
manufacturing systems. In this study, a general purpose
computational scheme employing a hybrid tabu search algorithm as
the core is proposed to solve the cell formation problem and its
variants. In the proposed scheme, great flexibilities are left to the
users. The core solution searching algorithm embedded in the scheme
can be easily changed to any other meta-heuristic algorithms, such as
the simulated annealing, genetic algorithm, etc., based on the
characteristics of the problems to be solved or the preferences the
users might have. In addition, several counters are designed to control
the timing of conducting intensified solution searching and diversified
solution searching strategies interactively.
Abstract: Structural redundancy is an interesting point in
seismic design of structures. Initially, the structural redundancy is
described as indeterminate degree of a system. Although many definitions are presented for redundancy in structures, recently the
definition of structural redundancy has been related to the configuration of structural system and the number of lateral load
transferring directions in the structure. The steel frames with infill walls are general systems in the constructing of usual residential buildings in some countries. It is
obviously declared that the performance of structures will be affected by adding masonry infill walls. In order to investigate the effect of
infill walls on the redundancy of the steel frame which constructed
with masonry walls, the components of redundancy including redundancy variation index, redundancy strength index and
redundancy response modification factor were extracted for the
frames with masonry infills. Several steel frames with typical storey number and various numbers of bays were designed and considered.
The redundancy of frames with and without infill walls was evaluated by proposed method. The results showed the presence of infill causes increase of redundancy.
Abstract: Three new algorithms based on minimization of autocorrelation of transmitted symbols and the SLM approach which are computationally less demanding have been proposed. In the first algorithm, autocorrelation of complex data sequence is minimized to a value of 1 that results in reduction of PAPR. Second algorithm generates multiple random sequences from the sequence generated in the first algorithm with same value of autocorrelation i.e. 1. Out of these, the sequence with minimum PAPR is transmitted. Third algorithm is an extension of the second algorithm and requires minimum side information to be transmitted. Multiple sequences are generated by modifying a fixed number of complex numbers in an OFDM data sequence using only one factor. The multiple sequences represent the same data sequence and the one giving minimum PAPR is transmitted. Simulation results for a 256 subcarrier OFDM system show that significant reduction in PAPR is achieved using the proposed algorithms.
Abstract: Current trends in manufacturing are characterized by
production broadening, innovation cycle shortening, and the products
having a new shape, material and functions. The production strategy
focused on time needed change from the traditional functional
production structure to flexible manufacturing cells and lines.
Production by automated manufacturing system (AMS) is one of the
most important manufacturing philosophies in the last years. The
main goals of the project we are involved in lies on building a
laboratory in which will be located a flexible manufacturing system
consisting of at least two production machines with NC control
(milling machines, lathe). These machines will be linked to a
transport system and they will be served by industrial robots. Within
this flexible manufacturing system a station for the quality control
consisting of a camera system and rack warehouse will be also
located. The design, analysis and improvement of this manufacturing
system, specially with a special focus on the communication among
devices constitute the main aims of this paper. The key determining
factors for the manufacturing system design are: the product, the
production volume, the used machines, the disposable manpower, the
disposable infrastructure and the legislative frame for the specific
cases.
Abstract: A linear system is called a fully fuzzy linear system (FFLS) if quantities in this system are all fuzzy numbers. For the FFLS, we investigate its solution and develop a new approximate method for solving the FFLS. Observing the numerical results, we find that our method is accurate than the iterative Jacobi and Gauss- Seidel methods on approximating the solution of FFLS.
Abstract: This paper will focus on modeling, analysis and simulation of a 42V/14V dc/dc converter based architecture. This architecture is considered to be technically a viable solution for automotive dual-voltage power system for passenger car in the near further. An interleaved dc/dc converter system is chosen for the automotive converter topology due to its advantages regarding filter reduction, dynamic response, and power management. Presented herein, is a model based on one kilowatt interleaved six-phase buck converter designed to operate in a Discontinuous Conduction Mode (DCM). The control strategy of the converter is based on a voltagemode- controlled Pulse Width Modulation (PWM) with a Proportional-Integral-Derivative (PID). The effectiveness of the interleaved step-down converter is verified through simulation results using control-oriented simulator, MatLab/Simulink.
Abstract: In this work a new platform for mobile-health systems is
presented. System target application is providing decision support to
rescue corps or military medical personnel in combat areas. Software
architecture relies on a distributed client-server system that manages a
wireless ad-hoc networks hierarchy in which several different types of
client operate. Each client is characterized for different hardware and
software requirements. Lower hierarchy levels rely in a network of
completely custom devices that store clinical information and patient
status and are designed to form an ad-hoc network operating in the
2.4 GHz ISM band and complying with the IEEE 802.15.4 standard
(ZigBee). Medical personnel may interact with such devices, that are
called MICs (Medical Information Carriers), by means of a PDA
(Personal Digital Assistant) or a MDA (Medical Digital Assistant),
and transmit the information stored in their local databases as well as
issue a service request to the upper hierarchy levels by using IEEE
802.11 a/b/g standard (WiFi). The server acts as a repository that
stores both medical evacuation forms and associated events (e.g., a
teleconsulting request). All the actors participating in the diagnostic
or evacuation process may access asynchronously to such repository
and update its content or generate new events. The designed system
pretends to optimise and improve information spreading and flow
among all the system components with the aim of improving both
diagnostic quality and evacuation process.
Abstract: Time series analysis often requires data that represents
the evolution of an observed variable in equidistant time steps. In
order to collect this data sampling is applied. While continuous
signals may be sampled, analyzed and reconstructed applying
Shannon-s sampling theorem, time-discrete signals have to be dealt
with differently. In this article we consider the discrete-event
simulation (DES) of job-shop-systems and study the effects of
different sampling rates on data quality regarding completeness and
accuracy of reconstructed inventory evolutions. At this we discuss
deterministic as well as non-deterministic behavior of system
variables. Error curves are deployed to illustrate and discuss the
sampling rate-s impact and to derive recommendations for its wellfounded
choice.
Abstract: A semi-active control strategy for suspension
systems of passenger cars is presented employing
Magnetorheological (MR) dampers. The vehicle is modeled with
seven DOFs including the, roll pitch and bounce of car body, and
the vertical motion of the four tires. In order to design an optimal
controller based on the actuator constraints, a Linear-Quadratic
Regulator (LQR) is designed. The design procedure of the LQR
consists of selecting two weighting matrices to minimize the energy
of the control system. This paper presents a hybrid optimization
procedure which is a combination of gradient-based and
evolutionary algorithms to choose the weighting matrices with
regards to the actuator constraint. The optimization algorithm is
defined based on maximum comfort and actuator constraints. It is
noted that utilizing the present control algorithm may significantly
reduce the vibration response of the passenger car, thus, providing
a comfortable ride.
Abstract: The posteroanterior manipulation technique is usually include in the procedure of the lumbar spine to evaluate the intervertebral motion according to mechanical resistance. The mechanical device with visual feedback was proposed that allows one to analysis the lumbar segments mobility “in vivo" facilitating for the therapist to take its treatment evolution. The measuring system uses load cell and displacement sensor to estimate spine stiffness. In this work, the device was tested by 2 therapists, female, applying posteroanterior force techniques to 5 volunteers, female, with frequency of approximately 1.2-1.8 Hz. A test-retest procedure was used for 2 periods of day. The visual feedback results small variation of forces and cycle time during 6 cycles rhythmic application. The stiffness values showed good agreement between test-retest procedures when used same order of maximum forces.
Abstract: The Sensor Network consists of densely deployed
sensor nodes. Energy optimization is one of the most important
aspects of sensor application design. Data acquisition and aggregation
techniques for processing data in-network should be energy efficient.
Due to the cross-layer design, resource-limited and noisy nature
of Wireless Sensor Networks(WSNs), it is challenging to study
the performance of these systems in a realistic setting. In this
paper, we propose optimizing queries by aggregation of data and
data redundancy to reduce energy consumption without requiring
all sensed data and directed diffusion communication paradigm to
achieve power savings, robust communication and processing data
in-network. To estimate the per-node power consumption POWERTossim
mica2 energy model is used, which provides scalable and
accurate results. The performance analysis shows that the proposed
methods overcomes the existing methods in the aspects of energy
consumption in wireless sensor networks.