Abstract: This paper unifies power optimization approaches in
various energy converters, such as: thermal, solar, chemical, and
electrochemical engines, in particular fuel cells. Thermodynamics
leads to converter-s efficiency and limiting power. Efficiency
equations serve to solve problems of upgrading and downgrading of
resources. While optimization of steady systems applies the
differential calculus and Lagrange multipliers, dynamic optimization
involves variational calculus and dynamic programming. In reacting
systems chemical affinity constitutes a prevailing component of an
overall efficiency, thus the power is analyzed in terms of an active
part of chemical affinity. The main novelty of the present paper in the
energy yield context consists in showing that the generalized heat
flux Q (involving the traditional heat flux q plus the product of
temperature and the sum products of partial entropies and fluxes of
species) plays in complex cases (solar, chemical and electrochemical)
the same role as the traditional heat q in pure heat engines.
The presented methodology is also applied to power limits in fuel
cells as to systems which are electrochemical flow engines propelled
by chemical reactions. The performance of fuel cells is determined by
magnitudes and directions of participating streams and mechanism of
electric current generation. Voltage lowering below the reversible
voltage is a proper measure of cells imperfection. The voltage losses,
called polarization, include the contributions of three main sources:
activation, ohmic and concentration. Examples show power maxima
in fuel cells and prove the relevance of the extension of the thermal
machine theory to chemical and electrochemical systems. The main
novelty of the present paper in the FC context consists in introducing
an effective or reduced Gibbs free energy change between products p
and reactants s which take into account the decrease of voltage and
power caused by the incomplete conversion of the overall reaction.
Abstract: The aim of this paper is to present the role of
myotonometry in assessment muscle viscoelasticity by measurement
of force index (IF) and stiffness (S) at thigh muscle groups. The
results are used for improve the muscle training. The method is based
on mechanic impulse on the muscle group, that involve a muscle
response like acceleration, speed and amplitude curves. From these
we have information about elasticity, stiffness beginning from
mechanic oscillations of muscle tissue. Using this method offer the
possibility for monitoring the muscle capacity for produce mechanic
energy, that allows a efficiency of movement with a minimal tissue
deformation.
Abstract: Whereas cellular wireless communication systems are
subject to short-and long-term fading. The effect of wireless channel
has largely been ignored in most of the teletraffic assessment
researches. In this paper, a mathematical teletraffic model is proposed
to estimate blocking and forced termination probabilities of cellular
wireless networks as a result of teletraffic behavior as well as the
outage of the propagation channel. To evaluate the proposed
teletraffic model, gamma inter-arrival and general service time
distributions have been considered based on wireless channel fading
effect. The performance is evaluated and compared with the classical
model. The proposed model is dedicated and investigated in different
operational conditions. These conditions will consider not only the
arrival rate process, but also, the different faded channels models.
Abstract: PT XYZ is a bottled drinking water company. To preserve production resources owned by the company so that the resources could be utilized well, it has implemented maintenance management system, which has important role in company's profitability, and is one of the factors influenced overall company's performance. Yet, up to now the company has never measured maintenance activities' contribution to company's performance. Performance evaluation is done according to adapted Balanced Scorecard model fitted to maintenance function context. This model includes six perspectives: innovation and growth, production, maintenance, environment, costumer, and finance. Actual performance measurement is done through Analytic Hierarchy Process and Objective Matrix. From the research done, we can conclude that the company's maintenance function is categorized in moderate performance. But, there are some indicators which has high priority but low performance, which are: costumers' complain rate, work lateness rate, and Return on Investment.
Abstract: The effective machine-job assignment of injection
molding machines is very important for industry because it is not
only directly affects the quality of the product but also the
performance and lifetime of the machine as well. The phase of
machine selection was mostly done by professionals or experienced
planners, so the possibility of matching a job with an inappropriate
machine might occur when it was conducted by an inexperienced
person. It could lead to an uneconomical plan and defects. This
research aimed to develop a machine selection system for plastic
injection machines as a tool to help in decision making of the user.
This proposed system could be used both in normal times and in
times of emergency. Fuzzy logic principle is applied to deal with
uncertainty and mechanical factors in the selection of both quantity
and quality criteria. The six criteria were obtained from a plastic
manufacturer's case study to construct a system based on fuzzy logic
theory using MATLAB. The results showed that the system was able
to reduce the defects of Short Shot and Sink Mark to 24.0% and
8.0% and the total defects was reduced around 8.7% per month.
Abstract: In this paper, we propose a novel limited feedback scheme for task planning with service robots. Instead of sending the full service robot state information for the task planning, the proposed scheme send the best-M indices of service robots with a indicator. With the indicator, the proposed scheme significantly reduces the communication overhead for task planning as well as mitigates the system performance degradation in terms of the utility. In addition, we analyze the system performance of the proposed scheme and compare the proposed scheme with the other schemes.
Abstract: The research study evaluated the performance of
irrigation system by using special scientific tools like Remote
Sensing and GIS technology, so that proper measurements could be
taken for the sustainable agriculture and water management.
Different performance evaluation parameters had been calculated for
the purposed data was gathered from field investigation and different
government and private organizations. According to the calculations,
organic matter ranges from 0.19% (low value) to 0.76% (high value).
In flat irrigation system for wheat yield ranges from 3347.16 to
5260.39 kg/ha, while the total water applied to wheat crop ranges
from 252.94 to 279.19 mm and WUE ranges from 13.07 to 18.37
kg/ha/mm. For rice yield ranges from 3347.47 to 5433.07 kg/ha with
total water supplied to rice crop ranges from 764.71 to 978.15 mm
and WUE ranges from 3.49 to 5.71 kg/ha/mm. Similarly, in raised
bed system wheat yield ranges from 4569.13 to 6008.60 kg/ha, total
water supplied ranges from 158.87 to 185.09 mm and WUE ranges
from 27.20 to 33.54 kg/ha/mm while in rice crop, yield ranges from
5285.04 to 6716.69 kg/ha, total water supplied ranges from 600.72 to
755.06 mm and WUE ranges from 6.41 to 10.05 kg/ha/mm. Almost
51.3% water saving is observed in bed irrigation system as compared
to flat system. Less water supplied to beds is more affective as its
WUE value is higher than flat system where more water is supplied
in both the seasons. Similarly, RWS values show that maximum
water deficit while minimum area is getting adequate water supply.
Greater yield is recorded in bed system as plant per square meter is
more in bed system in comparison of flat system Thus, the integration
of GIS tools to regularly compute performance indices could provide
irrigation managers with the means for managing efficiently the
irrigation system.
Abstract: This study deals with Computational Fluid Dynamics
(CFD) studies of the interactions between the air flow and louvered
fins which equipped the automotive heat exchangers. 3D numerical
simulation results are obtained by using the ANSYS Fluent 13.0 code
and compared to experimental data. The paper studies the effect of
louver angle and louver pitch geometrical parameters, on overall
thermal hydraulic performances of louvered fins.
The comparison between CFD simulations and experimental data
show that established 3-D CFD model gives a good agreement. The
validation agrees, with about 7% of deviation respectively of friction
and Colburn factors to experimental results. As first, it is found that
the louver angle has a strong influence on the heat transfer rate. Then,
louver angle and louver pitch variation of the louvers and their effects
on thermal hydraulic performances are studied. In addition to this
study, it is shown that the second half of the fin takes has a
significant contribution on pressure drop increase without any
increase in heat transfer.
Abstract: Maintenance costs incurred on building differs. The
difference can be as results of the types, functions, age, building
health index, size, form height, location and complexity of the
building. These are contributing to the difficulty in maintenance
development of deterministic maintenance cost model. This paper is
concerns with reporting the preliminary findings on the creation of
building maintenance cost distributions for universities in Malaysia.
This study is triggered by the need to provide guides on maintenance
costs distributions for decision making. For this purpose, a survey
questionnaire was conducted to investigate the distribution of
maintenance costs in the universities. Altogether, responses were
received from twenty universities comprising both private and
publicly owned. The research found that engineering services,
roofing and finishes were the elements contributing the larger
segment of the maintenance costs. Furthermore, the study indicates
the significance of maintenance cost distribution as decision making
tool towards maintenance management.
Abstract: This work presents a new phonetic transcription system based on a tree of hierarchical pronunciation rules expressed as context-specific grapheme-phoneme correspondences. The tree is automatically inferred from a phonetic dictionary by incrementally analyzing deeper context levels, eventually representing a minimum set of exhaustive rules that pronounce without errors all the words in the training dictionary and that can be applied to out-of-vocabulary words. The proposed approach improves upon existing rule-tree-based techniques in that it makes use of graphemes, rather than letters, as elementary orthographic units. A new linear algorithm for the segmentation of a word in graphemes is introduced to enable outof- vocabulary grapheme-based phonetic transcription. Exhaustive rule trees provide a canonical representation of the pronunciation rules of a language that can be used not only to pronounce out-of-vocabulary words, but also to analyze and compare the pronunciation rules inferred from different dictionaries. The proposed approach has been implemented in C and tested on Oxford British English and Basic English. Experimental results show that grapheme-based rule trees represent phonetically sound rules and provide better performance than letter-based rule trees.
Abstract: This paper presents a new circuit arrangement for a
current-mode Wheatstone bridge that is suitable for low-voltage
integrated circuits implementation. Compared to the other proposed
circuits, this circuit features severe reduction of the elements number,
low supply voltage (1V) and low power consumption (
Abstract: Decrease in hardware costs and advances in computer
networking technologies have led to increased interest in the use of
large-scale parallel and distributed computing systems. One of the
biggest issues in such systems is the development of effective
techniques/algorithms for the distribution of the processes/load of a
parallel program on multiple hosts to achieve goal(s) such as
minimizing execution time, minimizing communication delays,
maximizing resource utilization and maximizing throughput.
Substantive research using queuing analysis and assuming job
arrivals following a Poisson pattern, have shown that in a multi-host
system the probability of one of the hosts being idle while other host
has multiple jobs queued up can be very high. Such imbalances in
system load suggest that performance can be improved by either
transferring jobs from the currently heavily loaded hosts to the lightly
loaded ones or distributing load evenly/fairly among the hosts .The
algorithms known as load balancing algorithms, helps to achieve the
above said goal(s). These algorithms come into two basic categories -
static and dynamic. Whereas static load balancing algorithms (SLB)
take decisions regarding assignment of tasks to processors based on
the average estimated values of process execution times and
communication delays at compile time, Dynamic load balancing
algorithms (DLB) are adaptive to changing situations and take
decisions at run time.
The objective of this paper work is to identify qualitative
parameters for the comparison of above said algorithms. In future this
work can be extended to develop an experimental environment to
study these Load balancing algorithms based on comparative
parameters quantitatively.
Abstract: Support Vector Domain Description (SVDD) is one of the best-known one-class support vector learning methods, in which one tries the strategy of using balls defined on the feature space in order to distinguish a set of normal data from all other possible abnormal objects. As all kernel-based learning algorithms its performance depends heavily on the proper choice of the kernel parameter. This paper proposes a new approach to select kernel's parameter based on maximizing the distance between both gravity centers of normal and abnormal classes, and at the same time minimizing the variance within each class. The performance of the proposed algorithm is evaluated on several benchmarks. The experimental results demonstrate the feasibility and the effectiveness of the presented method.
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 atmospheric pressure plasma torch with a direct
current arc discharge stabilized by water vapor vortex was
experimentally investigated. Overheated up to 450K water vapor was
used as plasma forming gas. Plasma torch design is one of the most
important factors leading to a stable operation of the device. The
electrical and thermal characteristics of the plasma torch were
determined during the experimental investigations. The design and
the basic characteristics of the water vapor plasma torch are presented
in the paper.
Plasma torches with the electric arc stabilized by water vapor
vortex provide special performance characteristics in some plasma
processing applications such as thermal plasma neutralization and
destruction of organic wastes enabling to extract high caloric value
synthesis gas as by-product of the process. Syngas could be used as a
surrogate fuel partly replacing the dependence on the fossil fuels or
used as a feedstock for hydrogen, methanol production.
Abstract: In this paper, a new efficient method for load balancing in low voltage distribution systems is presented. The proposed method introduces an improved Leap-frog method for optimization. The proposed objective function includes the difference between three phase currents, as well as two other terms to provide the integer property of the variables; where the latter are the status of the connection of loads to different phases. Afterwards, a new algorithm is supplemented to undertake the integer values for the load connection status. Finally, the method is applied to different parts of Tabriz low voltage network, where the results have shown the good performance of the proposed method.
Abstract: This paper considers the problem of Null-Steering beamforming using Neural Network (NN) approach for antenna array system. Two cases are presented. First, unlike the other authors, the estimated Direction Of Arrivals (DOAs) are used for antenna array weights NN-based determination and the imprecise DOAs estimations are taken into account. Second, the blind null-steering beamforming is presented. In this case the antenna array outputs are presented at the input of the NN without DOAs estimation. The results of computer simulations will show much better relative mean error performances of the first NN approach compared to the NNbased blind beamforming.
Abstract: Many IT projects come to failure because of having
technical approach, focusing on the final product and lack of proper
attention to strategic alignment. Project management models quite
often have technical management view [4], [8], [13], [14]. These
models focus greatly on the finalization of the project product and the
delivery of the product to the customer. However, many project
problems are due to lack of attention to the needs and capabilities of
the organizations or disregarding how to deploy and use the product
in the organization. In this regard, in the current research we are
trying to present a solution with the purpose of raising the value of
the project in an organization. This way, the project outputs will be
properly deployed in the organization. Therefore, a comprehensive
model is presented which takes into account the whole processes
from initial step of project definition to the deployment of the final
outputs in the organization and then the definition of all roles and
responsibilities to put the model into practice. Taking into account
the opinions of experts and project managers, to prove the
performance of the model, the project problems were recognized and
based on the model, categorized and analyzed. And at the end it is
made clear that ignoring the proper definition of the project and not
having a proper understanding of the expected value on the one hand
and not supervising the emerged value in the process of production
and installment are among the most important factors that bring a
project to failure.
Abstract: The multiple traveling salesman problem (mTSP) can be used to model many practical problems. The mTSP is more complicated than the traveling salesman problem (TSP) because it requires determining which cities to assign to each salesman, as well as the optimal ordering of the cities within each salesman's tour. Previous studies proposed that Genetic Algorithm (GA), Integer Programming (IP) and several neural network (NN) approaches could be used to solve mTSP. This paper compared the results for mTSP, solved with Genetic Algorithm (GA) and Nearest Neighbor Algorithm (NNA). The number of cities is clustered into a few groups using k-means clustering technique. The number of groups depends on the number of salesman. Then, each group is solved with NNA and GA as an independent TSP. It is found that k-means clustering and NNA are superior to GA in terms of performance (evaluated by fitness function) and computing time.
Abstract: This paper presents an optimization technique to economic load dispatch (ELD) problems with considering the daily load patterns and generator constraints using a particle swarm optimization (PSO). The objective is to minimize the fuel cost. The optimization problem is subject to system constraints consisting of power balance and generation output of each units. The application of a constriction factor into PSO is a useful strategy to ensure convergence of the particle swarm algorithm. The proposed method is able to determine, the output power generation for all of the power generation units, so that the total constraint cost function is minimized. The performance of the developed methodology is demonstrated by case studies in test system of fifteen-generation units. The results show that the proposed algorithm scan give the minimum total cost of generation while satisfying all the constraints and benefiting greatly from saving in power loss reduction