Abstract: The market competition is moving from the single
firm to the whole supply chain because of increasing competition and
growing need for operational efficiencies and customer orientation.
Supply chain management allows companies to look beyond their
organizational boundaries to develop and leverage resources and
capabilities of their supply chain partners. This creates competitive
advantages in the marketplace and because of this SCM has acquired
strategic importance. Lean Approach is a management strategy that focuses on reducing
every type of waste present in an organization. This approach is
becoming more and more popular among supply chain managers. The supply chain application of lean approach is not frequent. In
particular, it is not well studied which are the impacts of lean
approach principles in a supply chain context. In literature there are
only few studies aimed at understanding the qualitative impact of the
lean approach in supply chains. Therefore, the goal of this research
work is to study the impacts of lean principles implementation along
a supply chain. To achieve this, a simulation model of a threeechelon
multi-product supply chain has been built. Kanban system (and several priority policies) and setup time
reduction degrees are implemented in the lean-configured supply
chain to apply pull and lot-sizing decrease principles respectively. To
evaluate the benefits of lean approach, lean supply chain is compared
with an EOQ-configured supply chain. The simulation results show
that Kanban system and setup-time reduction improve inventory
stock level. They also show that logistics efforts are affected to lean
implementation degree. The paper concludes describing
performances of lean supply chain in different contexts.
Abstract: We introduce a new model called the Marshall-Olkin Rayleigh distribution which extends the Rayleigh distribution using Marshall-Olkin transformation and has increasing and decreasing shapes for the hazard rate function. Various structural properties of the new distribution are derived including explicit expressions for the moments, generating and quantile function, some entropy measures, and order statistics are presented. The model parameters are estimated by the method of maximum likelihood and the observed information matrix is determined. The potentiality of the new model is illustrated by means of a simulation study.
Abstract: Multiple-input multiple-output (MIMO) radar has
received increasing attention in recent years. MIMO radar has many
advantages over conventional phased array radar such as target
detection,resolution enhancement, and interference suppression. In
this paper, the results are presented from a simulation study of MIMO
uniformly-spaced linear array (ULA) antennas. The performance is
investigated under varied parameters, including varied array size,
pseudo random (PN) sequence length, number of snapshots, and
signal to noise ratio (SNR). The results of MIMO are compared to a
traditional array antenna.
Abstract: The paper develops a Non-Linear Model Predictive
Control (NMPC) of water quality in Drinking Water Distribution
Systems (DWDS) based on the advanced non-linear quality dynamics
model including disinfections by-products (DBPs). A special attention
is paid to the analysis of an impact of the flow trajectories prescribed
by an upper control level of the recently developed two-time scale
architecture of an integrated quality and quantity control in DWDS.
The new quality controller is to operate within this architecture in the
fast time scale as the lower level quality controller. The controller
performance is validated by a comprehensive simulation study based
on an example case study DWDS.
Abstract: In general, classical methods such as maximum
likelihood (ML) and least squares (LS) estimation methods are used
to estimate the shape parameters of the Burr XII distribution.
However, these estimators are very sensitive to the outliers. To
overcome this problem we propose alternative robust estimators
based on the M-estimation method for the shape parameters of the
Burr XII distribution. We provide a small simulation study and a real
data example to illustrate the performance of the proposed estimators
over the ML and the LS estimators. The simulation results show that
the proposed robust estimators generally outperform the classical
estimators in terms of bias and root mean square errors when there
are outliers in data.
Abstract: Through the fast growing technologies, design of power factor correction (PFC) circuit is facing several challenges. In this paper, a two-phase interleaved boost converter with ripple steering technique is proposed. Among the various topologies, Interleaved Boost converter (IBC) is considered as superior due to enriched performance, lower ripple content, compact weight and size. A thorough investigation is presented here for the proposed topology. Simulation study for the IBC has been carried out using MATLAB/SIMULINK. Theoretical analysis and hardware prototype has been performed to validate the results.
Abstract: A comprehensive Bayesian analysis has been carried out in the context of informative and non-informative priors for the shape parameter of the Burr type X distribution under different symmetric and asymmetric loss functions. Elicitation of hyperparameter through prior predictive approach is also discussed. Also we derive the expression for posterior predictive distributions, predictive intervals and the credible Intervals. As an illustration, comparisons of these estimators are made through simulation study.
Abstract: This review paper aims at understanding the importance of implementing sustainable green practices in the current hotel industry and the perception of the same from the point of view of the customers as well as the industry experts. Many hotels have benefited from green management such as enhanced reputation of the firm and more worth customers. For the business standing, it reduces business’s cost for posting advertisements and the clear hotel’s orientation shows hotels’ positive image which might increase employees’ recognition toward the business. Sustainability in business is the growth in lively processes which enable people to understand the potential to protect the Earth’s existent support systems. Well, looking to the future today’s green concerns will definitely become facet of more synchronized business environment, perhaps the concerns discussed in this study, may exchange a few words which hotels may consider in near future to widen awareness and improve business model.
Abstract: Distributed Generation (DG) systems are considered an integral part in future distribution system planning. Appropriate size and location of distributed generation plays a significant role in minimizing power losses in distribution systems. Among the benefits of distributed generation is the reduction in active power losses, which can improve the system performance, reliability and power quality. In this paper, Artificial Bee Colony (ABC) algorithm is proposed to determine the optimal DG-unit size and location by loss sensitivity index in order to minimize the real power loss, total harmonic distortion (THD) and voltage sag index improvement. Simulation study is conducted on 69-bus radial test system to verify the efficacy of the proposed method.
Abstract: This paper investigates a method for the state estimation of nonlinear systems described by a class of differential-algebraic equation (DAE) models using the extended Kalman filter. The method involves the use of a transformation from a DAE to ordinary differential equation (ODE). A relevant dynamic power system model using decoupled techniques will be proposed. The estimation technique consists of a state estimator based on the EKF technique as well as the local stability analysis. High performances are illustrated through a simulation study applied on IEEE 13 buses test system.
Abstract: The paper deals with the maximum likelihood estimation of the parameters of the Burr type V distribution based on left censored samples. The maximum likelihood estimators (MLE) of the parameters have been derived and the Fisher information matrix for the parameters of the said distribution has been obtained explicitly. The confidence intervals for the parameters have also been discussed. A simulation study has been conducted to investigate the performance of the point and interval estimates.
Abstract: The article is concerned with analysis of failure rate (shape parameter) under the Topp Leone distribution using a Bayesian framework. Different loss functions and a couple of noninformative priors have been assumed for posterior estimation. The posterior predictive distributions have also been derived. A simulation study has been carried to compare the performance of different estimators. A real life example has been used to illustrate the applicability of the results obtained. The findings of the study suggest that the precautionary loss function based on Jeffreys prior and singly type II censored samples can effectively be employed to
obtain the Bayes estimate of the failure rate under Topp Leone distribution.
Abstract: This paper presents a cold flow simulation study of a small gas turbine combustor performed using laboratory scale test rig. The main objective of this investigation is to obtain physical insight of the main vortex, responsible for the efficient mixing of fuel and air. Such models are necessary for predictions and optimization of real gas turbine combustors. Air swirler can control the combustor performance by assisting in the fuel-air mixing process and by producing recirculation region which can act as flame holders and influences residence time. Thus, proper selection of a swirler is needed to enhance combustor performance and to reduce NOx emissions. Three different axial air swirlers were used based on their vane angles i.e., 30°, 45°, and 60°. Three-dimensional, viscous, turbulent, isothermal flow characteristics of the combustor model operating at room temperature were simulated via Reynolds- Averaged Navier-Stokes (RANS) code. The model geometry has been created using solid model, and the meshing has been done using GAMBIT preprocessing package. Finally, the solution and analysis were carried out in a FLUENT solver. This serves to demonstrate the capability of the code for design and analysis of real combustor. The effects of swirlers and mass flow rate were examined. Details of the complex flow structure such as vortices and recirculation zones were obtained by the simulation model. The computational model predicts a major recirculation zone in the central region immediately downstream of the fuel nozzle and a second recirculation zone in the upstream corner of the combustion chamber. It is also shown that swirler angles changes have significant effects on the combustor flowfield as well as pressure losses.
Abstract: Missing data yields many analysis challenges. In case of complex survey design, in addition to dealing with missing data, researchers need to account for the sampling design to achieve useful inferences. Methods for incorporating sampling weights in neural network imputation were investigated to account for complex survey designs. An estimate of variance to account for the imputation uncertainty as well as the sampling design using neural networks will be provided. A simulation study was conducted to compare estimation results based on complete case analysis, multiple imputation using a Markov Chain Monte Carlo, and neural network imputation. Furthermore, a public-use dataset was used as an example to illustrate neural networks imputation under a complex survey design
Abstract: IEEE 802.16 is a new wireless technology standard, it
has some advantages, including wider coverage, higher bandwidth,
and QoS support. As the new wireless technology for last mile
solution, there are designed two models in IEEE 802.16 standard. One
is PMP (point to multipoint) and the other is Mesh. In this paper we
only focus on IEEE 802.16 Mesh model. According to the IEEE
802.16 standard description, Mesh model has two scheduling modes,
centralized and distributed. Considering the pros and cons of the two
scheduling, we present the combined scheduling QoS framework that
the BS (Base Station) controls time frame scheduling and selects the
shortest path from source to destination directly. On the other hand, we
propose the Expedited Queue mechanism to cut down the transmission
time. The EQ mechanism can reduce a lot of end-to-end delay in our
QoS framework. Simulation study has shown that the average delay is
smaller than contrasts. Furthermore, our proposed scheme can also
achieve higher performance.
Abstract: Ratio and regression type estimators have been used by previous authors to estimate a population mean for the principal variable from samples in which both auxiliary x and principal y variable data are available. However, missing data are a common problem in statistical analyses with real data. Ratio and regression type estimators have also been used for imputing values of missing y data. In this paper, six new ratio and regression type estimators are proposed for imputing values for any missing y data and estimating a population mean for y from samples with missing x and/or y data. A simulation study has been conducted to compare the six ratio and regression type estimators with a previous estimator of Rueda. Two population sizes N = 1,000 and 5,000 have been considered with sample sizes of 10% and 30% and with correlation coefficients between population variables X and Y of 0.5 and 0.8. In the simulations, 10 and 40 percent of sample y values and 10 and 40 percent of sample x values were randomly designated as missing. The new ratio and regression type estimators give similar mean absolute percentage errors that are smaller than the Rueda estimator for all cases. The new estimators give a large reduction in errors for the case of 40% missing y values and sampling fraction of 30%.
Abstract: The conventional GA combined with a local search
algorithm, such as the 2-OPT, forms a hybrid genetic algorithm(HGA)
for the traveling salesman problem (TSP). However, the geometric
properties which are problem specific knowledge can be used to
improve the search process of the HGA. Some tour segments (edges)
of TSPs are fine while some maybe too long to appear in a short tour.
This knowledge could constrain GAs to work out with fine tour
segments without considering long tour segments as often.
Consequently, a new algorithm is proposed, called intelligent-OPT
hybrid genetic algorithm (IOHGA), to improve the GA and the 2-OPT
algorithm in order to reduce the search time for the optimal solution.
Based on the geometric properties, all the tour segments are assigned
2-level priorities to distinguish between good and bad genes. A
simulation study was conducted to evaluate the performance of the
IOHGA. The experimental results indicate that in general the IOHGA
could obtain near-optimal solutions with less time and better accuracy
than the hybrid genetic algorithm with simulated annealing algorithm
(HGA(SA)).
Abstract: In this study, we discussed the effects on the thermal
comfort of super high-rise residences that how effected by the high
thermal capacity structural components. We considered different
building orientations, structures, and insulation methods. We used the
dynamic simulation software THERB (simulation of the thermal
environment of residential buildings). It can estimate the temperature,
humidity, sensible temperature, and heating/cooling load for multiple
buildings. In the past studies, we examined the impact of
air-conditioning loads (hereinafter referred to as AC loads) on the
interior structural parts and the AC-usage patterns of super-high-rise
residences.
Super-high-rise residences have more structural components such
as pillars and beams than do ordinary apartment buildings. The
skeleton is generally made of concrete and steel, which have high
thermal-storage capacities. The thermal-storage capacity of
super-high-rise residences is considered to have a larger impact on the
AC load and thermal comfort than that of ordinary residences.
We show that the AC load of super-high-rise units would be
reduced by installing insulation on the surfaces of interior walls that
are not usually insulated in Japan.
Abstract: A kind of crash energy absorption structure adopted by vehicle simulator crash testing equipment based on mechanical energy
storage was studied. Dynamic explicit finite element simulation was achieved for thin-walled tube structure under different conditions of
section shape, thickness and inducement groove style. Crash energy absorption property of the structure was obtained. After optimization,
a reasonable structure was given which can meet current vehicle crash regulation. And the optimized structure can be adopted in vehicle
simulator, which can increase the practicability of the testing
equipment.
Abstract: Given a bivariate normal sample of correlated variables,
(Xi, Yi), i = 1, . . . , n, an alternative estimator of Pearson’s correlation
coefficient is obtained in terms of the ranges, |Xi − Yi|.
An approximate confidence interval for ρX,Y is then derived, and
a simulation study reveals that the resulting coverage probabilities
are in close agreement with the set confidence levels. As well, a
new approximant is provided for the density function of R, the
sample correlation coefficient. A mixture involving the proposed
approximate density of R, denoted by hR(r), and a density function
determined from a known approximation due to R. A. Fisher is shown
to accurately approximate the distribution of R. Finally, nearly exact
density approximants are obtained on adjusting hR(r) by a 7th degree
polynomial.