Abstract: MC (Management Control)& IC (Internal Control) – what is the relationship? (an empirical study into the definitions between MC and IC) based on the wider considerations of Internal Control and Management Control terms, attention is focused not only on the financial aspects but also more on the soft aspects of the business, such as culture, behaviour, standards and values. The limited considerations of Management Control are focused mainly in the hard, financial aspects of business operation. The definitions of Management Control and Internal Control are often used interchangeably and the results of this empirical study reveal that Management Control is part of Internal Control, there is no causal link between the two concepts. Based on the interpretation of the respondents, the term Management Control has moved from a broad term to a more limited term with the soft aspects of the influencing of behaviour, performance measurements, incentives and culture. This paper is an exploratory study based on qualitative research and on a qualitative matrix method analysis of the thematic definition of the terms Management Control and Internal Control.
Abstract: In this paper, the requirement for Coke quality
prediction, its role in Blast furnaces, and the model output is
explained. By applying method of Artificial Neural Networking
(ANN) using back propagation (BP) algorithm, prediction model has
been developed to predict CSR. Important blast furnace functions
such as permeability, heat exchanging, melting, and reducing
capacity are mostly connected to coke quality. Coke quality is further
dependent upon coal characterization and coke making process
parameters. The ANN model developed is a useful tool for process
experts to adjust the control parameters in case of coke quality
deviations. The model also makes it possible to predict CSR for new
coal blends which are yet to be used in Coke Plant. Input data to the
model was structured into 3 modules, for tenure of past 2 years and
the incremental models thus developed assists in identifying the
group causing the deviation of CSR.
Abstract: In this study, the numerical solution of unsteady flow
between two concentric rotating spheres with suction and blowing at
their boundaries is presented. The spheres are rotating about a
common axis of rotation while their angular velocities are constant.
The Navier-Stokes equations are solved by employing the finite
difference method and implicit scheme. The resulting flow patterns
are presented for various values of the flow parameters including
rotational Reynolds number Re , and a blowing/suction Reynolds
number Rew . Viscous torques at the inner and the outer spheres are
calculated, too. It is seen that increasing the amount of suction and
blowing decrease the size of eddies generated in the annulus.
Abstract: Validation of an automation system is an important issue. The goal is to check if the system under investigation, modeled by a Petri net, never enters the undesired states. Usually, tools dedicated to Petri nets such as DESIGN/CPN are used to make reachability analysis. The biggest problem with this approach is that it is impossible to generate the full occurence graph of the system because it is too large. In this paper, we show how computational methods such as temporal logic model checking and Groebner bases can be used to verify the correctness of the design of an automation system. We report our experimental results with two automation systems: the Automated Guided Vehicle (AGV) system and the traffic light system. Validation of these two systems ranged from 10 to 30 seconds on a PC depending on the optimizing parameters.
Abstract: In order to improve control performance and eliminate steady, a coupling compensation for 6-DOF parallel robot is presented. Taking dynamic load Tank Simulator as the research object, this paper analyzes the coupling of 6-DOC parallel robot considering the degree of freedom of the 6-DOF parallel manipulator. The coupling angle and coupling velocity are derived based on inverse kinematics model. It uses the mechanism-model combined method which takes practical moving track that considering the performance of motion controller and motor as its input to make the study. Experimental results show that the coupling compensation improves motion stability as well as accuracy. Besides, it decreases the dither amplitude of dynamic load Tank Simulator.
Abstract: Random Forests are a powerful classification technique, consisting of a collection of decision trees. One useful feature of Random Forests is the ability to determine the importance of each variable in predicting the outcome. This is done by permuting each variable and computing the change in prediction accuracy before and after the permutation. This variable importance calculation is similar to a one-factor-at a time experiment and therefore is inefficient. In this paper, we use a regular fractional factorial design to determine which variables to permute. Based on the results of the trials in the experiment, we calculate the individual importance of the variables, with improved precision over the standard method. The method is illustrated with a study of student attrition at Monash University.
Abstract: The development of the signal compression
algorithms is having compressive progress. These algorithms are
continuously improved by new tools and aim to reduce, an average,
the number of bits necessary to the signal representation by means of
minimizing the reconstruction error. The following article proposes
the compression of Arabic speech signal by a hybrid method
combining the wavelet transform and the linear prediction. The
adopted approach rests, on one hand, on the original signal
decomposition by ways of analysis filters, which is followed by the
compression stage, and on the other hand, on the application of the
order 5, as well as, the compression signal coefficients. The aim of
this approach is the estimation of the predicted error, which will be
coded and transmitted. The decoding operation is then used to
reconstitute the original signal. Thus, the adequate choice of the
bench of filters is useful to the transform in necessary to increase the
compression rate and induce an impercevable distortion from an
auditive point of view.
Abstract: This paper presents image compression with wavelet based method. The wavelet transformation divides image to low- and high pass filtered parts. The traditional JPEG compression technique requires lower computation power with feasible losses, when only compression is needed. However, there is obvious need for wavelet based methods in certain circumstances. The methods are intended to the applications in which the image analyzing is done parallel with compression. Furthermore, high frequency bands can be used to detect changes or edges. Wavelets enable hierarchical analysis for low pass filtered sub-images. The first analysis can be done for a small image, and only if any interesting is found, the whole image is processed or reconstructed.
Abstract: Recently, Cassava has been the driving force of many
developing countries- economic progress. To attain this level,
prerequisites were put in place enabling cassava sector to become an
industrial and a highly competitive crop. Cameroon can achieve the
same results. Moreover, it can upgrade the living conditions of both
rural and urban dwellers and stimulate the development of the whole
economy. Achieving this outcome calls for agricultural policy
reforms. The adoption and implementation of adequate policies go
along with efficient strategies. To choose effective strategies, an indepth
investigation of the sector-s problems is highly recommended.
This paper uses gap analysis method to evaluate cassava sector in
Cameroon. It studies the present situation (where it is now),
interrogates the future (where it should be) and finally proposes
solutions to fill the gap.
Abstract: Detection of incipient abnormal events is important to
improve safety and reliability of machine operations and reduce losses
caused by failures. Improper set-ups or aligning of parts often leads to
severe problems in many machines. The construction of prediction
models for predicting faulty conditions is quite essential in making
decisions on when to perform machine maintenance. This paper
presents a multivariate calibration monitoring approach based on the
statistical analysis of machine measurement data. The calibration
model is used to predict two faulty conditions from historical reference
data. This approach utilizes genetic algorithms (GA) based variable
selection, and we evaluate the predictive performance of several
prediction methods using real data. The results shows that the
calibration model based on supervised probabilistic principal
component analysis (SPPCA) yielded best performance in this work.
By adopting a proper variable selection scheme in calibration models,
the prediction performance can be improved by excluding
non-informative variables from their model building steps.
Abstract: In this paper, we are interested in attitude control of a satellite, which using wheels of reaction, by state feedback. First, we develop a method allowing us to put the control and its integral in the state-feedback form. Then, by using the theorem of Gronwall- Bellman, we put the sufficient conditions so that the nonlinear system modeling the satellite is stabilisable and observed by state feedback.
Abstract: Cooperative communication scheme can be substituted
for multiple-input multiple-output (MIMO) technique when it may
not be able to support multiple antennas due to size, cost or
hardware limitations. In other words, cooperative communication
scheme is an efficient method to achieve spatial diversity without
multiple antennas. For satisfaction of rising QoS, we propose a
reliable cooperative communication scheme with M-QAM based Dual
Carrier Modulation (M-DCM), which can increase diversity gain.
Although our proposed scheme is very simple method, it gives us
frequency and spatial diversity. Simulation result shows our proposed
scheme obtains diversity gain more than the conventional cooperative
communication scheme.
Abstract: In this paper, novel techniques in increasing the accuracy
and speed of convergence of a Feed forward Back propagation
Artificial Neural Network (FFBPNN) with polynomial activation
function reported in literature is presented. These technique was
subsequently used to determine the coefficients of Autoregressive
Moving Average (ARMA) and Autoregressive (AR) system. The
results obtained by introducing sequential and batch method of weight
initialization, batch method of weight and coefficient update, adaptive
momentum and learning rate technique gives more accurate result
and significant reduction in convergence time when compared t the
traditional method of back propagation algorithm, thereby making
FFBPNN an appropriate technique for online ARMA coefficient
determination.
Abstract: This paper examines many mathematical methods for
molding the hourly price forward curve (HPFC); the model will be
constructed by numerous regression methods, like polynomial
regression, radial basic function neural networks & a furrier series.
Examination the models goodness of fit will be done by means of
statistical & graphical tools. The criteria for choosing the model will
depend on minimize the Root Mean Squared Error (RMSE), using the
correlation analysis approach for the regression analysis the optimal
model will be distinct, which are robust against model
misspecification. Learning & supervision technique employed to
determine the form of the optimal parameters corresponding to each
measure of overall loss. By using all the numerical methods that
mentioned previously; the explicit expressions for the optimal model
derived and the optimal designs will be implemented.
Abstract: Focusing on the environmental issues, including the reduction of scrap and consumer residuals, along with the benefiting from the economic value during the life cycle of goods/products leads the companies to have an important competitive approach. The aim of this paper is to present a new mixed nonlinear facility locationallocation model in recycling collection networks by considering multi-echelon, multi-suppliers, multi-collection centers and multifacilities in the recycling network. To make an appropriate decision in reality, demands, returns, capacities, costs and distances, are regarded uncertain in our model. For this purpose, a fuzzy mathematical programming-based possibilistic approach is introduced as a solution methodology from the recent literature to solve the proposed mixed-nonlinear programming model (MNLP). The computational experiments are provided to illustrate the applicability of the designed model in a supply chain environment and to help the decision makers to facilitate their analysis.
Abstract: Falls are the primary cause of accidents in people over
the age of 65, and frequently lead to serious injuries. Since the early
detection of falls is an important step to alert and protect the aging
population, a variety of research on detecting falls was carried out
including the use of accelerators, gyroscopes and tilt sensors. In
exiting studies, falls were detected using an accelerometer with
errors. In this study, the proposed method for detecting falls was to
use two accelerometers to reject wrong falls detection. As falls are
accompanied by the acceleration of gravity and rotational motion, the
falls in this study were detected by using the z-axial acceleration
differences between two sites. The falls were detected by calculating
the difference between the analyses of accelerometers placed on two
different positions on the chest of the subject. The parameters of the
maximum difference of accelerations (diff_Z) and the integration of
accelerations in a defined region (Sum_diff_Z) were used to form the
fall detection algorithm. The falls and the activities of daily living
(ADL) could be distinguished by using the proposed parameters
without errors in spite of the impact and the change in the positions
of the accelerometers. By comparing each of the axial accelerations,
the directions of falls and the condition of the subject afterwards
could be determined.In this study, by using two accelerometers
without errors attached to two sites to detect falls, the usefulness of
the proposed fall detection algorithm parameters, diff_Z and
Sum_diff_Z, were confirmed.
Abstract: In a recent major industry-supported research and development study, a novel framework was developed and applied for assessment of reliability and quality performance levels in reallife power systems with practical large-scale sizes. The new assessment methodology is based on three metaphors (dimensions) representing the relationship between available generation capacities and required demand levels. The paper shares the results of the successfully completed stud and describes the implementation of the new methodology on practical zones in the Saudi electricity system.
Abstract: Effectiveness and efficiency of food distribution is necessary to maintain food security in a region. Food supply varies among regions depending on their production capacity; therefore, it is necessary to regulate food distribution. Sea transportation could play a great role in the food distribution system. To play this role and to support transportation needs in the Eastern Indonesia, sea transportation shall be supported by fleet which is adequate and reliable, both in terms of load and worthiness. This research uses Linear Programming (LP) method to analyze food distribution pattern in order to determine the optimal distribution system. In this research, transshipment points have been selected for regions in one province. Comparison between result of modeling and existing shipping route reveals that from 369 existing routes, 54 routes are used for transporting rice, corn, green bean, peanut, soybean, sweet potato, and cassava.
Abstract: Highly ordered TiO2 nanotube (TNT) arrays were
fabricated onto a pre-treated titanium foil by anodic oxidation with a
voltage of 20V in phosphoric acid/sodium fluoride electrolyte. A pretreatment
of titanium foil involved washing with acetone,
isopropanol, ethanol and deionized water. Carbon doped TiO2
nanotubes (C-TNT) was fabricated 'in-situ' with the same method in
the presence of polyvinyl alcohol and urea as carbon sources. The
affects of polyvinyl alcohol concentration and oxidation time on the
composition, morphology and structure of the C-TN were studied by
FE-SEM, EDX and XRD techniques. FESEM images of the
nanotubes showed uniform arrays of C-TNTs. The density and
microstructures of the nanotubes were greatly affected by the content
of PVA. The introduction of the polyvinyl alcohol into the electrolyte
increases the amount of C content inside TiO2 nanotube arrays
uniformly. The influence of carbon content on the photo-current of
C-TNT was investigated and the I-V profiles of the nanotubes were
established. The preliminary results indicated that the 'in-situ'
doping technique produced a superior quality nanotubes compared to
post doping techniques.
Abstract: The paper presents the results of the European EIE
project “Realising the potential for small scale renewable energy
sources in the home – Kyotointhehome". The project's global aim is
to inform and educate teachers, students and their families so that
they can realise the need and can assess the potential for energy
efficiency (EE) measures and renewable energy sources (RES) in
their homes. The project resources were translated and trialled by 16
partners in 10 European countries.
A web-based methodology which will enable families to assess
how RES can be incorporated into energy efficient homes was
accomplished. The web application “KYOTOINHOME" will help
the citizens to identify what they can do to help their community
meet the Kyoto target for greenhouse gas reductions and prevent
global warming. This application provides useful information on how
the citizens can use renewable energy sources in their home to
provide space heating and cooling, hot water and electricity. A
methodology for assessing heat loss in a dwelling and application of
heat pump system was elaborated and will be implemented this year.
For schools, we developed a set of practical activities concerned with
preventing climate change through using renewable energy sources.
Complementary resources will also developed in the Romanian
research project “Romania Contribution to the European Targets
Regarding the Development of Renewable Energy Sources" -
PROMES.