Abstract: This paper describes a system-level SoC energy
consumption estimation method based on a dynamic behavior of
embedded software in the early stages of the SoC development. A
major problem of SOC development is development rework caused by
unreliable energy consumption estimation at the early stages. The
energy consumption of an SoC used in embedded systems is strongly
affected by the dynamic behavior of the software. At the early stages
of SoC development, modeling with a high level of abstraction is
required for both the dynamic behavior of the software, and the
behavior of the SoC. We estimate the energy consumption by a UML
model-based simulation. The proposed method is applied for an actual
embedded system in an MFP. The energy consumption estimation of
the SoC is more accurate than conventional methods and this proposed
method is promising to reduce the chance of development rework in
the SoC development. ∈
Abstract: The term Enterprise 2.0 (E2.0) describes a collection of organizational and IT practices that help organizations establish flexible work models, visible knowledge-sharing practices, and higher levels of community participation. E2.0 parallels and builds on another term commonly being used in the industry – Web 2.0. E2.0 represents also new packaging for strategic collaboration and Knowledge Management (KM). Organizations rely on collaboration and KM initiatives to attain innovation, growth, productivity, and performance goals.
Abstract: The problem of laminar fluid flow which results from
the shrinking of a permeable surface in a nanofluid has been
investigated numerically. The model used for the nanofluid
incorporates the effects of Brownian motion and thermophoresis. A
similarity solution is presented which depends on the mass suction
parameter S, Prandtl number Pr, Lewis number Le, Brownian motion
number Nb and thermophoresis number Nt. It was found that the
reduced Nusselt number is decreasing function of each dimensionless
number.
Abstract: The paper deals with an application of quantitative analysis – the Data Envelopment Analysis (DEA) method to performance evaluation of the European Union Member States, in the reference years 2000 and 2011. The main aim of the paper is to measure efficiency changes over the reference years and to analyze a level of productivity in individual countries based on DEA method and to classify the EU Member States to homogeneous units (clusters) according to efficiency results. The theoretical part is devoted to the fundamental basis of performance theory and the methodology of DEA. The empirical part is aimed at measuring degree of productivity and level of efficiency changes of evaluated countries by basic DEA model – CCR CRS model, and specialized DEA approach – the Malmquist Index measuring the change of technical efficiency and the movement of production possibility frontier. Here, DEA method becomes a suitable tool for setting a competitive/uncompetitive position of each country because there is not only one factor evaluated, but a set of different factors that determine the degree of economic development.
Abstract: In this paper, we propose a single sample path based
algorithm with state aggregation to optimize the average rewards of
singularly perturbed Markov reward processes (SPMRPs) with a
large scale state spaces. It is assumed that such a reward process
depend on a set of parameters. Differing from the other kinds of
Markov chain, SPMRPs have their own hierarchical structure. Based
on this special structure, our algorithm can alleviate the load in the
optimization for performance. Moreover, our method can be applied
on line because of its evolution with the sample path simulated.
Compared with the original algorithm applied on these problems of
general MRPs, a new gradient formula for average reward
performance metric in SPMRPs is brought in, which will be proved
in Appendix, and then based on these gradients, the schedule of the
iteration algorithm is presented, which is based on a single sample
path, and eventually a special case in which parameters only
dominate the disturbance matrices will be analyzed, and a precise
comparison with be displayed between our algorithm with the old
ones which is aim to solve these problems in general Markov reward
processes. When applied in SPMRPs, our method will approach a fast
pace in these cases. Furthermore, to illustrate the practical value of
SPMRPs, a simple example in multiple programming in computer
systems will be listed and simulated. Corresponding to some practical
model, physical meanings of SPMRPs in networks of queues will be
clarified.
Abstract: Software testing is important stage of software development cycle. Current testing process involves tester and electronic documents with test case scenarios. In this paper we focus on new approach to testing process using automated test case generation and tester guidance through the system based on the model of the system. Test case generation and model-based testing is not possible without proper system model. We aim on providing better feedback from the testing process thus eliminating the unnecessary paper work.
Abstract: One of the determinants of a firm-s prosperity is the
customers- perceived service quality and satisfaction. While service
quality is wide in scope, and consists of various dimensions, there
may be differences in the relative importance of these dimensions in
affecting customers- overall satisfaction of service quality.
Identifying the relative rank of different dimensions of service quality
is very important in that it can help managers to find out which
service dimensions have a greater effect on customers- overall
satisfaction. Such an insight will consequently lead to more effective
resource allocation which will finally end in higher levels of
customer satisfaction. This issue –despite its criticality- has not
received enough attention so far. Therefore, using a sample of 240
bank customers in Iran, an artificial neural network is developed to
address this gap in the literature. As customers- evaluation of service
quality is a subjective process, artificial neural networks –as a brain
metaphor- may appear to have a potentiality to model such a
complicated process. Proposing a neural network which is able to
predict the customers- overall satisfaction of service quality with a
promising level of accuracy is the first contribution of this study. In
addition, prioritizing the service quality dimensions in affecting
customers- overall satisfaction –by using sensitivity analysis of
neural network- is the second important finding of this paper.
Abstract: Intravitreal injection (IVI) is the most common treatment for eye posterior segment diseases such as endopthalmitis, retinitis, age-related macular degeneration, diabetic retinopathy, uveitis, and retinal detachment. Most of the drugs used to treat vitreoretinal diseases, have a narrow concentration range in which they are effective, and may be toxic at higher concentrations. Therefore, it is critical to know the drug distribution within the eye following intravitreal injection. Having knowledge of drug distribution, ophthalmologists can decide on drug injection frequency while minimizing damage to tissues. The goal of this study was to develop a computer model to predict intraocular concentrations and pharmacokinetics of intravitreally injected drugs. A finite volume model was created to predict distribution of two drugs with different physiochemical properties in the rabbit eye. The model parameters were obtained from literature review. To validate this numeric model, the in vivo data of spatial concentration profile from the lens to the retina were compared with the numeric data. The difference was less than 5% between the numerical and experimental data. This validation provides strong support for the numerical methodology and associated assumptions of the current study.
Abstract: Plasmodium vivax malaria differs from P. falciparum malaria in that a person suffering from P. vivax infection can suffer relapses of the disease. This is due the parasite being able to remain dormant in the liver of the patients where it is able to re-infect the patient after a passage of time. During this stage, the patient is classified as being in the dormant class. The model to describe the transmission of P. vivax malaria consists of a human population divided into four classes, the susceptible, the infected, the dormant and the recovered. The effect of a time delay on the transmission of this disease is studied. The time delay is the period in which the P. vivax parasite develops inside the mosquito (vector) before the vector becomes infectious (i.e., pass on the infection). We analyze our model by using standard dynamic modeling method. Two stable equilibrium states, a disease free state E0 and an endemic state E1, are found to be possible. It is found that the E0 state is stable when a newly defined basic reproduction number G is less than one. If G is greater than one the endemic state E1 is stable. The conditions for the endemic equilibrium state E1 to be a stable spiral node are established. For realistic values of the parameters in the model, it is found that solutions in phase space are trajectories spiraling into the endemic state. It is shown that the limit cycle and chaotic behaviors can only be achieved with unrealistic parameter values.
Abstract: This paper presents a new data oriented model of image. Then a representation of it, ADBT, is introduced. The ability of ADBT is clustering, segmentation, measuring similarity of images etc, with desired precision and corresponding speed.
Abstract: A bond graph model of a hydroelectric plant is
proposed. In order to analyze the system some structural properties
of a bond graph are used. The structural controllability of
the hydroelctric plant is described. Also, the steady state of the
state variables applying the bond graph in a derivative causality
assignment is obtained. Finally, simulation results of the system
are shown.
Abstract: The present study has been carried out with a view to calculate the coastal vulnerability index (CVI) to know the high and low sensitive areas and area of inundation due to future SLR. Both conventional and remotely sensed data were used and analyzed through the modelling technique. Out of the total study area, 8.26% is very high risk, 14.21% high, 9.36% medium, 22.46% low and 7.35% in the very low vulnerable category, due to costal components. Results of the inundation analysis indicate that 225.2 km² and 397 km² of the land area will be submerged by flooding at 1m and 10m inundation levels. The most severely affected sectors are expected to be the residential, industrial and recreational areas. As this coast is planned for future coastal developmental activities, measures such as industrializations, building regulation, urban growth planning and agriculture, development of an integrated coastal zone management, strict enforcement of the Coastal Regulation Zone (CRZ) Act, monitoring of impacts and further research in this regard are recommended for the study area.
Abstract: In this work a surgical simulator is produced which
enables a training otologist to conduct a virtual, real-time prosthetic
insertion. The simulator provides the Ear, Nose and Throat surgeon
with real-time visual and haptic responses during virtual cochlear
implantation into a 3D model of the human Scala Tympani (ST). The
parametric model is derived from measured data as published in the
literature and accounts for human morphological variance, such as
differences in cochlear shape, enabling patient-specific pre- operative
assessment. Haptic modeling techniques use real physical data and
insertion force measurements, to develop a force model which
mimics the physical behavior of an implant as it collides with the ST
walls during an insertion. Output force profiles are acquired from the
insertion studies conducted in the work, to validate the haptic model.
The simulator provides the user with real-time, quantitative insertion
force information and associated electrode position as user inserts the
virtual implant into the ST model. The information provided by this
study may also be of use to implant manufacturers for design
enhancements as well as for training specialists in optimal force
administration, using the simulator. The paper reports on the methods
for anatomical modeling and haptic algorithm development, with
focus on simulator design, development, optimization and validation.
The techniques may be transferrable to other medical applications
that involve prosthetic device insertions where user vision is
obstructed.
Abstract: Undoubtedly, chassis is one of the most important
parts of a vehicle. Chassis that today are produced for vehicles are
made up of four parts. These parts are jointed together by screwing.
Transverse parts are called cross member.
This study reviews the stress generated by cyclic laboratory loads
in front cross member of Peugeot 405. In this paper the finite element
method is used to simulate the welding process and to determine the
physical response of the spot-welded joints. Analysis is done by the
Abaqus software.
The Stresses generated in cross member structure are generally
classified into two groups: The stresses remained in form of residual
stresses after welding process and the mechanical stress generated by
cyclic load. Accordingly the total stress must be obtained by
determining residual stress and mechanical stress separately and then
sum them according to the superposition principle.
In order to improve accuracy, material properties including
physical, thermal and mechanical properties were supposed to be
temperature-dependent. Simulation shows that maximum Von Misses
stresses are located at special points. The model results are then
compared to the experimental results which are reported by
producing factory and good agreement is observed.
Abstract: The fundamental defect inherent to the thermoforming
technology is wall-thickness variation of the products due to
inadequate thermal processing during production of polymer. A
nonlinear viscoelastic rheological model is implemented for
developing the process model. This model describes deformation
process of a sheet in thermoforming process. Because of relaxation
pause after plug-assist stage and also implementation of two stage
thermoforming process have minor wall-thickness variation and
consequently better mechanical properties of polymeric articles. For
model validation, a comparative analysis of the theoretical and
experimental data is presented.
Abstract: The oil and gas industry has moved towards Load and
Resistance Factor Design through API RP2A - LRFD and the
recently published international standard, ISO-19902, for design of
fixed steel offshore structures. The ISO 19902 is intended to provide
a harmonized design practice that offers a balanced structural fitness
for the purpose, economy and safety. As part of an ongoing work, the
reliability analysis of tubular joints of the jacket structure has been
carried out to calibrate the load and resistance factors for the design
of offshore platforms in Malaysia, as proposed in the ISO.
Probabilistic models have been established for the load effects (wave,
wind and current) and the tubular joints strengths. In this study the
First Order Reliability Method (FORM), coded in MATLAB
Software has been employed to evaluate the reliability index of the
typical joints, designed using API RP2A - WSD and ISO 19902.
Abstract: Short term electricity demand forecasts are required
by power utilities for efficient operation of the power grid. In a
competitive market environment, suppliers and large consumers also
require short term forecasts in order to estimate their energy
requirements in advance. Electricity demand is influenced (among
other things) by the day of the week, the time of year and special
periods and/or days such as Ramadhan, all of which must be
identified prior to modelling. This identification, known as day-type
identification, must be included in the modelling stage either by
segmenting the data and modelling each day-type separately or by
including the day-type as an input. Day-type identification is the
main focus of this paper. A Kohonen map is employed to identify the
separate day-types in Algerian data.
Abstract: As the trend of manufacturing is being dominated depending on services, products and processes are more and more related with sophisticated services. Thus, this research starts with the discussion about integration of the product, process, and service in the innovation process. In particular, this paper sets out some foundations for a theory of service innovation in the field of manufacturing, and proposes the dynamic model of service innovation related to product and process. Two dynamic models of service innovation are suggested to investigate major tendencies and dynamic variations during the innovation cycle: co-innovation and sequential innovation. To structure dynamic models of product, process, and service innovation, the innovation stages in which two models are mainly achieved are identified. The research would encourage manufacturers to formulate strategy and planning for service development with product and process.
Abstract: Bone remodeling occurs by the balanced action of
bone resorbing osteoclasts (OC) and bone-building osteoblasts.
Increased bone resorption by excessive OC activity contributes
to malignant and non-malignant diseases including osteoporosis.
To study OC differentiation and function, OC formed in
in vitro cultures are currently counted manually, a tedious
procedure which is prone to inter-observer differences. Aiming
for an automated OC-quantification system, classification of
OC and precursor cells was done on fluorescence microscope
images based on the distinct appearance of fluorescent nuclei.
Following ellipse fitting to nuclei, a combination of eight
features enabled clustering of OC and precursor cell nuclei.
After evaluating different machine-learning techniques, LOGREG
achieved 74% correctly classified OC and precursor cell
nuclei, outperforming human experts (best expert: 55%). In
combination with the automated detection of total cell areas,
this system allows to measure various cell parameters and most
importantly to quantify proteins involved in osteoclastogenesis.
Abstract: Subdivision is a method to create a smooth surface from a coarse mesh by subdividing the entire mesh. The conventional ways to compute and render surfaces are inconvenient both in terms of memory and computational time as the number of meshes will increase exponentially. An adaptive subdivision is the way to reduce the computational time and memory by subdividing only certain selected areas. In this paper, a new adaptive subdivision method for triangle meshes is introduced. This method defines a new adaptive subdivision rules by considering the properties of each triangle's neighbors and is embedded in a traditional Loop's subdivision. It prevents some undesirable side effects that appear in the conventional adaptive ways. Models that were subdivided by our method are compared with other adaptive subdivision methods