Abstract: Different countries have introduced different schemes
and policies to counter global warming. The rationale behind the
proposed policies and the potential barriers to successful
implementation of the policies adopted by the countries were
analyzed and estimated based on different models. It is argued that
these models enhance the transparency and provide a better
understanding to the policy makers. However, these models are
underpinned with several structural and baseline assumptions. These
assumptions, modeling features and future prediction of emission
reductions and other implication such as cost and benefits of a
transition to a low-carbon economy and its economy wide impacts
were discussed. On the other hand, there are potential barriers in the
form political, financial, and cultural and many others that pose a
threat to the mitigation options.
Abstract: Predicting earnings management is vital for the capital
market participants, financial analysts and managers. The aim of this
research is attempting to respond to this query: Is there a significant
difference between the regression model and neural networks’
models in predicting earnings management, and which one leads to a
superior prediction of it? In approaching this question, a Linear
Regression (LR) model was compared with two neural networks
including Multi-Layer Perceptron (MLP), and Generalized
Regression Neural Network (GRNN). The population of this study
includes 94 listed companies in Tehran Stock Exchange (TSE)
market from 2003 to 2011. After the results of all models were
acquired, ANOVA was exerted to test the hypotheses. In general, the
summary of statistical results showed that the precision of GRNN did
not exhibit a significant difference in comparison with MLP. In
addition, the mean square error of the MLP and GRNN showed a
significant difference with the multi variable LR model. These
findings support the notion of nonlinear behavior of the earnings
management. Therefore, it is more appropriate for capital market
participants to analyze earnings management based upon neural
networks techniques, and not to adopt linear regression models.
Abstract: This paper describes how to dimension the electric
components of a 48V hybrid system considering real customer use.
Furthermore, it provides information about savings in energy and
CO2 emissions by a customer-tailored 48V hybrid. Based on measured customer profiles, the electric units such as the
electric motor and the energy storage are dimensioned. Furthermore,
the CO2 reduction potential in real customer use is determined
compared to conventional vehicles. Finally, investigations are carried
out to specify the topology design and preliminary considerations in
order to hybridize a conventional vehicle with a 48V hybrid system.
The emission model results from an empiric approach also taking into
account the effects of engine dynamics on emissions. We analyzed
transient engine emissions during representative customer driving
profiles and created emission meta models. The investigation showed
a significant difference in emissions when simulating realistic
customer driving profiles using the created verified meta models
compared to static approaches which are commonly used for vehicle
simulation.
Abstract: In Automotive Industry, sliding door systems that are
also used as body closures are safety members. Extreme product tests
are realized to prevent failures in design process, but these tests
realized experimentally result in high costs. Finite element analysis is
an effective tool used for design process. These analyses are used
before production of prototype for validation of design according to
customer requirement. In result of this, substantial amount of time
and cost is saved. Finite element model is created for geometries that are designed in
3D CAD programs. Different element types as bar, shell and solid,
can be used for creating mesh model. Cheaper model can be created
by selection of element type, but combination of element type that
was used in model, number and geometry of element and degrees of
freedom affects the analysis result. Sliding door system is a good
example which used these methods for this study. Structural analysis
was realized for sliding door mechanism by using FE models. As
well, physical tests that have same boundary conditions with FE
models were realized. Comparison study for these element types,
were done regarding test and analyses results then optimum
combination was achieved.
Abstract: This study aims to increase understanding of the
transition of business models in servitization. The significance of
service in all business has increased dramatically during the past
decades. Service-dominant logic (SDL) describes this change in the
economy and questions the goods-dominant logic on which business
has primarily been based in the past. A business model canvas is one
of the most cited and used tools in defining end developing business
models. The starting point of this paper lies in the notion that the
traditional business model canvas is inherently goods-oriented and
best suits for product-based business. However, the basic differences
between goods and services necessitate changes in business model
representations when proceeding in servitization. Therefore, new
knowledge is needed on how the conception of business model and
the business model canvas as its representation should be altered in
servitized firms in order to better serve business developers and interfirm
co-creation. That is to say, compared to products, services are
intangible and they are co-produced between the supplier and the
customer. Value is always co-created in interaction between a
supplier and a customer, and customer experience primarily depends
on how well the interaction succeeds between the actors. The role of
service experience is even stronger in service business compared to
product business, as services are co-produced with the customer. This paper provides business model developers with a service
business model canvas, which takes into account the intangible,
interactive, and relational nature of service. The study employs a
design science approach that contributes to theory development via
design artifacts. This study utilizes qualitative data gathered in
workshops with ten companies from various industries. In particular,
key differences between Goods-dominant logic (GDL) and SDLbased
business models are identified when an industrial firm
proceeds in servitization. As the result of the study, an updated version of the business
model canvas is provided based on service-dominant logic. The
service business model canvas ensures a stronger customer focus and
includes aspects salient for services, such as interaction between
companies, service co-production, and customer experience. It can be
used for the analysis and development of a current service business
model of a company or for designing a new business model. It
facilitates customer-focused new service design and service
development. It aids in the identification of development needs, and
facilitates the creation of a common view of the business model.
Therefore, the service business model canvas can be regarded as a
boundary object, which facilitates the creation of a common
understanding of the business model between several actors involved.
The study contributes to the business model and service business
development disciplines by providing a managerial tool for
practitioners in service development. It also provides research insight
into how servitization challenges companies’ business models.
Abstract: Anammox is a novel and promising technology that has changed the traditional concept of biological nitrogen removal. The process facilitates direct oxidation of ammonical nitrogen under anaerobic conditions with nitrite as an electron acceptor without addition of external carbon sources. The present study investigated the feasibility of Anammox Hybrid Reactor (AHR) combining the dual advantages of suspended and attached growth media for biodegradation of ammonical nitrogen in wastewater. Experimental unit consisted of 4 nos. of 5L capacity AHR inoculated with mixed seed culture containing anoxic and activated sludge (1:1). The process was established by feeding the reactors with synthetic wastewater containing NH4-H and NO2-N in the ratio 1:1 at HRT (hydraulic retention time) of 1 day. The reactors were gradually acclimated to higher ammonium concentration till it attained pseudo steady state removal at a total nitrogen concentration of 1200 mg/l. During this period, the performance of the AHR was monitored at twelve different HRTs varying from 0.25-3.0 d with increasing NLR from 0.4 to 4.8 kg N/m3d. AHR demonstrated significantly higher nitrogen removal (95.1%) at optimal HRT of 1 day. Filter media in AHR contributed an additional 27.2% ammonium removal in addition to 72% reduction in the sludge washout rate. This may be attributed to the functional mechanism of filter media which acts as a mechanical sieve and reduces the sludge washout rate many folds. This enhances the biomass retention capacity of the reactor by 25%, which is the key parameter for successful operation of high rate bioreactors. The effluent nitrate concentration, which is one of the bottlenecks of anammox process was also minimised significantly (42.3-52.3 mg/L). Process kinetics was evaluated using first order and Grau-second order models. The first-order substrate removal rate constant was found as 13.0 d-1. Model validation revealed that Grau second order model was more precise and predicted effluent nitrogen concentration with least error (1.84±10%). A new mathematical model based on mass balance was developed to predict N2 gas in AHR. The mass balance model derived from total nitrogen dictated significantly higher correlation (R2=0.986) and predicted N2 gas with least error of precision (0.12±8.49%). SEM study of biomass indicated the presence of heterogeneous population of cocci and rod shaped bacteria of average diameter varying from 1.2-1.5 mm. Owing to enhanced NRE coupled with meagre production of effluent nitrate and its ability to retain high biomass, AHR proved to be the most competitive reactor configuration for dealing with nitrogen laden wastewater.
Abstract: Tannase (tannin acyl hydrolase, E.C.3.1.1.20) is an
important hydrolysable enzyme with innumerable applications and
industrial potential. In the present study, a kinetic model has been
developed for the batch fermentation used for the production of
tannase by A.flavus MTCC 3783. Maximum tannase activity of
143.30 U/ml was obtained at 96 hours under optimum operating
conditions at 35oC, an initial pH of 5.5 and with an inducer tannic
acid concentration of 3% (w/v) for a fermentation period of 120
hours. The biomass concentration reaches a maximum of 6.62 g/l at
96 hours and further there was no increase in biomass concentration
till the end of the fermentation. Various unstructured kinetic models
were analyzed to simulate the experimental values of microbial
growth, tannase activity and substrate concentration. The Logistic
model for microbial growth , Luedeking - Piret model for production
of tannase and Substrate utilization kinetic model for utilization of
substrate were capable of predicting the fermentation profile with
high coefficient of determination (R2) values of 0.980, 0.942 and
0.983 respectively. The results indicated that the unstructured models
were able to describe the fermentation kinetics more effectively.
Abstract: The current paper presents an extensive bottom-up
framework for assessing building sector-specific vulnerability to
climate change: energy supply and demand. The research focuses on
the application of downscaled seasonal models for estimating energy
performance of buildings in Greece. The ARW-WRF model has
been set-up and suitably parameterized to produce downscaled
climatological fields for Greece, forced by the output of the CFSv2
model. The outer domain, D01/Europe, included 345 x 345 cells of
horizontal resolution 20 x 20 km2 and the inner domain, D02/Greece,
comprised 180 x 180 cells of 5 x 5 km2 horizontal resolution. The
model run has been setup for a period with a forecast horizon of 6
months, storing outputs on a six hourly basis.
Abstract: The quantitative study of cell mechanics is of
paramount interest, since it regulates the behaviour of the living cells
in response to the myriad of extracellular and intracellular
mechanical stimuli. The novel experimental techniques together with
robust computational approaches have given rise to new theories and
models, which describe cell mechanics as combination of
biomechanical and biochemical processes. This review paper
encapsulates the existing continuum-based computational approaches
that have been developed for interpreting the mechanical responses of
living cells under different loading and boundary conditions. The
salient features and drawbacks of each model are discussed from both
structural and biological points of view. This discussion can
contribute to the development of even more precise and realistic
computational models of cell mechanics based on continuum
approaches or on their combination with microstructural approaches,
which in turn may provide a better understanding of
mechanotransduction in living cells.
Abstract: Single angle connections, which are bolted to the beam
web and the column flange, are studied to investigate their
moment-rotation behavior. Elastic–perfectly plastic material behavior
is assumed. ABAQUS software is used to analyze the nonlinear
behavior of a single angle connection. The identical geometric and
material conditions with Lipson’s test are used for verifying finite
element models. Since Kishi and Chen’s Power model and Lee and
Moon’s Log model are accurate only for a limited range of mechanism,
simpler and more accurate hyperbolic function models are proposed.
Abstract: 3-roller conical bending process is widely used in the
industries for manufacturing of conical sections and shells. It
involves static as well dynamic bending stages. Analytical models for
prediction of bending force during static as well as dynamic bending
stage are available in the literature. In this paper bending forces
required for static bending stage and dynamic bending stages have
been compared using the analytical models. It is concluded that force
required for dynamic bending is very less as compared to the bending
force required during the static bending stage.
Abstract: Rapid Prototyping (RP) technologies enable physical
parts to be produced from various materials without depending on the
conventional tooling. Fused Deposition Modeling (FDM) is one of
the famous RP processes used at present. Tensile strength and
compressive strength resistance will be identified for different sample
structures and different layer orientations of ABS rapid prototype
solid models. The samples will be fabricated by a FDM rapid
prototyping machine in different layer orientations with variations in
internal geometrical structure. The 0° orientation where layers were
deposited along the length of the samples displayed superior strength
and impact resistance over all the other orientations. The anisotropic
properties were probably caused by weak interlayer bonding and
interlayer porosity.
Abstract: This paper presents an application of a “Systematic
Soft Domain Driven Design Framework” as a soft systems approach
to domain-driven design of information systems development. The
framework use SSM as a guiding methodology within which we have
embedded a sequence of design tasks based on the UML leading to
the implementation of a software system using the Naked Objects
framework. This framework have been used in action research
projects that have involved the investigation and modelling of
business processes using object-oriented domain models and the
implementation of software systems based on those domain models.
Within this framework, Soft Systems Methodology (SSM) is used as
a guiding methodology to explore the problem situation and to
develop the domain model using UML for the given business
domain. The framework is proposed and evaluated in our previous
works, and a real case study “Information Retrieval System for
academic research” is used, in this paper, to show further practice and
evaluation of the framework in different business domain. We argue
that there are advantages from combining and using techniques from
different methodologies in this way for business domain modelling.
The framework is overviewed and justified as multimethodology
using Mingers multimethodology ideas.
Abstract: In this study, three robust predicting methods, namely artificial neural network (ANN), adaptive neuro fuzzy inference system (ANFIS) and support vector machine (SVM) were used for computing the resonant frequency of A-shaped compact microstrip antennas (ACMAs) operating at UHF band. Firstly, the resonant frequencies of 144 ACMAs with various dimensions and electrical parameters were simulated with the help of IE3D™ based on method of moment (MoM). The ANN, ANFIS and SVM models for computing the resonant frequency were then built by considering the simulation data. 124 simulated ACMAs were utilized for training and the remaining 20 ACMAs were used for testing the ANN, ANFIS and SVM models. The performance of the ANN, ANFIS and SVM models are compared in the training and test process. The average percentage errors (APE) regarding the computed resonant frequencies for training of the ANN, ANFIS and SVM were obtained as 0.457%, 0.399% and 0.600%, respectively. The constructed models were then tested and APE values as 0.601% for ANN, 0.744% for ANFIS and 0.623% for SVM were achieved. The results obtained here show that ANN, ANFIS and SVM methods can be successfully applied to compute the resonant frequency of ACMAs, since they are useful and versatile methods that yield accurate results.
Abstract: In this paper, a new concept of closed-loop design for a
product is presented. The closed-loop design model is developed by
integrating forward design and reverse design. Based on this new
concept, a closed-loop design model for sustainable manufacturing by
integrated evaluation of forward design, reverse design, and green
manufacturing using a fuzzy analytic network process is developed. In
the design stage of a product, with a given product requirement and
objective, there can be different ways to design the detailed
components and specifications. Therefore, there can be different
design cases to achieve the same product requirement and objective.
Subsequently, in the design evaluation stage, it is required to analyze
and evaluate the different design cases. The purpose of this research is
to develop a model for evaluating the design cases by integrated
evaluating the criteria in forward design, reverse design, and green
manufacturing. A fuzzy analytic network process method is presented
for integrated evaluation of the criteria in the three models. The
comparison matrices for evaluating the criteria in the three groups are
established. The total relational values among the three groups
represent the total relational effects. In applications, a super matrix
model is created and the total relational values can be used to evaluate
the design cases for decision-making to select the final design case. An
example product is demonstrated in this presentation. It shows that the
model is useful for integrated evaluation of forward design, reverse
design, and green manufacturing to achieve a closed-loop design for
sustainable manufacturing objective.
Abstract: This paper presents a method of evaluating the effect
of aggregate angularity on hot mix asphalt (HMA) properties and its
relationship to the Permanent Deformation resistance. The research
concluded that aggregate particle angularity had a significant effect
on the Permanent Deformation performance, and also that with an
increase in coarse aggregate angularity there was an increase in the
resistance of mixes to Permanent Deformation. A comparison
between the measured data and predictive data of permanent
deformation predictive models showed the limits of existing
prediction models. The numerical analysis described the permanent
deformation zones and concluded that angularity has an effect of the
onset of these zones. Prediction of permanent deformation help road
agencies and by extension economists and engineers determine the
best approach for maintenance, rehabilitation, and new construction
works of the road infrastructure.
Abstract: This paper analyzes the conceptual framework of three
statistical methods, multiple regression, path analysis, and structural
equation models. When establishing research model of the statistical
modeling of complex social phenomenon, it is important to know the
strengths and limitations of three statistical models. This study
explored the character, strength, and limitation of each modeling and
suggested some strategies for accurate explaining or predicting the
causal relationships among variables. Especially, on the studying of
depression or mental health, the common mistakes of research
modeling were discussed.
Abstract: We evaluate the performance of a numerical method
for global optimization of expensive functions. The method is using a
response surface to guide the search for the global optimum. This
metamodel could be based on radial basis functions, kriging, or a
combination of different models. We discuss how to set the cyclic
parameters of the optimization method to get a balance between local
and global search. We also discuss the eventual problem with Runge
oscillations in the response surface.
Abstract: This work is the first dowel in a rather wide research
activity in collaboration with Euro Mediterranean Center for Climate
Changes, aimed at introducing scalable approaches in Ocean
Circulation Models. We discuss designing and implementation of
a parallel algorithm for solving the Variational Data Assimilation
(DA) problem on Graphics Processing Units (GPUs). The algorithm
is based on the fully scalable 3DVar DA model, previously proposed
by the authors, which uses a Domain Decomposition approach
(we refer to this model as the DD-DA model). We proceed with
an incremental porting process consisting of 3 distinct stages:
requirements and source code analysis, incremental development of
CUDA kernels, testing and optimization. Experiments confirm the
theoretic performance analysis based on the so-called scale up factor
demonstrating that the DD-DA model can be suitably mapped on
GPU architectures.
Abstract: The main objective of this paper is to provide a new
methodology for road safety assessment in Oman through the
development of suitable accident prediction models. GLM technique
with Poisson or NBR using SAS package was carried out to develop
these models. The paper utilized the accidents data of 31 un-signalized
T-intersections during three years. Five goodness-of-fit
measures were used to assess the overall quality of the developed
models. Two types of models were developed separately; the flow-based
models including only traffic exposure functions, and the full
models containing both exposure functions and other significant
geometry and traffic variables.
The results show that, traffic exposure functions produced much
better fit to the accident data. The most effective geometric variables
were major-road mean speed, minor-road 85th percentile speed,
major-road lane width, distance to the nearest junction, and right-turn
curb radius.
The developed models can be used for intersection treatment or
upgrading and specify the appropriate design parameters of T-intersections.
Finally, the models presented in this thesis reflect the intersection
conditions in Oman and could represent the typical conditions in
several countries in the middle east area, especially gulf countries.