Abstract: The ever growing sentiment of environmentalism across the globe has made many people think on the green lines. But most of such ideas halt short of implementation because of the short term economic viability issues with the concept of going green. In this paper we have tried to amalgamate the green concept with social entrepreneurship for solving a variety of issues faced by the society today. In addition the paper also tries to ensure that the short term economic viability does not act as a deterrent. The paper comes up three sustainable models of social entrepreneurship which tackle a wide assortment of issues such as nutrition problem, land problems, pollution problems and employment problems. The models described fall under the following heads: - Spirulina cultivation: The model addresses nutrition, land and employment issues. It deals with cultivation of a blue green alga called Spirulina which can be used as a very nutritious food. Also, the implementation of this model would bring forth employment to the poor people of the area. - Biocomposites: The model comes up with various avenues in which biocomposites can be used in an economically sustainable manner. This model deals with the environmental concerns and addresses the depletion of natural resources. - Packaging material from empty fruit bunches (EFB) of oil palm: This one deals with air and land pollution. It is intended to be a substitute for packaging materials made from Styrofoam and plastics which are non-biodegradable. It takes care of the biodegradability and land pollution issues. It also reduces air pollution as the empty fruit bunches are not incinerated. All the three models are sustainable and do not deplete the natural resources any further. This paper explains each of the models in detail and deals with the operational/manufacturing procedures and cost analysis while also throwing light on the benefits derived and sustainability aspects.
Abstract: Skin color based tracking techniques often assume a
static skin color model obtained either from an offline set of library
images or the first few frames of a video stream. These models
can show a weak performance in presence of changing lighting or
imaging conditions. We propose an adaptive skin color model based
on the Gaussian mixture model to handle the changing conditions.
Initial estimation of the number and weights of skin color clusters
are obtained using a modified form of the general Expectation
maximization algorithm, The model adapts to changes in imaging
conditions and refines the model parameters dynamically using spatial
and temporal constraints. Experimental results show that the method
can be used in effectively tracking of hand and face regions.
Abstract: The present paper reports the removal of Cd(II) and
Zn(II) ions using synthetic Zeolit NaA. The adsorption capacity of
the sorbent (Zeolite NaA) strongly depends on simultaneous or not
simultaneous (concurrent) presence of Cd(II) and Zn(II) in the
sorbate. When Cd(II) and Zn(II) are present simultaneously
(concurrently) in the sorbate, Zn(II) ions were sorbed at higher rate.
Equilibrium data fitted Langmuir, Freundlich and Tempkin isotherms
well. The applicability of the isotherm equation to describe the
adsorption process was judged by the correlation coefficients R2. The
Langmuir model yielded the best fit with R2 values equal to or higher
than 0.970, as compared to the Freundlich and Tempkin models. The
fact that 1/n values range from 0.322 to 0.755 indicates that the
adsorption of Cd(II) and Zn(II) ions from aqueous solutions also
favored by the Freundlich model.
Abstract: The paper provides a discussion of the most relevant
aspects of yield curve modeling. Two classes of models are
considered: stochastic and parsimonious function based, through the
approaches developed by Vasicek (1977) and Nelson and Siegel
(1987). Yield curve estimates for Croatia are presented and their
dynamics analyzed and finally, a comparative analysis of models is
conducted.
Abstract: Experimental liquid-liquid equilibra of butan-2-ol -
ethanol -water; pentan-1-ol - ethanol - water and toluene - acetone -
water ternary systems were investigated at (25oC). The reliability of
the experimental tie-line data was ascertained by using Othmer-Tobias
and Hand plots. The distribution coefficients (D) and separation
factors (S) of the immiscibility region were evaluated for the three
systems.
Abstract: In this work, several ASP solutions were flooded into
fractured models initially saturated with heavy oil at a constant flow
rate and different geometrical characteristics of fracture. The ASP
solutions are constituted from 2 polymers i.e. a synthetic polymer,
hydrolyzed polyacrylamide as well as a biopolymer, a surfactant and
2types of alkaline. The results showed that using synthetic
hydrolyzed polyacrylamide polymer increases ultimate oil recovery;
however, type of alkaline does not play a significant rule on oil
recovery. In addition, position of the injection well respect to the
fracture system has remarkable effects on ASP flooding. For instance
increasing angle of fractures with mean flow direction causes more
oil recovery and delays breakthrough time. This work can be
accounted as a comprehensive survey on ASP flooding which
considers most of effective factors in this chemical EOR method.
Abstract: The deviation between the target state variable and the
practical state variable should be used to form the state tending factor
of complex systems, which can reflect the process for the complex
system to tend rationalization. Relating to the system of basic
equations of complete factor synergetics consisting of twenty
nonlinear stochastic differential equations, the two new models are
considered to set, which should be called respectively the
rationalizing tendency model and the non- rationalizing tendency
model. Therefore we can extend the theory of programming with the
objective function & constraint condition suitable only for the realm
of man-s activities into the new analysis with the tendency function &
constraint condition suitable for all the field of complex system.
Abstract: Semantic Web Technologies enable machines to
interpret data published in a machine-interpretable form on the web.
At the present time, only human beings are able to understand the
product information published online. The emerging semantic Web
technologies have the potential to deeply influence the further
development of the Internet Economy. In this paper we propose a
scenario based research approach to predict the effects of these new
technologies on electronic markets and business models of traders
and intermediaries and customers. Over 300 million searches are
conducted everyday on the Internet by people trying to find what
they need. A majority of these searches are in the domain of
consumer ecommerce, where a web user is looking for something to
buy. This represents a huge cost in terms of people hours and an
enormous drain of resources. Agent enabled semantic search will
have a dramatic impact on the precision of these searches. It will
reduce and possibly eliminate information asymmetry where a better
informed buyer gets the best value. By impacting this key
determinant of market prices semantic web will foster the evolution
of different business and economic models. We submit that there is a
need for developing these futuristic models based on our current
understanding of e-commerce models and nascent semantic web
technologies. We believe these business models will encourage
mainstream web developers and businesses to join the “semantic web
revolution."
Abstract: In this paper, subtractive clustering based fuzzy inference system approach is used for early detection of faults in the function oriented software systems. This approach has been tested with real time defect datasets of NASA software projects named as PC1 and CM1. Both the code based model and joined model (combination of the requirement and code based metrics) of the datasets are used for training and testing of the proposed approach. The performance of the models is recorded in terms of Accuracy, MAE and RMSE values. The performance of the proposed approach is better in case of Joined Model. As evidenced from the results obtained it can be concluded that Clustering and fuzzy logic together provide a simple yet powerful means to model the earlier detection of faults in the function oriented software systems.
Abstract: The zero truncated model is usually used in modeling
count data without zero. It is the opposite of zero inflated model.
Zero truncated Poisson and zero truncated negative binomial models
are discussed and used by some researchers in analyzing the
abundance of rare species and hospital stay. Zero truncated models
are used as the base in developing hurdle models. In this study, we
developed a new model, the zero truncated strict arcsine model,
which can be used as an alternative model in modeling count data
without zero and with extra variation. Two simulated and one real
life data sets are used and fitted into this developed model. The
results show that the model provides a good fit to the data. Maximum
likelihood estimation method is used in estimating the parameters.
Abstract: In this study the adsorption of Cu (II) ions from aqueous solutions on synthetic zeolite NaA was evaluated. The effect of solution temperature and the determination of the kinetic parameters of adsorption of Cu(II) from aqueous solution on zeolite NaA is important in understanding the adsorption mechanism. Variables of the system include adsorption time, temperature (293- 328K), initial solution concentration and pH for the system. The sorption kinetics of the copper ions were found to be strongly dependent on pH (the optimum pH 3-5), solute ion concentration and temperature (293 – 328 K). It was found, the pseudo-second-order model was the best choice among all the kinetic models to describe the adsorption behavior of Cu(II) onto ziolite NaA, suggesting that the adsorption mechanism might be a chemisorptions process The activation energy of adsorption (Ea) was determined as Cu(II) 13.5 kJ mol-1. The low value of Ea shows that Cu(II) adsorption process by zeolite NaA may be an activated chemical adsorption. The thermodynamic parameters (ΔG0, ΔH0, and ΔS0) were also determined from the temperature dependence. The results show that the process of adsorption Cu(II) is spontaneous and endothermic process and rise in temperature favors the adsorption.
Abstract: The mitigation of crop loss due to damaging freezes requires accurate air temperature prediction models. An improved model for temperature prediction in Georgia was developed by including information on seasonality and modifying parameters of an existing artificial neural network model. Alternative models were compared by instantiating and training multiple networks for each model. The inclusion of up to 24 hours of prior weather information and inputs reflecting the day of year were among improvements that reduced average four-hour prediction error by 0.18°C compared to the prior model. Results strongly suggest model developers should instantiate and train multiple networks with different initial weights to establish appropriate model parameters.
Abstract: In this research, we propose a weighted class based
queuing (WCBQ) mechanism to provide class differentiation and to
reduce the load for the IMS (IP Multimedia Subsystem) presence
server (PS). The tasks of admission controller for the PS are
demonstrated. Analysis and simulation models are developed to
quantify the performance of WCBQ scheme. An optimized dropping
time frame has been developed based on which some of the preexisting
messages are dropped from the PS-buffer. Cost functions are
developed and simulation comparison has been performed with FCFS
(First Come First Served) scheme. The results show that the PS
benefits significantly from the proposed queuing and dropping
algorithm (WCBQ) during heavy traffic.
Abstract: In this paper, the notion of Hyperbolic Klingenberg
plane is introduced via a set of axioms like as Affine Klingenberg
planes and Projective Klingenberg planes. Models of such planes are
constructed by deleting a certain number m of equivalence classes
of lines from a Projective Klingenberg plane. In the finite case, an
upper bound for m is established and some combinatoric properties
are investigated.
Abstract: Most of the commonly used blind equalization algorithms are based on the minimization of a nonconvex and nonlinear cost function and a neural network gives smaller residual error as compared to a linear structure. The efficacy of complex valued feedforward neural networks for blind equalization of linear and nonlinear communication channels has been confirmed by many studies. In this paper we present two neural network models for blind equalization of time-varying channels, for M-ary QAM and PSK signals. The complex valued activation functions, suitable for these signal constellations in time-varying environment, are introduced and the learning algorithms based on the CMA cost function are derived. The improved performance of the proposed models is confirmed through computer simulations.
Abstract: The data is available in abundance in any business
organization. It includes the records for finance, maintenance,
inventory, progress reports etc. As the time progresses, the data keep
on accumulating and the challenge is to extract the information from
this data bank. Knowledge discovery from these large and complex
databases is the key problem of this era. Data mining and machine
learning techniques are needed which can scale to the size of the
problems and can be customized to the application of business. For
the development of accurate and required information for particular
problem, business analyst needs to develop multidimensional models
which give the reliable information so that they can take right
decision for particular problem. If the multidimensional model does
not possess the advance features, the accuracy cannot be expected.
The present work involves the development of a Multidimensional
data model incorporating advance features. The criterion of
computation is based on the data precision and to include slowly
change time dimension. The final results are displayed in graphical
form.
Abstract: Activity-Based Costing (ABC) represents an
alternative paradigm to traditional cost accounting system and
it often provides more accurate cost information for decision
making such as product pricing, product mix, and make-orbuy
decisions. ABC models the causal relationships between
products and the resources used in their production and traces
the cost of products according to the activities through the use
of appropriate cost drivers. In this paper, the implementation
of the ABC in a manufacturing system is analyzed and a
comparison with the traditional cost based system in terms of
the effects on the product costs are carried out to highlight the
difference between two costing methodologies. By using this
methodology, a valuable insight into the factors that cause the
cost is provided, helping to better manage the activities of the
company.
Abstract: A sequential treatment of ozonation followed by a
Fenton or photo-Fenton process, using black light lamps (365 nm) in
this latter case, has been applied to remove a mixture of
pharmaceutical compounds and the generated by-products both in
ultrapure and secondary treated wastewater. The scientifictechnological
innovation of this study stems from the in situ
generation of hydrogen peroxide from the direct ozonation of
pharmaceuticals, and can later be used in the application of Fenton
and photo-Fenton processes. The compounds selected as models
were sulfamethoxazol and acetaminophen. It should be remarked that
the use of a second process is necessary as a result of the low
mineralization yield reached by the exclusive application of ozone.
Therefore, the influence of the water matrix has been studied in terms
of hydrogen peroxide concentration, individual compound
concentration and total organic carbon removed. Moreover, the
concentration of different iron species in solution has been measured.
Abstract: Unified Modeling Language (UML) extensions for real time embedded systems (RTES) co-design, are taking a growing interest by a great number of industrial and research communities. The extension mechanism is provided by UML profiles for RTES. It aims at improving an easily-understood method of system design for non-experts. On the other hand, one of the key items of the co- design methods is the Hardware/Software partitioning and scheduling tasks. Indeed, it is mandatory to define where and when tasks are implemented and run. Unfortunately the main goals of co-design are not included in the usual practice of UML profiles. So, there exists a need for mapping used models to an execution platform for both schedulability test and HW/SW partitioning. In the present work, test schedulability and design space exploration are performed at an early stage. The proposed approach adopts Model Driven Engineering MDE. It starts from UML specification annotated with the recent profile for the Modeling and Analysis of Real Time Embedded systems MARTE. Following refinement strategy, transformation rules allow to find a feasible schedule that satisfies timing constraints and to define where tasks will be implemented. The overall approach is experimented for the design of a football player robot application.
Abstract: Timing driven physical design, synthesis, and
optimization tools need efficient closed-form delay models for
estimating the delay associated with each net in an integrated circuit
(IC) design. The total number of nets in a modern IC design has
increased dramatically and exceeded millions. Therefore efficient
modeling of interconnection is needed for high speed IC-s. This
paper presents closed–form expressions for RC and RLC
interconnection trees in current mode signaling, which can be
implemented in VLSI design tool. These analytical model
expressions can be used for accurate calculation of delay after the
design clock tree has been laid out and the design is fully routed.
Evaluation of these analytical models is several orders of magnitude
faster than simulation using SPICE.