Abstract: Stochastic modeling concerns the use of probability
to model real-world situations in which uncertainty is present.
Therefore, the purpose of stochastic modeling is to estimate the
probability of outcomes within a forecast, i.e. to be able to predict
what conditions or decisions might happen under different situations.
In the present study, we present a model of a stochastic diffusion
process based on the bi-Weibull distribution function (its trend
is proportional to the bi-Weibull probability density function). In
general, the Weibull distribution has the ability to assume the
characteristics of many different types of distributions. This has
made it very popular among engineers and quality practitioners, who
have considered it the most commonly used distribution for studying
problems such as modeling reliability data, accelerated life testing,
and maintainability modeling and analysis. In this work, we start
by obtaining the probabilistic characteristics of this model, as the
explicit expression of the process, its trends, and its distribution by
transforming the diffusion process in a Wiener process as shown in
the Ricciaardi theorem. Then, we develop the statistical inference of
this model using the maximum likelihood methodology. Finally, we
analyse with simulated data the computational problems associated
with the parameters, an issue of great importance in its application to
real data with the use of the convergence analysis methods. Overall,
the use of a stochastic model reflects only a pragmatic decision on
the part of the modeler. According to the data that is available and
the universe of models known to the modeler, this model represents
the best currently available description of the phenomenon under
consideration.
Abstract: The purpose of this article is to find a method
of comparing designs for ordinal regression models using
quantile dispersion graphs in the presence of linear predictor
misspecification. The true relationship between response variable
and the corresponding control variables are usually unknown.
Experimenter assumes certain form of the linear predictor of the
ordinal regression models. The assumed form of the linear predictor
may not be correct always. Thus, the maximum likelihood estimates
(MLE) of the unknown parameters of the model may be biased due to
misspecification of the linear predictor. In this article, the uncertainty
in the linear predictor is represented by an unknown function. An
algorithm is provided to estimate the unknown function at the
design points where observations are available. The unknown function
is estimated at all points in the design region using multivariate
parametric kriging. The comparison of the designs are based on
a scalar valued function of the mean squared error of prediction
(MSEP) matrix, which incorporates both variance and bias of the
prediction caused by the misspecification in the linear predictor. The
designs are compared using quantile dispersion graphs approach.
The graphs also visually depict the robustness of the designs on the
changes in the parameter values. Numerical examples are presented
to illustrate the proposed methodology.
Abstract: Energy disaggregation has been focused by many energy companies since energy efficiency can be achieved when the breakdown of energy consumption is known. Companies have been investing in technologies to come up with software and/or hardware solutions that can provide this type of information to the consumer. On the other hand, not all people can afford to have these technologies. Therefore, in this paper, we present a methodology for breaking down the aggregate consumption and identifying the highdemanding end-uses profiles. These energy profiles will be used to build the forecast model for optimal control purpose. A facility with high cooling load is used as an illustrative case study to demonstrate the results of proposed methodology. We apply a high level energy disaggregation through a pattern recognition approach in order to extract the consumption profile of its rooftop packaged units (RTUs) and present a forecast model for the energy consumption.
Abstract: In this paper, we discuss a Bayesian approach to
quantile autoregressive (QAR) time series model estimation and
forecasting. Together with a combining forecasts technique, we then
predict USD to GBP currency exchange rates. Combined forecasts
contain all the information captured by the fitted QAR models
at different quantile levels and are therefore better than those
obtained from individual models. Our results show that an unequally
weighted combining method performs better than other forecasting
methodology. We found that a median AR model can perform well in
point forecasting when the predictive density functions are symmetric.
However, in practice, using the median AR model alone may involve
the loss of information about the data captured by other QAR models.
We recommend that combined forecasts should be used whenever
possible.
Abstract: Many organizations in the Water, Sanitation and Hygiene (WASH) sector provide education and training in order to increase the effectiveness of their WASH interventions. A key challenge for these organizations is measuring how well their education and training activities contribute to WASH improvements. It is crucial for implementers to understand the returns of their education and training activities so that they can improve and make better progress toward the desired outcomes. This paper presents information on CAWST’s development and piloting of the evaluation methodology. The Centre for Affordable Water and Sanitation Technology (CAWST) has developed a methodology for evaluating education and training activities, so that organizations can understand the effectiveness of their WASH activities and improve accordingly. CAWST developed this methodology through a series of research partnerships, followed by staged field pilots in Nepal, Peru, Ethiopia and Haiti. During the research partnerships, CAWST collaborated with universities in the UK and Canada to: review a range of available evaluation frameworks, investigate existing practices for evaluating education activities, and develop a draft methodology for evaluating education programs. The draft methodology was then piloted in three separate studies to evaluate CAWST’s, and CAWST’s partner’s, WASH education programs. Each of the pilot studies evaluated education programs in different locations, with different objectives, and at different times within the project cycles. The evaluations in Nepal and Peru were conducted in 2013 and investigated the outcomes and impacts of CAWST’s WASH education services in those countries over the past 5-10 years. In 2014, the methodology was applied to complete a rigorous evaluation of a 3-day WASH Awareness training program in Ethiopia, one year after the training had occurred. In 2015, the methodology was applied in Haiti to complete a rapid assessment of a Community Health Promotion program, which informed the development of an improved training program. After each pilot evaluation, the methodology was reviewed and improvements were made. A key concept within the methodology is that in order for training activities to lead to improved WASH practices at the community level, it is not enough for participants to acquire new knowledge and skills; they must also apply the new skills and influence the behavior of others following the training. The steps of the methodology include: development of a Theory of Change for the education program, application of the Kirkpatrick model to develop indicators, development of data collection tools, data collection, data analysis and interpretation, and use of the findings for improvement. The methodology was applied in different ways for each pilot and was found to be practical to apply and adapt to meet the needs of each case. It was useful in gathering specific information on the outcomes of the education and training activities, and in developing recommendations for program improvement. Based on the results of the pilot studies, CAWST is developing a set of support materials to enable other WASH implementers to apply the methodology. By using this methodology, more WASH organizations will be able to understand the outcomes and impacts of their training activities, leading to higher quality education programs and improved WASH outcomes.
Abstract: To provide an efficient solar generation system, the embodiment design of a two axis solar tracker for an array of photovoltaic (PV) panels destiny to supply the power demand on off-the-grid areas was developed. Photovoltaic cells have high costs in relation to t low efficiency; and while a lot of research and investment has been made to increases its efficiency a few points, there is a profitable solution that increases by 30-40% the annual power production: two axis solar trackers. A solar tracker is a device that supports a load in a perpendicular position toward the sun during daylight. Mounted on solar trackers, the solar panels remain perpendicular to the incoming sunlight at day and seasons so the maximum amount of energy is outputted. Through a preview research done it was justified why the generation of solar energy through photovoltaic panels mounted on dual axis structures is an attractive solution to bring electricity to remote off-the-grid areas. The work results are the embodiment design of an azimuth-altitude solar tracker to guide an array of photovoltaic panels based on a specific design methodology. The designed solar tracker is mounted on a pedestal that uses two slewing drives‚ with a nominal torque of 1950 Nm‚ to move a solar array that provides 3720 W from 12 PV panels.
Abstract: The paper deals with finding and describing of the
effective marketing communication forms relating to the segment
50+ in the financial market in the Czech Republic. The segment 50+
can be seen as a great marketing potential in the future but
unfortunately the Czech financial institutions haven´t still reacted
enough to this fact and they haven´t prepared appropriate marketing
programs for this customers´ segment. Demographic aging is a
fundamental characteristic of the current European population
evolution but the perspective of further population aging is more
noticeable in the Czech Republic. This paper is based on data from
one part of primary marketing research. Paper determinates the basic
problem areas as well as definition of marketing communication in
the financial market, defining the primary research problem,
hypothesis and primary research methodology. Finally suitable
marketing communication approach to selected sub-segment at age of
50-60 years is proposed according to marketing research findings.
Abstract: Location selection presents a crucial decision problem in today’s business world where strategic decision making processes have critical importance. Thus, location selection has strategic importance for companies in boosting their strength regarding competition, increasing corporate performances and efficiency in addition to lowering production and transportation costs. A right choice in location selection has a direct impact on companies’ commercial success. In this study, a store location selection problem of Carglass Turkey which operates in vehicle glass branch is handled. As this problem includes both tangible and intangible criteria, Analytic Network Process (ANP) was accepted as the main methodology. The model consists of control hierarchy and BOCR subnetworks which include clusters of actors, alternatives and criteria. In accordance with the management’s choices, five different locations were selected. In addition to the literature review, a strict cooperation with the actor group was ensured and maintained while determining the criteria and during whole process. Obtained results were presented to the management as a report and its feasibility was confirmed accordingly.
Abstract: Bisphenol A (BPA) is an organic synthetic compound that has many applications in various industries and is known as persistent pollutant. The aim of this research was to evaluate the efficiency of bone ash and banana peel as adsorbents for BPA adsorption from aqueous solution by using Response Surface Methodology. The effects of some variables such as sorbent dose, detention time, solution pH, and BPA concentration on the sorption efficiency was examined. All analyses were carried out according to Standard Methods. The sample size was performed using Box-Benken design and also optimization of BPA removal was done using response surface methodology (RSM). The results showed that the BPA adsorption increases with increasing of contact time and BPA concentration. However, it decreases with higher pH. More adsorption efficiency of a banana peel is very smaller than a bone ash so that BPA removal for bone ash and banana peel is 62 and 28 percent, respectively. It is concluded that a bone ash has a good ability for the BPA adsorption.
Abstract: The acceptance of sustainable products by the final
consumer is still one of the challenges of the industry, which
constantly seeks alternative approaches to successfully be accepted in
the global market. A large set of methods and approaches have been
discussed and analysed throughout the literature. Considering the current need for sustainable development and the
current pace of consumption, the need for a combined solution
towards the development of new products became clear, forcing
researchers in product development to propose alternatives to the
previous standard product development models. This paper presents, through a systemic analysis of the literature
on product development, eco-design and consumer involvement, a set
of alternatives regarding consumer involvement towards the
development of sustainable products and how these approaches could
help improve the sustainable industry’s establishment in the general
market. Still being developed in the course of the author’s PhD, the initial
findings of the research show that the understanding of the benefits of
sustainable behaviour lead to a more conscious acquisition and
eventually to the implementation of sustainable change in the
consumer. Thus this paper is the initial approach towards the
development of new sustainable products using the fashion industry
as an example of practical implementation and acceptance by the
consumers. By comparing the existing literature and critically analysing it, this
paper concluded that the consumer involvement is strategic to
improve the general understanding of sustainability and its features.
The use of consumers and communities has been studied since the
early 90s in order to exemplify uses and to guarantee a fast
comprehension. The analysis done also includes the importance of
this approach for the increase of innovation and ground breaking
developments, thus requiring further research and practical
implementation in order to better understand the implications and
limitations of this methodology.
Abstract: The Com-Poisson (CMP) model is one of the most
popular discrete generalized linear models (GLMS) that handles
both equi-, over- and under-dispersed data. In longitudinal context,
an integer-valued autoregressive (INAR(1)) process that incorporates
covariate specification has been developed to model longitudinal
CMP counts. However, the joint likelihood CMP function is
difficult to specify and thus restricts the likelihood-based estimating
methodology. The joint generalized quasi-likelihood approach
(GQL-I) was instead considered but is rather computationally
intensive and may not even estimate the regression effects due
to a complex and frequently ill-conditioned covariance structure.
This paper proposes a new GQL approach for estimating the
regression parameters (GQL-III) that is based on a single score vector
representation. The performance of GQL-III is compared with GQL-I
and separate marginal GQLs (GQL-II) through some simulation
experiments and is proved to yield equally efficient estimates as
GQL-I and is far more computationally stable.
Abstract: This article describes the results of research focused
on quality of railway freight transport services. Improvement of these
services has a crucial importance in customer considering on the
future use of railway transport. Processes filling the customer
demands and output quality assessment were defined as a part of the
research. In this contribution is introduced the map of quality
planning and the algorithm of applied methodology. It characterizes a
model which takes into account characters of transportation with
linking a perception services quality in ordinary and extraordinary
operation. Despite the fact that rail freight transport has its solid
position in the transport market, lots of carriers worldwide have been
experiencing a stagnation for a couple of years. Therefore, specific
results of the research have a significant importance and belong to
numerous initiatives aimed to develop and support railway transport
not only by creating a single railway area or reducing noise but also
by promoting railway services. This contribution is focused also on
the application of dynamic quality models which represent an
innovative method of evaluation quality services. Through this
conception, time factor, expected, and perceived quality in each
moment of the transportation process can be taken into account.
Abstract: In this study, students’ learning has been investigated
and satisfaction in one of the course offered at Qatar University
Foundation Program. Innovative teaching has been implied
methodology that emphasizes on enhancing students’ thinking skills,
decision making, and problem solving skills. Some interesting results
were found which could be used to further improvement of the
teaching methodology. In Fall 2012 in Foundation Program Math
department at Qatar University has started implementing new ways
of teaching Math by introducing MyMathLab (MML) as an
innovative interactive tool in addition of the use Blackboard to
support standard teaching such as Discussion board in Virtual class to
engage students outside of classroom and to enhance independent,
active learning that promote students’ critical thinking skills, decision
making, and problem solving skills through the learning process.
Abstract: We consider the problem of stabilization of an unstable
heat equation in a 2-D, 3-D and generally n-D domain by deriving a
generalized backstepping boundary control design methodology. To
stabilize the systems, we design boundary backstepping controllers
inspired by the 1-D unstable heat equation stabilization procedure.
We assume that one side of the boundary is hinged and the other
side is controlled for each direction of the domain. Thus, controllers
act on two boundaries for 2-D domain, three boundaries for 3-D
domain and ”n” boundaries for n-D domain. The main idea of the
design is to derive ”n” controllers for each of the dimensions by
using ”n” kernel functions. Thus, we obtain ”n” controllers for the
”n” dimensional case. We use a transformation to change the system
into an exponentially stable ”n” dimensional heat equation. The
transformation used in this paper is a generalized Volterra/Fredholm
type with ”n” kernel functions for n-D domain instead of the one
kernel function of 1-D design.
Abstract: Recently, numerous documents including large
volumes of unstructured data and text have been created because of the
rapid increase in the use of social media and the Internet. Usually,
these documents are categorized for the convenience of users. Because
the accuracy of manual categorization is not guaranteed, and such
categorization requires a large amount of time and incurs huge costs.
Many studies on automatic categorization have been conducted to help
mitigate the limitations of manual categorization. Unfortunately, most
of these methods cannot be applied to categorize complex documents
with multiple topics because they work on the assumption that
individual documents can be categorized into single categories only.
Therefore, to overcome this limitation, some studies have attempted to
categorize each document into multiple categories. However, the
learning process employed in these studies involves training using a
multi-categorized document set. These methods therefore cannot be
applied to the multi-categorization of most documents unless
multi-categorized training sets using traditional multi-categorization
algorithms are provided. To overcome this limitation, in this study, we
review our novel methodology for extending the category of a
single-categorized document to multiple categorizes, and then
introduce a survey-based verification scenario for estimating the
accuracy of our automatic categorization methodology.
Abstract: This research studies the joint production,
maintenance and subcontracting control policy for an unreliable
deteriorating manufacturing system. Production activities are
controlled by a derivation of the Hedging Point Policy, and given that
the system is subject to deterioration, it reduces progressively its
capacity to satisfy product demand. Multiple deterioration effects are
considered, reflected mainly in the quality of the parts produced and
the reliability of the machine. Subcontracting is available as support
to satisfy product demand; also, overhaul maintenance can be
conducted to reduce the effects of deterioration. The main objective
of the research is to determine simultaneously the production,
maintenance and subcontracting rate, which minimize the total,
incurred cost. A stochastic dynamic programming model is
developed and solved through a simulation-based approach
composed of statistical analysis and optimization with the response
surface methodology. The obtained results highlight the strong
interactions between production, deterioration and quality, which
justify the development of an integrated model. A numerical example
and a sensitivity analysis are presented to validate our results.
Abstract: The composite flour blend consisting of corn, pearl
millet, black gram and wheat bran in the ratio of 80:5:10:5 was taken
to prepare the extruded product and their effect on physical properties
of extrudate was studied. The extrusion process was conducted in
laboratory by using twin screw extruder. The physical characteristics
evaluated include lateral expansion, bulk density, water absorption
index, water solubility index, and rehydration ratio and moisture
retention. The Central Composite Rotatable Design (CCRD) was
used to decide the level of processing variables i.e. feed moisture
content (%), screw speed (rpm), and barrel temperature (oC) for the
experiment. The data obtained after extrusion process were analyzed
by using response surface methodology. A second order polynomial
model for the dependent variables was established to fit the
experimental data. The numerical optimization studies resulted in
127°C of barrel temperature, 246 rpm of screw speed, and 14.5% of
feed moisture as optimum variables to produce acceptable extruded
product. The responses predicted by the software for the optimum
process condition resulted in lateral expansion 126%, bulk density
0.28 g/cm3, water absorption index 4.10 g/g, water solubility index
39.90%, rehydration ratio 544% and moisture retention 11.90% with
75% desirability.
Abstract: A solution methodology without using integral
transformation is proposed to develop analytical solutions for
transient heat conduction in nonuniform hollow cylinders with
time-dependent boundary condition at the outer surface. It is shown
that if the thermal conductivity and the specific heat of the medium
are in arbitrary polynomial function forms, the closed solutions of the
system can be developed. The influence of physical properties on the
temperature distribution of the system is studied. A numerical
example is given to illustrate the efficiency and the accuracy of the
solution methodology.
Abstract: The design of Reverse logistics Network has attracted
growing attention with the stringent pressures from both
environmental awareness and business sustainability. Reverse
logistical activities include return, remanufacture, disassemble and
dispose of products can be quite complex to manage. In addition,
demand can be difficult to predict, and decision making is one of the
challenges task in such network. This complexity has amplified the
need to develop an integrated architecture for product return as an
enterprise system. The main purpose of this paper is to design Multi
Agent System (MAS) architecture using the Prometheus
methodology to efficiently manage reverse logistics processes. The
proposed MAS architecture includes five types of agents: Gate
keeping Agent, Collection Agent, Sorting Agent, Processing Agent
and Disposal Agent which act respectively during the five steps of
reverse logistics Network.
Abstract: ANDASA is a knowledge management platform for
the capitalization of knowledge and cultural assets for the artistic and
cultural sectors. It was built based on the priorities expressed by the
participating artists. Through mapping artistic activities and
specificities, it enables to highlight various aspects of the artistic
research and production. Such instrument will contribute to create
networks and partnerships, as it enables to evidentiate who does
what, in what field, using which methodology. The platform is
accessible to network participants and to the general public.