Abstract: In this paper, we provided a literature survey on the
artificial stock problem (ASM). The paper began by exploring the
complexity of the stock market and the needs for ASM. ASM
aims to investigate the link between individual behaviors (micro
level) and financial market dynamics (macro level). The variety of
patterns at the macro level is a function of the AFM complexity. The
financial market system is a complex system where the relationship
between the micro and macro level cannot be captured analytically.
Computational approaches, such as simulation, are expected to
comprehend this connection. Agent-based simulation is a simulation
technique commonly used to build AFMs. The paper proceeds by
discussing the components of the ASM. We consider the roles
of behavioral finance (BF) alongside the traditionally risk-averse
assumption in the construction of agent’s attributes. Also, the
influence of social networks in the developing of agents interactions is
addressed. Network topologies such as a small world, distance-based,
and scale-free networks may be utilized to outline economic
collaborations. In addition, the primary methods for developing
agents learning and adaptive abilities have been summarized.
These incorporated approach such as Genetic Algorithm, Genetic
Programming, Artificial neural network and Reinforcement Learning.
In addition, the most common statistical properties (the stylized facts)
of stock that are used for calibration and validation of ASM are
discussed. Besides, we have reviewed the major related previous
studies and categorize the utilized approaches as a part of these
studies. Finally, research directions and potential research questions
are argued. The research directions of ASM may focus on the macro
level by analyzing the market dynamic or on the micro level by
investigating the wealth distributions of the agents.
Abstract: Voting algorithms are extensively used to make
decisions in fault tolerant systems where each redundant module
gives inconsistent outputs. Popular voting algorithms include
majority voting, weighted voting, and inexact majority voters. Each
of these techniques suffers from scenarios where agreements do not
exist for the given voter inputs. This has been successfully overcome
in literature using fuzzy theory. Our previous work concentrated on a
neuro-fuzzy algorithm where training using the neuro system
substantially improved the prediction result of the voting system.
Weight training of Neural Network is sub-optimal. This study
proposes to optimize the weights of the Neural Network using
Artificial Bee Colony algorithm. Experimental results show the
proposed system improves the decision making of the voting
algorithms.
Abstract: Phonocardiography is important in appraisal of
congenital heart disease and pulmonary hypertension as it reflects the
duration of right ventricular systoles. The systolic murmur in patients
with intra-cardiac shunt decreases as pulmonary hypertension
develops and may eventually disappear completely as the pulmonary
pressure reaches systemic level. Phonocardiography and auscultation
are non-invasive, low-cost, and accurate methods to assess heart
disease. In this work an objective signal processing tool to extract
information from phonocardiography signal using Wavelet is
proposed to classify the murmur as normal or abnormal. Since the
feature vector is large, a Binary Particle Swarm Optimization (PSO)
with mutation for feature selection is proposed. The extracted
features improve the classification accuracy and were tested across
various classifiers including Naïve Bayes, kNN, C4.5, and SVM.
Abstract: To tackle the air pollution issues, Plug-in Hybrid
Electric Vehicles (PHEVs) are proposed as an appropriate solution.
Charging a large amount of PHEV batteries, if not controlled, would
have negative impacts on the distribution system. The control process
of charging of these vehicles can be centralized in parking lots that
may provide a chance for better coordination than the individual
charging in houses. In this paper, an optimization-based approach is
proposed to determine the optimum PHEV parking capacities in
candidate nodes of the distribution system. In so doing, a profile for
charging and discharging of PHEVs is developed in order to flatten
the network load profile. Then, this profile is used in solving an
optimization problem to minimize the distribution system losses. The
outputs of the proposed method are the proper place for PHEV
parking lots and optimum capacity for each parking. The application
of the proposed method on the IEEE-34 node test feeder verifies the
effectiveness of the method.
Abstract: Application of biochar to arable soils represents a new
approach to restore soil health and quality. Many studies reported the
positive effect of biochar application on soil fertility and
development of soil microbial community. Moreover biochar may
affect the soil water retention, but this effect has not been sufficiently
described yet. Therefore this study deals with the influence of
biochar application on: microbial activities in soil, availability of
mineral nitrogen in soil for microorganisms, mineral nitrogen
retention and plant production. To demonstrate the effect of biochar
addition on the above parameters, the pot experiment was realized.
As a model crop, Lactuca sativa L. was used and cultivated from
December 10th 2014 till March 22th 2015 in climate chamber in
thoroughly homogenized arable soil with and without addition of
biochar. Five variants of experiment (V1 – V5) with different regime
of irrigation were prepared. Variants V1 – V2 were fertilized by
mineral nitrogen, V3 – V4 by biochar and V5 was a control. The
significant differences were found only in plant production and
mineral nitrogen retention. The highest content of mineral nitrogen
in soil was detected in V1 and V2, about 250 % in comparison with
the other variants. The positive effect of biochar application on soil
fertility, mineral nitrogen availability was not found. On the other
hand results of plant production indicate the possible positive effect
of biochar application on soil water retention.
Abstract: Experiential marketing is one of the marketing
approaches that offer an exceptional framework to integrate elements
of experience and entertainment in a product or service. Experiential
marketing is defined as a memorable experience that goes deeply into
the customer’s mind. Besides that, customer satisfaction is defined as
an emotional response to the experiences provided by and associated
with particular products or services purchased. Thus, experiential
marketing activities can affect the level of customer satisfaction and
loyalty. In this context, the research aims to explore the relationship
among experiential marketing, customer satisfaction and customer
loyalty among the cosmetic products customers in Konya. The partial
least squares (PLS) method is used to analyze the survey data.
Findings of the present study revealed that experiential marketing has
been a significant predictor of customer satisfaction and customer
loyalty, and also experiential marketing has a significantly positive
effect on customer satisfaction and customer loyalty.
Abstract: Residential block construction of big cities in China
began in the 1950s, and four models had far-reaching influence on
modern residential block in its development process, including unit
compound and residential district in 1950s to 1980s, and gated
community and open community in 1990s to now. Based on analysis
of the four models’ fabric, the article takes residential blocks in
Hangzhou west area as an example and carries on the studies from
urban structure level and block spacial level, mainly including urban
road network, land use, community function, road organization, public
space and building fabric. At last, the article puts forward “Semi-open
Sub-community” strategy to improve the current fabric.
Abstract: The enormous amount of information stored on the
web increases from one day to the next, exposing the web currently
faced with the inevitable difficulties of research pertinent information
that users really want. The problem today is not limited to expanding
the size of the information highways, but to design a system for
intelligent search. The vast majority of this information is stored in
relational databases, which in turn represent a backend for managing
RDF data of the semantic web. This problem has motivated us to
write this paper in order to establish an effective approach to support
semantic transformation algorithm for SPARQL queries to SQL
queries, more precisely SPARQL SELECT queries; by adopting this
method, the relational database can be questioned easily with
SPARQL queries maintaining the same performance.
Abstract: The goal of this paper is to present the diagnostic
contribution that the screening instrument, Mini-Mental State
Examination-2: Expanded Version (MMSE-2:EV), brings in
detecting the cognitive impairment or in monitoring the progress of
degenerative disorders. The diagnostic signification is underlined by
the interpretation of the MMSE-2:EV scores, resulted from the test
application to patients with mild and major neurocognitive disorders.
The cases were selected from current practice, in order to cover vast
and significant neurocognitive pathology: mild cognitive impairment,
Alzheimer’s disease, vascular dementia, mixed dementia, Parkinson’s
disease, conversion of the mild cognitive impairment into
Alzheimer’s disease. The MMSE-2:EV version was used: it was
applied one month after the initial assessment, three months after the
first reevaluation and then every six months, alternating the blue and
red forms. Correlated with age and educational level, the raw scores
were converted in T scores and then, with the mean and the standard
deviation, the z scores were calculated. The differences of raw scores
between the evaluations were analyzed from the point of view of
statistic signification, in order to establish the progression in time of
the disease. The results indicated that the psycho-diagnostic approach
for the evaluation of the cognitive impairment with MMSE-2:EV is
safe and the application interval is optimal. In clinical settings with a
large flux of patients, the application of the MMSE-2:EV is a safe
and fast psychodiagnostic solution. The clinicians can draw objective
decisions and for the patients: it does not take too much time and
energy, it does not bother them and it doesn’t force them to travel
frequently.
Abstract: Ceramic Waste Aggregates (CWAs) were made from
electric porcelain insulator wastes supplied from an electric power
company, which were crushed and ground to fine aggregate sizes. In
this study, to develop the CWA mortar as an eco–efficient, ground
granulated blast–furnace slag (GGBS) as a Supplementary
Cementitious Material (SCM) was incorporated. The water–to–binder
ratio (W/B) of the CWA mortars was varied at 0.4, 0.5, and 0.6. The
cement of the CWA mortar was replaced by GGBS at 20 and 40% by
volume (at about 18 and 37% by weight). Mechanical properties of
compressive and splitting tensile strengths, and elastic modulus were
evaluated at the age of 7, 28, and 91 days. Moreover, the chloride
ingress test was carried out on the CWA mortars in a 5.0% NaCl
solution for 48 weeks. The chloride diffusion was assessed by using an
electron probe microanalysis (EPMA). To consider the relation of the
apparent chloride diffusion coefficient and the pore size, the pore size
distribution test was also performed using a mercury intrusion
porosimetry at the same time with the EPMA. The compressive
strength of the CWA mortars with the GGBS was higher than that
without the GGBS at the age of 28 and 91 days. The resistance to the
chloride ingress of the CWA mortar was effective in proportion to the
GGBS replacement level.
Abstract: This paper presents an approach of on-line control of
the state of technosphere and environment objects based on the
integration of Data Warehouse, OLAP and Expert systems
technologies. It looks at the structure and content of data warehouse
that provides consolidation and storage of monitoring data. There is a
description of OLAP-models that provide a multidimensional
analysis of monitoring data and dynamic analysis of principal
parameters of controlled objects. The authors suggest some criteria of
emergency risk assessment using expert knowledge about danger
levels. It is demonstrated now some of the proposed solutions could
be adopted in territorial decision making support systems.
Operational control allows authorities to detect threat, prevent natural
and anthropogenic emergencies and ensure a comprehensive safety of
territory.
Abstract: Significant attention has recently been paid to the
cross-cultural negotiations due to the growth of international
businesses. Despite the substantial body of literature examining the
influence of National Culture (NC) dimensions on negotiations, there
is a lack of studies comparing the influence of NC in Latin America
with a Western European countries, In particular, an extensive review
of the literature revealed that a contribution to knowledge would be
derived from the comparison of the influence of NC dimensions on
negotiations in UK and Venezuela. The primary data was collected
through qualitative interviews, to obtain an insight about the
perceptions and beliefs of Venezuelan and British business managers
about their negotiating styles. The findings of this study indicated
that NC has a great influence on the negotiating styles. In particular,
Venezuelan and British managers demonstrated to have opposed
negotiating styles, affecting the way they communicate, approach
people and their willingness to take risks.
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: A bauxite ore can be utilized in Bayer Process, if the
mass ratio of Al2O3 to SiO2 is greater than 10. Otherwise, its FexOy
and SiO2 content should be removed. On the other hand, removal of
TiO2 from the bauxite ore would be beneficial because of both
lowering the red mud residue and obtaining a valuable raw material
containing TiO2 mineral. In this study, the low grade diasporic
bauxite ore of Yalvaç, Isparta, Turkey was roasted under reducing
atmosphere and subjected to magnetic separation. According to the
experimental results, 800°C for reduction temperature and 20000
Gauss of magnetic intensity were found to be the optimum
parameters for removal of iron oxide and rutile from the nonmagnetic
ore. On the other hand, 600°C and 5000 Gauss were
determined to be the optimum parameters for removal of silica from
the non-magnetic ore.
Abstract: This paper will seek to clarify important key terms
such as home schooling and home education as well as the legalities
attached to such terms. It will reflect on the recent proposed changes
to terminology in NSW, Australia. The various pedagogical
approaches to home education will be explored including their
prominence in the Australian context. There is a strong focus on
literature from Australia. The historical background of home
education in Australia will be explained as well as the difference
between distance education and home education. The future of home
education in Australia will be discussed.
Abstract: The lifetime of a wireless sensor network can be
effectively increased by using scheduling operations. Once the
sensors are randomly deployed, the task at hand is to find the largest
number of disjoint sets of sensors such that every sensor set provides
complete coverage of the target area. At any instant, only one of these
disjoint sets is switched on, while all other are switched off. This
paper proposes a heuristic search method to find the maximum
number of disjoint sets that completely cover the region. A
population of randomly initialized members is made to explore the
solution space. A set of heuristics has been applied to guide the
members to a possible solution in their neighborhood. The heuristics
escalate the convergence of the algorithm. The best solution explored
by the population is recorded and is continuously updated. The
proposed algorithm has been tested for applications which require
sensing of multiple target points, referred to as point coverage
applications. Results show that the proposed algorithm outclasses the
existing algorithms. It always finds the optimum solution, and that
too by making fewer number of fitness function evaluations than the
existing approaches.
Abstract: In this paper, we present a new segmentation approach
for liver lesions in regions of interest within MRI (Magnetic
Resonance Imaging). This approach, based on a two-cluster Fuzzy CMeans
methodology, considers the parameter variable compactness
to handle uncertainty. Fine boundaries are detected by a local
recursive merging of ambiguous pixels with a sequential forward
floating selection with Zernike moments. The method has been tested
on both synthetic and real images. When applied on synthetic images,
the proposed approach provides good performance, segmentations
obtained are accurate, their shape is consistent with the ground truth,
and the extracted information is reliable. The results obtained on MR
images confirm such observations. Our approach allows, even for
difficult cases of MR images, to extract a segmentation with good
performance in terms of accuracy and shape, which implies that the
geometry of the tumor is preserved for further clinical activities (such
as automatic extraction of pharmaco-kinetics properties, lesion
characterization, etc.).
Abstract: In this paper, the specific sound Transmission Loss
(TL) of the Laminated Composite Plate (LCP) with different material
properties in each layer is investigated. The numerical method to
obtain the TL of the LCP is proposed by using elastic plate theory. The
transfer matrix approach is novelty presented for computational
efficiency in solving the numerous layers of dynamic stiffness matrix
(D-matrix) of the LCP. Besides the numerical simulations for
calculating the TL of the LCP, the material properties inverse method
is presented for the design of a laminated composite plate analogous to
a metallic plate with a specified TL. As a result, it demonstrates that
the proposed computational algorithm exhibits high efficiency with a
small number of iterations for achieving the goal. This method can be
effectively employed to design and develop tailor-made materials for
various applications.
Abstract: The purpose of the paper is to address the strategic
risk issues surrounding Hindi film distribution in Mumbai for a film
distributor, who acts as an entrepreneur when launching a product
(movie) in the market (film territory).The paper undertakes a
fundamental review of films and risk in the Hindi film industry and
applies Grounded Theory technique to understand the complex
phenomena of risk taking behavior of the film distributors (both
independent and studios) in Mumbai. Rich in-depth interviews with
distributors are coded to develop core categories through constant
comparison leading to conceptualization of the phenomena of
interest. This paper is a first-of-its-kind-attempt to understand risk
behavior of a distributor, which is akin to entrepreneurial risk
behavior under conditions of uncertainty.
Abstract: This study utilizes a frequency domain approach over
the period of 1996 to 2013 to examine the causal relationship between
governance and economic growth in ten Asian countries, which have
different levels of democracy; classified as “Free”, “Partly Free”, and
“Not Free” countries. The empirical results show that there is no
Granger causality running from governance to economic growth in
“Not Free” countries and “Partly Free” countries with the exception of
Singapore. As for “Free” countries such as South Korea and Taiwan,
there is a one-way causality running from governance to economic
growth. The findings of this study indicate that policy makers in South
Korea, Taiwan, and Singapore could use governance index to improve
their predictions of the future economic growth.