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: A knowledge base stores facts and rules about the
world that applications can use for the purpose of reasoning. By
applying the concept of granular computing to a knowledge base,
several advantages emerge. These can be harnessed by applications
to improve their capabilities and performance. In this paper, the
concept behind such a construct, called a granular knowledge cube,
is defined, and its intended use as an instrument that manages to
cope with different data types and detect knowledge domains is
elaborated. Furthermore, the underlying architecture, consisting of the
three layers of the storing, representing, and structuring of knowledge,
is described. Finally, benefits as well as challenges of deploying it
are listed alongside application types that could profit from having
such an enhanced knowledge base.
Abstract: There have been rigorous research and development
of unmanned aerial vehicles in the field of search and rescue (SAR)
operation recently. UAVs reduce unnecessary human risks while
assisting rescue efforts through aerial imagery, topographic mapping
and emergency delivery. The application of UAVs in offshore and
nearshore marine SAR missions is discussed in this paper. Projects
that integrate UAV technology into their systems are introduced to
highlight the great advantages and capabilities of UAVs. Scenarios
where UAVs could provide invaluable assistance are also suggested.
Abstract: Waste Load Allocation (WLA) strategies usually
intend to find economic policies for water resource management.
Water quality trading (WQT) is an approach that uses discharge
permit market to reduce total environmental protection costs. This
primarily requires assigning discharge limits known as total
maximum daily loads (TMDLs). These are determined by monitoring
organizations with respect to the receiving water quality and
remediation capabilities. The purpose of this study is to compare two
approaches of TMDL assignment for WQT policy in small catchment
area of Haraz River, in north of Iran. At first, TMDLs are assigned
uniformly for the whole point sources to keep the concentrations of
BOD and dissolved oxygen (DO) at the standard level at checkpoint
(terminus point). This was simply simulated and controlled by
Qual2kw software. In the second scenario, TMDLs are assigned
using multi objective particle swarm optimization (MOPSO) method
in which the environmental violation at river basin and total treatment
costs are minimized simultaneously. In both scenarios, the equity
index and the WLA based on trading discharge permits (TDP) are
calculated. The comparative results showed that using economically
optimized TMDLs (2nd scenario) has slightly more cost savings rather
than uniform TMDL approach (1st scenario). The former annually
costs about 1 M$ while the latter is 1.15 M$. WQT can decrease
these annual costs to 0.9 and 1.1 M$, respectively. In other word,
these approaches may save 35 and 45% economically in comparison
with command and control policy. It means that using multi objective
decision support systems (DSS) may find more economical WLA,
however its outcome is not necessarily significant in comparison with
uniform TMDLs. This may be due to the similar impact factors of
dischargers in small catchments. Conversely, using uniform TMDLs
for WQT brings more equity that makes stakeholders not feel that
much envious of difference between TMDL and WQT allocation. In
addition, for this case, determination of TMDLs uniformly would be
much easier for monitoring. Consequently, uniform TMDL for TDP
market is recommended as a sustainable approach. However,
economical TMDLs can be used for larger watersheds.
Abstract: The aim of this research was to reveal the link
between mental variables, such as spatial abilities, memory, intellect
and professional experience of drivers.
Participants were allocated to four groups: no experience,
inexperienced, skilled and professionals (total 85 participants). The
level of ability for spatial navigation and indicator of nonverbal
memory grow along the process of accumulation of driving
experience. At high levels of driving experience, this tendency is
especially noticeable. The professionals having personal
achievements in driving (racing) differ from skilled drivers in better
feeling of direction, which is specific for them not just in a short-term
situation of an experimental task, but also in life-size perspective.
The level of ability of mental rotation does not grow with the growth
of driving experience, which confirms the multiple intelligence
theory according to which spatial abilities represent specific, other
than logical intelligence type of intellect. The link between spatial
abilities, memory, intellect and professional experience of drivers
seems to be different relating spatial navigation or mental rotation as
different kinds of spatial abilities.
Abstract: This paper presents an approach for the classification of
an unstructured format description for identification of file formats.
The main contribution of this work is the employment of data mining
techniques to support file format selection with just the unstructured
text description that comprises the most important format features for
a particular organisation. Subsequently, the file format indentification
method employs file format classifier and associated configurations to
support digital preservation experts with an estimation of required file
format. Our goal is to make use of a format specification knowledge
base aggregated from a different Web sources in order to select file
format for a particular institution. Using the naive Bayes method,
the decision support system recommends to an expert, the file format
for his institution. The proposed methods facilitate the selection of
file format and the quality of a digital preservation process. The
presented approach is meant to facilitate decision making for the
preservation of digital content in libraries and archives using domain
expert knowledge and specifications of file formats. To facilitate
decision-making, the aggregated information about the file formats is
presented as a file format vocabulary that comprises most common
terms that are characteristic for all researched formats. The goal is to
suggest a particular file format based on this vocabulary for analysis
by an expert. The sample file format calculation and the calculation
results including probabilities are presented in the evaluation section.
Abstract: Exploration and exploitation capabilities are both
important within Operations as means for improvement when
managed separately, and for establishing dynamic improvement
capabilities when combined in balance. However, it is unclear what
exploration and exploitation capabilities imply in improvement and
development work within an Operations context. So, in order to
better understand how to develop exploration and exploitation
capabilities within Operations, the main characteristics of these
constructs needs to be identified and further understood. Thus, the
objective of this research is to increase the understanding about
exploitation and exploration characteristics, to concretize what they
translates to within the context of improvement and development
work in an Operations unit, and to identify practical challenges. A
literature review and a case study are presented. In the literature
review, different interpretations of exploration and exploitation are
portrayed, key characteristics have been identified, and a deepened
understanding of exploration and exploitation characteristics is
described. The case in the study is an Operations unit, and the aim is
to explore to what extent and in what ways exploration and
exploitation activities are part of the improvement structures and
processes. The contribution includes an identification of key
characteristics of exploitation and exploration, as well as an
interpretation of the constructs. Further, some practical challenges are
identified. For instance, exploration activities tend to be given low
priority, both in daily work as in the manufacturing strategy. Also,
the overall understanding about the concepts of exploitation and
exploration (or any similar aspect of dynamic improvement
capabilities) is very low.
Abstract: This study was aimed to investigate the machining
stability of a spindle tool with different preloaded amount. To this end,
the vibration tests were conducted on the spindle unit with different
preload to assess the dynamic characteristics and machining stability
of the milling machine. Current results demonstrate that the tool tip
frequency response characteristics and the machining stabilities in X
and Y direction are affected to change due to the different preload of
spindle bearings. As found from the results, a high preloaded spindle
tool shows higher limited cutting depth at mid position, while a spindle
with low preload shows a higher limited depth. This indicates that the
machining stability of a milling machine is affected to vary by the
spindle unit when it was assembled with different bearing preload.
Abstract: This paper examines the system protection for cyber-physical
systems (CPS). CPS are particularly characterized by their
networking system components. This means they are able to adapt to
the needs of their users and its environment. With this ability, CPS
have new, specific requirements on the protection against anti-counterfeiting,
know-how loss and manipulation. They increase the
requirements on system protection because piracy attacks can be
more diverse, for example because of an increasing number of
interfaces or through the networking abilities. The new requirements
were identified and in a next step matched with existing protective
measures. Due to the found gap the development of new protection
measures has to be forced to close this gap. Moreover a comparison
of the effectiveness between selected measures was realized and the
first results are presented in this paper.
Abstract: Cooperative spectrum sensing is a crucial challenge in
cognitive radio networks. Cooperative sensing can increase the
reliability of spectrum hole detection, optimize sensing time and
reduce delay in cooperative networks. In this paper, an efficient
central capacity optimization algorithm is proposed to minimize
cooperative sensing time in a homogenous sensor network using OR
decision rule subject to the detection and false alarm probabilities
constraints. The evaluation results reveal significant improvement in
the sensing time and normalized capacity of the cognitive sensors.
Abstract: The Speexx results revealed four main factors
affecting the success of 190 Thai sophomores as follows: 1) Future
English training should be pursued in applied Speexx development.
2) Thai students didn’t see the benefit of having an Online Language
Training Program. 3) There is a great need to educate the next
generation of learners on the benefits of Speexx within the
community. 4) A great majority of Thai Sophomores didn't know
what Speexx was.
A guideline for self-reliance planning consisted of four aspects: 1)
Development planning: by arranging groups to further improve
English abilities with the Speexx Language Training program and
encourage using Speexx into every day practice. Local communities
need to develop awareness of the usefulness of Speexx and share the
value of using the program among family and friends. 2) Humanities
and Social Science staff should develop skills using this Online
Language Training Program to expand on the benefits of Speexx
within their departments. 3) Further research should be pursued on
the Thai Students progression with Speexx and how it helps them
improve their language skills with Business English. 4) University’s
and Language centers should focus on using Speexx to encourage
learning for any language, not just English.
Abstract: The problems arising from unbalanced data sets
generally appear in real world applications. Due to unequal class
distribution, many researchers have found that the performance of
existing classifiers tends to be biased towards the majority class. The
k-nearest neighbors’ nonparametric discriminant analysis is a method
that was proposed for classifying unbalanced classes with good
performance. In this study, the methods of discriminant analysis are
of interest in investigating misclassification error rates for classimbalanced
data of three diabetes risk groups. The purpose of this
study was to compare the classification performance between
parametric discriminant analysis and nonparametric discriminant
analysis in a three-class classification of class-imbalanced data of
diabetes risk groups. Data from a project maintaining healthy
conditions for 599 employees of a government hospital in Bangkok
were obtained for the classification problem. The employees were
divided into three diabetes risk groups: non-risk (90%), risk (5%),
and diabetic (5%). The original data including the variables of
diabetes risk group, age, gender, blood glucose, and BMI were
analyzed and bootstrapped for 50 and 100 samples, 599 observations
per sample, for additional estimation of the misclassification error
rate. Each data set was explored for the departure of multivariate
normality and the equality of covariance matrices of the three risk
groups. Both the original data and the bootstrap samples showed nonnormality
and unequal covariance matrices. The parametric linear
discriminant function, quadratic discriminant function, and the
nonparametric k-nearest neighbors’ discriminant function were
performed over 50 and 100 bootstrap samples and applied to the
original data. Searching the optimal classification rule, the choices of
prior probabilities were set up for both equal proportions (0.33: 0.33:
0.33) and unequal proportions of (0.90:0.05:0.05), (0.80: 0.10: 0.10)
and (0.70, 0.15, 0.15). The results from 50 and 100 bootstrap samples
indicated that the k-nearest neighbors approach when k=3 or k=4 and
the defined prior probabilities of non-risk: risk: diabetic as 0.90:
0.05:0.05 or 0.80:0.10:0.10 gave the smallest error rate of
misclassification. The k-nearest neighbors approach would be
suggested for classifying a three-class-imbalanced data of diabetes
risk groups.
Abstract: In this work, we explore the capability of the mean
shift algorithm as a powerful preprocessing tool for improving the
quality of spatial data, acquired from airborne scanners, from densely
built urban areas. On one hand, high resolution image data corrupted
by noise caused by lossy compression techniques are appropriately
smoothed while at the same time preserving the optical edges and, on
the other, low resolution LiDAR data in the form of normalized
Digital Surface Map (nDSM) is upsampled through the joint mean
shift algorithm. Experiments on both the edge-preserving smoothing
and upsampling capabilities using synthetic RGB-z data show that the
mean shift algorithm is superior to bilateral filtering as well as to
other classical smoothing and upsampling algorithms. Application of
the proposed methodology for 3D reconstruction of buildings of a
pilot region of Athens, Greece results in a significant visual
improvement of the 3D building block model.
Abstract: The purpose of this study was to develop a descriptive
profile of the adapted physical activity research using single subject
experimental designs. All research articles using single subject
experimental designs published in the journal of Adapted Physical
Activity Quarterly from 1984 to 2013 were employed as the data
source. Each of the articles was coded in a subcategory of seven
categories: (a) the size of sample; (b) the age of participants; (c) the
type of disabilities; (d) the type of data analysis; (e) the type of
designs, (f) the independent variable, and (g) the dependent variable.
Frequencies, percentages, and trend inspection were used to analyze
the data and develop a profile. The profile developed characterizes a
small portion of research articles used single subject designs, in
which most researchers used a small sample size, recruited children
as subjects, emphasized learning and behavior impairments, selected
visual inspection with descriptive statistics, preferred a multiple
baseline design, focused on effects of therapy, inclusion, and
strategy, and measured desired behaviors more often, with a
decreasing trend over years.
Abstract: Quick adoption of e-business and emerging influence
of “Electronic Word of Mouth e-WOM” communication on guests
made leading hotel brands successful examples of electronic guest
relationship management. Main reasons behind such success are well
established procedures in collection, analysis and usage of highly
valuable data available on the Internet, generated through some form
of e-GRM programme. E-GRM is more than just a technology
solution. It’s a system which balance respective guest demands, hotel
technological capabilities and organizational culture of employees,
discharging the universal approach in guest relations “same for all”.
The purpose of this research derives from the necessity of
determining the importance of monitoring and applying e-WOM
communication as one of the methods used in managing guest
relations. This paper analyses and compares different hotelier’s
opinions on e-WOM communication.
Abstract: An adaptive nonparametric method is proposed for
stable real-time detection of seismoacoustic sources in multichannel
C-OTDR systems with a significant number of channels. This
method guarantees given upper boundaries for probabilities of Type I
and Type II errors. Properties of the proposed method are rigorously
proved. The results of practical applications of the proposed method
in a real C-OTDR-system are presented in this report.
Abstract: Theory of Mind (ToM) refers to the ability to infer
another’s mental state. With appropriate ToM, one can behave well in
social interactions. A growing body of evidence has demonstrated that
patients with temporal lobe epilepsy (TLE) may damage ToM by
affecting on regions of the underlying neural network of ToM.
However, the question of whether there is cerebral laterality for ToM
functions remains open. This study aimed to examine whether there is
cerebral lateralization for ToM abilities in TLE patients. Sixty-seven
adult TLE patients and 30 matched healthy controls (HC) were
recruited. Patients were classified into right (RTLE), left (LTLE), and
bilateral (BTLE) TLE groups on the basis of a consensus panel review
of their seizure semiology, EEG findings, and brain imaging results.
All participants completed an intellectual test and four tasks measuring
basic and advanced ToM. The results showed that, on all ToM tasks,
(1) each patient group performed worse than HC; (2) there were no
significant differences between LTLE and RTLE groups; and (3) the
BTLE group performed the worst. It appears that the neural network
responsible for ToM is distributed evenly between the cerebral
hemispheres.
Abstract: This paper proposes the application of the Smart
Security Concept in the East Mediterranean. Smart Security aims to
secure critical infrastructure, such as hydrocarbon platforms, against
asymmetrical threats. The concept is based on Anti Asymmetrical
Area Denial (A3D) which necessitates limiting freedom of action of
maritime terrorists and piracy by founding safe and secure maritime
areas through sea lines of communication using short range
capabilities.
Abstract: The efficiency of the actuation system of exoskeletons
and active orthoses for lower limbs is a significant aspect of the
design of such devices because it affects their efficacy. The F-IVT is
an innovative actuation system to power artificial knee joint with
energy recovery capabilities. Its key and non-conventional elements
are a flywheel that acts as a mechanical energy storage system, and
an Infinitely Variable Transmission (IVT). The design of the F-IVT
can be optimized for a certain walking condition, resulting in a heavy
reduction of both the electric energy consumption and of the electric
peak power. In this work, by means of simulations of level ground
walking at different speeds, it is demonstrated that the F-IVT is still
an advantageous actuator which permits to save energy consumption
and to downsize the electric motor even when it does not work in
nominal conditions.
Abstract: Reflux condensation occurs in vertical channels and tubes when there is an upward core flow of vapour (or gas-vapour mixture) and a downward flow of the liquid film. The understanding of this condensation configuration is crucial in the design of reflux condensers, distillation columns, and in loss-of-coolant safety analyses in nuclear power plant steam generators. The unique feature of this flow is the upward flow of the vapour-gas mixture (or pure vapour) that retards the liquid flow via shear at the liquid-mixture interface. The present model solves the full, elliptic governing equations in both the film and the gas-vapour core flow. The computational mesh is non-orthogonal and adapts dynamically the phase interface, thus produces a sharp and accurate interface. Shear forces and heat and mass transfer at the interface are accounted for fundamentally. This modeling is a big step ahead of current capabilities by removing the limitations of previous reflux condensation models which inherently cannot account for the detailed local balances of shear, mass, and heat transfer at the interface. Discretisation has been done based on finite volume method and co-located variable storage scheme. An in-house computer code was developed to implement the numerical solution scheme. Detailed results are presented for laminar reflux condensation from steam-air mixtures flowing in vertical parallel plate channels. The results include velocity and gas mass fraction profiles, as well as axial variations of film thickness.