Abstract: Organizational tendencies towards computer-based
information processing have been observed noticeably in the
third-world countries. Many enterprises are taking major initiatives
towards computerized working environment because of massive
benefits of computer-based information processing. However,
designing and developing information resource management software
for small and mid-size enterprises under budget costs and strict
deadline is always challenging for software engineers. Therefore, we
introduced an approach to design mid-size enterprise software by
using the Waterfall model, which is one of the SDLC (Software
Development Life Cycles), in a cost effective way. To fulfill research
objectives, in this study, we developed mid-sized enterprise software
named “BSK Management System” that assists enterprise software
clients with information resource management and perform complex
organizational tasks. Waterfall model phases have been applied to
ensure that all functions, user requirements, strategic goals, and
objectives are met. In addition, Rich Picture, Structured English, and
Data Dictionary have been implemented and investigated properly in
engineering manner. Furthermore, an assessment survey with 20
participants has been conducted to investigate the usability and
performance of the proposed software. The survey results indicated
that our system featured simple interfaces, easy operation and
maintenance, quick processing, and reliable and accurate transactions.
Abstract: Public-private partnerships (PPP) arrangements have
been extensively used in Canada, where the participation of private
companies in financing and managing infrastructure projects has
increased significantly in the last decade, particularly in the
transportation sector. This paper analyses the evolution of the PPP
market for transportation projects in Canada and examines the
participation of Spanish developers in this market, which have been
particularly successful in winning PPP contracts during the last
decade.
Abstract: The following article presents Technology Centre of
Ostrava (TCO) in the Czech Republic describing the structure and
main research areas realized by the project ENET - Energy Units for
Utilization of non Traditional Energy Sources. More details are
presented from the research program dealing with transformation,
accumulation and distribution of electric energy. Technology Centre
has its own energy mix consisting of alternative sources of fuel
sources that use of process gases from the storage part and also the
energy from distribution network. The article will be focus on the
properties and application possibilities SiC semiconductor devices for
power semiconductor converter for photovoltaic systems.
Abstract: Objects are usually horizontally sliced when printed by 3D printers. Therefore, if an object to be printed, such as a collection of fibers, originally has natural direction in shape, the printed direction contradicts with the natural direction. By using proper tools, such as field-oriented 3D paint software, field-oriented solid modelers, field-based tool-path generation software, and non-horizontal FDM 3D printers, the natural direction can be modeled and objects can be printed in a direction that is consistent with the natural direction. This consistence results in embodiment of momentum or force in expressions of the printed object. To achieve this goal, several design and manufacturing problems, but not all, have been solved. An application of this method is (Japanese) 3D calligraphy.
Abstract: Recently, there is a lot of interest in the field of under
water optical wireless communication for short range because of
its high bandwidth. But in most of the previous works line of
sight propagation or single scattering of photons only considered.
In practical case this is not applicable because of beam blockage in
underwater and multiple scattering also occurred during the photons
propagation through water. In this paper we consider a non-line
of sight underwater wireless optical communication system with
multiple scattering and examine the performance of the system using
monte carlo simulation. The distribution scattering angle of photons
are modeled by Henyey-Greenstein method. The average bit error
rate is calculated using on-off keying modulation for different water
types.
Abstract: Image compression based on fractal coding is a lossy
compression method and normally used for gray level images range
and domain blocks in rectangular shape. Fractal based digital image
compression technique provide a large compression ratio and in this
paper, it is proposed using YUV colour space and the fractal theory
which is based on iterated transformation. Fractal geometry is mainly
applied in the current study towards colour image compression
coding. These colour images possesses correlations among the colour
components and hence high compression ratio can be achieved by
exploiting all these redundancies. The proposed method utilises the
self-similarity in the colour image as well as the cross-correlations
between them. Experimental results show that the greater
compression ratio can be achieved with large domain blocks but more
trade off in image quality is good to acceptable at less than 1 bit per
pixel.
Abstract: Behavioral aspects of experience such as will power
are rarely subjected to quantitative study owing to the numerous
complexities involved. Will is a phenomenon that has puzzled
humanity for a long time. It is a belief that will power of an individual
affects the success achieved by them in life. It is also thought that a
person endowed with great will power can overcome even the most
crippling setbacks in life while a person with a weak will cannot make
the most of life even the greatest assets. This study is an attempt
to subject the phenomena of will to the test of an artificial neural
network through a computational model. The claim being tested is
that will power of an individual largely determines success achieved
in life. It is proposed that data pertaining to success of individuals
be obtained from an experiment and the phenomenon of will be
incorporated into the model, through data generated recursively using
a relation between will and success characteristic to the model.
An artificial neural network trained using part of the data, could
subsequently be used to make predictions regarding data points in
the rest of the model. The procedure would be tried for different
models and the model where the networks predictions are found to
be in greatest agreement with the data would be selected; and used
for studying the relation between success and will.
Abstract: The research of juice flavor forecasting has become
more important in China. Due to the fast economic growth in China,
many different kinds of juices have been introduced to the market. If a
beverage company can understand their customers’ preference well,
the juice can be served more attractive. Thus, this study intends to
introducing the basic theory and computing process of grapes juice
flavor forecasting based on support vector regression (SVR). Applying
SVR, BPN, and LR to forecast the flavor of grapes juice in real data
shows that SVR is more suitable and effective at predicting
performance.
Abstract: The past two decades, Thailand faced the natural
disasters, for instance, Gay typhoon in 1989, tsunami in 2004, and
huge flood in 2011. The disaster management in Thailand was
improved both structure and mechanism for cope with the natural
disaster since 2007. However, the natural disaster management in
Thailand has various problems, for examples, cooperation between
related an organizations have not unity, inadequate resources, the
natural disaster management of public sectors not proactive, people
has not awareness the risk of the natural disaster, and communities
did not participate in the natural disaster management.
Objective of this study is to find the methods for capacity building
in the natural disaster management of Thailand. The concept and
information about the capacity building and the natural disaster
management of Thailand were reviewed and analyzed by classifying
and organizing data. The result found that the methods for capacity
building in the natural disaster management of Thailand should be
consist of 1) link operation and information in the natural disaster
management between nation, province, local and community levels,
2) enhance competency and resources of public sectors which relate
to the natural disaster management, 3) establish proactive natural
disaster management both planning and implementation, 4)
decentralize the natural disaster management to local government
organizations, 5) construct public awareness in the natural disaster
management to community, 6) support Community Based Disaster
Risk Management (CBDRM) seriously, and 7) emphasis on
participation in the natural disaster management of all stakeholders.
Abstract: The exponential growth of social media arouses much
attention on public opinion information. The online forums, blogs,
micro blogs are proving to be extremely valuable resources and are
having bulk volume of information. However, most of the social
media data is unstructured and semi structured form. So that it is
more difficult to decipher automatically. Therefore, it is very much
essential to understand and analyze those data for making a right
decision. The online forums hotspot detection is a promising research
field in the web mining and it guides to motivate the user to take right
decision in right time. The proposed system consist of a novel
approach to detect a hotspot forum for any given time period. It uses
aging theory to find the hot terms and E-K-means for detecting the
hotspot forum. Experimental results demonstrate that the proposed
approach outperforms k-means for detecting the hotspot forums with
the improved accuracy.
Abstract: In the present work, Electrochemical Impedance
Spectrocopy (EIS) is applied to study the transport of different metal
cations through a cation-exchange membrane. This technique enables
the identification of the ionic-transport characteristics and to
distinguish between different transport mechanisms occurring at
different current density ranges. The impedance spectra are
dependent on the applied dc current density, on the type of cation and
on the concentration.
When the applied dc current density increases, the diameter of the
impedance spectra loops increases because all the components of
membrane system resistance increase. The diameter of the impedance
plots decreases in the order of Na(I), Ni(II) and Cr(III) due to the
increased interactions between the negatively charged sulfonic
groups of the membrane and the cations with greater charge. Nyquist
plots are shifted towards lower values of the real impedance, and its
diameter decreases with the increase of concentration due to the
decrease of the solution resistance.
Abstract: This paper is part of a study to develop robots for
farming. As such power requirement to operate equipment attach to
such robots become an important factor. Soil-tool interaction plays
major role in power consumption, thus predicting accurately the
forces which act on the blade during the farming is very important for
optimal designing of farm equipment. In this paper, a finite element
investigation for tillage tools and soil interaction is described by
using an inelastic constitutive material law for agriculture
application. A 3-dimensional (3D) nonlinear finite element analysis
(FEA) is developed to examine behavior of a blade with different
rake angles moving in a block of soil, and to estimate the blade force.
The soil model considered is an elastic-plastic with non-associated
Drucker-Prager material model. Special use of contact elements are
employed to consider connection between soil-blade and soil-soil
surfaces. The FEA results are compared with experimental ones,
which show good agreement in accurately predicting draft forces
developed on the blade when it moves through the soil. Also a very
good correlation was obtained between FEA results and analytical
results from classical soil mechanics theories for straight blades.
These comparisons verified the FEA model developed. For analyzing
complicated soil-tool interactions and for optimum design of blades,
this method will be useful.
Abstract: Indonesian higher education has experienced
significant changes over the last decade. In 1999, the government
published an overall strategy for decentralisation and enhancement of
local autonomy in many sectors, including (higher) education.
Indonesian higher education reforms have forced universities to
restructure their internal university governance to become more
entrepreneurial. These new types of internal university governance
are likely to affect the institutions’ leadership and management. This
paper discusses the approach and findings of a study on the
managerial leadership styles of deans in Indonesian universities. The
study aims to get a better understanding of styles exhibited by deans
manifested in their behaviours. Using the theories of reasoned action
and planned behaviour, in combination with the competing values
framework, a large-scale survey was conducted to gather information
on the deans’ behaviours, attitudes, subjective norms, and perceived
behavioural control. Based on the responses of a sample of 218
deans, the study identifies a number of leadership styles: the Master,
the Competitive Consultant, the Consensual Goal-Setter, the Focused
Team Captain, and the Informed Trust-Builder style. The study
demonstrates that attitudes are the primary determinant of the styles
that were found. Perceived behavioural control is a factor that
explains some managerial leadership styles. By understanding the
attitudes of deans in Indonesian universities, and their leadership
styles, universities can strengthen their management and governance,
and thus improve their effectiveness.
Abstract: In the past few years, the amount of malicious software
increased exponentially and, therefore, machine learning algorithms
became instrumental in identifying clean and malware files through
(semi)-automated classification. When working with very large
datasets, the major challenge is to reach both a very high malware
detection rate and a very low false positive rate. Another challenge
is to minimize the time needed for the machine learning algorithm to
do so. This paper presents a comparative study between different
machine learning techniques such as linear classifiers, ensembles,
decision trees or various hybrids thereof. The training dataset consists
of approximately 2 million clean files and 200.000 infected files,
which is a realistic quantitative mixture. The paper investigates the
above mentioned methods with respect to both their performance
(detection rate and false positive rate) and their practicability.
Abstract: One of the crucial parameters of digital cryptographic
systems is the selection of the keys used and their distribution. The
randomness of the keys has a strong impact on the system’s security
strength being difficult to be predicted, guessed, reproduced, or
discovered by a cryptanalyst. Therefore, adequate key randomness
generation is still sought for the benefit of stronger cryptosystems.
This paper suggests an algorithm designed to generate and test
pseudo random number sequences intended for cryptographic
applications. This algorithm is based on mathematically manipulating
a publically agreed upon information between sender and receiver
over a public channel. This information is used as a seed for
performing some mathematical functions in order to generate a
sequence of pseudorandom numbers that will be used for
encryption/decryption purposes. This manipulation involves
permutations and substitutions that fulfill Shannon’s principle of
“confusion and diffusion”. ASCII code characters were utilized in the
generation process instead of using bit strings initially, which adds
more flexibility in testing different seed values. Finally, the obtained
results would indicate sound difficulty of guessing keys by attackers.
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: A total of 115 yeast strains isolated from local cassava
processing wastes were measured for crude protein content. Among
these strains, the strain MSY-2 possessed the highest protein
concentration (>3.5 mg protein/mL). By using molecular
identification tools, it was identified to be a strain of Pichia
kudriavzevii based on similarity of D1/D2 domain of 26S rDNA
region. In this study, to optimize the protein production by MSY-2
strain, Response Surface Methodology (RSM) was applied. The
tested parameters were the carbon content, nitrogen content, and
incubation time. Here, the value of regression coefficient (R2) =
0.7194 could be explained by the model which is high to support the
significance of the model. Under the optimal condition, the protein
content was produced up to 3.77 g per L of the culture and MSY-2
strain contains 66.8 g protein per 100 g of cell dry weight. These
results revealed the plausibility of applying the novel strain of yeast
in single-cell protein production.
Abstract: The first part of the paper analyzes the dynamics of
the total fertility rate both at the national and regional level, pointing
out the regional disparities in the distribution of this indicator. At the
same time, we also focus on the collapse of the number of live births,
on the changes in the fertility rate by birth rank, as well as on the
failure of acquiring the desired number of children. The second part
of the study centres upon a survey applied to urban families with 3
and more than 3 offspring. The preliminary analysis highlights the
fact that an increased fertility (more than 3rd rank) is triggered by the
parents’ above the average material condition and superior education.
The current situation of Romania, which is still passing through a
period of relatively rapid demographic changes, marked by numerous
convulsions, requires a new approach, in compliance with the recent
interpretations appropriate to a new post-transitional demographic
regime.
Abstract: The paper presents a method for a simple and
immediate motion planning of a SCARA robot, whose end-effector
has to move along a given trajectory; the calculation procedure
requires the user to define in analytical form or by points the
trajectory to be followed and to assign the curvilinear abscissa as
function of the time. On the basis of the geometrical characteristics
of the robot, a specifically developed program determines the motion
laws of the actuators that enable the robot to generate the required
movement; this software can be used in all industrial applications for
which a SCARA robot has to be frequently reprogrammed, in order
to generate various types of trajectories with different motion times.
Abstract: We proposed a Hyperbolic Gompertz Growth Model
(HGGM), which was developed by introducing a shape parameter
(allometric). This was achieved by convoluting hyperbolic sine
function on the intrinsic rate of growth in the classical gompertz
growth equation. The resulting integral solution obtained
deterministically was reprogrammed into a statistical model and used
in modeling the height and diameter of Pines (Pinus caribaea). Its
ability in model prediction was compared with the classical gompertz
growth model, an approach which mimicked the natural variability of
height/diameter increment with respect to age and therefore provides
a more realistic height/diameter predictions using goodness of fit
tests and model selection criteria. The Kolmogorov Smirnov test and
Shapiro-Wilk test was also used to test the compliance of the error
term to normality assumptions while the independence of the error
term was confirmed using the runs test. The mean function of top
height/Dbh over age using the two models under study predicted
closely the observed values of top height/Dbh in the hyperbolic
gompertz growth models better than the source model (classical
gompertz growth model) while the results of R2, Adj. R2, MSE and
AIC confirmed the predictive power of the Hyperbolic Gompertz
growth models over its source model.