Abstract: Organizational culture fosters innovation, and
innovation is the main engine to be sustained within the uncertainty
market. Like other countries, the construction industry significantly
contributes to the economy, society and technology of Malaysia, yet,
innovation is still considered slow compared to other industries such
as manufacturing. Given the important role of an architect as the key
player and the contributor of new ideas in the construction industry,
there is a call to identify the issue and improve the current situation
by focusing on the architectural firms. In addition, the existing
studies tend to focus only on a few dimensions of organizational
culture and very few studies consider whether innovation is being
generated or adopted. Hence, the present research tends to fill in the
gap by identifying the organizational cultures that foster or hinder
innovation generation and/or innovation adoption, and propose a
model of organizational culture and innovation generation and/or
adoption.
Abstract: In this paper, low end Digital Signal Processors (DSPs)
are applied to accelerate integer neural networks. The use of DSPs
to accelerate neural networks has been a topic of study for some
time, and has demonstrated significant performance improvements.
Recently, work has been done on integer only neural networks, which
greatly reduces hardware requirements, and thus allows for cheaper
hardware implementation. DSPs with Arithmetic Logic Units (ALUs)
that support floating or fixed point arithmetic are generally more
expensive than their integer only counterparts due to increased circuit
complexity. However if the need for floating or fixed point math
operation can be removed, then simpler, lower cost DSPs can be
used. To achieve this, an integer only neural network is created in
this paper, which is then accelerated by using DSP instructions to
improve performance.
Abstract: The goal of this research is discovering the
determinants of the success or failure of external cooperation in small
and medium enterprises (SMEs). For this, a survey was given to 190
SMEs that experienced external cooperation within the last 3 years. A
logistic regression model was used to derive organizational or strategic
characteristics that significantly influence whether external
collaboration of domestic SMEs is successful or not. Results suggest
that research and development (R&D) features in general
characteristics (both idea creation and discovering market
opportunities) that focused on and emphasized indirected-market
stakeholders (such as complementary companies and affiliates) and
strategies in innovative strategic characteristics raise the probability of
successful external cooperation. This can be used meaningfully to
build a policy or strategy for inducing successful external cooperation
or to understand the innovation of SMEs.
Abstract: An Artificial Neural Network based modeling
technique has been used to study the influence of different
combinations of meteorological parameters on evaporation from a
reservoir. The data set used is taken from an earlier reported study.
Several input combination were tried so as to find out the importance
of different input parameters in predicting the evaporation. The
prediction accuracy of Artificial Neural Network has also been
compared with the accuracy of linear regression for predicting
evaporation. The comparison demonstrated superior performance of
Artificial Neural Network over linear regression approach. The
findings of the study also revealed the requirement of all input
parameters considered together, instead of individual parameters
taken one at a time as reported in earlier studies, in predicting the
evaporation. The highest correlation coefficient (0.960) along with
lowest root mean square error (0.865) was obtained with the input
combination of air temperature, wind speed, sunshine hours and
mean relative humidity. A graph between the actual and predicted
values of evaporation suggests that most of the values lie within a
scatter of ±15% with all input parameters. The findings of this study
suggest the usefulness of ANN technique in predicting the
evaporation losses from reservoirs.
Abstract: Intelligent deep-drawing is an instrumental research field in sheet metal forming. A set of 28 different experimental data have been employed in this paper, investigating the roles of die radius, punch radius, friction coefficients and drawing ratios for axisymmetric workpieces deep drawing. This paper focuses an evolutionary neural network, specifically, error back propagation in collaboration with genetic algorithm. The neural network encompasses a number of different functional nodes defined through the established principles. The input parameters, i.e., punch radii, die radii, friction coefficients and drawing ratios are set to the network; thereafter, the material outputs at two critical points are accurately calculated. The output of the network is used to establish the best parameters leading to the most uniform thickness in the product via the genetic algorithm. This research achieved satisfactory results based on demonstration of neural networks.
Abstract: In this study, a fuzzy-logic based control system was
designed to ensure that time and energy is saved during the operation
of load elevators which are used during the construction of tall
buildings. In the control system that was devised, for the load
elevators to work more efficiently, the energy interval where the
motor worked was taken as the output variable whereas the amount
of load and the building height were taken as input variables. The
most appropriate working intervals depending on the characteristics
of these variables were defined by the help of an expert. Fuzzy expert
system software was formed using Delphi programming language. In
this design, mamdani max-min inference mechanism was used and
the centroid method was employed in the clarification procedure. In
conclusion, it is observed that the system that was designed is
feasible and this is supported by statistical analyses..
Abstract: A gold coated copper rotating electrode was used to
eliminate surface oxidation effect. This study examined the effect of
electrode rotation on the ozone generation process and showed that an
ozonizer with an electrode rotating system might be a possible way to
increase ozone-synthesis efficiency. Two new phenomena appeared
during experiments with the rotating electrode. First was that ozone
concentration increased to about two times higher than that of the case
with no rotation. Second, input power and discharge area were found
to increase with the rotation speed. Both ozone concentration and
ozone production efficiency improved in the case of rotating electrode
compared to the case with a non-rotating electrode. One possible
reason for this was the increase in discharge length of
micro-discharges during electrode rotation. The rotating electrode
decreased onset voltage, while reactor capacitance increased with
rotation. Use of a rotating-type electrode allowed earlier observation
of the ozone zero phenomena compared with a non-rotating electrode
because, during rotation, the entire electrode surface was functional,
allowing nitrogen on the electrode surface to be evenly consumed.
Nitrogen demand increased with increasing rotation s
Abstract: This work deals with modeling and simulation of SO2 removal in a ceramic membrane by means of FEM. A mass transfer model was developed to predict the performance of SO2 absorption in a chemical solvent. The model was based on solving conservation equations for gas component in the membrane. Computational fluid dynamics (CFD) of mass and momentum were used to solve the model equations. The simulations aimed to obtain the distribution of gas concentration in the absorption process. The effect of the operating parameters on the efficiency of the ceramic membrane was evaluated. The modeling findings showed that the gas phase velocity has significant effect on the removal of gas whereas the liquid phase does not affect the SO2 removal significantly. It is also indicated that the main mass transfer resistance is placed in the membrane and gas phase because of high tortuosity of the ceramic membrane.
Abstract: Advancement in Artificial Intelligence has lead to the
developments of various “smart" devices. Character recognition
device is one of such smart devices that acquire partial human
intelligence with the ability to capture and recognize various
characters in different languages. Firstly multiscale neural training
with modifications in the input training vectors is adopted in this
paper to acquire its advantage in training higher resolution character
images. Secondly selective thresholding using minimum distance
technique is proposed to be used to increase the level of accuracy of
character recognition. A simulator program (a GUI) is designed in
such a way that the characters can be located on any spot on the
blank paper in which the characters are written. The results show that
such methods with moderate level of training epochs can produce
accuracies of at least 85% and more for handwritten upper case
English characters and numerals.
Abstract: Modern information and communication technologies
offer a variety of support options for the efficient handling of
customer relationships. CRM systems have been developed, which
are designed to support the processes in the areas of marketing, sales
and service. Along with technological progress, CRM systems are
constantly changing, i.e. the systems are continually enhanced by
new functions. However, not all functions are suitable for every
company because of different frameworks and business processes. In
this context the question arises whether or not CRM systems are
widely used in Austrian companies and which business processes are
most frequently supported by CRM systems. This paper aims to shed
light on the popularity of CRM systems in Austrian companies in
general and the use of different functions to support their daily
business. First of all, the paper provides a theoretical overview of the
structure of modern CRM systems and proposes a categorization of
currently available software functionality for collaborative,
operational and analytical CRM processes, which provides the
theoretical background for the empirical study. Apart from these
theoretical considerations, the paper presents the empirical results of
a field survey on the use of CRM systems in Austrian companies and
analyzes its findings.
Abstract: This paper aims to present the reviews of the
application of neural network in shunt active power filter (SAPF).
From the review, three out of four components of SAPF structure,
which are harmonic detection component, compensating current
control, and DC bus voltage control, have been adopted some of
neural network architecture as part of its component or even
substitution. The objectives of most papers in using neural network in
SAPF are to increase the efficiency, stability, accuracy, robustness,
tracking ability of the systems of each component. Moreover,
minimizing unneeded signal due to the distortion is the ultimate goal
in applying neural network to the SAPF. The most famous
architecture of neural network in SAPF applications are ADALINE
and Backpropagation (BP).
Abstract: An aqueous methanol sensor for use in direct
methanol fuel cells (DMFCs) applications is demonstrated; the
methanol sensor is built using dispersed single-walled carbon
nanotubes (SWCNTs) with Nafion117 solution to detect the methanol
concentration in water. The study is aimed at the potential use of the
carbon nanotubes array as a methanol sensor for direct methanol fuel
cells (DMFCs). The concentration of methanol in the fuel circulation
loop of a DMFC system is an important operating parameter, because
it determines the electrical performance and efficiency of the fuel cell
system. The sensor is also operative even at ambient temperatures
and responds quickly to changes in the concentration levels of the
methanol. Such a sensor can be easily incorporated into the methanol
fuel solution flow loop in the DMFC system.
Abstract: Simultaneous recovery of copper and DCA from
simulated MEUF concentrated stream was investigated. Effects of
surfactant (DCA) and metal (copper) concentrations, surfactant to
metal molar ratio (S/M ratio), electroplating voltage, EDTA
concentration, solution pH, and salt concentration on metal recovery
and current efficiency were studied. Electric voltage of -0.5 V was
shown to be optimum operation condition in terms of Cu recovery,
current efficiency, and surfactant recovery. Increasing Cu recovery and
current efficiency were observed with increases of Cu concentration
while keeping concentration of DCA constant. However, increasing
both Cu and DCA concentration while keeping S/M ratio constant at
2.5 showed detrimental effect on Cu recovery at DCA concentration
higher than 15 mM. Cu recovery decreases with increasing pH while
current efficiency showed an opposite trend. It is believed that
conductivity is the main cause for discrepancy of Cu recovery and
current efficiency observed at different pH. Finally, it was shown that
EDTA had adverse effect on both Cu recovery and current efficiency
while addition of NaCl salt had negative impact on current efficiency
at concentration higher than 8000 mg/L.
Abstract: With the exponential growth of networked system and
application such as eCommerce, the demand for effective internet
security is increasing. Cryptology is the science and study of systems
for secret communication. It consists of two complementary fields of
study: cryptography and cryptanalysis. The application of genetic
algorithms in the cryptanalysis of knapsack ciphers is suggested by
Spillman [7]. In order to improve the efficiency of genetic algorithm
attack on knapsack cipher, the previously published attack was
enhanced and re-implemented with variation of initial assumptions
and results are compared with Spillman results. The experimental
result of research indicates that the efficiency of genetic algorithm
attack on knapsack cipher can be improved with variation of initial
assumption.
Abstract: Fisheries management all around the world is
hampered by the lack, or poor quality, of critical data on fish
resources and fishing operations. The main reasons for the chronic
inability to collect good quality data during fishing operations is the
culture of secrecy common among fishers and the lack of modern
data gathering technology onboard most fishing vessels. In response,
OLRAC-SPS, a South African company, developed fisheries datalogging
software (eLog in short) and named it Olrac. The Olrac eLog
solution is capable of collecting, analysing, plotting, mapping,
reporting, tracing and transmitting all data related to fishing
operations. Olrac can be used by skippers, fleet/company managers,
offshore mariculture farmers, scientists, observers, compliance
inspectors and fisheries management authorities. The authors believe
that using eLog onboard fishing vessels has the potential to
revolutionise the entire process of data collection and reporting
during fishing operations and, if properly deployed and utilised,
could transform the entire commercial fleet to a provider of good
quality data and forever change the way fish resources are managed.
In addition it will make it possible to trace catches back to the actual
individual fishing operation, to improve fishing efficiency and to
dramatically improve control of fishing operations and enforcement
of fishing regulations.
Abstract: Computer languages are usually lumped together
into broad -paradigms-, leaving us in want of a finer classification
of kinds of language. Theories distinguishing between -genuine
differences- in language has been called for, and we propose that
such differences can be observed through a notion of expressive mode.
We outline this concept, propose how it could be operationalized and
indicate a possible context for the development of a corresponding
theory. Finally we consider a possible application in connection
with evaluation of language revision. We illustrate this with a case,
investigating possible revisions of the relational algebra in order to
overcome weaknesses of the division operator in connection with
universal queries.
Abstract: Hydrogen is an important chemical in many industries
and it is expected to become one of the major fuels for energy
generation in the future. Unfortunately, hydrogen does not exist in its
elemental form in nature and therefore has to be produced from
hydrocarbons, hydrogen-containing compounds or water.
Above its critical point (374.8oC and 22.1MPa), water has lower
density and viscosity, and a higher heat capacity than those of
ambient water. Mass transfer in supercritical water (SCW) is
enhanced due to its increased diffusivity and transport ability. The
reduced dielectric constant makes supercritical water a better solvent
for organic compounds and gases. Hence, due to the aforementioned
desirable properties, there is a growing interest toward studies
regarding the gasification of organic matter containing biomass or
model biomass solutions in supercritical water.
In this study, hydrogen and biofuel production by the catalytic
gasification of 2-Propanol in supercritical conditions of water was
investigated. Pt/Al2O3and Ni/Al2O3were the catalysts used in the
gasification reactions. All of the experiments were performed under a
constant pressure of 25MPa. The effects of five reaction temperatures
(400, 450, 500, 550 and 600°C) and five reaction times (10, 15, 20,
25 and 30 s) on the gasification yield and flammable component
content were investigated.
Abstract: LABVIEW is a graphical programming language that has its roots in automation control and data acquisition. In this paper we have utilized this platform to provide a powerful toolset for process identification and control of nonlinear systems based on artificial neural networks (ANN). This tool has been applied to the monitoring and control of a lab-scale distillation column DELTALAB DC-SP. The proposed control scheme offers high speed of response for changes in set points and null stationary error for dual composition control and shows robustness in presence of externally imposed disturbance.
Abstract: Water hyacinth has been used in aquatic systems for
wastewater purification in many years worldwide. The role of water
hyacinth (Eichhornia crassipes) species in polishing nitrate and
phosphorus concentration from municipal wastewater treatment plant
effluent by phytoremediation method was evaluated. The objective
of this project is to determine the removal efficiency of water
hyacinth in polishing nitrate and phosphorus, as well as chemical
oxygen demand (COD) and ammonia. Water hyacinth is considered
as the most efficient aquatic plant used in removing vast range of
pollutants such as organic matters, nutrients and heavy metals. Water
hyacinth, also referred as macrophytes, were cultivated in the
treatment house in a reactor tank of approximately 90(L) x 40(W) x
25(H) in dimension and built with three compartments. Three water
hyacinths were placed in each compartments and water sample in
each compartment were collected in every two days. The plant
observation was conducted by weight measurement, plant uptake and
new young shoot development. Water hyacinth effectively removed
approximately 49% of COD, 81% of ammonia, 67% of phosphorus
and 92% of nitrate. It also showed significant growth rate at starting
from day 6 with 0.33 shoot/day and they kept developing up to 0.38
shoot/day at the end of day 24. From the studies conducted, it was
proved that water hyacinth is capable of polishing the effluent of
municipal wastewater which contains undesirable amount of nitrate
and phosphorus concentration.
Abstract: Collaborative working environments for distance
education can be considered as a more generic form of contemporary
remote labs. At present, the majority of existing real laboratories are
not constructed to allow the involved participants to collaborate in
real time. To make this revolutionary learning environment possible
we must allow the different users to carry out an experiment
simultaneously. In recent times, multi-user environments are
successfully applied in many applications such as air traffic control
systems, team-oriented military systems, chat-text tools, multi-player
games etc. Thus, understanding the ideas and techniques behind these
systems could be of great importance in the contribution of ideas to
our e-learning environment for collaborative working. In this
investigation, collaborative working environments from theoretical
and practical perspectives are considered in order to build an
effective collaborative real laboratory, which allows two students or
more to conduct remote experiments at the same time as a team. In
order to achieve this goal, we have implemented distributed system
architecture, enabling students to obtain an automated help by either
a human tutor or a rule-based e-tutor.