Abstract: All climate models agree that the temperature in
Greece will increase in the range of 1° to 2°C by the year 2030 and
mean sea level in Mediterranean is expected to rise at the rate of 5
cm/decade. The aim of the present paper is the estimation of the
coastline displacement driven by the climate change and sea level
rise. In order to achieve that, all known statistical and non-statistical
computational methods are employed on some Greek coastal areas.
Furthermore, Kalman filtering techniques are for the first time
introduced, formulated and tested. Based on all the above, shoreline
change signals and noises are computed and an inter-comparison
between the different methods can be deduced to help evaluating
which method is most promising as far as the retrieve of shoreline
change rate is concerned.
Abstract: Enzymatic hydrolysis of starch from natural sources
finds potential application in commercial production of alcoholic
beverage and bioethanol. In this study the effect of starch
concentration, temperature, time and enzyme concentration were
studied and optimized for hydrolysis of Potato starch powder (of
mesh 80/120) into glucose syrup by immobilized (using Sodium
arginate) α-amylase using central composite design. The
experimental result on enzymatic hydrolysis of Potato starch was
subjected to multiple linear regression analysis using MINITAB 14
software. Positive linear effect of starch concentration, enzyme
concentration and time was observed on hydrolysis of Potato starch
by α-amylase. The statistical significance of the model was validated
by F-test for analysis of variance (p ≤ 0.01). The optimum value of
starch concentration, enzyme concentration, temperature, time and
were found to be 6% (w/v), 2% (w/v), 40°C and 80min respectively.
The maximum glucose yield at optimum condition was 2.34 mg/mL.
Abstract: The Far From Most Strings Problem (FFMSP) is to obtain a string which is far from as many as possible of a given set of strings. All the input and the output strings are of the same length, and two strings are said to be far if their hamming distance is greater than or equal to a given positive integer. FFMSP belongs to the class of sequences consensus problems which have applications in molecular biology. The problem is NP-hard; it does not admit a constant-ratio approximation either, unless P = NP. Therefore, in addition to exact and approximate algorithms, (meta)heuristic algorithms have been proposed for the problem in recent years. On the other hand, in the recent years, hybrid algorithms have been proposed and successfully used for many hard problems in a variety of domains. In this paper, a new metaheuristic algorithm, called Constructive Beam and Local Search (CBLS), is investigated for the problem, which is a hybridization of constructive beam search and local search algorithms. More specifically, the proposed algorithm consists of two phases, the first phase is to obtain several candidate solutions via the constructive beam search and the second phase is to apply local search to the candidate solutions obtained by the first phase. The best solution found is returned as the final solution to the problem. The proposed algorithm is also similar to memetic algorithms in the sense that both use local search to further improve individual solutions. The CBLS algorithm is compared with the most recent published algorithm for the problem, GRASP, with significantly positive results; the improvement is by order of magnitudes in most cases.
Abstract: Conceptualization strengthens intelligent systems in generalization skill, effective knowledge representation, real-time inference, and managing uncertain and indefinite situations in addition to facilitating knowledge communication for learning agents situated in real world. Concept learning introduces a way of abstraction by which the continuous state is formed as entities called concepts which are connected to the action space and thus, they illustrate somehow the complex action space. Of computational concept learning approaches, action-based conceptualization is favored because of its simplicity and mirror neuron foundations in neuroscience. In this paper, a new biologically inspired concept learning approach based on the probabilistic framework is proposed. This approach exploits and extends the mirror neuron-s role in conceptualization for a reinforcement learning agent in nondeterministic environments. In the proposed method, instead of building a huge numerical knowledge, the concepts are learnt gradually from rewards through interaction with the environment. Moreover the probabilistic formation of the concepts is employed to deal with uncertain and dynamic nature of real problems in addition to the ability of generalization. These characteristics as a whole distinguish the proposed learning algorithm from both a pure classification algorithm and typical reinforcement learning. Simulation results show advantages of the proposed framework in terms of convergence speed as well as generalization and asymptotic behavior because of utilizing both success and failures attempts through received rewards. Experimental results, on the other hand, show the applicability and effectiveness of the proposed method in continuous and noisy environments for a real robotic task such as maze as well as the benefits of implementing an incremental learning scenario in artificial agents.
Abstract: A multi-rate discrete-time model, whose response
agrees exactly with that of a continuous-time original at all sampling
instants for any sampling periods, is developed for a linear system,
which is assumed to have multiple real eigenvalues. The sampling
rates can be chosen arbitrarily and individually, so that their ratios
can even be irrational. The state space model is obtained as a
combination of a linear diagonal state equation and a nonlinear output
equation. Unlike the usual lifted model, the order of the proposed
model is the same as the number of sampling rates, which is less than
or equal to the order of the original continuous-time system. The
method is based on a nonlinear variable transformation, which can be
considered as a generalization of linear similarity transformation,
which cannot be applied to systems with multiple eigenvalues in
general. An example and its simulation result show that the proposed
multi-rate model gives exact responses at all sampling instants.
Abstract: The significance of emissions from the road transport
sector (such as air pollution, noise, etc) has grown considerably in
recent years. In Australia, 14.3% of national greenhouse gas
emissions in 2000 were the transport sector-s share which 12.9% of
net national emissions were related to a road transport alone.
Considering the growing attention to the green house gas(GHG)
emissions, this paper attempts to provide air pollution modeling
aspects of environmental consequences of the road transport by using
one of the best computer based tools including the Geographic
Information System (GIS). In other word, in this study, GIS and its
applications is explained, models which are used to model air
pollution and GHG emissions from vehicles are described and GIS is
applied in real case study that attempts to forecast GHG emission
from people who travel to work by car in 2031 in Melbourne for
analysing results as thematic maps.
Abstract: This paper discusses the investigation of a wearable
textile monopole antenna on specific absorption rate (SAR) for bodycentric
wireless communication applications at 2.45 GHz. The
antenna is characterized on a realistic 8 x 8 x 8 mm3 resolution
truncated Hugo body model in CST Microwave Studio software. The
result exhibited that the simulated SAR values were reduced
significantly by 83.5% as the position of textile monopole was
varying between 0 mm and 15 mm away from the human upper arm.
A power absorption reduction of 52.2% was also noticed as the
distance of textile monopole increased.
Abstract: Organizational communication is an administrative
function crucial especially for executives in the implementation of
organizational and administrative functions. Executives spend a
significant part of their time on communicative activities. Doing his or her daily routine, arranging meeting schedules, speaking on the telephone, reading or replying to business correspondence, or
fulfilling the control functions within the organization, an executive typically engages in communication processes.
Efficient communication is the principal device for the adequate implementation of administrative and organizational activities. For
this purpose, management needs to specify the kind of
communication system to be set up and the kind of communication
devices to be used. Communication is vital for any organization.
In conventional offices, communication takes place within the hierarchical pyramid called the organizational structure, and is known as formal or informal communication. Formal communication
is the type that works in specified structures within the organizational rules and towards the organizational goals. Informal communication, on the other hand, is the unofficial type taking place among staff as
face-to-face or telephone interaction.
Communication in virtual as well as conventional offices is
essential for obtaining the right information in administrative
activities and decision-making. Virtual communication technologies
increase the efficiency of communication especially in virtual teams.
Group communication is strengthened through an inter-group central
channel. Further, ease of information transmission makes it possible
to reach the information at the source, allowing efficient and correct decisions. Virtual offices can present as a whole the elements of information which conventional offices produce in different
environments.
At present, virtual work has become a reality with its pros and
cons, and will probably spread very rapidly in coming years, in line
with the growth in information technologies.
Abstract: Although, all high school students in Japan are required to learn informatics, many of them do not learn this topic sufficiently. In response to this situation, we propose a support package for high school informatics classes. To examine what students learned and if they sufficiently understood the context of the lessons, a questionnaire survey was distributed to 186 students. We analyzed the results of the questionnaire and determined the weakest units, which were “basic computer configuration” and “memory and secondary storage”. We then developed a package for teaching these units. We propose that our package be applied in high school classrooms.
Abstract: Lattice Monte Carlo methods are an excellent
choice for the simulation of non-linear thermal diffusion
problems. In this paper, and for the first time, Lattice Monte
Carlo analysis is performed on thermal diffusion combined
with convective heat transfer. Laminar flow of water modeled
as an incompressible fluid inside a copper pipe with a constant
surface temperature is considered. For the simulation of
thermal conduction, the temperature dependence of the
thermal conductivity of the water is accounted for. Using the
novel Lattice Monte Carlo approach, temperature distributions
and energy fluxes are obtained.
Abstract: Small-scale RC models of both piles and tunnel ducts
were produced as mockups of reality and loaded under soil
confinement conditionsto investigate the damage evolution of
structural RC interacting with soil. Experimental verifications usinga
3D nonlinear FE analysis program called COM3D, which was
developed at the University of Tokyo, are introduced. This analysis
has been used in practice for seismic performance assessment of
underground ducts and in-ground LNG storage tanks in consideration
of soil-structure interactionunder static and dynamic loading. Varying
modes of failure of RCpilessubjected to different magnitudes of soil
confinement were successfully reproduced in the proposed small-scale
experiments and numerically simulated as well. Analytical simulation
was applied to RC tunnel mockups under a wide variety of depth and
soil confinement conditions, and reasonable matching was confirmed.
Abstract: The interaction between wakes of bluff body and
airfoil have profound influences on system performance in many
industrial applications, e.g., turbo-machinery and cooling fan. The
present work investigates the effect of configuration include; airfoil-s
angle of attack, transverse and inline spacing of the models, on
frequency behavior of the cylinder-s near-wake. The experiments
carried on under subcritical flow regime, using the hot-wire
anemometry (HWA). The relationship between the Strouhal numbers
and arrangements provide an insight into the global physical
processes of wake interaction and vortex shedding.
Abstract: Poly-β-hydroxybutyrate (PHB) is one of the most
famous biopolymers that has various applications in production of
biodegradable carriers. The most important strategy for enhancing
efficiency in production process and reducing the price of PHB, is the
accurate expression of kinetic model of products formation and
parameters that are effective on it, such as Dry Cell Weight (DCW)
and substrate consumption. Considering the high capabilities of
artificial neural networks in modeling and simulation of non-linear
systems such as biological and chemical industries that mainly are
multivariable systems, kinetic modeling of microbial production of
PHB that is a complex and non-linear biological process, the three
layers perceptron neural network model was used in this study.
Artificial neural network educates itself and finds the hidden laws
behind the data with mapping based on experimental data, of dry cell
weight, substrate concentration as input and PHB concentration as
output. For training the network, a series of experimental data for
PHB production from Hydrogenophaga Pseudoflava by glucose
carbon source was used. After training the network, two other
experimental data sets that have not intervened in the network
education, including dry cell concentration and substrate
concentration were applied as inputs to the network, and PHB
concentration was predicted by the network. Comparison of predicted
data by network and experimental data, indicated a high precision
predicted for both fructose and whey carbon sources. Also in present
study for better understanding of the ability of neural network in
modeling of biological processes, microbial production kinetic of
PHB by Leudeking-Piret experimental equation was modeled. The
Observed result indicated an accurate prediction of PHB
concentration by artificial neural network higher than Leudeking-
Piret model.
Abstract: Non-stationary trend in R-R interval series is
considered as a main factor that could highly influence the evaluation
of spectral analysis. It is suggested to remove trends in order to obtain
reliable results. In this study, three detrending methods, the
smoothness prior approach, the wavelet and the empirical mode
decomposition, were compared on artificial R-R interval series with
four types of simulated trends. The Lomb-Scargle periodogram was
used for spectral analysis of R-R interval series. Results indicated that
the wavelet method showed a better overall performance than the other
two methods, and more time-saving, too. Therefore it was selected for
spectral analysis of real R-R interval series of thirty-seven healthy
subjects. Significant decreases (19.94±5.87% in the low frequency
band and 18.97±5.78% in the ratio (p
Abstract: This paper represents the results of long term strength of mortar incorporating Rice Husk Ash (RHA). For these work mortar samples were made according to ASTM standard C 109/C. OPC cement was partially replaced by RHA at 0, 10, 15, 20, 25 and 30 percent replacement level. After casting all samples were kept in controlled environment and curing was done up to 90 days. Test of mortar was performed on 3, 7, 28, 90, 365 and 700 days. It is noticed that OPC mortar shows better strength at early age than mortar having RHA but at 90 days and onward the picture is different. At 700 days it is observed that mortar containing 20% RHA shows better result than any other samples.
Abstract: This paper describes the design process and the realtime validation of an innovative autonomous mid-air flight and landing system developed by the Italian Aerospace Research Center in the framework of the Italian national funded project TECVOL (Technologies for the Autonomous Flight). In the paper it is provided an insight of the whole development process of the system under study. In particular, the project framework is illustrated at first, then the functional context and the adopted design and testing approach are described, and finally the on-ground validation test rig on purpose designed is addressed in details. Furthermore, the hardwarein- the-loop validation of the autonomous mid-air flight and landing system by means of the real-time test rig is described and discussed.
Abstract: Genetically modified (GM) technology in food
production continued to generate controversies. Consumers were
concerned with the GM foods about the healthy and environmental
risks. While consumers- acceptance was a critical factor affecting how
widely this technology be used. According to the research review,
consumers- lack of information was one of the reasons to explain
consumers- low acceptance toward GM foods. The objective for this
study wanted to find out would informative product package affect
consumers- behavior toward GM foods. An experiment was designed
to investigate consumer behavior toward different product package
information. The results indicated that the product package
information influenced consumer product trust toward GM foods.
Compared with the traceability production system information, the
information about the GM rice was approved by authorized
organizations could increase consumers product trust in GM foods.
Consumers in Taiwan saw the information provided by authorized
organizations more credible than other information.
Abstract: The aim of this study is to identify the conditions of
implementation for reconfigurability in summarizing past flexible
manufacturing systems (FMS) research by drawing overall
conclusions from many separate High Performance Manufacturing
(HPM) studies. Meta-analysis will be applied to links between HPM
programs and their practices related to FMS and manufacturing
performance with particular reference to responsiveness performance.
More specifically, an application of meta-analysis will be made with
reference to two of the main steps towards the development of an
empirically-tested theory: testing the adequacy of the measurement of
variables and testing the linkages between the variables.
Abstract: This paper represents four unsupervised clustering algorithms namely sIB, RandomFlatClustering, FarthestFirst, and FilteredClusterer that previously works have not been used for network traffic classification. The methodology, the result, the products of the cluster and evaluation of these algorithms with efficiency of each algorithm from accuracy are shown. Otherwise, the efficiency of these algorithms considering form the time that it use to generate the cluster quickly and correctly. Our work study and test the best algorithm by using classify traffic anomaly in network traffic with different attribute that have not been used before. We analyses the algorithm that have the best efficiency or the best learning and compare it to the previously used (K-Means). Our research will be use to develop anomaly detection system to more efficiency and more require in the future.
Abstract: Learning is the acquisition of new mental schemata, knowledge, abilities and skills which can be used to solve problems potentially more successfully. The learning process is optimum when it is assisted and personalized. Learning is not a single activity, but should involve many possible activities to make learning become meaningful. Many e-learning applications provide facilities to support teaching and learning activities. One way to identify whether the e-learning system is being used by the learners is through the number of hits that can be obtained from the e-learning system's log data. However, we cannot rely solely to the number of hits in order to determine whether learning had occurred meaningfully. This is due to the fact that meaningful learning should engage five characteristics namely active, constructive, intentional, authentic and cooperative. This paper aims to analyze the e-learning activities that is meaningful to learning. By focusing on the meaningful learning characteristics, we match it to the corresponding Moodle e-learning activities. This analysis discovers the activities that have high impact to meaningful learning, as well as activities that are less meaningful. The high impact activities is given high weights since it become important to meaningful learning, while the low impact has less weight and said to be supportive e-learning activities. The result of this analysis helps us categorize which e-learning activities that are meaningful to learning and guide us to measure the effectiveness of e-learning usage.