Abstract: In Virtual organization, Knowledge Discovery (KD)
service contains distributed data resources and computing grid nodes.
Computational grid is integrated with data grid to form Knowledge
Grid, which implements Apriori algorithm for mining association
rule on grid network. This paper describes development of parallel
and distributed version of Apriori algorithm on Globus Toolkit using
Message Passing Interface extended with Grid Services (MPICHG2).
The creation of Knowledge Grid on top of data and
computational grid is to support decision making in real time
applications. In this paper, the case study describes design and
implementation of local and global mining of frequent item sets. The
experiments were conducted on different configurations of grid
network and computation time was recorded for each operation. We
analyzed our result with various grid configurations and it shows
speedup of computation time is almost superlinear.
Abstract: Crude oil blending is an important unit operation in
petroleum refining industry. A good model for the blending system is
beneficial for supervision operation, prediction of the export
petroleum quality and realizing model-based optimal control. Since
the blending cannot follow the ideal mixing rule in practice, we
propose a static neural network to approximate the blending
properties. By the dead-zone approach, we propose a new robust
learning algorithm and give theoretical analysis. Real data of crude
oil blending is applied to illustrate the neuro modeling approach.
Abstract: In a pilot plant scale of a fluidized bed reactor, a
reduction reaction of sodium sulfate by natural gas has been
investigated. Natural gas is applied in this study as a reductant. Feed
density, feed mass flow rate, natural gas and air flow rate
(independent parameters)and temperature of bed and CO
concentration in inlet and outlet of reactor (dependent parameters)
were monitored and recorded at steady state. The residence time was
adjusted close to value of traditional reaction [1]. An artificial neural
network (ANN) was established to study dependency of yield and
carbon gradient on operating parameters. Resultant 97% accuracy of
applied ANN is a good prove that natural gas can be used as a
reducing agent. Predicted ANN model for relation between other
sources carbon gradient (accuracy 74%) indicates there is not a
meaningful relation between other sources carbon variation and
reduction process which means carbon in granule does not have
significant effect on the reaction yield.
Abstract: Game theory could be used to analyze the conflicted
issues in the field of information hiding. In this paper, 2-phase game
can be used to build the embedder-attacker system to analyze the
limits of hiding capacity of embedding algorithms: the embedder
minimizes the expected damage and the attacker maximizes it. In the
system, the embedder first consumes its resource to build embedded
units (EU) and insert the secret information into EU. Then the attacker
distributes its resource evenly to the attacked EU. The expected
equilibrium damage, which is maximum damage in value from the
point of view of the attacker and minimum from the embedder against
the attacker, is evaluated by the case when the attacker attacks a
subset from all the EU. Furthermore, the optimal equilibrium capacity
of hiding information is calculated through the optimal number of EU
with the embedded secret information. Finally, illustrative examples
of the optimal equilibrium capacity are presented.
Abstract: Young patients suffering from Cerebral Palsy are
facing difficult choices concerning heavy surgeries. Diagnosis settled
by surgeons can be complex and on the other hand decision for
patient about getting or not such a surgery involves important
reflection effort. Proposed software combining prediction for
surgeries and post surgery kinematic values, and from 3D model
representing the patient is an innovative tool helpful for both patients
and medicine professionals. Beginning with analysis and
classification of kinematics values from Data Base extracted from
gait analysis in 3 separated clusters, it is possible to determine close
similarity between patients. Prediction surgery best adapted to
improve a patient gait is then determined by operating a suitable
preconditioned neural network. Finally, patient 3D modeling based
on kinematic values analysis, is animated thanks to post surgery
kinematic vectors characterizing the closest patient selected from
patients clustering.
Abstract: The present work deals with the structural analysis of
turbine blades and modeling of turbine blades. A common failure
mode for turbine machines is high cycle of fatigue of compressor and
turbine blades due to high dynamic stresses caused by blade vibration
and resonance within the operation range of the machinery. In this
work, proper damping system will be analyzed to reduce the
vibrating blade. The main focus of the work is the modeling of under
platform damper to evaluate the dynamic analysis of turbine-blade
vibrations. The system is analyzed using Bond graph technique. Bond
graph is one of the most convenient ways to represent a system from
the physical aspect in foreground. It has advantage of putting together
multi-energy domains of a system in a single representation in a
unified manner. The bond graph model of dry friction damper is
simulated on SYMBOLS-shakti® software. In this work, the blades
are modeled as Timoshenko beam. Blade Vibrations under different
working conditions are being analyzed numerically.
Abstract: Laser engraving is a manufacturing method for those applications where previously Electrical Discharge Machining (EDM) was the only choice. Laser engraving technology removes material layer-by-layer and the thickness of layers is usually in the range of few microns. The aim of the present work is to investigate the influence of the process parameters on the surface quality when machined by laser engraving. The examined parameters were: the pulse frequency, the beam speed and the layer thickness. The surface quality was determined by the surface roughness for every set of parameters. Experimental results on Al7075 material showed that the surface roughness strictly depends on the process parameters used.
Abstract: This paper addresses the problem of recognizing and
interpreting the behavior of human workers in industrial
environments for the purpose of integrating humans in software
controlled manufacturing environments. In this work we propose a
generic concept in order to derive solutions for task-related manual
production applications. Thus, we are able to use a versatile concept
providing flexible components and being less restricted to a specific
problem or application. We instantiate our concept in a spot welding
scenario in which the behavior of a human worker is interpreted
when performing a welding task with a hand welding gun. We
acquire signals from inertial sensors, video cameras and triggers and
recognize atomic actions by using pose data from a marker based
video tracking system and movement data from inertial sensors.
Recognized atomic actions are analyzed on a higher evaluation level
by a finite state machine.
Abstract: Team efficacy beliefs show promise in enhancing
team performance. Using a model-based quantitative research design,
we investigated the antecedents and performance consequences of
generalized team efficacy (potency) in a sample of 56 capital projects
executed by 15 Fortune 500 companies in the process industries.
Empirical analysis of our field survey identified that generalized
team efficacy beliefs were positively associated with an objective
measure of project cost performance. Regression analysis revealed
that team competence, empowering leadership, and performance
feedback all predicted generalized team efficacy beliefs. Tests of
mediation revealed that generalized team efficacy fully mediated
between these three inputs and project cost performance.
Abstract: The purpose of this study is to explore how the emotions at the moment of conflict escalation are expressed nonverbally and how it can be detected by the parties involved in the conflicting situation. The study consists of two parts, in the first part it starts with the definition of "conflict" and "nonverbal communication". Further it includes the analysis of emotions and types of emotions, which may bring to the conflict escalation. Four types of emotions and emotion constructs are analyzed, particularly fear, anger, guilt and frustration. The second part of the study analyses the general role of nonverbal behavior in interaction and communication, which information it may give during communication to the person, who sends or receives those signals. The study finishes with the analysis of the nonverbal expression of analyzed emotions and on how it can be used during interaction.
Abstract: This study describes the methodology for the development of a validated in-vitro in-vivo correlation (IVIVC) for metoprolol tartrate modified release dosage forms with distinctive release rate characteristics. Modified release dosage forms were formulated by microencapsulation of metoprolol tartrate into different amounts of ethylcellulose by non-solvent addition technique. Then in-vitro and in-vivo studies were conducted to develop and validate level A IVIVC for metoprolol tartrate. The values of regression co-efficient (R2-values) for IVIVC of T2 and T3 formulations were not significantly (p
Abstract: This paper presents the combination of different precipitation data sets and the distributed hydrological model, in order to examine the flood runoff reproductivity of scattered observation catchments. The precipitation data sets were obtained from observation using rain-gages, satellite based estimate (TRMM), and numerical weather prediction model (NWP), then were coupled with the super tank model. The case study was conducted in three basins (small, medium, and large size) located in Central Vietnam. Calculated hydrographs based on ground observation rainfall showed best fit to measured stream flow, while those obtained from TRMM and NWP showed high uncertainty of peak discharges. However, calculated hydrographs using the adjusted rainfield depicted a promising alternative for the application of TRMM and NWP in flood modeling for scattered observation catchments, especially for the extension of forecast lead time.
Abstract: A mathematical model for determining the overall efficiency
of a multistage tractor gearbox including all gear, lubricant,
surface finish related parameters and operating conditions is
presented. Sliding friction, rolling friction and windage losses were
considered as the main sources of power loss in the gearing system. A
computer code in FORTRAN was developed to simulate the model.
Sliding friction contributes about 98% of the total power loss for
gear trains operating at relatively low speeds (less than 2000 rpm
input speed). Rolling frictional losses decrease with increased load
while windage losses are only significant for gears running at very
high speeds (greater than 3000 rpm). The results also showed that the
overall efficiency varies over the path of contact of the gear meshes
ranging between 94% to 99.5%.
Abstract: This study was to search for the desirable direction of
the sidewalk planning in Korea by establishing the concepts of
walking and pedestrian space, and analyzing the advanced precedents
in and out of country. Also, based on the precedent studies and
relevant laws, regulations, and systems, it aimed for the following
sequential process: firstly, to derive design elements from the
functions and characteristics of sidewalk and cluster the similar
elements by each characteristics, sampling representative
characteristics and making them hierarchical; then, to analyze their
significances via the first questionnaire survey, and the relative
weights and priorities of each elements via the Analytic Hierarchy
Process(AHP); finally, based on the analysis result, to establish the
frame of suggesting the direction of policy to improve the pedestrian
environment of sidewalk in urban commercial district for the future
planning and design of pedestrian space.
Abstract: detecting the deadlock is one of the important
problems in distributed systems and different solutions have been
proposed for it. Among the many deadlock detection algorithms,
Edge-chasing has been the most widely used. In Edge-chasing
algorithm, a special message called probe is made and sent along
dependency edges. When the initiator of a probe receives the probe
back the existence of a deadlock is revealed. But these algorithms are
not problem-free. One of the problems associated with them is that
they cannot detect some deadlocks and they even identify false
deadlocks. A key point not mentioned in the literature is that when
the process is waiting to obtain the required resources and its
execution has been blocked, how it can actually respond to probe
messages in the system. Also the question of 'which process should
be victimized in order to achieve a better performance when multiple
cycles exist within one single process in the system' has received
little attention. In this paper, one of the basic concepts of the
operating system - daemon - will be used to solve the problems
mentioned. The proposed Algorithm becomes engaged in sending
probe messages to the mandatory daemons and collects enough
information to effectively identify and resolve multi-cycle deadlocks
in distributed systems.
Abstract: New graph similarity methods have been proposed in this work with the aim to refining the chemical information extracted from molecules matching. For this purpose, data fusion of the isomorphic and nonisomorphic subgraphs into a new similarity measure, the Approximate Similarity, was carried out by several approaches. The application of the proposed method to the development of quantitative structure-activity relationships (QSAR) has provided reliable tools for predicting several pharmacological parameters: binding of steroids to the globulin-corticosteroid receptor, the activity of benzodiazepine receptor compounds, and the blood brain barrier permeability. Acceptable results were obtained for the models presented here.
Abstract: Logic based methods for learning from structured data
is limited w.r.t. handling large search spaces, preventing large-sized
substructures from being considered by the resulting classifiers. A
novel approach to learning from structured data is introduced that
employs a structure transformation method, called finger printing, for
addressing these limitations. The method, which generates features
corresponding to arbitrarily complex substructures, is implemented in
a system, called DIFFER. The method is demonstrated to perform
comparably to an existing state-of-art method on some benchmark
data sets without requiring restrictions on the search space.
Furthermore, learning from the union of features generated by finger
printing and the previous method outperforms learning from each
individual set of features on all benchmark data sets, demonstrating
the benefit of developing complementary, rather than competing,
methods for structure classification.
Abstract: Importance of strategic planning is unquestionable. However, the practical implementation of a strategic plan faces too many obstacles. The aim of the article is explained the importance of strategic planning and to find how companies in Moravian-Silesian Region deal with strategic planning, and to introduce the model, which helps to set strategic goals in financial indicators area. This model should be part of the whole process of strategic planning and can be use to predict the future values of financial indicators of the company with regard to the factor, which influence these indicators.
Abstract: Organic farmers across Saskatchewan face soil
phosphorus (P) shortages. Due to the restriction on inputs in organic
systems, farmers rely on crop rotation and naturally-occurring
arbuscular mycorrhizal fungi (AMF) for plant P supply. Crop rotation
is important for disease, pest, and weed management. Crops that are
not colonized by AMF (non-mycorrhizal) can decrease colonization
of a following crop. An experiment was performed to quantify soil P
cycling in four cropping sequences under organic management and
determine if mustard (non-mycorrhizal) was delaying the
colonization of subsequent wheat. Soils from the four cropping
sequences were measured for inorganic soil P (Pi), AMF spore
density (SD), phospholipid fatty acid analysis (PLFA, for AMF
biomarker counts), and alkaline phosphatase activity (ALPase,
related to AMF metabolic activity). Plants were measured for AMF
colonization and P content and uptake of above-ground biomass. A
lack of difference in AMF activity indicated that mustard was not
depressing colonization. Instead, AMF colonization was largely
determined by crop type and crop rotation.
Abstract: The aim of the paper work is to investigate and predict
the static performance of journal bearing in turbulent flow condition
considering micropolar lubrication. The Reynolds equation has been
modified considering turbulent micropolar lubrication and is solved
for steady state operations. The Constantinescu-s turbulence model is
adopted using the coefficients. The analysis has been done for a
parallel and inertia less flow. Load capacity and friction factor have
been evaluated for various operating parameters.