Abstract: This article discusses event monitoring options for
heterogeneous event sources as they are given in nowadays
heterogeneous distributed information systems. It follows the central
assumption, that a fully generic event monitoring solution cannot
provide complete support for event monitoring; instead, event source
specific semantics such as certain event types or support for certain
event monitoring techniques have to be taken into account.
Following from this, the core result of the work presented here is
the extension of a configurable event monitoring (Web) service for a
variety of event sources. A service approach allows us to trade
genericity for the exploitation of source specific characteristics. It
thus delivers results for the areas of SOA, Web services, CEP and
EDA.
Abstract: This paper presents development results of the method
of seismoacoustic activity monitoring based on usage vibrosensitive
properties of optical fibers. Analysis of Rayleigh backscattering
radiation parameters changes, which take place due to microscopic
seismoacoustic impacts on the optical fiber, allows to determine
seismoacoustic emission sources positions and to identify their types.
Results of using this approach are successful for complex monitoring
of railways.
Abstract: This paper introduces an original method for
guaranteed estimation of the accuracy for an ensemble of Lipschitz
classifiers. The solution was obtained as a finite closed set of
alternative hypotheses, which contains an object of classification with
probability of not less than the specified value. Thus, the
classification is represented by a set of hypothetical classes. In this
case, the smaller the cardinality of the discrete set of hypothetical
classes is, the higher is the classification accuracy. Experiments have
shown that if cardinality of the classifiers ensemble is increased then
the cardinality of this set of hypothetical classes is reduced. The
problem of the guaranteed estimation of the accuracy for an ensemble
of Lipschitz classifiers is relevant in multichannel classification of
target events in C-OTDR monitoring systems. Results of suggested
approach practical usage to accuracy control in C-OTDR monitoring
systems are present.
Abstract: Corrosion of concrete sewer pipes induced by sulfuric
acid is an acknowledged problem and a ticking time-bomb to sewer
operators. Whilst the chemical reaction of the corrosion process is
well-understood, the indirect roles of other parameters in the
corrosion process which are found in sewer environment are not
highly reflected on. This paper reports on a field studies undertaken
in Austria and United Kingdom, where the parameters of
temperature, pH, H2S and CO2 were monitored over a period of time.
The study establishes that (i) effluent temperature and pH have
similar daily pattern and peak times, when examined in minutes
scale; (ii) H2S and CO2 have an identical hourly pattern; (iii) H2S
instant or shifted relation to effluent temperature is governed by the
root mean square value of CO2.
Abstract: The main goal of this article is to describe the online
flood monitoring and prediction system Floreon+ primarily developed
for the Moravian-Silesian region in the Czech Republic and the basic
process it uses for running automatic rainfall-runoff and
hydrodynamic simulations along with their calibration and
uncertainty modeling. It takes a long time to execute such process
sequentially, which is not acceptable in the online scenario, so the use
of a high performance computing environment is proposed for all
parts of the process to shorten their duration. Finally, a case study on
the Ostravice River catchment is presented that shows actual
durations and their gain from the parallel implementation.
Abstract: Soil quality monitoring is a science-based soil
management tool that assesses soil ecosystem health.
A soil monitoring program in Auckland, New Zealand’s largest
city extends from 1995 to the present. The objective of this study was
to firstly determine changes in soil parameters (basic soil properties
and heavy metals) that were assessed from rural land in 1995-2000
and repeated in 2008-2012. The second objective was to determine
differences in soil parameters across various land uses including
native bush, rural (horticulture, pasture and plantation forestry) and
urban land uses using soil data collected in more recent years (2009-
2013).
Across rural land, mean concentrations of Olsen P had
significantly increased in the second sampling period and was
identified as the indicator of most concern, followed by soil
macroporosity, particularly for horticultural and pastoral land. Mean
concentrations of Cd were also greatest for pastoral and horticultural
land and a positive correlation existed between these two parameters,
which highlights the importance of analysing basic soil parameters in
conjunction with heavy metals. In contrast, mean concentrations of
As, Cr, Pb, Ni and Zn were greatest for urban sites. Native bush sites
had the lowest concentrations of heavy metals and were used to
calculate a ‘pollution index’ (PI). The mean PI was classified as high
(PI > 3) for Cd and Ni and moderate for Pb, Zn, Cr, Cu, As and Hg,
indicating high levels of heavy metal pollution across both rural and
urban soils. From a land use perspective, the mean ‘integrated
pollution index’ was highest for urban sites at 2.9 followed by
pasture, horticulture and plantation forests at 2.7, 2.6 and 0.9,
respectively.
It is recommended that soil sampling continues over time because
a longer spanning record will allow further identification of where
soil problems exist and where resources need to be targeted in the
future. Findings from this study will also inform policy and science
direction in regional councils.
Abstract: A Smart Building Controller (SBC) is a server
software that offers secured access to a pool of building specific
resources, executes monitoring tasks and performs automatic
administration of a building, thus optimizing the exploitation cost and
maximizing comfort. This paper brings to discussion the issues that
arise with the secure exploitation of the SBC administered resources
and proposes a technical solution to implement a robust secure access
system based on roles, individual rights and privileges (special
rights).
Abstract: Most people today are aware that global climate
change is not just a scientific theory but also a fact with worldwide
consequences. Global climate change is due to rapid urbanization,
industrialization, high population growth and current vulnerability of
the climatic condition. Water is becoming scarce as a result of global
climate change. To mitigate the problem arising due to global climate
change and its drought effect, harvesting rainwater from green roofs,
an environmentally-friendly and versatile technology, is becoming
one of the best assessment criteria and gaining attention in Malaysia.
This paper addresses the sustainability of green roofs and examines
the quality of water harvested from green roofs in comparison to
rainwater. The factors that affect the quality of such water, taking
into account, for example, roofing materials, climatic conditions, the
frequency of rainfall frequency and the first flush. A green roof was
installed on the Humid Tropic Centre (HTC) is a place of the study
on monitoring program for urban Stormwater Management Manual
for Malaysia (MSMA), Eco-Hydrological Project in Kuala Lumpur,
and the rainwater was harvested and evaluated on the basis of four
parameters i.e., conductivity, dissolved oxygen (DO), pH and
temperature. These parameters were found to fall between Class I and
Class III of the Interim National Water Quality Standards (INWQS)
and the Water Quality Index (WQI). Some preliminary treatment
such as disinfection and filtration could likely to improve the value of
these parameters to class I. This review paper clearly indicates that
there is a need for more research to address other microbiological and
chemical quality parameters to ensure that the harvested water is
suitable for use potable water for domestic purposes. The change in
all physical, chemical and microbiological parameters with respect to
storage time will be a major focus of future studies in this field.
Abstract: The detection of moving objects from a video image
sequences is very important for object tracking, activity recognition,
and behavior understanding in video surveillance.
The most used approach for moving objects detection / tracking is
background subtraction algorithms. Many approaches have been
suggested for background subtraction. But, these are illumination
change sensitive and the solutions proposed to bypass this problem
are time consuming.
In this paper, we propose a robust yet computationally efficient
background subtraction approach and, mainly, focus on the ability to
detect moving objects on dynamic scenes, for possible applications in
complex and restricted access areas monitoring, where moving and
motionless persons must be reliably detected. It consists of three
main phases, establishing illumination changes invariance,
background/foreground modeling and morphological analysis for
noise removing.
We handle illumination changes using Contrast Limited Histogram
Equalization (CLAHE), which limits the intensity of each pixel to
user determined maximum. Thus, it mitigates the degradation due to
scene illumination changes and improves the visibility of the video
signal. Initially, the background and foreground images are extracted
from the video sequence. Then, the background and foreground
images are separately enhanced by applying CLAHE.
In order to form multi-modal backgrounds we model each channel
of a pixel as a mixture of K Gaussians (K=5) using Gaussian Mixture
Model (GMM). Finally, we post process the resulting binary
foreground mask using morphological erosion and dilation
transformations to remove possible noise.
For experimental test, we used a standard dataset to challenge the
efficiency and accuracy of the proposed method on a diverse set of
dynamic scenes.
Abstract: This paper presents powerful techniques for the
development of a new monitoring method based on multi-scale
entropy (MSE) in order to characterize the behaviour of the
concentrations of different gases present in the synthesis of Ammonia
and soft-sensor based on Principal Component Analysis (PCA).
Abstract: The detection of the polymer melt state during
manufacture process is regarded as an efficient way to control the
molded part quality in advance. Online monitoring rheological
property of polymer melt during processing procedure provides an
approach to understand the melt state immediately. Rheological
property reflects the polymer melt state at different processing
parameters and is very important in injection molding process
especially. An approach that demonstrates how to calculate
rheological property of polymer melt through in-process
measurement, using injection molding as an example, is proposed in
this study. The system consists of two sensors and a data acquisition
module can process the measured data, which are used for the
calculation of rheological properties of polymer melt. The rheological
properties of polymer melt discussed in this study include shear rate
and viscosity which are investigated with respect to injection speed
and melt temperature. The results show that the effect of injection
speed on the rheological properties is apparent, especially for high
melt temperature and should be considered for precision molding
process.
Abstract: Operations, maintenance and reliability of wind
turbines have received much attention over the years due to the rapid
expansion of wind farms. This paper explores early fault diagnosis
technique for a 5MW wind turbine system subjected to multiple
faults, where genetic optimization algorithm is employed to make the
residual sensitive to the faults, but robust against disturbances. The
proposed technique has a potential to reduce the downtime mostly
caused by the breakdown of components and exploit the productivity
consistency by providing timely fault alarms. Simulation results show
the effectiveness of the robust fault detection methods used under
Matlab/Simulink/Gatool environment.
Abstract: ESPRIT-TLS method appears a good choice for high
resolution fault detection in induction machines. It has a very high
effectiveness in the frequency and amplitude identification.
Contrariwise, it presents a high computation complexity which
affects its implementation in real time fault diagnosis. To avoid this
problem, a Fast-ESPRIT algorithm that combined the IIR band-pass
filtering technique, the decimation technique and the original
ESPRIT-TLS method was employed to enhance extracting accurately
frequencies and their magnitudes from the wind stator current with
less computation cost. The proposed algorithm has been applied to
verify the wind turbine machine need in the implementation of an online,
fast, and proactive condition monitoring. This type of remote
and periodic maintenance provides an acceptable machine lifetime,
minimize its downtimes and maximize its productivity. The
developed technique has evaluated by computer simulations under
many fault scenarios. Study results prove the performance of Fast-
ESPRIT offering rapid and high resolution harmonics recognizing
with minimum computation time and less memory cost.
Abstract: Remote sensing plays a vital role in mapping of
resources and monitoring of environments of the earth. In the present
research study, mapping and monitoring of clay siltations occurred in
the Alkhod Dam of Muscat, Sultanate of Oman are carried out using
low-cost multispectral Landsat and ASTER data. The dam is
constructed across the Wadi Samail catchment for ground water
recharge. The occurrence and spatial distribution of siltations in the
dam are studied with five years of interval from the year 1987 of
construction to 2014. The deposits are mainly due to the clay, sand
and silt occurrences derived from the weathering rocks of ophiolite
sequences occurred in the Wadi Samail catchment. The occurrences
of clays are confirmed by minerals identification using ASTER
VNIR-SWIR spectral bands and Spectral Angle Mapper supervised
image processing method. The presence of clays and their spatial
distribution are verified in the field. The study recommends the
technique and the low-cost satellite data to similar region of the
world.
Abstract: This paper describes the tradeoffs and the design from
scratch of a self-contained, easy-to-use health dashboard software
system that provides customizable data tracking for patients in smart
homes. The system is made up of different software modules and
comprises a front-end and a back-end component. Built with HTML,
CSS, and JavaScript, the front-end allows adding users, logging into
the system, selecting metrics, and specifying health goals. The backend
consists of a NoSQL Mongo database, a Python script, and a
SimpleHTTPServer written in Python. The database stores user
profiles and health data in JSON format. The Python script makes use
of the PyMongo driver library to query the database and displays
formatted data as a daily snapshot of user health metrics against
target goals. Any number of standard and custom metrics can be
added to the system, and corresponding health data can be fed
automatically, via sensor APIs or manually, as text or picture data
files. A real-time METAR request API permits correlating weather
data with patient health, and an advanced query system is
implemented to allow trend analysis of selected health metrics over
custom time intervals. Available on the GitHub repository system,
the project is free to use for academic purposes of learning and
experimenting, or practical purposes by building on it.
Abstract: In this paper, we propose an intelligent system that is
used for monitoring the health conditions of patients. Monitoring the
health condition of patients is a complex problem that involves
different medical units and requires continuous monitoring especially
in rural areas because of inadequate number of available specialized
physicians. The proposed system will improve patient care and drive
costs down comparing to the existing system in Jordan. The proposed
system will be the start point to faster and improve the
communication between different units in the health system in
Jordan. Connecting patients and their physicians beyond hospital
doors regarding their geographical area is an important issue in
developing the health system in Jordan. The ability of making
medical decisions, the quality of medical is expected to be improved.
Abstract: Macro invertebrates have been used to monitor
organic pollution in rivers and streams. Several biotic indices based
on macro invertebrates have been developed over the years including
the Biological Monitoring Working Party (BMWP). A new biotic
index, the Gammarus:Asellus ratio has been recently proposed as an
index of organic pollution. This study tested the validity of the
Gammarus:Asellus ratio as an index of organic pollution, by
examining the relationship between the Gammarus:Asellus ratio and
physical chemical parameters, and other biotic indices such as
BMWP and, Average Score Per Taxon (ASPT) from lakes and
streams at Markeaton Park, Allestree Park and Kedleston Hall,
Derbyshire. Macro invertebrates were sampled using the standard
five minute kick sampling techniques physical and chemical
environmental variables were obtained based on standard sampling
techniques. Eighteen sites were sampled, six sites from Markeaton
Park (three sites across the stream and three sites across the lake). Six
sites each were also sampled from Allestree Park and Kedleston Hall
lakes. The Gammarus:Asellus ratio showed an opposite significant
positive correlations with parameters indicative of organic pollution
such as the level of nitrates, phosphates, and calcium and also
revealed a negatively significant correlations with other biotic indices
(BMWP/ASPT). The BMWP score correlated positively significantly
with some water quality parameters such as dissolved oxygen and
flow rate, but revealed no correlations with other chemical
environmental variables. The BMWP score was significantly higher
in the stream than the lake in Markeaton Park, also The ASPT scores
appear to be significantly higher in the upper Lakes than the middle
and lower lakes. This study has further strengthened the use of
BMWP/ASPT score as an index of organic pollution. But additional
application is required to validate the use of Gammarus:Asellus as a
rapid bio monitoring tool.
Abstract: As the use of geothermal energy grows internationally
more effort is required to monitor and protect areas with rare and
important geothermal surface features. A number of approaches are
presented for developing and calibrating numerical geothermal
reservoir models that are capable of accurately representing
geothermal surface features. The approaches are discussed in the
context of cases studies of the Rotorua geothermal system and the
Orakei-korako geothermal system, both of which contain important
surface features. The results show that models are able to match the
available field data accurately and hence can be used as valuable
tools for predicting the future response of the systems to changes in
use.
Abstract: Urban areas have been expanded throughout the
globe. Monitoring and modelling urban growth have become a
necessity for a sustainable urban planning and decision making.
Urban prediction models are important tools for analyzing the causes
and consequences of urban land use dynamics. The objective of this
research paper is to analyze and model the urban change, which has
been occurred from 1990 to 2000 using CORINE land cover maps.
The model was developed using drivers of urban changes (such as
road distance, slope, etc.) under an Artificial Neural Network
modelling approach. Validation was achieved using a prediction map
for 2006 which was compared with a real map of Urban Atlas of
2006. The accuracy produced a Kappa index of agreement of 0,639
and a value of Cramer's V of 0,648. These encouraging results
indicate the importance of the developed urban growth prediction
model which using a set of available common biophysical drivers
could serve as a management tool for the assessment of urban
change.
Abstract: Logistics processes of perishable food in the supply
chain include the distribution activities and the real time temperature
monitoring to fulfil the cold chain requirements. The paper presents
the use of RFID (Radio Frequency Identification) technology as an
identification tool of receiving and shipping activities in the cold
store. At the same time, the use of RFID data loggers with
temperature sensors is presented to observe and store the
temperatures for the purpose of analyzing the processes and having
the history data available for traceability purposes and efficient recall
management.