Abstract: This study aims at improving the urban hydrological
cycle of the Orléans agglomeration (France) and understanding the
relationship between physical and chemical parameters of urban
surface runoff and the hydrological conditions. In particular water
quality parameters such as pH, conductivity, total dissolved solids,
major dissolved cations and anions, and chemical and biological
oxygen demands were monitored for three types of urban water
discharges (wastewater treatment plant output (WWTP), storm
overflow and stormwater outfall) under two hydrologic scenarios (dry
and wet weather). The first results were obtained over a period of five
months. Each investigated (Ormes, l’Egoutier and La Corne) outfall
represents an urban runoff source that receives water from runoff
roads, gutters, the irrigation of gardens and other sources of flow over
the Earth’s surface that drains in its catchments and carries it to the
Loire River. In wet weather conditions there is rain water runoff and
an additional input from the roof gutters that have entered the
stormwater system during rainfall. For the comparison the results La
Chilesse is a storm overflow that was selected in our study as a
potential source of waste water which is located before the (WWTP). The comparison of the physical-chemical parameters (total
dissolved solids, turbidity, pH, conductivity, dissolved organic
carbon (DOC), concentration of major cations and anions) together
with the chemical oxygen demand (COD) and biological oxygen
demand (BOD) helped to characterize sources of runoff waters in the
different watersheds. It also helped to highlight the infiltration of
wastewater in some stormwater systems that reject directly in the
Loire River. The values of the conductivity measured in the outflow
of Ormes were always higher than those measured in the other two
outlets. The results showed a temporal variation for the Ormes outfall
of conductivity from 1465 μS cm-1 in the dry weather flow to 650 μS
cm-1 in the wet weather flow and also a spatial variation in the wet
weather flow from 650 μS cm-1 in the Ormes outfall to 281 μS cm-1
in L’Egouttier outfall. The ultimate BOD (BOD28) showed a
significant decrease in La Corne outfall from 181 mg L-1 in the wet
weather flow to 95 mg L-1 in the dry weather flow because of the
nutrient load that was transported by the runoff.
Abstract: Heart is the most important part in the body of living
organisms. It affects and is affected by any factor in the body.
Therefore, it is a good detector for all conditions in the body. Heart
signal is a non-stationary signal; thus, it is utmost important to study
the variability of heart signal. The Heart Rate Variability (HRV) has
attracted considerable attention in psychology, medicine and has
become important dependent measure in psychophysiology and
behavioral medicine. The standards of measurements, physiological
interpretation and clinical use for HRV that are most often used were
described in many researcher papers, however, remain complex
issues are fraught with pitfalls. This paper presents one of the nonlinear
techniques to analyze HRV. It discusses many points like, what
Poincaré plot is and how Poincaré plot works; also, Poincaré plot's
merits especially in HRV. Besides, it discusses the limitation of
Poincaré cause of standard deviation SD1, SD2 and how to overcome
this limitation by using complex correlation measure (CCM). The
CCM is most sensitive to changes in temporal structure of the
Poincaré plot as compared toSD1 and SD2.
Abstract: The current tools for real time management of sewer
systems are based on two software tools: the software of weather
forecast and the software of hydraulic simulation. The use of the first
ones is an important cause of imprecision and uncertainty, the use of
the second requires temporal important steps of decision because of
their need in times of calculation. This way of proceeding fact that
the obtained results are generally different from those waited. The major idea of this project is to change the basic paradigm by
approaching the problem by the "automatic" face rather than by that
"hydrology". The objective is to make possible the realization of a
large number of simulations at very short times (a few seconds)
allowing to take place weather forecasts by using directly the real
time meditative pluviometric data. The aim is to reach a system
where the decision-making is realized from reliable data and where
the correction of the error is permanent. A first model of control laws was realized and tested with different
return-period rainfalls. The gains obtained in rejecting volume vary
from 19 to 100 %. The development of a new algorithm was then
used to optimize calculation time and thus to overcome the
subsequent combinatorial problem in our first approach. Finally, this
new algorithm was tested with 16- year-rainfall series. The obtained
gains are 40 % of total volume rejected to the natural environment
and of 65 % in the number of discharges.
Abstract: This research presents the main ideas to implement an
intelligent system composed by communicating wireless sensors
measuring environmental data linked to drought indicators (such as
air temperature, soil moisture , etc...). On the other hand, the setting
up of a spatio temporal database communicating with a Web mapping
application for a monitoring in real time in activity 24:00 /day, 7
days/week is proposed to allow the screening of the drought
parameters time evolution and their extraction. Thus this system
helps detecting surfaces touched by the phenomenon of drought.
Spatio-temporal conceptual models seek to answer the users who
need to manage soil water content for irrigating or fertilizing or other
activities pursuing crop yield augmentation. Effectively, spatiotemporal
conceptual models enable users to obtain a diagram of
readable and easy data to apprehend. Based on socio-economic
information, it helps identifying people impacted by the phenomena
with the corresponding severity especially that this information is
accessible by farmers and stakeholders themselves. The study will be
applied in Siliana watershed Northern Tunisia.
Abstract: Studying on the response of vegetation phenology to
climate change at different temporal and spatial scales is important for
understanding and predicting future terrestrial ecosystem dynamics
and the adaptation of ecosystems to global change. In this study, the
Moderate Resolution Imaging Spectroradiometer (MODIS)
Normalized Difference Vegetation Index (NDVI) dataset and climate
data were used to analyze the dynamics of grassland phenology as well
as their correlation with climatic factors in different eco-geographic
regions and elevation units across the Tibetan Plateau. The results
showed that during 2003–2012, the start of the grassland greening
season (SOS) appeared later while the end of the growing season
(EOS) appeared earlier following the plateau’s precipitation and heat
gradients from southeast to northwest. The multi-year mean value of
SOS showed differences between various eco-geographic regions and
was significantly impacted by average elevation and regional average
precipitation during spring. Regional mean differences for EOS were
mainly regulated by mean temperature during autumn. Changes in
trends of SOS in the central and eastern eco-geographic regions were
coupled to the mean temperature during spring, advancing by about
7d/°C. However, in the two southwestern eco-geographic regions,
SOS was delayed significantly due to the impact of spring
precipitation. The results also showed that the SOS occurred later with
increasing elevation, as expected, with a delay rate of 0.66 d/100m.
For 2003–2012, SOS showed an advancing trend in low-elevation
areas, but a delayed trend in high-elevation areas, while EOS was
delayed in low-elevation areas, but advanced in high-elevation areas.
Grassland SOS and EOS changes may be influenced by a variety of
other environmental factors in each eco-geographic region.
Abstract: Live video streaming is one of the most widely used
service among end users, yet it is a big challenge for the network
operators in terms of quality. The only way to provide excellent
Quality of Experience (QoE) to the end users is continuous
monitoring of live video streaming. For this purpose, there are several
objective algorithms available that monitor the quality of the video in
a live stream. Subjective tests play a very important role in fine
tuning the results of objective algorithms. As human perception is
considered to be the most reliable source for assessing the quality of a
video stream subjective tests are conducted in order to develop more
reliable objective algorithms. Temporal impairments in a live video
stream can have a negative impact on the end users. In this paper we
have conducted subjective evaluation tests on a set of video
sequences containing temporal impairment known as frame freezing.
Frame Freezing is considered as a transmission error as well as a
hardware error which can result in loss of video frames on the
reception side of a transmission system. In our subjective tests, we
have performed tests on videos that contain a single freezing event
and also for videos that contain multiple freezing events. We have
recorded our subjective test results for all the videos in order to give a
comparison on the available No Reference (NR) objective
algorithms. Finally, we have shown the performance of no reference
algorithms used for objective evaluation of videos and suggested the
algorithm that works better. The outcome of this study shows the
importance of QoE and its effect on human perception. The results
for the subjective evaluation can serve the purpose for validating
objective algorithms.
Abstract: Aurèsregion is one of the arid and semi-arid areas that
have suffered climate crises and overexploitation of natural resources
they have led to significant land degradation. The use of remote sensing data allowed us to analyze the land and
its spatiotemporal changes in the Aurès between 1987 and 2013, for
this work, we adopted a method of analysis based on the exploitation
of the images satellite Landsat TM 1987 and Landsat OLI 2013, from
the supervised classification likelihood coupled with field surveys of
the mission of May and September of 2013. Using ENVI EX software by the superposition of the ground cover
maps from 1987 and 2013, one can extract a spatial map change of
different land cover units. The results show that between 1987 and
2013 vegetation has suffered negative changes are the significant
degradation of forests and steppe rangelands, and sandy soils and
bare land recorded a considerable increase. The spatial change map land cover units between 1987 and 2013
allows us to understand the extensive or regressive orientation of
vegetation and soil, this map shows that dense forests give his place
to clear forests and steppe vegetation develops from a degraded forest
vegetation and bare, sandy soils earn big steppe surfaces that explain
its remarkable extension.
The analysis of remote sensing data highlights the profound
changes in our environment over time and quantitative monitoring of
the risk of desertification.
Abstract: In this paper air quality conditions in Makkah and
Leeds are compared. These two cities have totally different climatic
conditions. Makkah climate is characterised as hot and dry (arid)
whereas that of Leeds is characterised as cold and wet (temperate).
This study uses air quality data from 2012 collected in Makkah,
Saudi Arabia and Leeds, UK. The concentrations of all pollutants,
except NO are higher in Makkah. Most notable, the concentrations of
PM10 are much higher in Makkah than in Leeds. This is probably due
to the arid nature of climatic conditions in Makkah and not solely due
to anthropogenic emission sources, otherwise like PM10 some of the
other pollutants, such as CO, NO, and SO2 would have shown much
greater difference between Leeds and Makkah. Correlation analysis is
performed between different pollutants at the same site and the same
pollutants at different sites. In Leeds the correlation between PM10
and other pollutants is significantly stronger than in Makkah. Weaker
correlation in Makkah is probably due to the fact that in Makkah
most of the gaseous pollutants are emitted by combustion processes,
whereas most of the PM10 is generated by other sources, such as
windblown dust, re-suspension, and construction activities. This is in
contrast to Leeds where all pollutants including PM10 are
predominantly emitted by combustions, such as road traffic.
Furthermore, in Leeds frequent rains wash out most of the
atmospheric particulate matter and suppress re-suspension of dust.
Temporal trends of various pollutants are compared and discussed.
This study emphasises the role of climatic conditions in managing air
quality, and hence the need for region-specific controlling strategies
according to the local climatic and meteorological conditions.
Abstract: Background subtraction and temporal difference are
often used for moving object detection in video. Both approaches are
computationally simple and easy to be deployed in real-time image
processing. However, while the background subtraction is highly
sensitive to dynamic background and illumination changes, the
temporal difference approach is poor at extracting relevant pixels of
the moving object and at detecting the stopped or slowly moving
objects in the scene. In this paper, we propose a simple moving object
detection scheme based on adaptive background subtraction and
temporal difference exploiting dynamic background updates. The
proposed technique consists of histogram equalization, a linear
combination of background and temporal difference, followed by the
novel frame-based and pixel-based background updating techniques.
Finally, morphological operations are applied to the output images.
Experimental results show that the proposed algorithm can solve the
drawbacks of both background subtraction and temporal difference
methods and can provide better performance than that of each method.
Abstract: Neural activity in the human brain starts from the
early stages of prenatal development. This activity or signals
generated by the brain are electrical in nature and represent not only
the brain function but also the status of the whole body. At the
present moment, three methods can record functional and
physiological changes within the brain with high temporal resolution
of neuronal interactions at the network level: the
electroencephalogram (EEG), the magnet oencephalogram (MEG),
and functional magnetic resonance imaging (fMRI); each of these has
advantages and shortcomings. EEG recording with a large number of
electrodes is now feasible in clinical practice. Multichannel EEG
recorded from the scalp surface provides very valuable but indirect
information about the source distribution. However, deep electrode
measurements yield more reliable information about the source
locations intracranial recordings and scalp EEG are used with the
source imaging techniques to determine the locations and strengths of
the epileptic activity. As a source localization method, Low
Resolution Electro-Magnetic Tomography (LORETA) is solved for
the realistic geometry based on both forward methods, the Boundary
Element Method (BEM) and the Finite Difference Method (FDM). In
this paper, we review the findings EEG- LORETA about epilepsy.
Abstract: Land Use Land Cover (LULC) changes due to human
activities and natural causes have become a major environmental
concern. Assessment of temporal remote sensing data provides
information about LULC impacts on environment. Land Surface
Temperature (LST) is one of the important components for modeling
environmental changes in climatological, hydrological, and
agricultural studies. In this study, LULC changes (September 7, 1984
and July 8, 2014) especially in agricultural lands together with
population changes (1985-2014) and LST status were investigated
using remotely sensed and census data in South Marmara Watershed,
Turkey. LULC changes were determined using Landsat TM and
Landsat OLI data acquired in 1984 and 2014 summers. Six-band TM
and OLI images were classified using supervised classification
method to prepare LULC map including five classes including Forest
(F), Grazing Land (G), Agricultural Land (A), Water Surface (W),
Residential Area-Bare Soil (R-B) classes. The LST image was also
derived from thermal bands of the same dates.
LULC classification results showed that forest areas, agricultural
lands, water surfaces and residential area-bare soils were increased as
65751 ha, 20163 ha, 1924 ha and 20462 ha respectively. In
comparison, a dramatic decrement occurred in grazing land (107985
ha) within three decades. The population increased 29% between
years 1984-2014 in whole study area. Along with the natural causes,
migration also caused this increase since the study area has an
important employment potential. LULC was transformed among the
classes due to the expansion in residential, commercial and industrial
areas as well as political decisions. In the study, results showed that
agricultural lands around the settlement areas transformed to
residential areas in 30 years.
The LST images showed that mean temperatures were ranged
between 26-32°C in 1984 and 27-33°C in 2014. Minimum
temperature of agricultural lands was increased 3°C and reached to
23°C. In contrast, maximum temperature of A class decreased to
41°C from 44°C. Considering temperatures of the 2014 R-B class and
1984 status of same areas, it was seen that mean, min and max
temperatures increased by 2°C.
As a result, the dynamism of population, LULC and LST resulted
in increasing mean and maximum surface temperatures, living
spaces/industrial areas and agricultural lands.
Abstract: The new era of digital communication has brought up
many challenges that network operators need to overcome. The high
demand of mobile data rates require improved networks, which is a
challenge for the operators in terms of maintaining the quality of
experience (QoE) for their consumers. In live video transmission,
there is a sheer need for live surveillance of the videos in order to
maintain the quality of the network. For this purpose objective
algorithms are employed to monitor the quality of the videos that are
transmitted over a network. In order to test these objective algorithms,
subjective quality assessment of the streamed videos is required, as the
human eye is the best source of perceptual assessment. In this paper we
have conducted subjective evaluation of videos with varying spatial
and temporal impairments. These videos were impaired with frame
freezing distortions so that the impact of frame freezing on the quality
of experience could be studied. We present subjective Mean Opinion
Score (MOS) for these videos that can be used for fine tuning the
objective algorithms for video quality assessment.
Abstract: The main objective of this study was to assess the
annual concentration and seasonal variation of benzo(a)pyrene (BaP)
associated with PM10 in an urban site of Győr and in a rural site of
Sarród in the sampling period of 2008–2012. A total of 280 PM10
aerosol samples were collected in each sampling site and analyzed for
BaP by gas chromatography method. The BaP concentrations ranged
from undetected to 8 ng/m3 with the mean value of 1.01 ng/m3 in the
sampling site of Győr, and from undetected to 4.07 ng/m3 with the
mean value of 0.52 ng/m3 in the sampling site of Sarród, respectively.
Relatively higher concentrations of BaP were detected in samples
collected in both sampling sites in the heating seasons compared with
non-heating periods. The annual mean BaP concentrations were
comparable with the published data of different other Hungarian
sites.
Abstract: This paper presented a study of three algorithms, the
equalization algorithm to equalize the transmission channel with ZF
and MMSE criteria, application of channel Bran A, and adaptive
filtering algorithms LMS and RLS to estimate the parameters of the
equalizer filter, i.e. move to the channel estimation and therefore
reflect the temporal variations of the channel, and reduce the error in
the transmitted signal. So far the performance of the algorithm
equalizer with ZF and MMSE criteria both in the case without noise,
a comparison of performance of the LMS and RLS algorithm.
Abstract: The aim of the current study was to develop and
validate a Response to Stressful Situations Scale (RSSS) for the
Portuguese population. This scale assesses the degree of stress
experienced in scenarios that can constitute positive, negative and
more neutral stressors, and also describes the physiological,
emotional and behavioral reactions to those events according to their
intensity. These scenarios include typical stressor scenarios relevant
to patients with schizophrenia, which are currently absent from most
scales, assessing specific risks that these stressors may bring on
subjects, which may prove useful in non-clinical and clinical
populations (i.e. Patients with mood or anxiety disorders,
schizophrenia). Results from Principal Components Analysis and
Confirmatory Factor Analysis of two adult samples from general
population allowed to confirm a three-factor model with good fit
indices: χ2 (144)= 370.211, p = 0.000; GFI = 0.928; CFI = 0.927; TLI =
0.914, RMSEA = 0.055, P(rmsea ≤0.005) = .096; PCFI = .781.
Further data analysis of the scale revealed that RSSS is an adequate
assessment tool of stress response in adults to be used in further
research and clinical settings, with good psychometric characteristics,
adequate divergent and convergent validity, good temporal stability
and high internal consistency.
Abstract: The concentrations of heavy metals in sediments of
Qua Iboe River Estuary (QIRE) were monitored at four different
sampling locations in wet and dry seasons. A preliminary survey to
determine the four sampling stations along the river continuum
showed that the area spanned between
Abstract: In this paper the problem of the application of
temporal reasoning and case-based reasoning in intelligent decision
support systems is considered. The method of case-based reasoning
with temporal dependences for the solution of problems of real-time
diagnostics and forecasting in intelligent decision support systems is
described. This paper demonstrates how the temporal case-based
reasoning system can be used in intelligent decision support systems
of the car access control. This work was supported by RFBR.
Abstract: In the Hierarchical Temporal Memory (HTM) paradigm
the effect of overlap between inputs on the activation of columns in
the spatial pooler is studied. Numerical results suggest that similar
inputs are represented by similar sets of columns and dissimilar inputs
are represented by dissimilar sets of columns. It is shown that the
spatial pooler produces these results under certain conditions for
the connectivity and proximal thresholds. Following the discussion
of the initialization of parameters for the thresholds, corresponding
qualitative arguments about the learning dynamics of the spatial
pooler are discussed.
Abstract: Theory of Mind (ToM) refers to the ability to infer
another’s mental state. With appropriate ToM, one can behave well in
social interactions. A growing body of evidence has demonstrated that
patients with temporal lobe epilepsy (TLE) may damage ToM by
affecting on regions of the underlying neural network of ToM.
However, the question of whether there is cerebral laterality for ToM
functions remains open. This study aimed to examine whether there is
cerebral lateralization for ToM abilities in TLE patients. Sixty-seven
adult TLE patients and 30 matched healthy controls (HC) were
recruited. Patients were classified into right (RTLE), left (LTLE), and
bilateral (BTLE) TLE groups on the basis of a consensus panel review
of their seizure semiology, EEG findings, and brain imaging results.
All participants completed an intellectual test and four tasks measuring
basic and advanced ToM. The results showed that, on all ToM tasks,
(1) each patient group performed worse than HC; (2) there were no
significant differences between LTLE and RTLE groups; and (3) the
BTLE group performed the worst. It appears that the neural network
responsible for ToM is distributed evenly between the cerebral
hemispheres.
Abstract: Dengue outbreaks are affected by biological,
ecological, socio-economic and demographic factors that vary over
time and space. These factors have been examined separately and still
require systematic clarification. The present study aimed to investigate
the spatial-temporal clustering relationships between these factors and
dengue outbreaks in the northern region of Sri Lanka. Remote sensing
(RS) data gathered from a plurality of satellites were used to develop
an index comprising rainfall, humidity and temperature data. RS data
gathered by ALOS/AVNIR-2 were used to detect urbanization, and a
digital land cover map was used to extract land cover information.
Other data on relevant factors and dengue outbreaks were collected
through institutions and extant databases. The analyzed RS data and
databases were integrated into geographic information systems,
enabling temporal analysis, spatial statistical analysis and space-time
clustering analysis. Our present results showed that increases in the
number of the combination of ecological factor and socio-economic
and demographic factors with above the average or the presence
contribute to significantly high rates of space-time dengue clusters.