Abstract: Terminal localization for indoor Wireless Local Area
Networks (WLANs) is critical for the deployment of location-aware
computing inside of buildings. A major challenge is obtaining high
localization accuracy in presence of fluctuations of the received signal
strength (RSS) measurements caused by multipath fading. This paper
focuses on reducing the effect of the distance-varying noise by spatial
filtering of the measured RSS. Two different survey point geometries
are tested with the noise reduction technique: survey points arranged
in sets of clusters and survey points uniformly distributed over the
network area. The results show that the location accuracy improves
by 16% when the filter is used and by 18% when the filter is applied
to a clustered survey set as opposed to a straight-line survey set.
The estimated locations are within 2 m of the true location, which
indicates that clustering the survey points provides better localization
accuracy due to superior noise removal.
Abstract: This paper presents a low cost automatic system for
sampling the electric field in a limited area. The scanning area is a
flat surface parallel to the ground at a selected height. We discuss
in detail the hardware, software and all the arrangements involved
in the system operation. In order to show the system performance
we include a campaign of narrow band measurements with 6017
sample points in the surroundings of a cellular base station. A
commercial isotropic antenna with three orthogonal axes was used
as sampling device. The results are analyzed in terms of its space
average, standard deviation and statistical distribution.
Abstract: In recent years, many researches to mine the exploding Web world, especially User Generated Content (UGC) such as
weblogs, for knowledge about various phenomena and events in the physical world have been done actively, and also Web services
with the Web-mined knowledge have begun to be developed for
the public. However, there are few detailed investigations on how accurately Web-mined data reflect physical-world data. It must be
problematic to idolatrously utilize the Web-mined data in public Web services without ensuring their accuracy sufficiently. Therefore,
this paper introduces the simplest Web Sensor and spatiotemporallynormalized
Web Sensor to extract spatiotemporal data about a target
phenomenon from weblogs searched by keyword(s) representing the
target phenomenon, and tries to validate the potential and reliability of the Web-sensed spatiotemporal data by four kinds of granularity
analyses of coefficient correlation with temperature, rainfall, snowfall,
and earthquake statistics per day by region of Japan Meteorological
Agency as physical-world data: spatial granularity (region-s population
density), temporal granularity (time period, e.g., per day vs. per week), representation granularity (e.g., “rain" vs. “heavy rain"), and
media granularity (weblogs vs. microblogs such as Tweets).
Abstract: In this work, we analyze the deformation of surface
waves in shallow flows conditions, propagating in a channel of
slowly varying cross-section. Based on a singular perturbation
technique, the main purpose is to predict the motion of waves by
using a dimensionless formulation of the governing equations,
considering that the longitudinal variation of the transversal section
obey a power-law distribution. We show that the spatial distribution
of the waves in the varying cross-section is a function of a kinematic
parameter,κ , and two geometrical parameters εh
and w ε . The above
spatial behavior of the surface elevation is modeled by an ordinary
differential equation. The use of single formulas to model the varying
cross sections or transitions considered in this work can be a useful
approximation to natural or artificial geometrical configurations.
Abstract: The shortest path (SP) problem concerns with finding the shortest path from a specific origin to a specified destination in a given network while minimizing the total cost associated with the path. This problem has widespread applications. Important applications of the SP problem include vehicle routing in transportation systems particularly in the field of in-vehicle Route Guidance System (RGS) and traffic assignment problem (in transportation planning). Well known applications of evolutionary methods like Genetic Algorithms (GA), Ant Colony Optimization, Particle Swarm Optimization (PSO) have come up to solve complex optimization problems to overcome the shortcomings of existing shortest path analysis methods. It has been reported by various researchers that PSO performs better than other evolutionary optimization algorithms in terms of success rate and solution quality. Further Geographic Information Systems (GIS) have emerged as key information systems for geospatial data analysis and visualization. This research paper is focused towards the application of PSO for solving the shortest path problem between multiple points of interest (POI) based on spatial data of Allahabad City and traffic speed data collected using GPS. Geovisualization of results of analysis is carried out in GIS.
Abstract: Bones are dynamic and responsive organs, they
regulate their strength and mass according to the loads which they are subjected. Because, the Wnt/β-catenin pathway has profound
effects on the regulation of bone mass, we hypothesized that mechanical loading of bone cells stimulates Wnt/β-catenin signaling, which results in the generation of new bone mass.
Mechanical loading triggers the secretion of the Wnt molecule, which after binding to transmembrane proteins, causes GSK-3β (Glycogen synthase kinase 3 beta) to cease the phosphorylation of β-catenin. β-catenin accumulation in the cytoplasm, followed by its
transport into the nucleus, binding to transcription factors (TCF/LEF)
that initiate transcription of genes related to bone formation. To test this hypothesis, we used TOPGAL (Tcf Optimal Promoter
β-galactosidase) mice in an experiment in which cyclic loads were
applied to the forearm. TOPGAL mice are reporters for cells effected
by the Wnt/β-catenin signaling pathway. TOPGAL mice are genetically engineered mice in which transcriptional activation of β-
catenin, results in the production of an enzyme, β-galactosidase. The
presence of this enzyme allows us to localize transcriptional
activation of β-catenin to individual cells, thereby, allowing us to quantify the effects that mechanical loading has on the Wnt/β-catenin pathway and new bone formation. The ulnae of loaded TOPGAL
mice were excised and transverse slices along different parts of the
ulnar shaft were assayed for the presence of β-galactosidase.
Our results indicate that loading increases β-catenin transcriptional
activity in regions where this pathway is already primed (i.e. where basal activity is already higher) in a load magnitude dependent
manner. Further experiments are needed to determine the temporal and spatial activation of this signaling in relation to bone formation.
Abstract: Crime is a major societal problem for most of the
world's nations. Consequently, the police need to develop new
methods to improve their efficiency in dealing with these ever increasing crime rates. Two of the common difficulties that the police
face in crime control are crime investigation and the provision of crime information to the general public to help them protect themselves. Crime control in police operations involves the use of
spatial data, crime data and the related crime data from different organizations (depending on the nature of the analysis to be made).
These types of data are collected from several heterogeneous sources
in different formats and from different platforms, resulting in a lack of standardization. Moreover, there is no standard framework for
crime data collection, integration and dissemination through mobile
devices. An investigation into the current situation in crime control was carried out to identify the needs to resolve these issues. This
paper proposes and investigates the use of service oriented
architecture (SOA) and the mobile spatial information service in crime control. SOA plays an important role in crime control as an
appropriate way to support data exchange and model sharing from
heterogeneous sources. Crime control also needs to facilitate mobile
spatial information services in order to exchange, receive, share and release information based on location to mobile users anytime and
anywhere.
Abstract: Role of acoustic driving pressure on the
translational-radial dynamics of a moving single bubble
sonoluminescence (m-SBSL) has been numerically
investigated. The results indicate that increase in the
amplitude of the driving pressure leads to increase in the
bubble peak temperature. The length and the shape of the
trajectory of the bubble depends on the acoustic pressure and
because of the spatially dependence of the radial dynamics of
the moving bubble, its peak temperature varies during the
acoustical pulses. The results are in good agreement with the
experimental reports on m-SBSL.
Abstract: The study of tourist activities and the mapping of their routes in space and time has become an important issue in tourism management. Here we represent space-time paths for the tourism industry by visualizing individual tourist activities and the paths followed using a 3D Geographic Information System (GIS). Considerable attention has been devoted to the measurement of accessibility to shopping, eating, walking and other services at the tourist destination. I turns out that GIS is a useful tool for studying the spatial behaviors of tourists in the area. The value of GIS is especially advantageous for space-time potential path area measures, especially for the accurate visualization of possible paths through existing city road networks. This study seeks to apply space-time concepts with a detailed street network map obtained from Google Maps to measure tourist paths both spatially and temporally. These paths are further determined based on data obtained from map questionnaires regarding the trip activities of 40 individuals. The analysis of the data makes it possible to determining the locations of the more popular paths. The results can be visualized using 3D GIS to show the areas and potential activity opportunities accessible to tourists during their travel time.
Abstract: Dengue disease is an infectious vector-borne viral
disease that is commonly found in tropical and sub-tropical regions,
especially in urban and semi-urban areas, around the world and
including Malaysia. There is no currently available vaccine or
chemotherapy for the prevention or treatment of dengue disease.
Therefore prevention and treatment of the disease depend on vector
surveillance and control measures. Disease risk mapping has been
recognized as an important tool in the prevention and control
strategies for diseases. The choice of statistical model used for
relative risk estimation is important as a good model will
subsequently produce a good disease risk map. Therefore, the aim of
this study is to estimate the relative risk for dengue disease based
initially on the most common statistic used in disease mapping called
Standardized Morbidity Ratio (SMR) and one of the earliest
applications of Bayesian methodology called Poisson-gamma model.
This paper begins by providing a review of the SMR method, which
we then apply to dengue data of Perak, Malaysia. We then fit an
extension of the SMR method, which is the Poisson-gamma model.
Both results are displayed and compared using graph, tables and
maps. Results of the analysis shows that the latter method gives a
better relative risk estimates compared with using the SMR. The
Poisson-gamma model has been demonstrated can overcome the
problem of SMR when there is no observed dengue cases in certain
regions. However, covariate adjustment in this model is difficult and
there is no possibility for allowing spatial correlation between risks in
adjacent areas. The drawbacks of this model have motivated many
researchers to propose other alternative methods for estimating the
risk.
Abstract: Cameron Highlands is a mountainous area subjected
to torrential tropical showers. It extracts 5.8 million liters of water
per day for drinking supply from its rivers at several intake points.
The water quality of rivers in Cameron Highlands, however, has
deteriorated significantly due to land clearing for agriculture,
excessive usage of pesticides and fertilizers as well as construction
activities in rapidly developing urban areas. On the other hand, these
pollution sources known as non-point pollution sources are diverse
and hard to identify and therefore they are difficult to estimate.
Hence, Geographical Information Systems (GIS) was used to provide
an extensive approach to evaluate landuse and other mapping
characteristics to explain the spatial distribution of non-point sources
of contamination in Cameron Highlands. The method to assess
pollution sources has been developed by using Cameron Highlands
Master Plan (2006-2010) for integrating GIS, databases, as well as
pollution loads in the area of study. The results show highest annual
runoff is created by forest, 3.56 × 108 m3/yr followed by urban
development, 1.46 × 108 m3/yr. Furthermore, urban development
causes highest BOD load (1.31 × 106 kgBOD/yr) while agricultural
activities and forest contribute the highest annual loads for
phosphorus (6.91 × 104 kgP/yr) and nitrogen (2.50 × 105 kgN/yr),
respectively. Therefore, best management practices (BMPs) are
suggested to be applied to reduce pollution level in the area.
Abstract: This paper investigates the spatial structure of employment in the Jakarta Metropolitan Area (JMA), with reference to the concept of the Southeast Asian extended metropolitan region (EMR). A combination of factor analysis and local Getis-Ord (Gi*) hot-spot analysis is used to identify clusters of employment in the region, including those of the urban and agriculture sectors. Spatial statistical analysis is further used to probe the spatial association of identified employment clusters with their surroundings on several dimensions, including the spatial association between the central business district (CBD) in Jakarta city on employment density in the region, the spatial impacts of urban expansion on population growth and the degree of urban-rural interaction. The degree of spatial interaction for the whole JMA is measured by the patterns of commuting trips destined to the various employment clusters. Results reveal the strong role of the urban core of Jakarta, and the regional CBD, as the centre for mixed job sectors such as retail, wholesale, services and finance. Manufacturing and local government services, on the other hand, form corridors radiating out of the urban core, reaching out to the agriculture zones in the fringes. Strong associations between the urban expansion corridors and population growth, and urban-rural mix, are revealed particularly in the eastern and western parts of JMA. Metropolitan wide commuting patterns are focussed on the urban core of Jakarta and the CBD, while relatively local commuting patterns are shown to be prevalent for the employment corridors.
Abstract: Fourier transform infrared (FT-IR) spectroscopic imaging
is an emerging technique that provides both chemically and
spatially resolved information. The rich chemical content of data
may be utilized for computer-aided determinations of structure and
pathologic state (cancer diagnosis) in histological tissue sections for
prostate cancer. FT-IR spectroscopic imaging of prostate tissue has
shown that tissue type (histological) classification can be performed to
a high degree of accuracy [1] and cancer diagnosis can be performed
with an accuracy of about 80% [2] on a microscopic (≈ 6μm)
length scale. In performing these analyses, it has been observed
that there is large variability (more than 60%) between spectra from
different points on tissue that is expected to consist of the same
essential chemical constituents. Spectra at the edges of tissues are
characteristically and consistently different from chemically similar
tissue in the middle of the same sample. Here, we explain these
differences using a rigorous electromagnetic model for light-sample
interaction. Spectra from FT-IR spectroscopic imaging of chemically
heterogeneous samples are different from bulk spectra of individual
chemical constituents of the sample. This is because spectra not
only depend on chemistry, but also on the shape of the sample.
Using coupled wave analysis, we characterize and quantify the nature
of spectral distortions at the edges of tissues. Furthermore, we
present a method of performing histological classification of tissue
samples. Since the mid-infrared spectrum is typically assumed to
be a quantitative measure of chemical composition, classification
results can vary widely due to spectral distortions. However, we
demonstrate that the selection of localized metrics based on chemical
information can make our data robust to the spectral distortions
caused by scattering at the tissue boundary.
Abstract: Spatial trends are one of the valuable patterns in geo
databases. They play an important role in data analysis and
knowledge discovery from spatial data. A spatial trend is a regular
change of one or more non spatial attributes when spatially moving
away from a start object. Spatial trend detection is a graph search
problem therefore heuristic methods can be good solution. Artificial
immune system (AIS) is a special method for searching and
optimizing. AIS is a novel evolutionary paradigm inspired by the
biological immune system. The models based on immune system
principles, such as the clonal selection theory, the immune network
model or the negative selection algorithm, have been finding
increasing applications in fields of science and engineering.
In this paper, we develop a novel immunological algorithm based
on clonal selection algorithm (CSA) for spatial trend detection. We
are created neighborhood graph and neighborhood path, then select
spatial trends that their affinity is high for antibody. In an
evolutionary process with artificial immune algorithm, affinity of
low trends is increased with mutation until stop condition is satisfied.
Abstract: A general stochastic spatial MIMO channel model is
proposed for evaluating various MIMO techniques in this paper. It can
generate MIMO channels complying with various MIMO
configurations such as smart antenna, spatial diversity and spatial
multiplexing. The modeling method produces the stochastic fading
involving delay spread, Doppler spread, DOA (direction of arrival),
AS (angle spread), PAS (power azimuth Spectrum) of the scatterers,
antenna spacing and the wavelength. It can be applied in various
MIMO technique researches flexibly with low computing complexity.
Abstract: A systems approach model for prostate cancer in prostate duct, as a sub-system of the organism is developed. It is accomplished in two steps. First this research work starts with a nonlinear system of coupled Fokker-Plank equations which models continuous process of the system like motion of cells. Then extended to PDEs that include discontinuous processes like cell mutations, proliferation and deaths. The discontinuous processes is modeled by using intensity poisson processes. The model incorporates the features of the prostate duct. The system of PDEs spatial coordinate is along the proximal distal axis. Its parameters depend on features of the prostate duct. The movement of cells is biased towards distal region and mutations of prostate cancer cells is localized in the proximal region. Numerical solutions of the full system of equations are provided, and are exhibit traveling wave fronts phenomena. This motivates the use of the standard transformation to derive a canonically related system of ODEs for traveling wave solutions. The results obtained show persistence of prostate cancer by showing that the non-negative cone for the traveling wave system is time invariant. The traveling waves have a unique global attractor is proved also. Biologically, the global attractor verifies that evolution of prostate cancer stem cells exhibit the avascular tumor growth. These numerical solutions show that altering prostate stem cell movement or mutation of prostate cancer cells lead to avascular tumor. Conclusion with comments on clinical implications of the model is discussed.
Abstract: We present a new method to reconstruct a temporally
coherent 3D animation from single or multi-view RGB-D video data
using unbiased feature point sampling. Given RGB-D video data, in
form of a 3D point cloud sequence, our method first extracts feature
points using both color and depth information. In the subsequent
steps, these feature points are used to match two 3D point clouds in
consecutive frames independent of their resolution. Our new motion
vectors based dynamic alignement method then fully reconstruct
a spatio-temporally coherent 3D animation. We perform extensive
quantitative validation using novel error functions to analyze the
results. We show that despite the limiting factors of temporal and
spatial noise associated to RGB-D data, it is possible to extract
temporal coherence to faithfully reconstruct a temporally coherent
3D animation from RGB-D video data.
Abstract: Today we tend to go back to the past to our root
relation to nature. Therefore in search of friendly spaces there are
elements of natural environment introduced as elements of spatial
composition. Though reinvented through the use of the new
substance such as greenery, water etc. made possible by state of the
art technologies, still, in principal, they remain the same. As a result,
sustainable design, based upon the recognized means of composition
in addition to the relation of architecture and urbanism vs. nature
introduces a new aesthetical values into architectural and urban
space.
Abstract: Phase-Contrast MR imaging methods are widely used
for measurement of blood flow velocity components. Also there are
some other tools such as CT and Ultrasound for velocity map
detection in intravascular studies. These data are used in deriving
flow characteristics. Some clinical applications are investigated
which use pressure distribution in diagnosis of intravascular disorders
such as vascular stenosis. In this paper an approach to the problem of
measurement of intravascular pressure field by using velocity field
obtained from flow images is proposed. The method presented in this
paper uses an algorithm to calculate nonlinear equations of Navier-
Stokes, assuming blood as an incompressible and Newtonian fluid.
Flow images usually suffer the lack of spatial resolution. Our
attempt is to consider the effect of spatial resolution on the pressure
distribution estimated from this method. In order to achieve this aim,
velocity map of a numerical phantom is derived at six different
spatial resolutions. To determine the effects of vascular stenoses on
pressure distribution, a stenotic phantom geometry is considered. A
comparison between the pressure distribution obtained from the
phantom and the pressure resulted from the algorithm is presented. In
this regard we also compared the effects of collocated and staggered
computational grids on the pressure distribution resulted from this
algorithm.
Abstract: Soil chemical and physical properties have important
roles in compartment of the environment and agricultural
sustainability and human health. The objectives of this research is
determination of spatial distribution patterns of Cd, Zn, K, pH, TNV,
organic material and electrical conductivity (EC) in agricultural soils
of Natanz region in Esfehan province. In this study geostatistic and
non-geostatistic methods were used for prediction of spatial
distribution of these parameters. 64 composite soils samples were
taken at 0-20 cm depth. The study area is located in south of
NATANZ agricultural lands with area of 21660 hectares. Spatial
distribution of Cd, Zn, K, pH, TNV, organic material and electrical
conductivity (EC) was determined using geostatistic and geographic
information system. Results showed that Cd, pH, TNV and K data
has normal distribution and Zn, OC and EC data had not normal
distribution. Kriging, Inverse Distance Weighting (IDW), Local
Polynomial Interpolation (LPI) and Redial Basis functions (RBF)
methods were used to interpolation. Trend analysis showed that
organic carbon in north-south and east to west did not have trend
while K and TNV had second degree trend. We used some error
measurements include, mean absolute error(MAE), mean squared
error (MSE) and mean biased error(MBE). Ordinary
kriging(exponential model), LPI(Local polynomial interpolation),
RBF(radial basis functions) and IDW methods have been chosen as
the best methods to interpolating of the soil parameters. Prediction
maps by disjunctive kriging was shown that in whole study area was
intensive shortage of organic matter and more than 63.4 percent of
study area had shortage of K amount.