Abstract: In this paper, we present an improved fast and robust
search algorithm for copy detection using histogram-based features for
short MPEG video clips from large video database. There are two
types of histogram features used to generate more robust features. The
first one is based on the adjacent pixel intensity difference quantization
(APIDQ) algorithm, which had been reliably applied to human face
recognition previously. An APIDQ histogram is utilized as the feature
vector of the frame image. Another one is ordinal histogram feature
which is robust to color distortion. Furthermore, by Combining with a
temporal division method, the spatial and temporal features of the
video sequence are integrated to realize fast and robust video search
for copy detection. Experimental results show the proposed algorithm
can detect the similar video clip more accurately and robust than
conventional fast video search algorithm.
Abstract: We present a general comparison of punctual kriging based image restoration for different neighbourhood sizes. The formulation of the technique under consideration is based on punctual kriging and fuzzy concepts for image restoration in spatial domain. Three different neighbourhood windows are considered to estimate the semivariance at different lags for studying its effect in reduction of negative weights resulted in punctual kriging, consequently restoration of degraded images. Our results show that effect of neighbourhood size higher than 5x5 on reduction in negative weights is insignificant. In addition, image quality measures, such as structure similarity indices, peak signal to noise ratios and the new variogram based quality measures; show that 3x3 window size gives better performance as compared with larger window sizes.
Abstract: Multi criteria decision analysis (MDCA) covers both
data and experience. It is very common to solve the problems with
many parameters and uncertainties. GIS supported solutions improve
and speed up the decision process. Weighted grading as a MDCA
method is employed for solving the geotechnical problems. In this
study, geotechnical parameters namely soil type; SPT (N) blow
number, shear wave velocity (Vs) and depth of underground water
level (DUWL) have been engaged in MDCA and GIS. In terms of
geotechnical aspects, the settlement suitability of the municipal area
was analyzed by the method. MDCA results were compatible with
the geotechnical observations and experience. The method can be
employed in geotechnical oriented microzoning studies if the criteria
are well evaluated.
Abstract: In this paper, with the purpose of further reducing the
complexity of the system, while keeping its temporal and spatial
focusing performance, we investigate the possibility of using optimal
one bit time reversal (TR) system for impulse radio ultra wideband
multi-user wireless communications. The results show that, by optimally
selecting the number of used taps in the pre-filter the optimal
one bit TR system can outperform the full one bit TR system. In
some cases, the temporal and spatial focusing performance of the
optimal one bit TR system appears to be compatible with that of the
original TR system. This is a significant result as the overhead cost
is much lower than it is required in the original TR system.
Abstract: This paper proposes an alternative control mechanism
for an interactive Pan/Tilt/Zoom (PTZ) camera control system.
Instead of using a mouse or a joystick, the proposed mechanism
utilizes a Nintendo Wii remote and infrared (IR) sensor bar. The Wii
remote has buttons that allows the user to control the movement of a
PTZ camera through Bluetooth connectivity. In addition, the Wii
remote has a built-in motion sensor that allows the user to give
control signals to the PTZ camera through pitch and roll movement.
A stationary IR sensor bar, placed at some distance away opposite the
Wii remote, enables the detection of yaw movement. In addition, the
Wii remote-s built-in IR camera has the ability to detect its spatial
position, and thus generates a control signal when the user moves the
Wii remote. Some experiments are carried out and their performances
are compared with an industry-standard PTZ joystick.
Abstract: Clustering algorithms are attractive for the task of class identification in spatial databases. However, the application to large spatial databases rises the following requirements for clustering algorithms: minimal requirements of domain knowledge to determine the input parameters, discovery of clusters with arbitrary shape and good efficiency on large databases. The well-known clustering algorithms offer no solution to the combination of these requirements. In this paper, a density based clustering algorithm (DCBRD) is presented, relying on a knowledge acquired from the data by dividing the data space into overlapped regions. The proposed algorithm discovers arbitrary shaped clusters, requires no input parameters and uses the same definitions of DBSCAN algorithm. We performed an experimental evaluation of the effectiveness and efficiency of it, and compared this results with that of DBSCAN. The results of our experiments demonstrate that the proposed algorithm is significantly efficient in discovering clusters of arbitrary shape and size.
Abstract: This paper describes a novel and effective approach to content-based image retrieval (CBIR) that represents each image in the database by a vector of feature values called “Standard deviation of mean vectors of color distribution of rows and columns of images for CBIR". In many areas of commerce, government, academia, and hospitals, large collections of digital images are being created. This paper describes the approach that uses contents as feature vector for retrieval of similar images. There are several classes of features that are used to specify queries: colour, texture, shape, spatial layout. Colour features are often easily obtained directly from the pixel intensities. In this paper feature extraction is done for the texture descriptor that is 'variance' and 'Variance of Variances'. First standard deviation of each row and column mean is calculated for R, G, and B planes. These six values are obtained for one image which acts as a feature vector. Secondly we calculate variance of the row and column of R, G and B planes of an image. Then six standard deviations of these variance sequences are calculated to form a feature vector of dimension six. We applied our approach to a database of 300 BMP images. We have determined the capability of automatic indexing by analyzing image content: color and texture as features and by applying a similarity measure Euclidean distance.
Abstract: Data mining is an extraordinarily demanding field referring to extraction of implicit knowledge and relationships, which are not explicitly stored in databases. A wide variety of methods of data mining have been introduced (classification, characterization, generalization...). Each one of these methods includes more than algorithm. A system of data mining implies different user categories,, which mean that the user-s behavior must be a component of the system. The problem at this level is to know which algorithm of which method to employ for an exploratory end, which one for a decisional end, and how can they collaborate and communicate. Agent paradigm presents a new way of conception and realizing of data mining system. The purpose is to combine different algorithms of data mining to prepare elements for decision-makers, benefiting from the possibilities offered by the multi-agent systems. In this paper the agent framework for data mining is introduced, and its overall architecture and functionality are presented. The validation is made on spatial data. Principal results will be presented.
Abstract: In this paper we present a new approach to detecting a
flaw in T.O.F.D (Time Of Flight Diffraction) type ultrasonic image
based on texture features. Texture is one of the most important
features used in recognizing patterns in an image. The paper
describes texture features based on 2D Gabor functions, i.e.,
Gaussian shaped band-pass filters, with dyadic treatment of the radial
spatial frequency range and multiple orientations, which represent an
appropriate choice for tasks requiring simultaneous measurement in
both space and frequency domains. The most relevant features are
used as input data on a Fuzzy c-mean clustering classifier. The
classes that exist are only two: 'defects' or 'no defects'. The proposed
approach is tested on the T.O.F.D image achieved at the laboratory
and on the industrial field.
Abstract: In the paper a detailed analysis of the dynamic
response of a cooling tower shell to mining tremors originated from
two main regions of mining activity in Poland (Upper Silesian Coal
Basin and Legnica-Glogow Copper District) was presented. The
representative time histories registered in the both regions were used
as ground motion data in calculations of the dynamic response of the
structure. It was proved that the dynamic response of the shell is
strongly dependent not only on the level of vibration amplitudes but
on the dominant frequency range of the mining shock typical for the
mining region as well. Also a vertical component of vibrations
occurred to have considerable influence on the total dynamic
response of the shell. Finally, it turned out that non-uniformity of
kinematic excitation resulting from spatial variety of ground motion
plays a significant role in dynamic analysis of large-dimensional
shells under mining shocks.
Abstract: An epidemiological cross sectional study was
undertaken in Yaoundé in 2002 and updated in 2005. Focused on
health within the city, the objectives were to measure diarrheal
prevalence and to identify the risk factors associated with them.
Results of microbiological examinations have revealed an urban
average prevalence rate of 14.5%. Access to basic services in the
living environment appears to be an important risk factor for
diarrheas. Statistical and spatial analyses conducted have revealed
that prevalence of diarrheal diseases vary among the two main types
of settlement (informal and planned). More importantly, this study
shows that, diarrhea prevalence rates (notably bacterial and parasitic
diarrheas) vary according to the sub- category of settlements. The
study draws a number of theoretical and policy implications for
researchers and policy decision makers.
Abstract: We introduce an effective approach for automatic offline au- thentication of handwritten samples where the forgeries are skillfully done, i.e., the true and forgery sample appearances are almost alike. Subtle details of temporal information used in online verification are not available offline and are also hard to recover robustly. Thus the spatial dynamic information like the pen-tip pressure characteristics are considered, emphasizing on the extraction of low density pixels. The points result from the ballistic rhythm of a genuine signature which a forgery, however skillful that may be, always lacks. Ten effective features, including these low density points and den- sity ratio, are proposed to make the distinction between a true and a forgery sample. An adaptive decision criteria is also derived for better verification judgements.
Abstract: We present in this paper a new approach for specific JPEG steganalysis and propose studying statistics of the compressed DCT coefficients. Traditionally, steganographic algorithms try to preserve statistics of the DCT and of the spatial domain, but they cannot preserve both and also control the alteration of the compressed data. We have noticed a deviation of the entropy of the compressed data after a first embedding. This deviation is greater when the image is a cover medium than when the image is a stego image. To observe this deviation, we pointed out new statistic features and combined them with the Multiple Embedding Method. This approach is motivated by the Avalanche Criterion of the JPEG lossless compression step. This criterion makes possible the design of detectors whose detection rates are independent of the payload. Finally, we designed a Fisher discriminant based classifier for well known steganographic algorithms, Outguess, F5 and Hide and Seek. The experiemental results we obtained show the efficiency of our classifier for these algorithms. Moreover, it is also designed to work with low embedding rates (< 10-5) and according to the avalanche criterion of RLE and Huffman compression step, its efficiency is independent of the quantity of hidden information.
Abstract: This study aims to investigate the gender differences in
spatial navigation using the tasks of 2-D matrix navigation and
recognition of real driving scene. The results can be summarized as
followings. First, female subjects responded faster in 2-D matrix
navigation task than male subjects when landmark instructions were
provided. Second, in recognition task, male subjects recognized the
key elements involved in the past driving scene more accurately than
female subjects. In particular, female subjects tended to miss
peripheral information. These results suggest the possibility of gender
differences in spatial navigation.
Abstract: This paper presents a CFD analysis of the flow around
a 30° inclined flat plate of infinite span. Numerical predictions have
been compared to experimental measurements, in order to assess the
potential of the finite volume code of determining the aerodynamic
forces acting on a flat plate invested by a fluid stream of infinite
extent.
Several turbulence models and spatial node distributions have
been tested and flow field characteristics in the neighborhood of the
flat plate have been numerically investigated, allowing the
development of a preliminary procedure to be used as guidance in
selecting the appropriate grid configuration and the corresponding
turbulence model for the prediction of the flow field over a twodimensional
inclined plate.
Abstract: Does the spatial perspective provide a common thread for rural sociology? Have rural sociologists succeeded in bringing order to their data using spatial analysis models and techniques? A trial answer to such questions, as touchstones of theoretical and applied sociological studies in rural areas, is the point at issue in the present paper. Spatial analyses have changed the way rural sociologists approach scientific problems. Rural sociology is spatial by nature because much, if not most, of its research topics has a spatial “awareness." However, such spatial awareness is not quite the same as spatial analysis because it is not typically associated with underlying theories and hypotheses about spatial patterns that are designed to be tested for their specific spatial content. This paper presents pressing issues for future research to reintroduce mainstream rural sociology to the concept of space.
Abstract: In this paper, we introduce a novel algorithm for object tracking in video sequence. In order to represent the object to be tracked, we propose a spatial color histogram model which encodes both the color distribution and spatial information. The object tracking from frame to frame is accomplished via center voting and back projection method. The center voting method has every pixel in the new frame to cast a vote on whereabouts the object center is. The back projection method segments the object from the background. The segmented foreground provides information on object size and orientation, omitting the need to estimate them separately. We do not put any assumption on camera motion; the proposed algorithm works equally well for object tracking in both static and moving camera videos.
Abstract: In this work we evaluate the possibility of predicting
the emotional state of a person based on the EEG. We investigate
the problem of classifying valence from EEG signals during
the presentation of affective pictures, utilizing the "frontal EEG
asymmetry" phenomenon. To distinguish positive and negative
emotions, we applied the Common Spatial Patterns algorithm.
In contrast to our expectations, the affective pictures did not
reliably elicit changes in frontal asymmetry. The classifying task
thereby becomes very hard as reflected by the poor classifier
performance. We suspect that the masking of the source of the
brain activity related to emotions, coming mostly from deeper
structures in the brain, and the insufficient emotional engagement
are among main reasons why it is difficult to predict the emotional
state of a person.
Abstract: Heat pipes are used to control the thermal problem for
electronic cooling. It is especially difficult to dissipate heat to a heat
sink in an environment in space compared to earth. For solving this
problem, in this study, the Poiseuille (Po) number, which is the main
measure of the performance of a heat pipe, is studied by CFD; then, the
heat pipe performance is verified with experimental results. A heat
pipe is then fabricated for a spatial environment, and an in-house code
is developed. Further, a heat pipe subsystem, which consists of a heat
pipe, MLI (Multi Layer Insulator), SSM (Second Surface Mirror), and
radiator, is tested and correlated with the TMM (Thermal
Mathematical Model) through a commercial code. The correlation
results satisfy the 3K requirement, and the generated thermal model is
verified for application to a spatial environment.
Abstract: Clustering algorithms help to understand the hidden
information present in datasets. A dataset may contain intrinsic and
nested clusters, the detection of which is of utmost importance. This
paper presents a Distributed Grid-based Density Clustering algorithm
capable of identifying arbitrary shaped embedded clusters as well as
multi-density clusters over large spatial datasets. For handling
massive datasets, we implemented our method using a 'sharednothing'
architecture where multiple computers are interconnected
over a network. Experimental results are reported to establish the
superiority of the technique in terms of scale-up, speedup as well as
cluster quality.