Abstract: One of research issues in social network analysis is to
evaluate the position/importance of users in social networks. As the
information diffusion in social network is evolving, it seems difficult
to evaluate the importance of users using traditional approaches. In
this paper, we propose an evaluation approach for user importance
with fractal view in social networks. In this approach, the global importance
(Fractal Importance) and the local importance (Topological
Importance) of nodes are considered. The basic idea is that the bigger
the product of fractal importance and topological importance of a
node is, the more important of the node is. We devise the algorithm
called TFRank corresponding to the proposed approach. Finally, we
evaluate TFRank by experiments. Experimental results demonstrate
our TFRank has the high correlations with PageRank algorithm
and potential ranking algorithm, and it shows the effectiveness and
advantages of our approach.
Abstract: The catalytic dehydroxylation of glycerol to propylene
glycol was investigated over Cu-ZnO/Al2O3 prepared by incipient
wetness impregnation (IWI) method with different purity feedstocks -
refined glycerol and technical grade glycerol. The main purpose is to
investigate the effects of feed impurities that cause the catalyst
deactivation. The prepared catalyst were tested for its catalytic
activity and selectivity in a continuous flow fixed bed reactor at 523
K, 500 psig, H2/feed molar ratio of 4 and WHSV of 3 h-1. The results
showed that conversion of refined glycerol and technical grade
glycerol at time on stream 6 hour are 99% and 71% and selectivity to
propylene glycol are 87% and 56% respectively. The ICP-EOS and
TPO results indicated that the cause of catalyst deactivation was the
amount of impurities in the feedstock. The higher amount of
impurities (especially Na and K) the lower catalytic activity.
Abstract: This paper analyzes the patterns of the Monte Carlo
data for a large number of variables and minterms, in order to
characterize the circuit path length behavior. We propose models
that are determined by training process of shortest path length
derived from a wide range of binary decision diagram (BDD)
simulations. The creation of the model was done use of feed forward
neural network (NN) modeling methodology. Experimental results
for ISCAS benchmark circuits show an RMS error of 0.102 for the
shortest path length complexity estimation predicted by the NN
model (NNM). Use of such a model can help reduce the time
complexity of very large scale integrated (VLSI) circuitries and
related computer-aided design (CAD) tools that use BDDs.
Abstract: A new current-mode multifunction filter using minimum number of passive elements is proposed. The proposed filter has single-input and four high-impedance outputs. It uses four passive elements (two capacitors and two resistors) and four dual output second generation current conveyors. Each output provides a different filter response, namely, low-pass, high-pass, band-pass and band-reject. The sensitivity analysis is also carried out on both ideal and non-ideal filter configurations. The validity of the proposed filter is verified through PSPICE simulations.
Abstract: This paper presents a novel approach for representing
the spatio-temporal topology of the camera network with overlapping
and non-overlapping fields of view (FOVs). The topology is
determined by tracking moving objects and establishing object
correspondence across multiple cameras. To track people successfully
in multiple camera views, we used the Merge-Split (MS) approach for
object occlusion in a single camera and the grid-based approach for
extracting the accurate object feature. In addition, we considered the
appearance of people and the transition time between entry and exit
zones for tracking objects across blind regions of multiple cameras
with non-overlapping FOVs. The main contribution of this paper is to
estimate transition times between various entry and exit zones, and to
graphically represent the camera topology as an undirected weighted
graph using the transition probabilities.
Abstract: One of the main concerns about parallel mechanisms
is the presence of singular points within their workspaces. In singular
positions the mechanism gains or loses one or several degrees of
freedom. It is impossible to control the mechanism in singular
positions. Therefore, these positions have to be avoided. This is a
vital need especially in computer controlled machine tools designed
and manufactured on the basis of parallel mechanisms. This need has
to be taken into consideration when selecting design parameters. A
prerequisite to this is a thorough knowledge about the effect of
design parameters and constraints on singularity. In this paper,
quality condition index was introduced as a criterion for evaluating
singularities of different configurations of a hexapod mechanism
obtainable by different design parameters. It was illustrated that this
method can effectively be employed to obtain the optimum
configuration of hexapod mechanism with the aim of avoiding
singularity within the workspace. This method was then employed to
design the hexapod table of a CNC milling machine.
Abstract: This study presents a blower for air management system of fuel cell modules. A blower is composed of BLDC motor and impeller. Magnetic equivalent circuit model and finite element analysis are used to design the motor, and an improved structure is considered to reduce a mechanical loss induced from bearing units. Finally, air blower system combined with the motor and an impeller is manufactured and output properties, such as an air pressure and an amount of flowing air, are measured. Through the experimental results, a validity of the simulated one is confirmed.
Abstract: This paper applies fuzzy clustering algorithm in classifying real estate companies in China according to some general financial indexes, such as income per share, share accumulation fund, net profit margins, weighted net assets yield and shareholders' equity. By constructing and normalizing initial partition matrix, getting fuzzy similar matrix with Minkowski metric and gaining the transitive closure, the dynamic fuzzy clustering analysis for real estate companies is shown clearly that different clustered result change gradually with the threshold reducing, and then, it-s shown there is the similar relationship with the prices of those companies in stock market. In this way, it-s great valuable in contrasting the real estate companies- financial condition in order to grasp some good chances of investment, and so on.
Abstract: Wireless sensor network is formed with the combination of sensor nodes and sink nodes. Recently Wireless sensor network has attracted attention of the research community. The main application of wireless sensor network is security from different attacks both for mass public and military. However securing these networks, by itself is a critical issue due to many constraints like limited energy, computational power and lower memory. Researchers working in this area have proposed a number of security techniques for this purpose. Still, more work needs to be done.In this paper we provide a detailed discussion on security in wireless sensor networks. This paper will help to identify different obstacles and requirements for security of wireless sensor networks as well as highlight weaknesses of existing techniques.
Abstract: We propose a novel graphical technique (SVision) for
intrusion detection, which pictures the network as a community of
hosts independently roaming in a 3D space defined by the set of
services that they use. The aim of SVision is to graphically cluster
the hosts into normal and abnormal ones, highlighting only the ones
that are considered as a threat to the network. Our experimental
results using DARPA 1999 and 2000 intrusion detection and
evaluation datasets show the proposed technique as a good candidate
for the detection of various threats of the network such as vertical
and horizontal scanning, Denial of Service (DoS), and Distributed
DoS (DDoS) attacks.
Abstract: Recently, as the scale of construction projects has
increases, more ground excavation for foundations is carried out than ever before. Consequently, damage to underground ducts (gas, water/sewage or oil pipelines, communication cables or power cable ducts) or superannuated pipelines frequently cause serious accidents
resulting in damage to life and property. (In Korea, the total length of city water pipelines was approximately 2,000 km as of the end of 2009.) In addition, large amounts of damage caused by fractures, water
and gas leakage caused by superannuation or damage to underground
ducts in construction has been reported. Therefore, a system is required to precisely detect defects and deterioration in underground
pipelines and the locations of such defects, for timely and accurate
maintenance or replacement of the ducts. In this study, a system was
developed which can locate underground structures (gas and water
pipelines, power cable ducts, etc.) in 3D-coordinates and monitor the
degree and position of defects using an Inertial Measurement Unit
(IMU) sensing technique. The system can prevent damage to underground ducts and superannuated pipelines during construction,
and provide reliable data for maintenance. The utility of the IMU sensing technique used in aircraft and ships in civil applications was
verified.
Abstract: Retinal vascularity assessment plays an important role in diagnosis of ophthalmic pathologies. The employment of digital images for this purpose makes possible a computerized approach and has motivated development of many methods for automated vascular tree segmentation. Metrics based on contingency tables for binary classification have been widely used for evaluating performance of these algorithms and, concretely, the accuracy has been mostly used as measure of global performance in this topic. However, this metric shows very poor matching with human perception as well as other notable deficiencies. Here, a new similarity function for measuring quality of retinal vessel segmentations is proposed. This similarity function is based on characterizing the vascular tree as a connected structure with a measurable area and length. Tests made indicate that this new approach shows better behaviour than the current one does. Generalizing, this concept of measuring descriptive properties may be used for designing functions for measuring more successfully segmentation quality of other complex structures.
Abstract: Fly ash is one of the residues generated in
combustion, and comprises the fine particles that rise with the flue
gases. Ash which does not rise is termed bottom ash [1]. In our
country, it is expected that will be occurred 50 million tons of waste
ash per year until 2020. Released waste from the thermal power
plants is caused very significant problems as known. The fly ashes
can be evaluated by using as adsorbent material.
The purpose of this study is to investigate the possibility of use of
Tuncbilek fly ash like low-cost adsorbents for heavy metal
adsorption. First of all, Tuncbilek fly ash was characterized. For this
purpose; analysis such as sieve analysis, XRD, XRF, SEM and FT-IR
were performed.
Abstract: In this study, the kinetics of osmotic dehydration of melons (Tille variety) in a ternary system followed by air-drying for preserving melons in the summer to be used in the winter were investigated. The effect of different osmotic solution concentrations 30, 40 and 50% (w/w) of sucrose with 10% NaCl salt and fruit to solution ratios 1:4, 1:5 and 1:6 on the mass transfer kinetics during osmotic dehydration of melon in ternary solution namely sucrosesalt- water followed by air-drying were studied. The diffusivity of water during air-drying was enhanced after the fruit samples were immersed in the osmotic solution after 60 min. Samples non-treated and pre-treated during one hour in osmotic solutions with 60% (w/w) of sucrose with 10% NaCl salt and fruit to solution ratio of 1:4 were dried in a hot air-dryer at 60oC (2 m/s) until equilibrium was achieved.
Abstract: Image interpolation is a common problem in imaging applications. However, most interpolation algorithms in existence suffer visually the effects of blurred edges and jagged artifacts in the image to some extent. This paper presents an adaptive feature preserving bidirectional flow process, where an inverse diffusion is performed to sharpen edges along the normal directions to the isophote lines (edges), while a normal diffusion is done to remove artifacts (“jaggies") along the tangent directions. In order to preserve image features such as edges, corners and textures, the nonlinear diffusion coefficients are locally adjusted according to the directional derivatives of the image. Experimental results on synthetic images and nature images demonstrate that our interpolation algorithm substantially improves the subjective quality of the interpolated images over conventional interpolations.
Abstract: An embedded system for SEU(single event upset) test
needs to be designed to prevent system failure by high-energy particles
during measuring SEU. SEU is a phenomenon in which the data is changed temporary in semiconductor device caused by high-energy particles. In this paper, we present an embedded system for
SRAM(static random access memory) SEU test. SRAMs are on the DUT(device under test) and it is separated from control board which
manages the DUT and measures the occurrence of SEU. It needs to
have considerations for preventing system failure while managing the
DUT and making an accurate measurement of SEUs. We measure the occurrence of SEUs from five different SRAMs at three different
cyclotron beam energies 30, 35, and 40MeV. The number of SEUs of SRAMs ranges from 3.75 to 261.00 in average.
Abstract: In text categorization problem the most used method
for documents representation is based on words frequency vectors
called VSM (Vector Space Model). This representation is based only
on words from documents and in this case loses any “word context"
information found in the document. In this article we make a
comparison between the classical method of document representation
and a method called Suffix Tree Document Model (STDM) that is
based on representing documents in the Suffix Tree format. For the
STDM model we proposed a new approach for documents
representation and a new formula for computing the similarity
between two documents. Thus we propose to build the suffix tree
only for any two documents at a time. This approach is faster, it has
lower memory consumption and use entire document representation
without using methods for disposing nodes. Also for this method is
proposed a formula for computing the similarity between documents,
which improves substantially the clustering quality. This
representation method was validated using HAC - Hierarchical
Agglomerative Clustering. In this context we experiment also the
stemming influence in the document preprocessing step and highlight
the difference between similarity or dissimilarity measures to find
“closer" documents.
Abstract: The intent of this essay is to evaluate the effectiveness
of surge suppressor aimed at power supply used for automation
devices in power distribution system which is consist of MOV and
T type low-pass filter. Books, journal articles and e-sources related
to surge protection of power supply used for automation devices in
power distribution system were consulted, and the useful information
was organized, analyzed and developed into five parts: characteristics
of surge wave, protection against surge wave, impedance characteristics
of target, using Matlab to simulate circuit response after
5kV,1.2/50s surge wave and suggestions for surge protection. The
results indicate that various types of load situation have great impact
on the effectiveness of surge protective device. Therefore, type and
parameters of surge protective device need to be carefully selected,
and load matching is also vital to be concerned.
Abstract: The use of polypropylene mesh devices for Pelvic
Organ Prolapse (POP) spread rapidly during the last decade, yet our
knowledge of the mesh-tissue interaction is far from complete. We
aimed to perform a thorough pathological examination of explanted
POP meshes and describe findings that may explain mechanisms of
complications resulting in product excision. We report a spectrum of
important findings, including nerve ingrowth, mesh deformation,
involvement of detrusor muscle with neural ganglia, and
polypropylene degradation. Analysis of these findings may improve
and guide future treatment strategies.
Abstract: In this paper we present an autoregressive model with
neural networks modeling and standard error backpropagation
algorithm training optimization in order to predict the gross domestic
product (GDP) growth rate of four countries. Specifically we propose
a kind of weighted regression, which can be used for econometric
purposes, where the initial inputs are multiplied by the neural
networks final optimum weights from input-hidden layer after the
training process. The forecasts are compared with those of the
ordinary autoregressive model and we conclude that the proposed
regression-s forecasting results outperform significant those of
autoregressive model in the out-of-sample period. The idea behind
this approach is to propose a parametric regression with weighted
variables in order to test for the statistical significance and the
magnitude of the estimated autoregressive coefficients and
simultaneously to estimate the forecasts.