Abstract: The nanoindentation behaviour and phase
transformation of annealed single-crystal silicon wafers are examined.
The silicon specimens are annealed at temperatures of 250, 350 and
450ºC, respectively, for 15 minutes and are then indented to maximum
loads of 30, 50 and 70 mN. The phase changes induced in the indented
specimens are observed using transmission electron microscopy
(TEM) and micro-Raman scattering spectroscopy (RSS). For all
annealing temperatures, an elbow feature is observed in the unloading
curve following indentation to a maximum load of 30 mN. Under
higher loads of 50 mN and 70 mN, respectively, the elbow feature is
replaced by a pop-out event. The elbow feature reveals a complete
amorphous phase transformation within the indented zone, whereas
the pop-out event indicates the formation of Si XII and Si III phases.
The experimental results show that the formation of these crystalline
silicon phases increases with an increasing annealing temperature and
indentation load. The hardness and Young’s modulus both decrease as
the annealing temperature and indentation load are increased.
Abstract: Mammography is widely used technique for breast cancer
screening. There are various other techniques for breast cancer screening
but mammography is the most reliable and effective technique. The
images obtained through mammography are of low contrast which
causes problem for the radiologists to interpret. Hence, a high quality
image is mandatory for the processing of the image for extracting any
kind of information from it. Many contrast enhancement algorithms have
been developed over the years. In the present work, an efficient
morphology based technique is proposed for contrast enhancement of
masses in mammographic images. The proposed method is based on
Multiscale Morphology and it takes into consideration the scale of the
structuring element. The proposed method is compared with other stateof-
the-art techniques. The experimental results show that the proposed
method is better both qualitatively and quantitatively than the other
standard contrast enhancement techniques.
Abstract: We present a refined multiscale Shannon entropy for
analyzing electroencephalogram (EEG), which reflects the underlying
dynamics of EEG over multiple scales. The rationale behind
this method is that neurological signals such as EEG possess
distinct dynamics over different spectral modes. To deal with the
nonlinear and nonstationary nature of EEG, the recently developed
empirical mode decomposition (EMD) is incorporated, allowing a
decomposition of EEG into its inherent spectral components, referred
to as intrinsic mode functions (IMFs). By calculating the Shannon
entropy of IMFs in a time-dependent manner and summing them over
adaptive multiple scales, it results in an adaptive subscale entropy
measure of EEG. Simulation and experimental results show that
the proposed entropy properly reveals the dynamical changes over
multiple scales.
Abstract: Intermetallic materials are among advanced
technology materials that have outstanding mechanical and physical
properties for high temperature applications. Especially creep
resistance, low density and high hardness properties stand out in such
intermetallics. The microstructure, mechanical properties of %88Ni-
%10Cr and %2Mn powders were investigated using specimens
produced by tube furnace sintering at 900-1300°C temperature. A
composite consisting of ternary additions, a metallic phase, Fe, Cr
and Mn have been prepared under Ar shroud and then tube furnace
sintered. XRD, SEM (Scanning Electron Microscope), were
investigated to characterize the properties of the specimens.
Experimental results carried out for composition %88Ni-%10Cr and
%2Mn at 1300°C suggest that the best properties as 138,80HV and
6,269/cm3 density were obtained at 1300°C.
Abstract: Aim of this work is to determine the theoretical and
experimental properties of filament wound glass fiber/epoxy resin
composite pipes with different winding design subjected under
bending. For determination of bending strength of composite samples
three point bending tests were conducted. Good correlation between
theoretical and experimental results has been obtained, where sample
No4 has shown the highest value of bending strength. All samples
have demonstrated matrix cracking and fiber failure followed by
layers delamination during testing. Also, it was found that smaller
winding angles lead to an increase in bending stress. From presented
results good merger between glass fibers and epoxy resin was
confirmed by SEM analysis.
Abstract: A new steganographic method via the use of numeric
data on public websites with a self-authentication capability is
proposed. The proposed technique transforms a secret message into
partial shares by Shamir’s (k, n)-threshold secret sharing scheme with
n = k + 1. The generated k+1 partial shares then are embedded into the
numeric items to be disguised as part of the website’s numeric content,
yielding the stego numeric content. Afterward, a receiver links to the
website and extracts every k shares among the k+1 ones from the stego
numeric content to compute k+1 copies of the secret, and the
phenomenon of value consistency of the computed k+1 copies is taken
as an evidence to determine whether the extracted message is authentic
or not, attaining the goal of self-authentication of the extracted secret
message. Experimental results and discussions are provided to show
the feasibility and effectiveness of the proposed method.
Abstract: Plasmin plays an important role in the human
circulatory system owing to its catalytic ability of fibrinolysis. The
immediate injection of plasmin in patients of strokes has intrigued
many scientists to design vectors that can transport plasmin to the
desired location in human body. Here we predict the structure of
human plasmin and investigate the interaction of plasmin with the
gold-nanoparticle.
Because the crystal structure of plasminogen has been solved, we
deleted N-terminal domain (Pan-apple domain) of plasminogen and
generate a mimic of the active form of this enzyme (plasmin). We
conducted a simulated annealing process on plasmin and discovered a
very large conformation occurs. Kringle domains 1, 4 and 5 had been
observed to leave its original location relative to the main body of the
enzyme and the original doughnut shape of this enzyme has been
transformed to a V-shaped by opening its two arms. This observation
of conformational change is consistent with the experimental results of
neutron scattering and centrifugation.
We subsequently docked the plasmin on the simulated gold surface
to predict their interaction. The V-shaped plasmin could utilize its
Kringle domain and catalytic domain to contact the gold surface.
Our findings not only reveal the flexibility of plasmin structure but
also provide a guide for the design of a plasmin-gold nanoparticle.
Abstract: Al6061 alloy base matrix, reinforced with particles of
silicon carbide (10 wt %) and Graphite powder (1wt%), known as
hybrid composites have been fabricated by liquid metallurgy route
(stir casting technique) and optimized at different parameters like
applied load, sliding speed and sliding distance by taguchi method. A
plan of experiment generated through taguchi technique was used to
perform experiments based on L27 orthogonal array. The developed
ANOVA and regression equations are used to find the optimum
coefficient of friction and wear under the influence of applied load,
sliding speed and sliding distance. On the basis of “smaller the best”
the dry sliding wear resistance was analysed and finally confirmation
tests were carried out to verify the experimental results.
Abstract: In the present study, RBF neural networks were used
for predicting the performance and emission parameters of a
biodiesel engine. Engine experiments were carried out in a 4 stroke
diesel engine using blends of diesel and Honge methyl ester as the
fuel. Performance parameters like BTE, BSEC, Tex and emissions
from the engine were measured. These experimental results were
used for ANN modeling.
RBF center initialization was done by random selection and by
using Clustered techniques. Network was trained by using fixed and
varying widths for the RBF units. It was observed that RBF results
were having a good agreement with the experimental results.
Networks trained by using clustering technique gave better results
than using random selection of centers in terms of reduced MRE and
increased prediction accuracy. The average MRE for the performance
parameters was 3.25% with the prediction accuracy of 98% and for
emissions it was 10.4% with a prediction accuracy of 80%.
Abstract: With the growing of computer and network, digital
data can be spread to anywhere in the world quickly. In addition,
digital data can also be copied or tampered easily so that the security
issue becomes an important topic in the protection of digital data.
Digital watermark is a method to protect the ownership of digital data.
Embedding the watermark will influence the quality certainly. In this
paper, Vector Quantization (VQ) is used to embed the watermark into
the image to fulfill the goal of data hiding. This kind of watermarking
is invisible which means that the users will not conscious the existing
of embedded watermark even though the embedded image has tiny
difference compared to the original image. Meanwhile, VQ needs a lot
of computation burden so that we adopt a fast VQ encoding scheme by
partial distortion searching (PDS) and mean approximation scheme to
speed up the data hiding process.
The watermarks we hide to the image could be gray, bi-level and
color images. Texts are also can be regarded as watermark to embed.
In order to test the robustness of the system, we adopt Photoshop to
fulfill sharpen, cropping and altering to check if the extracted
watermark is still recognizable. Experimental results demonstrate that
the proposed system can resist the above three kinds of tampering in
general cases.
Abstract: Image compression based on fractal coding is a lossy
compression method and normally used for gray level images range
and domain blocks in rectangular shape. Fractal based digital image
compression technique provide a large compression ratio and in this
paper, it is proposed using YUV colour space and the fractal theory
which is based on iterated transformation. Fractal geometry is mainly
applied in the current study towards colour image compression
coding. These colour images possesses correlations among the colour
components and hence high compression ratio can be achieved by
exploiting all these redundancies. The proposed method utilises the
self-similarity in the colour image as well as the cross-correlations
between them. Experimental results show that the greater
compression ratio can be achieved with large domain blocks but more
trade off in image quality is good to acceptable at less than 1 bit per
pixel.
Abstract: The exponential growth of social media arouses much
attention on public opinion information. The online forums, blogs,
micro blogs are proving to be extremely valuable resources and are
having bulk volume of information. However, most of the social
media data is unstructured and semi structured form. So that it is
more difficult to decipher automatically. Therefore, it is very much
essential to understand and analyze those data for making a right
decision. The online forums hotspot detection is a promising research
field in the web mining and it guides to motivate the user to take right
decision in right time. The proposed system consist of a novel
approach to detect a hotspot forum for any given time period. It uses
aging theory to find the hot terms and E-K-means for detecting the
hotspot forum. Experimental results demonstrate that the proposed
approach outperforms k-means for detecting the hotspot forums with
the improved accuracy.
Abstract: Ulexite (Na2O.2CaO.5B2O3.16H2O) is boron mineral
that is found in large quantities in the Turkey and world. In this
study, the dissolution of this mineral in the disodium hydrogen
phosphate solutions has been studied. Temperature, concentration,
stirring speed, solid liquid ratio and particle size were selected as
parameters. The experimental results were successfully correlated by
linear regression using Statistica program. Dissolution curves were
evaluated shrinking core models for solid-fluid systems. It was
observed that increase in the reaction temperature and decrease in the
solid/liquid ratio causes an increase the dissolution rate of ulexite.
The activation energy was found to be 63.4 kJ/mol. The leaching of
ulexite was controlled by chemical reaction.
Abstract: We report the microstructural and magnetic properties
of Ni50Mn39Sn11 and Ni50Mn36Sn14 ribbon Heusler alloys.
Experimental results were obtained by differential scanning
calorymetry, X-ray diffraction and vibrating sample magnetometry
techniques. The Ni-Mn-Sn system undergoes a martensitic structural
transformation in a wide temperature range. For example, for
Ni50Mn39Sn11 the start and finish temperatures of the martensitic and
austenite phase transformation for ribbon alloy were Ms=336K,
Mf=328K, As=335K and Af=343K whereas no structural
transformation is observed for Ni50Mn36Sn14 alloys. Magnetic
measurements show the typical ferromagnetic behavior with Curie
temperature 207 K at low applied field of 50 Oe. The complex
behavior exhibited by these Heusler alloys should be ascribed to the
strong coupling between magnetism and structure, being their
magnetic behavior determined by the distance between Mn atoms.
Abstract: Image enhancement is a challenging issue in many applications. In the last two decades, there are various filters developed. This paper proposes a novel method which removes Gaussian noise from the gray scale images. The proposed technique is compared with Enhanced Fuzzy Peer Group Filter (EFPGF) for various noise levels. Experimental results proved that the proposed filter achieves better Peak-Signal-to-Noise-Ratio PSNR than the existing techniques. The proposed technique achieves 1.736dB gain in PSNR than the EFPGF technique.
Abstract: In this study, ultrasonic assisted machining (UAM) technique is applied in side-surface milling experiment for glass-ceramic workpiece material. The tungsten carbide cutting-tool with diamond coating is used in conjunction with two kinds of cooling/lubrication mediums such as water-soluble (WS) cutting fluid and minimum quantity lubricant (MQL). Full factorial process parameter combinations on the milling experiments are planned to investigate the effect of process parameters on cutting performance. From the experimental results, it tries to search for the better process parameter combination which the edge-indentation and the surface roughness are acceptable. In the machining experiments, ultrasonic oscillator was used to excite a cutting-tool along the radial direction producing a very small amplitude of vibration frequency of 20KHz to assist the machining process. After processing, toolmaker microscope was used to detect the side-surface morphology, edge-indentation and cutting tool wear under different combination of cutting parameters, and analysis and discussion were also conducted for experimental results. The results show that the main leading parameters to edge-indentation of glass ceramic are cutting depth and feed rate. In order to reduce edge-indentation, it needs to use lower cutting depth and feed rate. Water-soluble cutting fluid provides a better cooling effect in the primary cutting area; it may effectively reduce the edge-indentation and improve the surface morphology of the glass ceramic. The use of ultrasonic assisted technique can effectively enhance the surface finish cleanness and reduce cutting tool wear and edge-indentation.
Abstract: Association rule mining is one of the most important fields of data mining and knowledge discovery. In this paper, we propose an efficient multiple support frequent pattern growth algorithm which we called “MSFP-growth” that enhancing the FPgrowth algorithm by making infrequent child node pruning step with multiple minimum support using maximum constrains. The algorithm is implemented, and it is compared with other common algorithms: Apriori-multiple minimum supports using maximum constraints and FP-growth. The experimental results show that the rule mining from the proposed algorithm are interesting and our algorithm achieved better performance than other algorithms without scarifying the accuracy.
Abstract: This work proposes a data-driven multiscale based
quantitative measures to reveal the underlying complexity of
electroencephalogram (EEG), applying to a rodent model of
hypoxic-ischemic brain injury and recovery. Motivated by that real
EEG recording is nonlinear and non-stationary over different
frequencies or scales, there is a need of more suitable approach over
the conventional single scale based tools for analyzing the EEG data.
Here, we present a new framework of complexity measures
considering changing dynamics over multiple oscillatory scales. The
proposed multiscale complexity is obtained by calculating entropies of
the probability distributions of the intrinsic mode functions extracted
by the empirical mode decomposition (EMD) of EEG. To quantify
EEG recording of a rat model of hypoxic-ischemic brain injury
following cardiac arrest, the multiscale version of Tsallis entropy is
examined. To validate the proposed complexity measure, actual EEG
recordings from rats (n=9) experiencing 7 min cardiac arrest followed
by resuscitation were analyzed. Experimental results demonstrate that
the use of the multiscale Tsallis entropy leads to better discrimination
of the injury levels and improved correlations with the neurological
deficit evaluation after 72 hours after cardiac arrest, thus suggesting an
effective metric as a prognostic tool.
Abstract: This paper is concerned with knowledge representation
and extraction of fuzzy if-then rules using Interval Type-2
Context-based Fuzzy C-Means clustering (IT2-CFCM) with the aid of
fuzzy granulation. This proposed clustering algorithm is based on
information granulation in the form of IT2 based Fuzzy C-Means
(IT2-FCM) clustering and estimates the cluster centers by preserving
the homogeneity between the clustered patterns from the IT2 contexts
produced in the output space. Furthermore, we can obtain the
automatic knowledge representation in the design of Radial Basis
Function Networks (RBFN), Linguistic Model (LM), and Adaptive
Neuro-Fuzzy Networks (ANFN) from the numerical input-output data
pairs. We shall focus on a design of ANFN in this paper. The
experimental results on an estimation problem of energy performance
reveal that the proposed method showed a good knowledge
representation and performance in comparison with the previous
works.
Abstract: This paper presents a model for a modified T-junction
device for microspheres generation. The numerical model is
developed using a commercial software package: COMSOL
Multiphysics. In order to test the accuracy of the numerical model,
multiple variables, such as the flow rate of cross-flow, fluid properties,
structure, and geometry of the microdevice are applied. The results
from the model are compared with the experimental results in the
diameter of the microsphere generated. The comparison shows a good
agreement. Therefore the model is useful in further optimization of the
device and feedback control of microsphere generation if any.