Abstract: Advances in the field of image processing envision a
new era of evaluation techniques and application of procedures in
various different fields. One such field being considered is the
biomedical field for prognosis as well as diagnosis of diseases. This
plethora of methods though provides a wide range of options to select
from, it also proves confusion in selecting the apt process and also in
finding which one is more suitable. Our objective is to use a series of
techniques on bone scans, so as to detect the occurrence of
rheumatoid arthritis (RA) as accurately as possible. Amongst other
techniques existing in the field our proposed system tends to be more
effective as it depends on new methodologies that have been proved
to be better and more consistent than others. Computer aided
diagnosis will provide more accurate and infallible rate of
consistency that will help to improve the efficiency of the system.
The image first undergoes histogram smoothing and specification,
morphing operation, boundary detection by edge following algorithm
and finally image subtraction to determine the presence of
rheumatoid arthritis in a more efficient and effective way. Using preprocessing
noises are removed from images and using segmentation,
region of interest is found and Histogram smoothing is applied for a
specific portion of the images. Gray level co-occurrence matrix
(GLCM) features like Mean, Median, Energy, Correlation, Bone
Mineral Density (BMD) and etc. After finding all the features it
stores in the database. This dataset is trained with inflamed and noninflamed
values and with the help of neural network all the new
images are checked properly for their status and Rough set is
implemented for further reduction.
Abstract: The impact deformation and fracture behaviour of cobalt-based Haynes 188 superalloy are investigated by means of a split Hopkinson pressure bar. Impact tests are performed at strain rates ranging from 1×103 s-1 to 5×103 s-1 and temperatures between 25°C and 800°C. The experimental results indicate that the flow response and fracture characteristics of cobalt-based Haynes 188 superalloy are significantly dependent on the strain rate and temperature. The flow stress, work hardening rate and strain rate sensitivity all increase with increasing strain rate or decreasing temperature. It is shown that the impact response of the Haynes 188 specimens is adequately described by the Zerilli-Armstrong fcc model. The fracture analysis results indicate that the Haynes 188 specimens fail predominantly as the result of intensive localised shearing. Furthermore, it is shown that the flow localisation effect leads to the formation of adiabatic shear bands. The fracture surfaces of the deformed Haynes 188 specimens are characterised by dimple- and / or cleavage-like structure with knobby features. The knobby features are thought to be the result of a rise in the local temperature to a value greater than the melting point.
Abstract: The case study presents the progression of a project management of Al-Shifa, a healthcare information system in Oman. The case study describes the evolution of the implementation of a healthcare information system tailored to meet the needs of the healthcare units under the supervision of the Ministry of Health (MOH) in Oman. A focus group methodology was used for collecting the relevant information from the main project's stakeholders. In addition reports about the project made available for the researchers. The case analysis is made based on the Project Management approach developed by the Project Management Institute (PMI). The main finding that there was no formal project management approach adopted by the MOH for the development and implementation of the herewith mentioned healthcare information system project. Furthermore, the project had suffered a scope creep in terms of features, cost and time-schedule. The recommendations of the authors, for the rescue of the project from its current dilemma, consist of technological, administrative and human resources development actions.
Abstract: In this paper, the comparison between k-Nearest Neighbor (kNN) algorithms for classifying the 3D EEG model in brain balancing is presented. The EEG signal recording was conducted on 51 healthy subjects. Development of 3D EEG models involves pre-processing of raw EEG signals and construction of spectrogram images. Then, maximum PSD values were extracted as features from the model. There are three indexes for balanced brain; index 3, index 4 and index 5. There are significant different of the EEG signals due to the brain balancing index (BBI). Alpha-α (8–13 Hz) and beta-β (13–30 Hz) were used as input signals for the classification model. The k-NN classification result is 88.46% accuracy. These results proved that k-NN can be used in order to predict the brain balancing application.
Abstract: Blood gamma irradiation is the only available method
to prevent transfusion associated graft versus host disease (TAGVHD).
However, when blood is irradiated, determine blood shelf
time is crucial. Non irradiated blood have a self-time from 21 to 35
days when is preserved with anticoagulated solution and stored at
4°C. During their storage, red blood cells (RBC) undergo a series of
biochemical, biomechanical and molecular changes involving what is
known as storage lesion (SL). SL include loss of structural integrity
of RBC, decrease of 2,3-diphosphatidylglyceric acid levels, and
increase of both ion potassium concentration and hemoglobin (Hb).
On the other hand, Atomic force Microscopy (AFM) represents a
versatile tool for a nano-scale high resolution topographic analysis in
biological systems. In order to evaluate SL in irradiated and nonirradiated
blood, RBC topography and morphometric parameters
were obtained from an AFM XE-BIO system. Cell viability was
followed using flow cytometry. Our results showed that early
markers as nanoscale roughness, allow us to evaluate blood quality
since other perspective.
Abstract: There have been a lot of efforts and researches undertaken in developing efficient tools for performing several tasks in data mining. Due to the massive amount of information embedded in huge data warehouses maintained in several domains, the extraction of meaningful pattern is no longer feasible. This issue turns to be more obligatory for developing several tools in data mining. Furthermore the major aspire of data mining software is to build a resourceful predictive or descriptive model for handling large amount of information more efficiently and user friendly. Data mining mainly contracts with excessive collection of data that inflicts huge rigorous computational constraints. These out coming challenges lead to the emergence of powerful data mining technologies. In this survey a diverse collection of data mining tools are exemplified and also contrasted with the salient features and performance behavior of each tool.
Abstract: Various biomass based resources, which can be used
as an extender, or a complete substitute of diesel fuel may have very
significant role in the development of agriculture, industrial and
transport sectors in the energy crisis. Use of Karanja oil methyl ester
biodiesel in a CI DI engine was found highly compatible with engine
performance along with lower exhaust emission as compared to
diesel fuel but with slightly higher NOx emission and low wear
characteristics. The combustion related properties of vegetable oils
are somewhat similar to diesel oil. Neat vegetable oils or their blends
with diesel, however, pose various long-term problems in
compression ignition engines. These undesirable features of
vegetable oils are because of their inherent properties like high
viscosity, low volatility, and polyunsaturated character. Pongamia
methyl ester (PME) was prepared by transesterification process using
methanol for long term engine operations. The physical and
combustion-related properties of the fuels thus developed were found
to be closer to that of the diesel. A neat biodiesel (PME) was selected
as a fuel for the tribological study of biofuels.
Two similar new engines were completely disassembled and
subjected to dimensioning of various vital moving parts and then
subjected to long-term endurance tests on neat biodiesel and diesel
respectively. After completion of the test, both the engines were
again disassembled for physical inspection and wear measurement of
various vital parts. The lubricating oil samples drawn from both
engines were subjected to atomic absorption spectroscopy (AAS) for
measurement of various wear metal traces present. The additional
lubricating property of biodiesel fuel due to higher viscosity as
compared to diesel fuel resulted in lower wear of moving parts and
thus improved the engine durability with a bio-diesel fuel. Results
reported from AAS tests confirmed substantially lower wear and thus
improved life for biodiesel operated engines.
Abstract: This paper presents a comparative study between two
neural network models namely General Regression Neural Network
(GRNN) and Back Propagation Neural Network (BPNN) are used
to estimate radial overcut produced during Electrical Discharge
Machining (EDM). Four input parameters have been employed:
discharge current (Ip), pulse on time (Ton), Duty fraction (Tau) and
discharge voltage (V). Recently, artificial intelligence techniques, as
it is emerged as an effective tool that could be used to replace
time consuming procedures in various scientific or engineering
applications, explicitly in prediction and estimation of the complex
and nonlinear process. The both networks are trained, and the
prediction results are tested with the unseen validation set of the
experiment and analysed. It is found that the performance of both the
networks are found to be in good agreement with average percentage
error less than 11% and the correlation coefficient obtained for the
validation data set for GRNN and BPNN is more than 91%. However,
it is much faster to train GRNN network than a BPNN and GRNN is
often more accurate than BPNN. GRNN requires more memory space
to store the model, GRNN features fast learning that does not require
an iterative procedure, and highly parallel structure. GRNN networks
are slower than multilayer perceptron networks at classifying new
cases.
Abstract: The study aimed to collect morphological data of
secretory structures that contribute to taxonomy of Indigofera. Detail
features of trichomes occurrence in vegetative and reproductive
organs of Indigofera wightii Grah. ex Wigh & Arn., a species
traditionally used as source of indigo to dye “Thaisongdam” clothing
were investigated. Examination through light microscopy and
scanning electrom microscopy were done. Non secretory, T-shaped
trichomes appeared throughout surfaces of stems, leaves, flowers and
fruits. Secretory or glandular trichomes occurred in two types; one
has big cylindrical head and short peduncle, distributed on adaxial
surface of sepals and around the pedicel, whereas another possesses
smaller cylindrical head but long peduncle. The latter was found on
apical surface of immature pods. No phenolic and lipophilic
compounds were detected from these glands.
Abstract: Microalgae due to the ability to accumulate high levels of practically valuable polyunsaturated fatty acids attract attention as a promising raw material for commercial products. The features of the growth processes of cells green protococcal microalgae Oocystis rhomboideus, Scenedesmus obliquus, Dictyochlorella globosa at cultivation in different nutritional mediums were determined. For the rapid accumulation of biomass, combined with high productivity of total lipids fraction yield recommended to use the Fitzgerald medium (Scenodesmus obliquus, Oocystis rhomboideus) and/or Bold medium (Dictyochlorella globosa). Productivity of lipids decreased in sequence Dictyochlorella globosa > Scenodesmus obliquus > Oocystis rhomboideus. The bulk of fatty acids fraction of the total lipids is unsaturated fatty acids, which accounts for 70 to 83% of the total number of fatty acids. The share of monoenic acids accounts from 18 to 34%, while the share of unsaturated fatty acids - from 44 to 62% of the total number of unsaturated fatty acids fraction. Among the unsaturated acids dominate α-linolenic acid (C18:3n-3), hexadecatetraenic acid (C16:4) and linoleic acid (C18:2).
Abstract: In this study, we developed a complementary electrochromic device consisting of WO3 and NiO films fabricated by rf-magnetron sputtered. The electrochromic properties of WO3 and NiO films were investigated using cyclic voltammograms (CV), performed on WO3 and NiO films immersed in an electrolyte of 1 M LiClO4 in propylene carbonate (PC). Optical and electrochemical of the films, as a function of coloration–bleaching cycle, were characterized using an UV-Vis-NIR spectrophotometer and cyclic voltammetry (CV). After investigating the properties of WO3 film, NiO film, and complementary electrochromic devices, we concluded that this device provides good reversibility, low power consumption of -2.5 V in color state, high variation of transmittance of 58.96%, changes in optical density of 0.81 and good memory effect under open-circuit conditions. In addition, electrochromic component penetration rate can be retained below 20% within 24h, showing preferred memory features; however, component coloring and bleaching response time are about 33s.
Abstract: Seismic design criteria based on performance of
structures have recently been adopted by practicing engineers in
response to destructive earthquakes. A simple but efficient
structural-analysis tool capable of predicting both the strength and
ductility is needed to analyze reinforced concrete (RC) structures
under such event. A three-dimensional lattice model is developed in
this study to analyze torsions in high-strength RC members.
Optimization techniques for determining optimal variables in each
lattice model are introduced. Pure torsion tests of RC members are
performed to validate the proposed model. Correlation studies
between the numerical and experimental results confirm that the
proposed model is well capable of representing salient features of the
experimental results.
Abstract: To develop the useful acoustic environmental
recognition system, the method of estimating 3D-position of a
stationary random acoustic source using bispectral analysis of
4-point detected signals is proposed. The method uses information
about amplitude attenuation and propagation delay extracted from
amplitude ratios and angles of auto- and cross-bispectra of the
detected signals. It is expected that using bispectral analysis affects
less influence of Gaussian noises than using conventional power
spectral one. In this paper, the basic principle of the method is
mentioned first, and its validity and features are considered from
results of the fundamental experiments assumed ideal circumstances.
Abstract: One of the main features of the Maghreb is its linguistic richness. The multilingualism is a fact which always marked the Maghreb since the beginning of the history up to know. Since the arrival of the Phoenicians, followed by the Carthaginians, Romans, and Arabs, etc, there was a social group in the Maghreb which controlled two kinds of idioms. The libyc one remained, despite everything, the local language used by the major part of the population. This language had a support of written transmission attested by many inscriptions. Among all the forms of the Maghreb writing, this alphabet, however, continues to cause a certain number of questions about the origin and the date of its appearance. The archaeological, linguistic and historical data remain insufficient to answer these questions. This did not prevent the researchers from giving an opinion. In order to answer these questions we will expose here the various assumptions adopted by various authors who are founded on more or less explicit arguments. We will also speak about the various forms taken by the libyc writing during antiquity.
Abstract: Systems running these days are huge, complex and exist in many versions. Controlling these versions and tracking their changes became a very hard process as some versions are created using meaningless names or specifications. Many versions of a system are created with no clear difference between them. This leads to mismatching between a user’s request and the version he gets. In this paper, we present a system versions meta-modeling approach that produces versions based on system’s features. This model reduced the number of steps needed to configure a release and gave each version its unique specifications. This approach is applicable for systems that use features in its specification.
Abstract: This paper presents a fault identification, classification and fault location estimation method based on Discrete Wavelet Transform and Adaptive Network Fuzzy Inference System (ANFIS) for medium voltage cable in the distribution system.
Different faults and locations are simulated by ATP/EMTP, and then certain selected features of the wavelet transformed signals are used as an input for a training process on the ANFIS. Then an accurate fault classifier and locator algorithm was designed, trained and tested using current samples only. The results obtained from ANFIS output were compared with the real output. From the results, it was found that the percentage error between ANFIS output and real output is less than three percent. Hence, it can be concluded that the proposed technique is able to offer high accuracy in both of the fault classification and fault location.
Abstract: Human face has a fundamental role in the appearance
of individuals. So the importance of facial surgeries is undeniable.
Thus, there is a need for the appropriate and accurate facial skin
segmentation in order to extract different features. Since Fuzzy CMeans
(FCM) clustering algorithm doesn’t work appropriately for
noisy images and outliers, in this paper we exploit Possibilistic CMeans
(PCM) algorithm in order to segment the facial skin. For this
purpose, first, we convert facial images from RGB to YCbCr color
space. To evaluate performance of the proposed algorithm, the
database of Sahand University of Technology, Tabriz, Iran was used.
In order to have a better understanding from the proposed algorithm;
FCM and Expectation-Maximization (EM) algorithms are also used
for facial skin segmentation. The proposed method shows better
results than the other segmentation methods. Results include
misclassification error (0.032) and the region’s area error (0.045) for
the proposed algorithm.
Abstract: This paper presents a facial expression recognition system. It performs identification and classification of the seven basic expressions; happy, surprise, fear, disgust, sadness, anger, and neutral states. It consists of three main parts. The first one is the detection of a face and the corresponding facial features to extract the most expressive portion of the face, followed by a normalization of the region of interest. Then calculus of curvelet coefficients is performed with dimensionality reduction through principal component analysis. The resulting coefficients are combined with two ratios; mouth ratio and face edge ratio to constitute the whole feature vector. The third step is the classification of the emotional state using the SVM method in the feature space.
Abstract: In the article are considered the problems arising at increasing of transferring from rolling stock axles on rail loading from 210 KN up to 270 KN and is offered for rail strength analysis definition of rail force loading complex integral characteristic with taking into account all affecting force factors that is characterizing specific operation condition of rail structure and defines the working capability of structure.
As result of analysis due mentioned method is obtained that in the conditions of 270 KN loading the rail meets the working assessment criteria of rail and rail structures: Strength, rail track stability, rail links stability and its transverse stability, traffic safety condition that is rather important for post-Soviet countries railways.
Abstract: This action research accentuates the outcome of a development in English pronunciation, using principles of phonetics for English major students at Loei Rajabhat University. The research is split into 5 separate modules: 1) Organs of Speech and How to Produce Sounds, 2) Monopthongs, 3) Diphthongs, 4) Consonant sounds, and 5) Suprasegmental Features. Each module followed a 4 step action research process, 1) Planning, 2) Acting, 3) Observing, and 4) Reflecting. The research targeted 2nd year students who were majoring in English Education at Loei Rajabhat University during the academic year of 2011. A mixed methodology employing both quantitative and qualitative research was used, which put theory into action, taking segmental features up to suprasegmental features. Multiple tools were employed which included the following documents: pre-test and post-test papers, evaluation and assessment papers, group work assessment forms, a presentation grading form, an observation of participants form and a participant self-reflection form.
All 5 modules for the target group showed that results from the post-tests were higher than those of the pre-tests, with 0.01 statistical significance. All target groups attained results ranging from low to moderate and from moderate to high performance. The participants who attained low to moderate results had to re-sit the second round. During the first development stage, participants attended classes with group participation, in which they addressed planning through mutual co-operation and sharing of responsibility. Analytic induction of strong points for this operation illustrated that learner cognition, comprehension, application, and group practices were all present whereas the participants with weak results could be attributed to biological differences, differences in life and learning, or individual differences in responsiveness and self-discipline.
Participants who were required to be re-treated in Spiral 2 received the same treatment again. Results of tests from the 5 modules after the 2nd treatment were that the participants attained higher scores than those attained in the pre-test. Their assessment and development stages also showed improved results. They showed greater confidence at participating in activities, produced higher quality work, and correctly followed instructions for each activity. Analytic induction of strong and weak points for this operation remains the same as for Spiral 1, though there were improvements to problems which existed prior to undertaking the second treatment.