Abstract: Fibrin degradation is an important part in prevention
or treatment of intravascular thrombosis and cardiovascular diseases.
Plasmin like fibrinolytic enzymes has given new hope to patient with
cardiovascular diseases by treating fibrin aggregation related diseases
with traditional plasminogen activator which have many side effects.
Various researches involving wide range of sources for production of
fibrinolytic proteases, from bacteria, fungi, insects and fermented
foods. But few have looked into endophytic fungi as a potential
source. Sixteen (16) endophytic fungi were isolated from Hibiscus sp.
leaves from six different locations in Shah Alam, Selangor. Only two
endophytic fungi, FH3 and S13 showed positive fibrinolytic protease
activities. FH3 produced 5.78cm and S13 produced 4.48cm on Skim
Milk Agar after 4 days of incubation at 27°C. Fibrinolytic activity
was observed; 3.87cm and 1.82cm diameter clear zone on fibrin plate
of FH3 and S13 respectively. 18srRNA was done for identification of
the isolated fungi with positive fibrinolytic protease. S13 had the
highest similarity (100%) to that of Penicillium citrinum strain TG2
and FH3 had the highest similarity (99%) to that of Fusarium sp.
FW2PhC1, Fusarium sp. 13002, Fusarium sp. 08006, Fusarium
equiseti strain Salicorn 8 and Fungal sp. FCASAn-2. Media
composition variation showed the effects of carbon nitrogen on
protein concentration, where the decrement of 50% of media
composition caused drastic decrease in protease of FH3 from 1.081 to
0.056 and also S13 from 2.946 to 0.198.
Abstract: This paper presents circular polar coordinates
transformation of periodic fuzzy membership function. The purpose
is identification of domain of periodic membership functions in
consequent part of IF-THEN rules. Proposed methods in this paper
remove complicatedness concerning domain of periodic membership
function from defuzzification in fuzzy approximate reasoning.
Defuzzification on circular polar coordinates is also proposed.
Abstract: Control of a semi-batch polymerization reactor using
an adaptive radial basis function (RBF) neural network method is
investigated in this paper. A neural network inverse model is used to
estimate the valve position of the reactor; this method can identify the
controlled system with the RBF neural network identifier. The
weights of the adaptive PID controller are timely adjusted based on
the identification of the plant and self-learning capability of RBFNN.
A PID controller is used in the feedback control to regulate the actual
temperature by compensating the neural network inverse model
output. Simulation results show that the proposed control has strong
adaptability, robustness and satisfactory control performance and the
nonlinear system is achieved.
Abstract: The aim of this paper is to create a proposal for determining the costs of logistics processes by using process-oriented calculation methods. The traditional approach is that logistics costs are part of manufacturing overhead which is usually calculated as a percentage surcharge. Therefore in the traditional approach it is not obvious where and in which activities costs were incurred. So it is impossible to trace logistics costs to products. Our point of view is trying to fix or at least improve this issue. Another benefit of applying the process approach is identification of logistics processes which are otherwise part of manufacturing overhead. In the first part this paper describes the development of process-oriented methods over time. The next part shows the possibility of implementing the process-oriented method called Prozesskostenrechnung to logistics processes. The conclusion summarizes advantages and disadvantages of using this method in logistics.
Abstract: This study deals with an advanced numerical
techniques to detect tensile forces in cable-stayed structures. The
proposed method allows us not only to avoid the trap of minimum at
initial searching stage but also to find their final solutions in better
numerical efficiency. The validity of the technique is numerically
verified using a set of dynamic data obtained from a simulation of the
cable model modeled using the finite element method. The results
indicate that the proposed method is computationally efficient in
characterizing the tensile force variation for cable-stayed structures.
Abstract: This paper presents breast cancer detection by
observing the specific absorption rate (SAR) intensity for
identification tumor location, the tumor is identified in coordinates
(x,y,z) system. We examined the frequency between 4-8 GHz to look
for the most appropriate frequency. Results are simulated in
frequency 4-8 GHz, the model overview include normal breast with
50 mm radian, 5 mm diameter of tumor, and ultra wideband (UWB)
bowtie antenna. The models are created and simulated in CST
Microwave Studio. For this simulation, we changed antenna to 5
location around the breast, the tumor can be detected when an
antenna is close to the tumor location, which the coordinate of
maximum SAR is approximated the tumor location. For reliable, we
experiment by random tumor location to 3 position in the same size
of tumor and simulation the result again by varying the antenna
position in 5 position again, and it also detectable the tumor position
from the antenna that nearby tumor position by maximum value of
SAR, which it can be detected the tumor with precision in all
frequency between 4-8 GHz.
Abstract: This paper describes a blind algorithm, which is
compared with two another algorithms proposed in the literature,
for estimating of the minimum phase channel parameters. In order to
identify blindly the impulse response of these channels, we have used
Higher Order Statistics (HOS) to build our algorithm. The simulation
results in noisy environment, demonstrate that the proposed method
could estimate the phase and magnitude with high accuracy of these
channels blindly and without any information about the input, except
that the input excitation is identically and independent distribute
(i.i.d) and non-Gaussian.
Abstract: Zinc borate is an important boron compound that can be used as multi-functional flame retardant additive due to its high dehydration temperature property. In this study, theraw materials of ZnSO4.7H2O, NaOH and H3BO3werecharacterized by X-Ray Diffraction (XRD) and Fourier Transform Infrared Spectroscopy (FT-IR) and used in the synthesis of zinc borates.The synthesis parameters were set to 100°C reaction temperature and 120 minutes of reaction time, with different molar ratio of starting materials (ZnSO4.7H2O:NaOH:H3BO3). After the zinc borate synthesis, the identifications of the products were conducted by XRD and FT-IR. As a result,Zinc Oxide Borate Hydrate [Zn3B6O12.3.5H2O], were synthesized at the molar ratios of 1:1:3, 1:1:4, 1:2:5 and 1:2:6. Among these ratios 1:2:6 had the best results.
Abstract: This paper describes an identification of specific shapes within binary images using the morphological Hit-or-Miss Transform (HMT). Hit-or-Miss transform is a general binary morphological operation that can be used in searching of particular patterns of foreground and background pixels in an image. It is actually a basic operation of binary morphology since almost all other binary morphological operators are derived from it. The input of this method is a binary image and a structuring element (a template which will be searched in a binary image) while the output is another binary image. In this paper a modification of Hit-or-Miss transform has been proposed. The accuracy of algorithm is adjusted according to the similarity of the template and the sought template. The implementation of this method has been done by C language. The algorithm has been tested on several images and the results have shown that this new method can be used for similar shape detection.
Abstract: Protein kinases participate in a myriad of cellular
processes of major biomedical interest. The in vivo substrate
specificity of these enzymes is a process determined by several
factors, and despite several years of research on the topic, is still
far from being totally understood. In the present work, we have
quantified the contributions to the kinase substrate specificity of
i) the phosphorylation sites and their surrounding residues in the
sequence and of ii) the association of kinases to adaptor or scaffold
proteins. We have used position-specific scoring matrices (PSSMs),
to represent the stretches of sequences phosphorylated by 93 families
of kinases. We have found negative correlations between the number
of sequences from which a PSSM is generated and the statistical
significance and the performance of that PSSM. Using a subset
of 22 statistically significant PSSMs, we have identified specificity
determinant residues (SDRs) for 86% of the corresponding kinase
families. Our results suggest that different SDRs can function as
positive or negative elements of substrate recognition by the different
families of kinases. Additionally, we have found that human proteins
with known function as adaptors or scaffolds (kAS) tend to interact
with a significantly large fraction of the substrates of the kinases to
which they associate. Based on this characteristic we have identified
a set of 279 potential adaptors/scaffolds (pAS) for human kinases,
which is enriched in Pfam domains and functional terms tightly
related to the proposed function. Moreover, our results show that
for 74.6% of the kinase–pAS association found, the pAS colocalize
with the substrates of the kinases they are associated to. Finally, we
have found evidence suggesting that the association of kinases to
adaptors and scaffolds, may contribute significantly to diminish the
in vivo substrate crossed-specificity of protein kinases. In general, our
results indicate the relevance of several SDRs for both the positive
and negative selection of phosphorylation sites by kinase families and
also suggest that the association of kinases to pAS proteins may be
an important factor for the localization of the enzymes with their set
of substrates.
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: In this work, an experimental technique is applied
for the measurements of the vibrations and deformation of a test
transformer core. Since the grid voltage contains some higher
harmonics, in addition to a purely sinusoidal magnetisation of the
core the presence of third harmonic is also studied. The vibrations of
the transformer core for points as well as the surface scan of the leg
show more deformation in the corners of the leg than the middle of
the leg. The influence of the higher harmonic of the magnetisation
on the core deformation is also more significant in the corners of the
leg. The core deformation shape under a sinusoidal magnetisation
with a higher harmonic is more wavy and fluctuating than that under
a purely sinusoidal magnetisation.
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: Machine learning represents a set of topics dealing with the creation and evaluation of algorithms that facilitate pattern recognition, classification, and prediction, based on models derived from existing data. The data can present identification patterns which are used to classify into groups. The result of the analysis is the pattern which can be used for identification of data set without the need to obtain input data used for creation of this pattern. An important requirement in this process is careful data preparation validation of model used and its suitable interpretation. For breeders, it is important to know the origin of animals from the point of the genetic diversity. In case of missing pedigree information, other methods can be used for traceability of animal´s origin. Genetic diversity written in genetic data is holding relatively useful information to identify animals originated from individual countries. We can conclude that the application of data mining for molecular genetic data using supervised learning is an appropriate tool for hypothesis testing and identifying an individual.
Abstract: The aim of this paper is to assess the influence of several indicators determining innovativeness of countries' economies by applying selected soft computing methods. Such methods enable us to identify correlations between indicators for period 2006-2010. The main attention in the paper is focused on selecting proper computer tools for solving this problem. As a tool supporting identification, the X-means clustering algorithm, the Apriori rules generation algorithm as well as Self-Organizing Feature Maps (SOMs) have been selected. The paper has rather a rudimentary character. We briefly describe usefulness of the selected approaches and indicate some challenges for further research.
Abstract: The MyD88 is an evolutionarily conserved host-expressed adaptor protein that is essential for proper TLR/ IL1R immune-response signaling. A previously identified complete cDNA (1626 bp) of OfMyD88 comprised an ORF of 867 bp encoding a protein of 288 amino acids (32.9 kDa). The gDNA (3761 bp) of OfMyD88 revealed a quinquepartite genome organization composed of 5 exons (with the sizes of 310, 132, 178, 92 and 155 bp) separated by 4 introns. All the introns displayed splice signals consistent with the consensus GT/AG rule. A bipartite domain structure with two domains namely death domain (24-103) coded by 1st exon, and TIR domain (151-288) coded by last 3 exons were identified through in silico analysis. Moreover, homology modeling of these two domains revealed a similar quaternary folding nature between human and rock bream homologs. A comprehensive comparison of vertebrate MyD88 genes showed that they possess a 5-exonic structure.In this structure, the last three exons were strongly conserved, and this suggests that a rigid structure has been maintained during vertebrate evolution.A cluster of TATA box-like sequences were found 0.25 kb upstream of cDNA starting position. In addition, putative 5'-flanking region of OfMyD88 was predicted to have TFBS implicated with TLR signaling, including copies of NFkB1, APRF/ STAT3, Sp1, IRF1 and 2 and Stat1/2. Using qPCR technique, a ubiquitous mRNA expression was detected in liver and blood. Furthermore, a significantly up-regulated transcriptional expression of OfMyD88 was detected in head kidney (12-24 h; >2-fold), spleen (6 h; 1.5-fold), liver (3 h; 1.9-fold) and intestine (24 h; ~2-fold) post-Fla challenge. These data suggest a crucial role for MyD88 in antibacterial immunity of teleosts.
Abstract: This study presented the investigation of the influence of the tool holder interface stiffness on the dynamic characteristics of a spindle tool system. The interface stiffness was produced by drawbar force on the tool holder, which tends to affect the spindle dynamics. In order to assess the influence of interface stiffness on the vibration characteristic of spindle unit, we first created a three dimensional finite element model of a high speed spindle system integrated with tool holder. The key point for the creation of FEM model is the modeling of the rolling interface within the angular contact bearings and the tool holder interface. The former can be simulated by a introducing a series of spring elements between inner and outer rings. The contact stiffness was calculated according to Hertz contact theory and the preload applied on the bearings. The interface stiffness of the tool holder was identified through the experimental measurement and finite element modal analysis. Current results show that the dynamic stiffness was greatly influenced by the tool holder system. In addition, variations of modal damping, static stiffness and dynamic stiffness of the spindle tool system were greatly determined by the interface stiffness of the tool holder which was in turn dependent on the draw bar force applied on the tool holder. Overall, this study demonstrates that identification of the interface characteristics of spindle tool holder is of very importance for the refinement of the spindle tooling system to achieve the optimum machining performance.
Abstract: Hydrological modelling plays a crucial role in the planning and management of water resources, most especially in water stressed regions where the need to effectively manage the available water resources is of critical importance. However, due to the complex, nonlinear and dynamic behaviour of hydro-climatic interactions, achieving reliable modelling of water resource systems and accurate projection of hydrological parameters are extremely challenging. Although a significant number of modelling techniques (process-based and data-driven) have been developed and adopted in that regard, the field of hydrological modelling is still considered as one that has sluggishly progressed over the past decades. This is majorly as a result of the identification of some degree of uncertainty in the methodologies and results of techniques adopted. In recent times, evolutionary computation (EC) techniques have been developed and introduced in response to the search for efficient and reliable means of providing accurate solutions to hydrological related problems. This paper presents a comprehensive review of the underlying principles, methodological needs and applications of a promising evolutionary computation modelling technique – genetic programming (GP). It examines the specific characteristics of the technique which makes it suitable to solving hydrological modelling problems. It discusses the opportunities inherent in the application of GP in water related-studies such as rainfall estimation, rainfall-runoff modelling, streamflow forecasting, sediment transport modelling, water quality modelling and groundwater modelling among others. Furthermore, the means by which such opportunities could be harnessed in the near future are discussed. In all, a case for total embracement of GP and its variants in hydrological modelling studies is made so as to put in place strategies that would translate into achieving meaningful progress as it relates to modelling of water resource systems, and also positively influence decision-making by relevant stakeholders.
Abstract: This paper presents a nonparametric identification of
continuous-time nonlinear systems by using a Gaussian process
(GP) model. The GP prior model is trained by artificial bee colony
algorithm. The nonlinear function of the objective system is estimated
as the predictive mean function of the GP, and the confidence
measure of the estimated nonlinear function is given by the predictive
covariance of the GP. The proposed identification method is applied
to modeling of a simplified electric power system. Simulation results
are shown to demonstrate the effectiveness of the proposed method.
Abstract: The procedure for the assessment of the urinary mucosal cryoglobulin (UMCG) is being reviewed, testified and evaluated. The major features of UMCG are rather similar to that of serum cryoglobulin. Such evident similarities are forming the reality for the existence of the UMCG. There were seven characterizing criteria useable for the identification for UMCG. Upon matching them to the Irish criteria for serum cryoglobulin, some modifications are being proposed to the 16th standards that has been formulated and built as an Irish criteria. The existence of UMCG is being reported for the first time in human chronic infectious bacterial disease.