Abstract: This paper presents the prediction of kidney
dysfunction using different neural network (NN) approaches. Self
organization Maps (SOM), Probabilistic Neural Network (PNN) and
Multi Layer Perceptron Neural Network (MLPNN) trained with Back
Propagation Algorithm (BPA) are used in this study. Six hundred and
sixty three sets of analytical laboratory tests have been collected from
one of the private clinical laboratories in Baghdad. For each subject,
Serum urea and Serum creatinin levels have been analyzed and tested
by using clinical laboratory measurements. The collected urea and
cretinine levels are then used as inputs to the three NN models in
which the training process is done by different neural approaches.
SOM which is a class of unsupervised network whereas PNN and
BPNN are considered as class of supervised networks. These
networks are used as a classifier to predict whether kidney is normal
or it will have a dysfunction. The accuracy of prediction, sensitivity
and specificity were found for each type of the proposed networks
.We conclude that PNN gives faster and more accurate prediction of
kidney dysfunction and it works as promising tool for predicting of
routine kidney dysfunction from the clinical laboratory data.
Abstract: A company CSR commitment, as stated in its Social
Report is, actually, perceived by its stakeholders?And in what
measure? Moreover, are stakeholders satisfied with the company
CSR efforts? Indeed, business returns from Corporate Social
Responsibility (CSR) practices, such as company reputation and
customer loyalty, depend heavily on how stakeholders perceive the
company social conduct. In this paper, we propose a methodology to
assess a company CSR commitment based on Global Reporting
Initiative (GRI) indicators, Content Analysis and a CSR positioning
matrix. We evaluate three aspects of CSR: the company commitment
disclosed through its Social Report; the company commitment
perceived by its stakeholders; the CSR commitment that stakeholders
require to the company. The positioning of the company under study
in the CSR matrix is based on the comparison among the three
commitment aspects (disclosed, perceived, required) and it allows
assessment and development of CSR strategies.
Abstract: Reinforced concrete crash barriers used in road traffic
must meet a number of criteria. Crash barriers are laid lengthwise,
one behind another, and joined using specially designed steel locks.
While developing BSV reinforced concrete crash barriers (type
ŽPSV), experiments and calculations aimed to optimize the shape of
a newly designed lock and the reinforcement quantity and
distribution in a crash barrier were carried out. The tension carrying
capacity of two parallelly joined locks was solved experimentally.
Based on the performed experiments, adjustments of nonlinear
properties of steel were performed in the calculations. The obtained
results served as a basis to optimize the lock design using a
computational model that takes into account the plastic behaviour of
steel and the influence of the surrounding concrete [6]. The response
to the vehicle impact has been analyzed using a specially elaborated
complex computational model, comprising both the nonlinear model
of the damping wall or crash barrier and the detailed model of the
vehicle [7].
Abstract: the data quality is a kind of complex and unstructured concept, which is concerned by information systems managers. The reason of this attention is the high amount of Expenses for maintenance and cleaning of the inefficient data. Such a data more than its expenses of lack of quality, cause wrong statistics, analysis and decisions in organizations. Therefor the managers intend to improve the quality of their information systems' data. One of the basic subjects of quality improvement is the evaluation of the amount of it. In this paper, we present a precautionary method, which with its application the data of information systems would have a better quality. Our method would cover different dimensions of data quality; therefor it has necessary integrity. The presented method has tested on three dimensions of accuracy, value-added and believability and the results confirm the improvement and integrity of this method.
Abstract: A different concept for designing and detailing of
reinforced concrete precast frame structures is analyzed in this paper.
The new detailing of the joints derives from the special hybrid
moment frame joints. The special reinforcements of this alternative
detailing, named modified special hybrid joint, are bondless with
respect to both column and beams. Full scale tests were performed on
a plan model, which represents a part of 5 story structure, cropped in
the middle of the beams and columns spans. Theoretical approach
was developed, based on testing results on twice repaired model,
subjected to lateral seismic type loading. Discussion regarding the
modified special hybrid joint behavior and further on widening
research needed concludes the presentation.
Abstract: An electric power system includes a generating, a
transmission, a distribution, and consumers subsystems. An electrical
power network in Tanzania keeps growing larger by the day and
become more complex so that, most utilities have long wished for
real-time monitoring and remote control of electrical power system
elements such as substations, intelligent devices, power lines,
capacitor banks, feeder switches, fault analyzers and other physical
facilities. In this paper, the concept of automation of management of
power systems from generation level to end user levels was
determined by using Power System Simulator for Engineering
(PSS/E) version 30.3.2.
Abstract: Color image segmentation can be considered as a
cluster procedure in feature space. k-means and its adaptive
version, i.e. competitive learning approach are powerful tools
for data clustering. But k-means and competitive learning suffer
from several drawbacks such as dead-unit problem and need to
pre-specify number of cluster. In this paper, we will explore to
use competitive and cooperative learning approach to perform
color image segmentation. In competitive and cooperative
learning approach, seed points not only compete each other, but
also the winner will dynamically select several nearest
competitors to form a cooperative team to adapt to the input
together, finally it can automatically select the correct number
of cluster and avoid the dead-units problem. Experimental
results show that CCL can obtain better segmentation result.
Abstract: The objective of this paper is twofold: (1) discuss and
analyze the successful case studies worldwide, and (2) identify the
similarities and differences of case studies worldwide. Design
methodology/approach: The nature of this research is mainly method
qualitative (multi-case studies, literature review). This investigation
uses ten case studies, and the data was mainly collected and
organizational documents from the international countries. Finding:
The finding of this research can help incubator manager, policy
maker and government parties for successful implementation.
Originality/value: This paper contributes to the current literate review
on the best practices worldwide. Additionally, it presents future
perspective for academicians and practitioners.
Abstract: Recently, malware attacks have become more serious
over the Internet by e-mail, denial of service (DoS) or distributed
denial of service (DDoS). The Botnets have become a significant part
of the Internet malware attacks. The traditional botnets include three
parts – botmaster, command and control (C&C) servers and bots. The
C&C servers receive commands from botmaster and control the
distributions of computers remotely. Bots use DNS to find the
positions of C&C server. In this paper, we propose an advanced hybrid
peer-to-peer (P2P) botnet 2.0 (AHP2P botnet 2.0) using web 2.0
technology to hide the instructions from botmaster into social sites,
which are regarded as C&C servers. Servent bots are regarded as
sub-C&C servers to get the instructions from social sites. The AHP2P
botnet 2.0 can evaluate the performance of servent bots, reduce DNS
traffics from bots to C&C servers, and achieve harder detection bots
actions than IRC-based botnets over the Internet.
Abstract: This paper deals with the evaluation of flow properties
of polymeric matrix with natural animal fillers. Technical university
of Liberec cooperates on the long-term development of “green
materials“ that should replace conventionally used materials
(especially in automotive industry). Natural fibres (of animal and
plant origin) from all over the world are collected and adapted
(drying, cutting etc.) for extrusion processing. Inside the extruder
these natural additives are blended with polymeric (synthetic and
biodegradable - PLA) matrix and created compound is subsequently
cut for pellets in the wet way. These green materials with unique
recipes are then studied and their mechanical, physical and
processing properties are determined. The main goal of this research
is to develop new ecological materials very similar to unfilled
polymers. In this article the rheological behaviour of chosen natural
animal fibres is introduced considering their shape and surface that
were observed with use of SEM microscopy.
Abstract: Through a proper analysis of residual strain and stress
distributions obtained at the surface of high speed milled specimens
of AA 6082–T6 aluminium alloy, the performance of an improved
indentation method is evaluated. This method integrates a special
device of indentation to a universal measuring machine. The
mentioned device allows introducing elongated indents allowing to
diminish the absolute error of measurement. It must be noted that the
present method offers the great advantage of avoiding both the
specific equipment and highly qualified personnel, and their inherent
high costs. In this work, the cutting tool geometry and high speed
parameters are selected to introduce reduced plastic damage.
Through the variation of the depth of cut, the stability of the shapes
adopted by the residual strain and stress distributions is evaluated.
The results show that the strain and stress distributions remain
unchanged, compressive and small. Moreover, these distributions
reveal a similar asymmetry when the gradients corresponding to
conventional and climb cutting zones are compared.
Abstract: The physical methods for RNA secondary structure prediction are time consuming and expensive, thus methods for computational prediction will be a proper alternative. Various algorithms have been used for RNA structure prediction including dynamic programming and metaheuristic algorithms. Musician's behaviorinspired harmony search is a recently developed metaheuristic algorithm which has been successful in a wide variety of complex optimization problems. This paper proposes a harmony search algorithm (HSRNAFold) to find RNA secondary structure with minimum free energy and similar to the native structure. HSRNAFold is compared with dynamic programming benchmark mfold and metaheuristic algorithms (RnaPredict, SetPSO and HelixPSO). The results showed that HSRNAFold is comparable to mfold and better than metaheuristics in finding the minimum free energies and the number of correct base pairs.
Abstract: This paper presents the work of signal discrimination
specifically for Electrocardiogram (ECG) waveform. ECG signal is
comprised of P, QRS, and T waves in each normal heart beat to
describe the pattern of heart rhythms corresponds to a specific
individual. Further medical diagnosis could be done to determine any
heart related disease using ECG information. The emphasis on QRS
Complex classification is further discussed to illustrate the
importance of it. Pan-Tompkins Algorithm, a widely known
technique has been adapted to realize the QRS Complex
classification process. There are eight steps involved namely
sampling, normalization, low pass filter, high pass filter (build a band
pass filter), derivation, squaring, averaging and lastly is the QRS
detection. The simulation results obtained is represented in a
Graphical User Interface (GUI) developed using MATLAB.
Abstract: A major part of the flow field involves no complicated
turbulent behavior in many turbulent flows. In this research work, in
order to reduce required memory and CPU time, the flow field was
decomposed into several blocks, each block including its special
turbulence. A two dimensional backward facing step was considered
here. Four combinations of the Prandtl mixing length and standard k-
E models were implemented as well. Computer memory and CPU
time consumption in addition to numerical convergence and accuracy
of the obtained results were mainly investigated. Observations
showed that, a suitable combination of turbulence models in different
blocks led to the results with the same accuracy as the high order
turbulence model for all of the blocks, in addition to the reductions in
memory and CPU time consumption.
Abstract: Bioinformatics and Cheminformatics use computer as disciplines providing tools for acquisition, storage, processing, analysis, integrate data and for the development of potential applications of biological and chemical data. A chemical database is one of the databases that exclusively designed to store chemical information. NMRShiftDB is one of the main databases that used to represent the chemical structures in 2D or 3D structures. SMILES format is one of many ways to write a chemical structure in a linear format. In this study we extracted Antimicrobial Structures in SMILES format from NMRShiftDB and stored it in our Local Data Warehouse with its corresponding information. Additionally, we developed a searching tool that would response to user-s query using the JME Editor tool that allows user to draw or edit molecules and converts the drawn structure into SMILES format. We applied Quick Search algorithm to search for Antimicrobial Structures in our Local Data Ware House.
Abstract: The present study attempted to improve the Mercury
(Hg) sorption capacity of kanuma volcanic ash soil (KVAS) by
impregnating the cupper (Cu). Impregnation was executed by 1 and
5% Cu powder and sorption characterization of optimum Hg
removing Cu impregnated KVAS was performed under different
operational conditions, contact time, solution pH, sorbent dosage and
Hg concentration using the batch operation studies. The 1% Cu
impregnated KVAS pronounced optimum improvement (79%) in
removing Hg from water compare to control. The present
investigation determined the equilibrium state of maximum Hg
adsorption at 6 h contact period. The adsorption revealed a pH
dependent response and pH 3.5 showed maximum sorption capacity
of Hg. Freundlich isotherm model is well fitted with the experimental
data than that of Langmuir isotherm. It can be concluded that the Cu
impregnation improves the Hg sorption capacity of KVAS and 1%
Cu impregnated KVAS could be employed as cost-effective
adsorbent media for treating Hg contaminated water.
Abstract: This research aimed to study on the potential of
recycling organic waste in Suan Sunandha Rajabhat University as
compost. In doing so, the composition of solid waste generated in the
campus was investigated while physical and chemical properties of
organic waste were analyzed in order to evaluate the portion of waste
suitable for recycling as compost. As a result of the study, it was
found that (1) the amount of organic waste was averaged at 299.8
kg/day in which mixed food wastes had the highest amount of 191.9
kg/day followed by mixed leave & yard wastes and mixed fruit &
vegetable wastes at the amount of 66.3 and 41.6 kg/day respectively;
(2) physical and chemical properties of organic waste in terms of
moisture content was between 69.54 to 78.15%, major elements for
plant as N, P and K were 0.14 to 0.17%, 0.46 to 0.52% and 0.16 to
0.18% respectively, and carbon/nitrogen ratio (C/N) was about 15:1
to 17.5:1; (3) recycling organic waste as compost was designed by
aerobic decomposition using mixed food wastes : mixed leave & yard
wastes : mixed fruit & vegetable wastes at the portion of 3:2:1 by
weight in accordance with the potential of their amounts and their
physical and chemical properties.
Abstract: Yogurt is a coagulated milk product obtained from
the lactic acid fermentation by the action of Lactobacillus
bulgaricus and Streptococcus thermophilus. The additions of fruits
into milk may enhance the taste and the therapeutical values of milk
products. However fruits also may change the fermentation
behaviour. In this present study, the changes in physicochemical, the
peptide concentration, total phenolics content and the antioxidant
potential of yogurt upon the addition of Hylocereus polyrhizus and
Hylocereus undatus (white and red dragon fruit) were investigated.
Fruits enriched yogurt (10%, 20%, 30% w/w) were prepared and the
pH, TTA, syneresis measurement, peptide concentration, total
phenolics content and DPPH antioxidant inhibition percentage were
determined. Milk fermentation rate was enhanced in red dragon fruit
yogurt for all doses (-0.3606 - -0.4126 pH/h) while only white
dragon fruit yogurt with 20% and 30% (w/w) composition showed
increment in fermentation rate (-0.3471 - -0.3609 pH/h) compared to
plain yogurt (-0.3369pH/h). All dragon fruit enriched yogurts
generally showed lower pH readings (pH 3.95 - 4.03) compared to
plain yogurt (pH 4.05). Both fruit yogurts showed a higher lactic
acid percentage (1.14-1.23%) compared to plain yogurt (1.08%).
Significantly higher syneresis percentage (57.19 - 70.32%)
compared to plain yogurt (52.93%) were seen in all fruit enriched
yogurts. The antioxidant activity of plain yogurt (19.16%) was
enhanced by the presence of white and red dragon fruit (24.97-
45.74%). All fruit enriched yogurt showed an increment in total
phenolic content (36.44 - 64.43mg/ml) compared to plain yogurt
(20.25mg/ml). However, the addition of white and red dragon fruit
did not enhance the proteolysis of milk during fermentation.
Therefore, it could be concluded that the addition of white and red
dragon fruit into yogurt enhanced the milk fermentation rate, lactic
acid content, syneresis percentage, antioxidant activity, and total
phenolics content in yogurt.
Abstract: This study was designed to investigate the role of serum nitric oxide and sialic acid in the development of diabetic nephropathy as disease marker. Total 210 diabetic patients (age and sex matched) were selected followed by informed consent and divided into four groups (70 each) as I: control; II: diabetic; III: diabetic hypertensive; IV: diabetic nephropathy. The blood samples of all subjects were collected and analyzed for serum nitric oxide, sialic acid, fasting blood glucose, serum urea, creatinine, HbA1c and GFR. The BMI, systolic and diastolic blood pressures, blood glucose, HbA1c and serum sialic acid levels were high (p
Abstract: The study of piezoelectric material in the past was in
T-Domain form; however, no one has studied piezoelectric material in the S-Domain form. This paper will present the piezoelectric material in the transfer function or S-Domain model. S-Domain is a
well known mathematical model, used for analyzing the stability of the material and determining the stability limits. By using S-Domain
in testing stability of piezoelectric material, it will provide a new tool for the scientific world to study this material in various forms.