Abstract: This paper presents the study of induced currents and
temperature distribution in gear heated by induction process using 2D
finite element (FE) model. The model is developed by coupling
Maxwell and heat transfer equations into a multi-physics model. The
obtained results allow comparing the medium frequency (MF) and
high frequency (HF) cases and the effect of machine parameters on
the evolution of induced currents and temperature during heating.
The sensitivity study of the temperature profile is conducted and the
case hardness is predicted using the final temperature profile. These
results are validated using tests and give a good understanding of
phenomena during heating process.
Abstract: Decision making preferences to certain criteria
usually focus on positive degrees without considering the negative
degrees. However, in real life situation, evaluation becomes more
comprehensive if negative degrees are considered concurrently.
Preference is expected to be more effective when considering both
positive and negative degrees of preference to evaluate the best
selection. Therefore, the aim of this paper is to propose the
conflicting bifuzzy preference relations in group decision making by
utilization of a novel score function. The conflicting bifuzzy
preference relation is obtained by introducing some modifications on
intuitionistic fuzzy preference relations. Releasing the intuitionistic
condition by taking into account positive and negative degrees
simultaneously and utilizing the novel score function are the main
modifications to establish the proposed preference model. The
proposed model is tested with a numerical example and proved to be
simple and practical. The four-step decision model shows the
efficiency of obtaining preference in group decision making.
Abstract: The empirical mode decomposition (EMD) represents any time series into a finite set of basis functions. The bases are termed as intrinsic mode functions (IMFs) which are mutually orthogonal containing minimum amount of cross-information. The EMD successively extracts the IMFs with the highest local frequencies in a recursive way, which yields effectively a set low-pass filters based entirely on the properties exhibited by the data. In this paper, EMD is applied to explore the properties of the multi-year air temperature and to observe its effects on climate change under global warming. This method decomposes the original time-series into intrinsic time scale. It is capable of analyzing nonlinear, non-stationary climatic time series that cause problems to many linear statistical methods and their users. The analysis results show that the mode of EMD presents seasonal variability. The most of the IMFs have normal distribution and the energy density distribution of the IMFs satisfies Chi-square distribution. The IMFs are more effective in isolating physical processes of various time-scales and also statistically significant. The analysis results also show that the EMD method provides a good job to find many characteristics on inter annual climate. The results suggest that climate fluctuations of every single element such as temperature are the results of variations in the global atmospheric circulation.
Abstract: The complexity of today-s software systems makes
collaborative development necessary to accomplish tasks.
Frameworks are necessary to allow developers perform their tasks
independently yet collaboratively. Similarity detection is one of the
major issues to consider when developing such frameworks. It allows
developers to mine existing repositories when developing their own
views of a software artifact, and it is necessary for identifying the
correspondences between the views to allow merging them and
checking their consistency. Due to the importance of the
requirements specification stage in software development, this paper
proposes a framework for collaborative development of Object-
Oriented formal specifications along with a similarity detection
approach to support the creation, merging and consistency checking
of specifications. The paper also explores the impact of using
additional concepts on improving the matching results. Finally, the
proposed approach is empirically evaluated.
Abstract: This paper examines the implementation of RC5 block cipher for digital images along with its detailed security analysis. A complete specification for the method of application of the RC5 block cipher to digital images is given. The security analysis of RC5 block cipher for digital images against entropy attack, bruteforce, statistical, and differential attacks is explored from strict cryptographic viewpoint. Experiments and results verify and prove that RC5 block cipher is highly secure for real-time image encryption from cryptographic viewpoint. Thorough experimental tests are carried out with detailed analysis, demonstrating the high security of RC5 block cipher algorithm.
Abstract: In [4], Kipnis and Shamir have cryptanalised
a version of HFE of degree 2. In this paper, we describe the
generalization of this attack of HFE of degree more than 2.
We are based on Fourier Transformation to acheive partially
this attack.
Abstract: Arrack is one of the forms of alcoholic beverage or
liquor which is produced from palm or date juice and commonly
consumed by the lower social class of all religious/ethnic
communities in the north-western villages of Bangladesh. The
purpose of the study was to compare arrack drinking patterns
associated with socio-demographic status among the Muslim, Hindu,
Santal, and Oraon communities in the Rasulpur union of Bangladesh.
A total of 391 respondents (Muslim n-109, Hindu n-103, Santal n-89,
Oraon n-90) selected by cluster random sampling were interviewed
by ADP (Arrack Drinking Pattern) questionnaire. The results of
Pearson Chi-Squire test revealed that arrack drinking patterns were
significantly differed among the Muslim, Hindu, Santal, and Oraon
communities- drinkers. In addition, the results of Spearman-s
bivariate correlation coefficients also revealed that sociodemographic
characteristics of the communities- drinkers were the
significantly positive and negative associations with the arrack
drinking patterns in the Rasulpur union, Bangladesh. The study
suggests that further cross-cultural researches should be conducted
on the consequences of arrack drinking patterns on the communities-
drinkers.
Abstract: The performance of mortar subjected to high
temperature and cooled in normal ambient temperature was examined
in the laboratory to comply with the situation of burning & cooling of
a structure. Four series of cubical (5 X 5 X 5 cm) mortar specimens
were made from OPC, and partial replacement (10, 15, 20, 25 &
30%) of OPC by Rice Husk Ash (RHA) produced in the uncontrolled
environment. These specimens were heated in electric furnace to 200,
300, 400, 500 and 7000C. The specimens were kept in normal room
temperature for cooling. They were then tested for mechanical
properties and the results shows that particular 20% RHA mixed
mortar shows better fire performance.
Abstract: Composite steel shear wall is a lateral load resisting system which consists of a steel plate with concrete wall attached to one or both sides to prevent it from elastic buckling. The composite behavior is ensured by utilizing high-strength bolts. This paper investigates the effect of distance between bolts, and for this purpose 14 one-story one-bay specimens with various bolts spacing were modeled by finite element code which is developed by the authors. To verify the model, numerical results were compared with a valid experiment which illustrate proper agreement. Results depict increasing the distance between bolts would improve the seismic ever, this increase must be limited, because of large distances will cause widespread buckling of the steel plate in free subpanels between bolts and would result in no improvement. By comparing the results in elastic region, it was observed initial stiffness is not affected by changing the distance.
Abstract: The operating control parameters of injection
flushing type of electrical discharge machining process on stainless
steel 304 workpiece using copper tools are being optimized
according to its individual machining characteristic i.e. Electrode
Wear Ratio (EWR). Higher EWR would give bad dimensional
precision for the EDM machined workpiece because of high
electrode wear. Hence, the quality characteristic for EWR is set to
lower-the-better to achieve the optimum dimensional precision for
the machined workpiece. Taguchi method has been used for the
construction, layout and analysis of the experiment for EWR
machining characteristic. The use of Taguchi method in the
experiment saves a lot of time and cost of preparing and machining
the experiment samples. Therefore, an L18 Orthogonal array
which was the fundamental component in the statistical design of
experiments has been used to plan the experiments and Analysis of
Variance (ANOVA) is used to determine the optimum machining
parameters for this machining characteristic. The control
parameters selected for this optimization experiments are polarity,
pulse on duration, discharge current, discharge voltage, machining
depth, machining diameter and dielectric liquid pressure. The
result had shown that negative polarity machining parameter
setting will decreases EWR.
Abstract: In this paper, we present a new learning algorithm for
anomaly based network intrusion detection using improved self
adaptive naïve Bayesian tree (NBTree), which induces a hybrid of
decision tree and naïve Bayesian classifier. The proposed approach
scales up the balance detections for different attack types and keeps
the false positives at acceptable level in intrusion detection. In
complex and dynamic large intrusion detection dataset, the detection
accuracy of naïve Bayesian classifier does not scale up as well as
decision tree. It has been successfully tested in other problem
domains that naïve Bayesian tree improves the classification rates in
large dataset. In naïve Bayesian tree nodes contain and split as
regular decision-trees, but the leaves contain naïve Bayesian
classifiers. The experimental results on KDD99 benchmark network
intrusion detection dataset demonstrate that this new approach scales
up the detection rates for different attack types and reduces false
positives in network intrusion detection.
Abstract: The present study has been taken to explore the
screening of in vitro antimicrobial activities of D-galactose-binding
sponge lectin (HOL-30). HOL-30 was purified from the marine
demosponge Halichondria okadai by affinity chromatography. The
molecular mass of the lectin was determined to be 30 kDa with a
single polypeptide by SDS-PAGE under non-reducing and reducing
conditions. HOL-30 agglutinated trypsinized and glutaraldehydefixed
rabbit and human erythrocytes with preference for type O
erythrocytes. The lectin was subjected to evaluation for inhibition of
microbial growth by the disc diffusion method against eleven human
pathogenic gram-positive and gram-negative bacteria. The lectin
exhibited strong antibacterial activity against gram-positive bacteria,
such as Bacillus megaterium and Bacillus subtilis. However, it did
not affect against gram-negative bacteria such as Salmonella typhi
and Escherichia coli. The largest zone of inhibition was recorded of
Bacillus megaterium (12 in diameter) and Bacillus subtilis (10 mm in
diameter) at a concentration of the lectin (250 μg/disc). On the other
hand, the antifungal activity of the lectin was investigated against six
phytopathogenic fungi based on food poisoning technique. The lectin
has shown maximum inhibition (22.83%) of mycelial growth of
Botrydiplodia theobromae at a concentration of 100 μg/mL media.
These findings indicate that the lectin may be of importance to
clinical microbiology and have therapeutic applications.
Abstract: Air conditioning is mainly use as human comfort
cooling medium. It use more in high temperatures are country such as
Malaysia. Proper estimation of cooling load will archive ideal
temperature. Without proper estimation can lead to over estimation or
under estimation. The ideal temperature should be comfort enough.
This study is to develop a program to calculate an ideal cooling load
demand, which is match with heat gain. Through this study, it is easy
to calculate cooling load estimation. Objective of this study are to
develop user-friendly and easy excess cooling load program. This is
to insure the cooling load can be estimate by any of the individual
rather than them using rule-of-thumb. Developed software is carryout
by using Matlab-GUI. These developments are only valid for
common building in Malaysia only. An office building was select as
case study to verify the applicable and accuracy of develop software.
In conclusion, the main objective has successfully where developed
software is user friendly and easily to estimate cooling load demand.
Abstract: Supercritical carbon dioxide (SC-CO2) was used as a
solvent to extract oil from wheat bran. Extractions were carried out in a
semi-batch process at temperatures ranging from 40 to 60ºC and
pressures ranging from 10 to 30 MPa, with a carbon dioxide (CO2)
flow rate of 26.81 g/min. The oil obtained from wheat bran at different
extraction conditions was quantitatively measured to investigate the
solubility of oil in SC-CO2. The solubility of wheat bran oil was found
to be enhanced in high temperature and pressure. The composition of
fatty acids in wheat bran oil was measured by gas chromatography
(GC). Linoleic, palmitic, oleic and γ-linolenic acid were the major
fatty acids of wheat bran oil. Tocopherol contents in oil were analyzed
by high performance liquid chromatography (HPLC). The highest
amount of phenolics and tocopherols (α and β) were found at
temperature of 60ºC and pressure of 30 MPa.
Abstract: The effects of global warming on India vary from the
submergence of low-lying islands and coastal lands to the melting of
glaciers in the Indian Himalayas, threatening the volumetric flow rate
of many of the most important rivers of India and South Asia. In
India, such effects are projected to impact millions of lives. As a
result of ongoing climate change, the climate of India has become
increasingly volatile over the past several decades; this trend is
expected to continue.
Climate change is one of the most important global environmental
challenges, with implications for food production, water supply,
health, energy, etc. Addressing climate change requires a good
scientific understanding as well as coordinated action at national and
global level. The climate change issue is part of the larger challenge
of sustainable development. As a result, climate policies can be more
effective when consistently embedded within broader strategies
designed to make national and regional development paths more
sustainable. The impact of climate variability and change, climate
policy responses, and associated socio-economic development will
affect the ability of countries to achieve sustainable development
goals.
A very well calibrated Soil and Water Assessment Tool (R2 =
0.9968, NSE = 0.91) was exercised over the Khatra sub basin of the
Kangsabati River watershed in Bankura district of West Bengal,
India, in order to evaluate projected parameters for agricultural
activities. Evapotranspiration, Transmission Losses, Potential
Evapotranspiration and Lateral Flow to reach are evaluated from the
years 2041-2050 in order to generate a picture for sustainable
development of the river basin and its inhabitants.
India has a significant stake in scientific advancement as well as
an international understanding to promote mitigation and adaptation.
This requires improved scientific understanding, capacity building,
networking and broad consultation processes. This paper is a
commitment towards the planning, management and development of
the water resources of the Kangsabati River by presenting detailed
future scenarios of the Kangsabati river basin, Khatra sub basin, over
the mentioned time period.
India-s economy and societal infrastructures are finely tuned to the
remarkable stability of the Indian monsoon, with the consequence
that vulnerability to small changes in monsoon rainfall is very high.
In 2002 the monsoon rains failed during July, causing profound loss
of agricultural production with a drop of over 3% in India-s GDP.
Neither the prolonged break in the monsoon nor the seasonal rainfall
deficit was predicted. While the general features of monsoon
variability and change are fairly well-documented, the causal
mechanisms and the role of regional ecosystems in modulating the
changes are still not clear. Current climate models are very poor at
modelling the Asian monsoon: this is a challenging and critical
region where the ocean, atmosphere, land surface and mountains all
interact. The impact of climate change on regional ecosystems is
likewise unknown. The potential for the monsoon to become more
volatile has major implications for India itself and for economies
worldwide. Knowledge of future variability of the monsoon system,
particularly in the context of global climate change, is of great
concern for regional water and food security.
The major findings of this paper were that of all the chosen
projected parameters, transmission losses, soil water content,
potential evapotranspiration, evapotranspiration and lateral flow to
reach, display an increasing trend over the time period of years 2041-
2050.
Abstract: The massive proliferation of affordable computers, Internet broadband connectivity and rich education content has created a global phenomenon in which information and communication technology (ICT) is being used to transform education. Therefore, there is a need to redesign the educational system to meet the needs better. The advent of computers with sophisticated software has made it possible to solve many complex problems very fast and at a lower cost. This paper introduces the characteristics of the current E-Learning and then analyses the concept of cloud computing and describes the architecture of cloud computing platform by combining the features of E-Learning. The authors have tried to introduce cloud computing to e-learning, build an e-learning cloud, and make an active research and exploration for it from the following aspects: architecture, construction method and external interface with the model.
Abstract: Many organisations are nowadays interested to adopt
lean manufacturing strategy that would enable them to compete in
this competitive globalisation market. In this respect, it is necessary
to assess the implementation of lean manufacturing in different
organisations so that the important best practices can be identified.
This paper describes the development of key areas which will be
used to assess the adoption and implementation of lean
manufacturing practices. There are some key areas developed to
evaluate and reduce the most optimal projects so as to enhance their
production efficiency and increase the purpose of the economic
benefits of the manufacturing unit.
Lean manufacturing is becoming lean enterprise by treating its
customers and suppliers as partners. This gives the extra edge in
today-s cost and time competitive markets. The organisation is
becoming strong in all the conventional competition points. They are
Price, Quality and Delivery. Lean enterprise owners can deliver high
quality products quickly, with low price.
Abstract: The clustering ensembles combine multiple partitions
generated by different clustering algorithms into a single clustering
solution. Clustering ensembles have emerged as a prominent method
for improving robustness, stability and accuracy of unsupervised
classification solutions. So far, many contributions have been done to
find consensus clustering. One of the major problems in clustering
ensembles is the consensus function. In this paper, firstly, we
introduce clustering ensembles, representation of multiple partitions,
its challenges and present taxonomy of combination algorithms.
Secondly, we describe consensus functions in clustering ensembles
including Hypergraph partitioning, Voting approach, Mutual
information, Co-association based functions and Finite mixture
model, and next explain their advantages, disadvantages and
computational complexity. Finally, we compare the characteristics of
clustering ensembles algorithms such as computational complexity,
robustness, simplicity and accuracy on different datasets in previous
techniques.
Abstract: Heart failure is the most common reason of death
nowadays, but if the medical help is given directly, the patient-s life
may be saved in many cases. Numerous heart diseases can be
detected by means of analyzing electrocardiograms (ECG). Artificial
Neural Networks (ANN) are computer-based expert systems that
have proved to be useful in pattern recognition tasks. ANN can be
used in different phases of the decision-making process, from
classification to diagnostic procedures. This work concentrates on a
review followed by a novel method.
The purpose of the review is to assess the evidence of healthcare
benefits involving the application of artificial neural networks to the
clinical functions of diagnosis, prognosis and survival analysis, in
ECG signals. The developed method is based on a compound neural
network (CNN), to classify ECGs as normal or carrying an
AtrioVentricular heart Block (AVB). This method uses three
different feed forward multilayer neural networks. A single output
unit encodes the probability of AVB occurrences. A value between 0
and 0.1 is the desired output for a normal ECG; a value between 0.1
and 1 would infer an occurrence of an AVB. The results show that
this compound network has a good performance in detecting AVBs,
with a sensitivity of 90.7% and a specificity of 86.05%. The accuracy
value is 87.9%.
Abstract: This paper presents a system overview of Mobile to Server Face Recognition, which is a face recognition application developed specifically for mobile phones. Images taken from mobile phone cameras lack of quality due to the low resolution of the cameras. Thus, a prototype is developed to experiment the chosen method. However, this paper shows a result of system backbone without the face recognition functionality. The result demonstrated in this paper indicates that the interaction between mobile phones and server is successfully working. The result shown before the database is completely ready. The system testing is currently going on using real images and a mock-up database to test the functionality of the face recognition algorithm used in this system. An overview of the whole system including screenshots and system flow-chart are presented in this paper. This paper also presents the inspiration or motivation and the justification in developing this system.