Abstract: This paper presents a experiment to estimate the
influences of cutting conditions in microstructure changes of
machining austenitic 304 stainless steel, especially for wear insert. The
wear insert were prefabricated with a width of 0.5 mm. And the forces,
temperature distribution, RS, and microstructure changes were
measured by force dynamometer, infrared thermal camera, X-ray
diffraction, XRD, SEM, respectively. The results told that the different
combinations of machining condition have a significant influence on
machined surface microstructure changes. In addition to that, the
ANOVA and AOMwere used to tell the different influences of cutting
speed, feed rate, and wear insert.
Abstract: The extraction of meaningful information from image
could be an alternative method for time series analysis. In this paper,
we propose a graphical analysis of time series grouped into table
with adjusted colour scale for numerical values. The advantages of
this method are also discussed. The proposed method is easy to
understand and is flexible to implement the standard methods of
pattern recognition and verification, especially for noisy
environmental data.
Abstract: Recent theorizations on the cognitive process of moral
judgment have focused on the role of intuitions and emotions, marking
a departure from previous emphasis on conscious, step-by-step
reasoning. My study investigated how being in a disgusted mood state
affects moral judgment.
Participants were induced to enter a disgusted mood state through
listening to disgusting sounds and reading disgusting descriptions.
Results shows that they, when compared to control who have not been
induced to feel disgust, are more likely to endorse actions that are
emotionally aversive but maximizes utilitarian return
The result is analyzed using the 'emotion-as-information' approach
to decision making. The result is consistent with the view that
emotions play an important role in determining moral judgment.
Abstract: The proposed system identifies the species of the wood
using the textural features present in its barks. Each species of a wood
has its own unique patterns in its bark, which enabled the proposed
system to identify it accurately. Automatic wood recognition system
has not yet been well established mainly due to lack of research in this
area and the difficulty in obtaining the wood database. In our work, a
wood recognition system has been designed based on pre-processing
techniques, feature extraction and by correlating the features of those
wood species for their classification. Texture classification is a problem
that has been studied and tested using different methods due to its
valuable usage in various pattern recognition problems, such as wood
recognition, rock classification. The most popular technique used
for the textural classification is Gray-level Co-occurrence Matrices
(GLCM). The features from the enhanced images are thus extracted
using the GLCM is correlated, which determines the classification
between the various wood species. The result thus obtained shows a
high rate of recognition accuracy proving that the techniques used in
suitable to be implemented for commercial purposes.
Abstract: This study was carried out in Ankara, the capital city of Turkey, in order to determine how people living in the slums of Ankara benefit from educational equality. Within the scope of the research, interviews were made with 64 families whose children have been getting education from the primary schools of these parts and the data of the study was collected by the researcher. The results of the research demonstrate that the children getting education in the slums of Ankara can not experience educational equality and justice. The results of this study show that the opportunities of the schools in the slums of Ankara are very limited, so the individuals in these districts can not equally benefit from the education. The families are aware of the problem they are faced with. KeywordsDiscrimination, inequality, primary education, slums of Turkey.
Abstract: There have been different approaches to compute the
analytic instantaneous frequency with a variety of background reasoning
and applicability in practice, as well as restrictions. This paper presents an adaptive Fourier decomposition and (α-counting) based
instantaneous frequency computation approach. The adaptive Fourier
decomposition is a recently proposed new signal decomposition
approach. The instantaneous frequency can be computed through the so called mono-components decomposed by it. Due to the fast energy
convergency, the highest frequency of the signal will be discarded by the adaptive Fourier decomposition, which represents the noise of
the signal in most of the situation. A new instantaneous frequency
definition for a large class of so-called simple waves is also proposed
in this paper. Simple wave contains a wide range of signals for which
the concept instantaneous frequency has a perfect physical sense.
The α-counting instantaneous frequency can be used to compute the highest frequency for a signal. Combination of these two approaches one can obtain the IFs of the whole signal. An experiment is demonstrated the computation procedure with promising results.
Abstract: This paper describes an optimal approach for feature
subset selection to classify the leaves based on Genetic Algorithm
(GA) and Kernel Based Principle Component Analysis (KPCA). Due
to high complexity in the selection of the optimal features, the
classification has become a critical task to analyse the leaf image
data. Initially the shape, texture and colour features are extracted
from the leaf images. These extracted features are optimized through
the separate functioning of GA and KPCA. This approach performs
an intersection operation over the subsets obtained from the
optimization process. Finally, the most common matching subset is
forwarded to train the Support Vector Machine (SVM). Our
experimental results successfully prove that the application of GA
and KPCA for feature subset selection using SVM as a classifier is
computationally effective and improves the accuracy of the classifier.
Abstract: The hypercube Qn is one of the most well-known
and popular interconnection networks and the k-ary n-cube Qk
n is
an enlarged family from Qn that keeps many pleasing properties
from hypercubes. In this article, we study the panpositionable
hamiltonicity of Qk
n for k ≥ 3 and n ≥ 2. Let x, y of V (Qk
n)
be two arbitrary vertices and C be a hamiltonian cycle of Qk
n.
We use dC(x, y) to denote the distance between x and y on the
hamiltonian cycle C. Define l as an integer satisfying d(x, y) ≤ l ≤ 1
2 |V (Qk
n)|. We prove the followings:
• When k = 3 and n ≥ 2, there exists a hamiltonian cycle C
of Qk
n such that dC(x, y) = l.
• When k ≥ 5 is odd and n ≥ 2, we request that l /∈ S
where S is a set of specific integers. Then there exists a
hamiltonian cycle C of Qk
n such that dC(x, y) = l.
• When k ≥ 4 is even and n ≥ 2, we request l-d(x, y) to be
even. Then there exists a hamiltonian cycle C of Qk
n such
that dC(x, y) = l.
The result is optimal since the restrictions on l is due to the
structure of Qk
n by definition.
Abstract: In a product development process, understanding the functional behavior of the system, the role of components in achieving functions and failure modes if components/subsystem fails its required function will help develop appropriate design validation and verification program for reliability assessment. The integration of these three issues will help design and reliability engineers in identifying weak spots in design and planning future actions and testing program. This case study demonstrate the advantage of unascertained theory described in the subjective cognition uncertainty, and then applies blind number (BN) theory in describing the uncertainty of the mechanical system failure process and the same time used the same theory in bringing out another mechanical reliability system model. The practical calculations shows the BN Model embodied the characters of simply, small account of calculation but betterforecasting capability, which had the value of macroscopic discussion to some extent.
Abstract: Although agriculture is an important part of the world
economy, accounting in agriculture still has many shortcomings. The
adoption of IAS 41 “Agriculture” has tried to improve this situation
and increase the comparability of financial statements of entities in
the agricultural sector. Although controversial, IAS 41 is the first
step of a consistent transition to fair value assessment in the
agricultural sector. The objective of our work is the analysis of IAS
41 and current accounting agricultural situation in Romania.
Accounting regulations in Romania are in accordance with European
directives and, in many respects, converged with IFRS referential.
Provisions of IAS 41, however, are not reflected directly in
Romanian regulations. With the increase of forest land transactions,
it is expected that recognition and measurement of biological assets
under IAS 41 to become a necessity.
Abstract: In this paper, a new approach for target recognition based on the Empirical mode decomposition (EMD) algorithm of Huang etal. [11] and the energy tracking operator of Teager [13]-[14] is introduced. The conjunction of these two methods is called Teager-Huang analysis. This approach is well suited for nonstationary signals analysis. The impulse response (IR) of target is first band pass filtered into subsignals (components) called Intrinsic mode functions (IMFs) with well defined Instantaneous frequency (IF) and Instantaneous amplitude (IA). Each IMF is a zero-mean AM-FM component. In second step, the energy of each IMF is tracked using the Teager energy operator (TEO). IF and IA, useful to describe the time-varying characteristics of the signal, are estimated using the Energy separation algorithm (ESA) algorithm of Maragos et al .[16]-[17]. In third step, a set of features such as skewness and kurtosis are extracted from the IF, IA and IMF energy functions. The Teager-Huang analysis is tested on set of synthetic IRs of Sonar targets with different physical characteristics (density, velocity, shape,? ). PCA is first applied to features to discriminate between manufactured and natural targets. The manufactured patterns are classified into spheres and cylinders. One hundred percent of correct recognition is achieved with twenty three echoes where sixteen IRs, used for training, are free noise and seven IRs, used for testing phase, are corrupted with white Gaussian noise.
Abstract: In this work, we are interested in developing a speech denoising tool by using a discrete wavelet packet transform (DWPT). This speech denoising tool will be employed for applications of recognition, coding and synthesis. For noise reduction, instead of applying the classical thresholding technique, some wavelet packet nodes are set to zero and the others are thresholded. To estimate the non stationary noise level, we employ the spectral entropy. A comparison of our proposed technique to classical denoising methods based on thresholding and spectral subtraction is made in order to evaluate our approach. The experimental implementation uses speech signals corrupted by two sorts of noise, white and Volvo noises. The obtained results from listening tests show that our proposed technique is better than spectral subtraction. The obtained results from SNR computation show the superiority of our technique when compared to the classical thresholding method using the modified hard thresholding function based on u-law algorithm.
Abstract: This Paper proposes a new facial feature extraction approach, Wash-Hadamard Transform (WHT). This approach is based on correlation between local pixels of the face image. Its primary advantage is the simplicity of its computation. The paper compares the proposed approach, WHT, which was traditionally used in data compression with two other known approaches: the Principal Component Analysis (PCA) and the Discrete Cosine Transform (DCT) using the face database of Olivetti Research Laboratory (ORL). In spite of its simple computation, the proposed algorithm (WHT) gave very close results to those obtained by the PCA and DCT. This paper initiates the research into WHT and the family of frequency transforms and examines their suitability for feature extraction in face recognition applications.
Abstract: The city of Melbourne in Victoria, Australia, provides a number of examples of how a growing city can integrate urban planning and water planning to achieve sustainable urban development, environmental protection, liveability and integrated water management outcomes, and move towards becoming a “Water Sensitive City". Three examples are provided - the development at Botanic Ridge, where a 318 hectare residential development is being planned and where integrated water management options are being implemented using a “triple bottom line" sustainability investment approach; the Toolern development, which will capture and reuse stormwater and recycled water to greatly reduce the suburb-s demand for potable water, and the development at Kalkallo where a 1,200 hectare industrial precinct development is planned which will merge design of the development's water supply, sewerage services and stormwater system. The Paper argues that an integrated urban planning and water planning approach is fundamental to creating liveable, vibrant communities which meet social and financial needs while being in harmony with the local environment. Further work is required on developing investment frameworks and risk analysis frameworks to ensure that all possible solutions can be assessed equally.
Abstract: Milk is a very important nutrient. Low productivity is
a problem of Turkish dairy farming. During recent years, Turkish government has supported cooperatives that assist milk producers and
encouraged farmers to become cooperative members. Turkish
government established several ways to support specially smallholders. For example Ministry of Agriculture and Rural Affairs
(MARA) provided two to four cows to villagers on a grant or loan basis with a long repayment period at low interest rates by
cooperatives. Social Support Project in Rural Areas (SSPRA) is
another support program targeting only disadvantaged people,
especially poor villager. Both programs have a very strong social
support component and similar objectives. But there are minor
differences between them in terms of target people, terms and conditions of the credit supplied Isparta province in Mediterranean region of Turkey is one of the
supported regions. MARA distributed dairy cows to 1072 farmers through 16 agricultural cooperatives in Isparta province in the context
of SSPRA. In this study, economic-social impacts on dairy cattle project
implemented through cooperatives were examined in Isparta. Primary data were collected from 12 cooperatives- president. The
data were obtained by personal interview through a questionnaire and
to cooperatives and given to farms benefiting from the project in
order to reveal the economic and social developments.
Finding of the study revealed that project provided new job
opportunities and improved quality of livestock. It was found that producers who benefited from the project were more willing to
participate in cooperative or other producer organizations.
Abstract: The present work represents an investigation of the
hydrolysis of hull-less pumpkin (Cucurbita Pepo L.) oil cake protein
isolate (PuOC PI) by pepsin. To examine the effectiveness and
suitability of pepsin towards PuOC PI the kinetic parameters for
pepsin on PuOC PI were determined and then, the hydrolysis process
was studied using Response Surface Methodology (RSM). The
hydrolysis was carried out at temperature of 30°C and pH 3.00. Time
and initial enzyme/substrate ratio (E/S) at three levels were selected
as the independent parameters. The degree of hydrolysis, DH, was
mesuared after 20, 30 and 40 minutes, at initial E/S of 0.7, 1 and 1.3
mA/mg proteins. Since the proposed second-order polynomial model
showed good fit with the experimental data (R2 = 0.9822), the
obtained mathematical model could be used for monitoring the
hydrolysis of PuOC PI by pepsin, under studied experimental
conditions, varying the time and initial E/S. To achieve the highest
value of DH (39.13 %), the obtained optimum conditions for time
and initial E/S were 30 min and 1.024 mA/mg proteins.
Abstract: Intelligent Video-Surveillance (IVS) systems are
being more and more popular in security applications. The analysis
and recognition of abnormal behaviours in a video sequence has
gradually drawn the attention in the field of IVS, since it allows
filtering out a large number of useless information, which guarantees
the high efficiency in the security protection, and save a lot of human
and material resources. We present in this paper ADABeV, an
intelligent video-surveillance framework for event recognition in
crowded scene to detect the abnormal human behaviour. This
framework is attended to be able to achieve real-time alarming,
reducing the lags in traditional monitoring systems. This architecture
proposal addresses four main challenges: behaviour understanding in
crowded scenes, hard lighting conditions, multiple input kinds of
sensors and contextual-based adaptability to recognize the active
context of the scene.
Abstract: This paper presents initiatives of Knowledge
Management (KM) applied to Forensic Sciences field, especially
developed at the Forensic Science Institute of the Brazilian Federal
Police. Successful projects, related to knowledge sharing, drugs
analysis and environmental crimes, are reported in the KM
perspective. The described results are related to: a) the importance of
having an information repository, like a digital library, in such a
multidisciplinary organization; b) the fight against drug dealing and
environmental crimes, enabling the possibility to map the evolution
of crimes, drug trafficking flows, and the advance of deforestation in
Amazon rain forest. Perspectives of new KM projects under
development and studies are also presented, tracing an evolution line
of the KM view at the Forensic Science Institute.
Abstract: In this paper we introduce the notion of protein interaction network. This is a graph whose vertices are the protein-s amino acids and whose edges are the interactions between them. Using a graph theory approach, we observe that according to their structural roles, the nodes interact differently. By leading a community structure detection, we confirm this specific behavior and describe thecommunities composition to finally propose a new approach to fold a protein interaction network.
Abstract: Green propellants used for satellite-level propulsion
system become attractive in recent years because the non-toxicity and
lower requirements of safety protection. One of the green propellants,
high-concentration hydrogen peroxide H2O2 solution (≥70% w/w,
weight concentration percentage), often known as high-test peroxide
(HTP), is considered because it is ITAR-free, easy to manufacture and
the operating temperature is lower than traditional monopropellant
propulsion. To establish satellite propulsion technology, the National
Space Organization (NSPO) in Taiwan has initialized a long-term
cooperation project with the National Cheng Kung University to
develop compatible tank and thruster. An experimental propulsion
payload has been allocated for the future self-reliant satellite to
perform orbit transfer and maintenance operations. In the present
research, an 1-Newton thruster prototype is designed and the thrusting
force is measured by a pendulum-type platform. The preliminary
hot-firing test at ambient environment showed the generated thrust and
the specific impulse are about 0.7 Newton and 102 seconds,
respectively.