Abstract: Flat double-layer grid is from category of space structures that are formed from two flat layers connected together with diagonal members. Increased stiffness and better seismic resistance in relation to other space structures are advantages of flat double layer space structures. The objective of this study is assessment and calculation of Behavior factor of flat double layer space structures. With regarding that these structures are used widely but Behavior factor used to design these structures against seismic force is not determined and exact, the necessity of study is obvious. This study is theoretical. In this study we used structures with span length of 16m and 20 m. All connections are pivotal. ANSYS software is used to non-linear analysis of structures.
Abstract: This paper describes the NEAR (Navigating Exhibitions, Annotations and Resources) panel, a novel interactive visualization technique designed to help people navigate and interpret groups of resources, exhibitions and annotations by revealing hidden relations such as similarities and references. NEAR is implemented on A•VI•RE, an extended online information repository. A•VI•RE supports a semi-structured collection of exhibitions containing various resources and annotations. Users are encouraged to contribute, share, annotate and interpret resources in the system by building their own exhibitions and annotations. However, it is hard to navigate smoothly and efficiently in A•VI•RE because of its high capacity and complexity. We present a visual panel that implements new navigation and communication approaches that support discovery of implied relations. By quickly scanning and interacting with NEAR, users can see not only implied relations but also potential connections among different data elements. NEAR was tested by several users in the A•VI•RE system and shown to be a supportive navigation tool. In the paper, we further analyze the design, report the evaluation and consider its usage in other applications.
Abstract: Flood management is one of the important fields in
urban storm water management. Floods are influenced by the
increase of huge storm event, or improper planning of the area. This study mainly provides the flood protection in four stages; planning,
flood event, responses and evaluation. However it is most effective then flood protection is considered in planning/design and
evaluation stages since both stages represent the land development of the area. Structural adjustments are often more reliable than nonstructural
adjustments in providing flood protection, however
structural adjustments are constrained by numerous factors such as
political constraints and cost. Therefore it is important to balance
both adjustments with the situation. The technical decisions provided
will have to be approved by the higher-ups who have the power to
decide on the final solution. Costs however, are the biggest factor in
determining the final decision. Therefore this study recommends
flood protection system should have been integrated and enforces
more in the early stages (planning and design) as part of the storm
water management plan. Factors influencing the technical decisions
provided should be reduced as low as possible to avoid a reduction in
the expected performance of the proposed adjustments.
Abstract: S-boxes (Substitution boxes) are keystones of modern
symmetric cryptosystems (block ciphers, as well as stream ciphers).
S-boxes bring nonlinearity to cryptosystems and strengthen their
cryptographic security. They are used for confusion in data security
An S-box satisfies the strict avalanche criterion (SAC), if and only if
for any single input bit of the S-box, the inversion of it changes each
output bit with probability one half. If a function (cryptographic
transformation) is complete, then each output bit depends on all of
the input bits. Thus, if it were possible to find the simplest Boolean
expression for each output bit in terms of the input bits, each of these
expressions would have to contain all of the input bits if the function
is complete. From some important properties of S-box, the most
interesting property SAC (Strict Avalanche Criterion) is presented
and to analyze this property three analysis methods are proposed.
Abstract: Waste management is now a global concern due to its
high environmental impact on climate change. Because of generating
huge amount of waste through our daily activities, managing waste in
an efficient way has become more important than ever. Alternative
Waste Technology (AWT), a new category of waste treatment
technology has been developed for energy recovery in recent years to
address this issue. AWT describes a technology that redirects waste
away from landfill, recovers more useable resources from the waste
flow and reduces the impact on the surroundings. Australia is one of
the largest producers of waste per-capita. A number of AWTs are
using in Australia to produce energy from waste. Presently, it is vital
to identify an appropriate AWT to establish a sustainable waste
management system in Australia. Identification of an appropriate
AWT through Multi-criteria analysis (MCA) of four AWTs by using
five key decision making criteria is presented and discussed in this
paper.
Abstract: Numerical analysis naturally finds applications in all
fields of engineering and the physical sciences, but in the
21st century, the life sciences and even the arts have adopted
elements of scientific computations. The numerical data analysis
became key process in research and development of all the fields [6].
In this paper we have made an attempt to analyze the specified
numerical patterns with reference to the association rule mining
techniques with minimum confidence and minimum support mining
criteria. The extracted rules and analyzed results are graphically
demonstrated. Association rules are a simple but very useful form of
data mining that describe the probabilistic co-occurrence of certain
events within a database [7]. They were originally designed to
analyze market-basket data, in which the likelihood of items being
purchased together within the same transactions are analyzed.
Abstract: Based on the component approach, three kinds of
dynamic load models, including a single –motor model, a two-motor
model and composite load model have been developed for the
stability studies of Khuzestan power system. The study results are
presented in this paper. Voltage instability is a dynamic phenomenon
and therefore requires dynamic representation of the power system
components. Industrial loads contain a large fraction of induction
machines. Several models of different complexity are available for
the description investigations. This study evaluates the dynamic
performances of several dynamic load models in combination with
the dynamics of a load changing transformer. Case study is steel
industrial substation in Khuzestan power systems.
Abstract: Effectiveness of Artificial Neural Networks (ANN)
and Support Vector Machines (SVM) classifiers for fault diagnosis of
rolling element bearings are presented in this paper. The
characteristic features of vibration signals of rotating driveline that
was run in its normal condition and with faults introduced were used
as input to ANN and SVM classifiers. Simple statistical features such
as standard deviation, skewness, kurtosis etc. of the time-domain
vibration signal segments along with peaks of the signal and peak of
power spectral density (PSD) are used as features to input the ANN
and SVM classifier. The effect of preprocessing of the vibration
signal by Discreet Wavelet Transform (DWT) prior to feature
extraction is also studied. It is shown from the experimental results
that the performance of SVM classifier in identification of bearing
condition is better then ANN and pre-processing of vibration signal
by DWT enhances the effectiveness of both ANN and SVM classifier
Abstract: The electromagnetic spectrum is a natural resource
and hence well-organized usage of the limited natural resources is the
necessities for better communication. The present static frequency
allocation schemes cannot accommodate demands of the rapidly
increasing number of higher data rate services. Therefore, dynamic
usage of the spectrum must be distinguished from the static usage to
increase the availability of frequency spectrum. Cognitive radio is not
a single piece of apparatus but it is a technology that can incorporate
components spread across a network. It offers great promise for
improving system efficiency, spectrum utilization, more effective
applications, reduction in interference and reduced complexity of
usage for users. Cognitive radio is aware of its environmental,
internal state, and location, and autonomously adjusts its operations
to achieve designed objectives. It first senses its spectral environment
over a wide frequency band, and then adapts the parameters to
maximize spectrum efficiency with high performance. This paper
only focuses on the analysis of Bit-Error-Rate in cognitive radio by
using Particle Swarm Optimization Algorithm. It is theoretically as
well as practically analyzed and interpreted in the sense of
advantages and drawbacks and how BER affects the efficiency and
performance of the communication system.
Abstract: Thirty six samples from each (aerobic and anoxic)
activated sludge were collected from two wastewater treatment plants
with MBRs in Berlin, Germany. The samples were prepared for count
and definition of fungal isolates; these isolates were purified by
conventional techniques and identified by microscopic examination.
Sixty tow species belonging to 28 genera were isolated from
activated sludge samples under aerobic conditions (28 genera and 58
species) and anoxic conditions (26 genera and 52 species). The
obtained data show that, Aspergillus was found at 94.4% followed by
Penicillium 61.1 %, Fusarium (61.1 %), Trichoderma (44.4 %) and
Geotrichum candidum (41.6 %) species were the most prevalent in all
activated sludge samples. The study confirmed that fungi can thrive
in activated sludge and sporulation, but isolated in different numbers
depending on the effect of aeration system. Some fungal species in
our study are saprophytic, and other a pathogenic to plants and
animals.
Abstract: It is crucial to quantitatively evaluate the treatment of
epilepsy patients. This study was undertaken to test the hypothesis that
compared to the healthy control subjects, the epilepsy patients have
abnormal resting-state connectivity. In this study, we used the
imaginary part of coherency to measure the resting-state connectivity.
The analysis results shown that compared to the healthy control
subjects, epilepsy patients tend to have abnormal rhythm brain
connectivity over their epileptic focus.
Abstract: This calculation focus on the effect of exchange
interaction J and Coulomb interaction U on spin magnetic moments
(ms) of MnO by using the local spin density approximation plus the
Coulomb interaction (LSDA+U) method within full potential linear
muffin-tin orbital (FP-LMTO). Our calculated results indicated that
the spin magnetic moments correlated to J and U. The relevant
results exhibited the increasing spin magnetic moments with
increasing exchange interaction and Coulomb interaction.
Furthermore, equations of spin magnetic moment, which h good
correspondence to the experimental data 4.58μB, are defined ms =
0.11J +4.52μB and ms = 0.03U+4.52μB. So, the relation of J and U
parameter is obtained, it is obviously, J = -0.249U+1.346 eV.
Abstract: Well-being has been given special emphasis in quality
of life. It involves living a meaningful, life satisfaction, stability and
happiness in life. Well-being also concerns the satisfaction of
physical, psychological, social needs and demands of an individual.
The purpose of this study was to validate three-factor measurement
model of well-being using structural equation modeling (SEM). The
conceptions of well-being measured such dimensions as physical,
psychological and social well-being. This study was done based on a
total sample of 650 adolescents from east-coast of peninsular
Malaysia. The Well-Being Scales which was adapted from [1] was
used in this study. The items were hypothesized a priori to have nonzero
loadings on all dimensions in the model. The findings of the
SEM demonstrated that it is a good fitting model which the proposed
model fits the driving theory; (x2df = 1.268; GFI = .994; CFI = .998;
TLI= .996; p = .255; RMSEA = .021). Composite reliability (CR)
was .93 and average variance extracted (AVE) was 58%. The model
in this study fits with the sample of data and well-being is important
to bring sustainable development to the mainstream.
Abstract: Prospective readers can quickly determine whether a document is relevant to their information need if the significant phrases (or keyphrases) in this document are provided. Although keyphrases are useful, not many documents have keyphrases assigned to them, and manually assigning keyphrases to existing documents is costly. Therefore, there is a need for automatic keyphrase extraction. This paper introduces a new domain independent keyphrase extraction algorithm. The algorithm approaches the problem of keyphrase extraction as a classification task, and uses a combination of statistical and computational linguistics techniques, a new set of attributes, and a new machine learning method to distinguish keyphrases from non-keyphrases. The experiments indicate that this algorithm performs better than other keyphrase extraction tools and that it significantly outperforms Microsoft Word 2000-s AutoSummarize feature. The domain independence of this algorithm has also been confirmed in our experiments.
Abstract: The aim of the present paper is to investigate the
interdependency among ego-identity status, autobiographical memory
and cultural life story schema. The study shows considerable
differences between autobiographical memory characteristics and
“family script", which is typical for participants (adolescents, M age
years = 17.84, SD = 1.18, N = 58), with different ego-identity
statuses. Participants with diffused ego-identity status recalled fewer
autobiographical memories. Additionally, this group of participants
recalled fewer events from their parents- life. Participants with
moratorium ego-identity status dated their first recollections to a later
age than others, and recalled fewer memories relating to their
childhood. Participants with achieved identity status recalled more
self-defining memories and events from their parents- life. They used
more functions from the autobiographical memory. There weren-t
any significant differences between the foreclosed identity status
group and the others. These findings support the idea of a
bidirectional relation between culture, memory and self.
Abstract: The objective of this project is to produce computer
assisted instruction(CAI) for welding and brazing in order to
determine the efficiency of the instruction package and the study
accomplishment of learner by studying through computer assisted
instruction for welding and brazing it was examined through the
target group surveyed from the 30 students studying in the two year
of 5-year-academic program, department of production technology
education, faculty of industrial education and technology, king
mongkut-s university of technology thonburi. The result of the
research indicated that the media evaluated by experts and subject
matter quality evaluation of computer assisted instruction for welding
and brazing was in line for the good criterion. The mean of score
evaluated before the study, during the study and after the study was
34.58, 83.33 and 83.43, respectively. The efficiency of the lesson was
83.33/83.43 which was higher than the expected value, 80/80. The
study accomplishment of the learner, who utilizes computer assisted
instruction for welding and brazing as a media, was higher and equal
to the significance statistical level of 95%. The value was 1.669
which was equal to 35.36>1.669. It could be summarized that
computer assisted instruction for welding and brazing was the
efficient media to use for studying and teaching.
Abstract: In this paper the authors propose a protocol, which uses Elliptic Curve Cryptography (ECC) based on the ElGamal-s algorithm, for sending small amounts of data via an authentication server. The innovation of this approach is that there is no need for a symmetric algorithm or a safe communication channel such as SSL. The reason that ECC has been chosen instead of RSA is that it provides a methodology for obtaining high-speed implementations of authentication protocols and encrypted mail techniques while using fewer bits for the keys. This means that ECC systems require smaller chip size and less power consumption. The proposed protocol has been implemented in Java to analyse its features and vulnerabilities in the real world.
Abstract: Data mining uses a variety of techniques each of which
is useful for some particular task. It is important to have a deep
understanding of each technique and be able to perform sophisticated
analysis. In this article we describe a tool built to simulate a variation
of the Kohonen network to perform unsupervised clustering and
support the entire data mining process up to results visualization. A
graphical representation helps the user to find out a strategy to
optimize classification by adding, moving or delete a neuron in order
to change the number of classes. The tool is able to automatically
suggest a strategy to optimize the number of classes optimization, but
also support both tree classifications and semi-lattice organizations of
the classes to give to the users the possibility of passing from one
class to the ones with which it has some aspects in common.
Examples of using tree and semi-lattice classifications are given to
illustrate advantages and problems. The tool is applied to classify
macroeconomic data that report the most developed countries- import
and export. It is possible to classify the countries based on their
economic behaviour and use the tool to characterize the commercial
behaviour of a country in a selected class from the analysis of
positive and negative features that contribute to classes formation.
Possible interrelationships between the classes and their meaning are
also discussed.
Abstract: In automatic manufacturing and assembling of mechanical, electrical and electronic parts one needs to reliably identify the position of components and to extract the information of these components. Data Matrix Codes (DMC) are established by these days in many areas of industrial manufacturing thanks to their concentration of information on small spaces. In today’s usually order-related industry, where increased tracing requirements prevail, they offer further advantages over other identification systems. This underlines in an impressive way the necessity of a robust code reading system for detecting DMC on the components in factories. This paper compares two methods for estimating the angle of orientation of Data Matrix Codes: one method based on the Hough Transform and the other based on the Mean Shift Algorithm. We concentrate on Data Matrix Codes in industrial environment, punched, milled, lasered or etched on different materials in arbitrary orientation.
Abstract: This research proposes an Interactive 3D Experience to
enhance customer value in the fantasy era. As products reach maturity,
they become more similar in the range of functions that they provide.
This leads to competition via reduced retail price and ultimately
reduced profitability. A competitive design method is therefore
needed that can produce higher value products. An Enhanced Value
Experience has been identified that can assist designers to provide
quality products and to give them a unique positioning. On the basis of
this value opportunity, the method of Interactive 3D Experience has
been formulated and applied to the domain of retail furniture. Through
this, customers can create their own personalized styling via the
interactive 3D platform.