Abstract: Suspended cable structures are most preferable for large spans covering due to rational use of structural materials, but the problem of suspended cable structures is initial shape change under the action of non-symmetrical load. The problem can be solved by increasing of relation of dead weight and imposed load, but this methods cause increasing of materials consumption.Prestressed cable truss usage is another way how the problem of shape change under the action of non-symmetrical load can be fixed. The better results can be achieved if we replace top chord with cable truss with cross web. Rational structure of the cable truss for prestressed cable truss top chord was developed using optimization realized in FEM program ANSYS 12 environment. Single cable and cable truss model work was discovered.Analytical and model testing results indicate, that usage of cable truss with the cross web as a top chord of prestressed cable truss instead of single cable allows to reduce total displacements by 13-16% in the case of non-symmetrical load. In case of uniformly distributed load single cable is preferable.
Abstract: Fiber optic sensor technology offers the possibility of
sensing different parameters like strain, temperature, pressure in
harsh environment and remote locations. these kinds of sensors
modulates some features of the light wave in an optical fiber such an
intensity and phase or use optical fiber as a medium for transmitting
the measurement information.
The advantages of fiber optic sensors in contrast to conventional
electrical ones make them popular in different applications and now a
day they consider as a key component in improving industrial
processes, quality control systems, medical diagnostics, and
preventing and controlling general process abnormalities.
This paper is an introduction to fiber optic sensor technology and
some of the applications that make this branch of optic technology,
which is still in its early infancy, an interesting field.
Abstract: Non-profit organizations, especially religious-based
institutions, have long played a very important role in society.
Nevertheless, scandals such as inefficient management and the use of
unlawful fundraising activities have raised questions regarding the
governance and accountability of these organizations. As such, the
issues have attracted considerable research interest. However, there is
still limited research on accountability in religious based
organizations, especially in the context of Islamic religious
organizations. Hence, the purpose of this paper is to discuss the
issues of accounting and accountability in religious organizations,
specifically in Islamic religious establishments. The paper starts by
looking at the conventional meaning and concept of accountability.
This is followed by a discussion of the principles of accountability
within the Islamic framework. In so doing, the history of the role of
accounting within Muslim society and also the differences between
the Islamic and conventional view of accountability are reviewed.
Insights gained from previous research on accountability in faith
based organizations are also discussed
Abstract: As open innovation has received increasingly attention
in the management of innovation, the importance of identifying
potential partnership is increasing. This paper suggests a methodology
to identify the interested parties as one of Innovation intermediaries to
enable open innovation with patent network. To implement the
methodology, multi-stage patent citation analysis such as
bibliographic coupling and information visualization method such as
keyword vector mapping are utilized. This paper has contribution in
that it can present meaningful collaboration keywords to identified
potential partners in network since not only citation information but
also patent textual information is used.
Abstract: Number of documents being created increases at an
increasing pace while most of them being in already known topics
and little of them introducing new concepts. This fact has started a
new era in information retrieval discipline where the requirements
have their own specialties. That is digging into topics and concepts
and finding out subtopics or relations between topics. Up to now IR
researches were interested in retrieving documents about a general
topic or clustering documents under generic subjects. However these
conventional approaches can-t go deep into content of documents
which makes it difficult for people to reach to right documents they
were searching. So we need new ways of mining document sets
where the critic point is to know much about the contents of the
documents. As a solution we are proposing to enhance LSI, one of
the proven IR techniques by supporting its vector space with n-gram
forms of words. Positive results we have obtained are shown in two
different application area of IR domain; querying a document
database, clustering documents in the document database.
Abstract: Amphawa is the most popular weekend destination for
both domestic and international tourists in Thailand. More than 112
homestays and resorts have been developed along the water
resources. This research aims to initiate appropriate environmental
management system for riverside tourist accommodations in
Amphawa by investigating current environmental characteristics.
Eighty-eight riverside tourist accommodations were survey from
specific questionnaire, GPS data were also gathered for spatial
analysis. The results revealed that the accommodations are welled
manage in regards to some environmental aspects. In order to reduce
economic costs, energy efficiency equipment is utilized. A substantial
number of tourist accommodations encouraged waste separation,
followed by transfer to local administration organization. Grease
traps also utilized in order to decrease chemical discharged, grease
and oil from canteen and restaurants on natural environment. The
most notable mitigation is to initiate environmental friendly cleansers
for tourist accommodation along the riverside in tourism destinations.
Abstract: A considerable amount of energy is consumed during
transmission and reception of messages in a wireless mesh network
(WMN). Reducing per-node transmission power would greatly
increase the network lifetime via power conservation in addition to
increasing the network capacity via better spatial bandwidth reuse. In
this work, the problem of topology control in a hybrid WMN of
heterogeneous wireless devices with varying maximum transmission
ranges is considered. A localized distributed topology control
algorithm is presented which calculates the optimal transmission
power so that (1) network connectivity is maintained (2) node
transmission power is reduced to cover only the nearest neighbours
(3) networks lifetime is extended. Simulations and analysis of results
are carried out in the NS-2 environment to demonstrate the
correctness and effectiveness of the proposed algorithm.
Abstract: Logic based methods for learning from structured data
is limited w.r.t. handling large search spaces, preventing large-sized
substructures from being considered by the resulting classifiers. A
novel approach to learning from structured data is introduced that
employs a structure transformation method, called finger printing, for
addressing these limitations. The method, which generates features
corresponding to arbitrarily complex substructures, is implemented in
a system, called DIFFER. The method is demonstrated to perform
comparably to an existing state-of-art method on some benchmark
data sets without requiring restrictions on the search space.
Furthermore, learning from the union of features generated by finger
printing and the previous method outperforms learning from each
individual set of features on all benchmark data sets, demonstrating
the benefit of developing complementary, rather than competing,
methods for structure classification.
Abstract: The distillation process in the general sense is a
relatively simple technique from the standpoints of its principles.
When dedicating distillation to water treatment and specifically
producing fresh water from sea, ocean and/ briny waters it is
interesting to notice that distillation has no limitations or domains of
applicability regarding the nature or the type of the feedstock water.
This is not the case however for other techniques that are
technologically quite complex, necessitate bigger capital investments
and are limited in their usability. In a previous paper we have
explored some of the effects of temperature on yield. In this paper,
we continue building onto that knowledge base and focus on the
effects of several additional engineering and design variables on
productivity.
Abstract: Organic farmers across Saskatchewan face soil
phosphorus (P) shortages. Due to the restriction on inputs in organic
systems, farmers rely on crop rotation and naturally-occurring
arbuscular mycorrhizal fungi (AMF) for plant P supply. Crop rotation
is important for disease, pest, and weed management. Crops that are
not colonized by AMF (non-mycorrhizal) can decrease colonization
of a following crop. An experiment was performed to quantify soil P
cycling in four cropping sequences under organic management and
determine if mustard (non-mycorrhizal) was delaying the
colonization of subsequent wheat. Soils from the four cropping
sequences were measured for inorganic soil P (Pi), AMF spore
density (SD), phospholipid fatty acid analysis (PLFA, for AMF
biomarker counts), and alkaline phosphatase activity (ALPase,
related to AMF metabolic activity). Plants were measured for AMF
colonization and P content and uptake of above-ground biomass. A
lack of difference in AMF activity indicated that mustard was not
depressing colonization. Instead, AMF colonization was largely
determined by crop type and crop rotation.
Abstract: In this paper we propose a new content-weighted
method for full reference (FR) video quality control using a region of
interest (ROI) and wherein two-component weighted metrics for Deaf
People Video Communication. In our approach, an image is
partitioned into region of interest and into region "dry-as-dust", then
region of interest is partitioned into two parts: edges and background
(smooth regions), while the another methods (metrics) combined and
weighted three or more parts as edges, edges errors, texture, smooth
regions, blur, block distance etc. as we proposed. Using another idea
that different image regions from deaf people video communication
have different perceptual significance relative to quality. Intensity
edges certainly contain considerable image information and are
perceptually significant.
Abstract: According to celebrated Hurwitz theorem, there exists
four division algebras consisting of R (real numbers), C (complex
numbers), H (quaternions) and O (octonions). Keeping in view
the utility of octonion variable we have tried to extend the three
dimensional vector analysis to seven dimensional one. Starting with
the scalar and vector product in seven dimensions, we have redefined
the gradient, divergence and curl in seven dimension. It is shown
that the identity n(n - 1)(n - 3)(n - 7) = 0 is satisfied only
for 0, 1, 3 and 7 dimensional vectors. We have tried to write all
the vector inequalities and formulas in terms of seven dimensions
and it is shown that same formulas loose their meaning in seven
dimensions due to non-associativity of octonions. The vector formulas
are retained only if we put certain restrictions on octonions and split
octonions.
Abstract: The increasing recognition of the need for education to be closely aligned with team playing, project based learning and problem solving approaches has increase the interest in collaborative learning among university and college instructors. Using online collaboration learning in learning can enhance the outcome and achievement of students as well as improve their communication, critical thinking and personnel skills. The current research aims at examining the effect of OCL on the student's achievement at Kingdom of Bahrain. Numbers of objectives were set to achieve the aim of the research include: investigating the current situation regarding the collaborative learning and OCL at the Kingdom of Bahrain by identifying the advantages and effectiveness of OCL as a learning tool over traditional learning, examining the factors that affect OCL as well as examining the impact of OCL on the student's achievement. To achieve these objectives, quantitative method was adopted. Two hundred and thirty one questionnaires were distributed to students in different local and private universities at Kingdom of Bahrain. The findings of the research show that most of the students prefer to use FTFCL in learning and that OCL is already adopted in some universities especially in University of Bahrain. Moreover, the most factors affecting the adopted OCL are perceived readiness, and guidance and support.
Abstract: To create a solution for a specific problem in machine
learning, the solution is constructed from the data or by use a search
method. Genetic algorithms are a model of machine learning that can
be used to find nearest optimal solution. While the great advantage of
genetic algorithms is the fact that they find a solution through
evolution, this is also the biggest disadvantage. Evolution is inductive,
in nature life does not evolve towards a good solution but it evolves
away from bad circumstances. This can cause a species to evolve into
an evolutionary dead end. In order to reduce the effect of this
disadvantage we propose a new a learning tool (criteria) which can be
included into the genetic algorithms generations to compare the
previous population and the current population and then decide
whether is effective to continue with the previous population or the
current population, the proposed learning tool is called as Keeping
Efficient Population (KEP). We applied a GA based on KEP to the
production line layout problem, as a result KEP keep the evaluation
direction increases and stops any deviation in the evaluation.
Abstract: This paper deals with an adaptive multiuser detector for direct sequence code division multiple-access (DS-CDMA) systems. A modified receiver, precombinig LMMSE is considered under time varying channel environment. Detector updating is performed with two criterions, mean square estimation (MSE) and MOE optimization technique. The adaptive implementation issues of these two schemes are quite different. MSE criterion updates the filter weights by minimizing error between data vector and adaptive vector. MOE criterion together with canonical representation of the detector results in a constrained optimization problem. Even though the canonical representation is very complicated under time varying channels, it is analyzed with assumption of average power profile of multipath replicas of user of interest. The performance of both schemes is studied for practical SNR conditions. Results show that for poor SNR, MSE precombining LMMSE is better than the blind precombining LMMSE but for greater SNR, MOE scheme outperforms with better result.
Abstract: We present here the results for a comparative study of
some techniques, available in the literature, related to the relevance
feedback mechanism in the case of a short-term learning. Only one
method among those considered here is belonging to the data mining
field which is the K-nearest neighbors algorithm (KNN) while the
rest of the methods is related purely to the information retrieval field
and they fall under the purview of the following three major axes:
Shifting query, Feature Weighting and the optimization of the
parameters of similarity metric. As a contribution, and in addition to
the comparative purpose, we propose a new version of the KNN
algorithm referred to as an incremental KNN which is distinct from
the original version in the sense that besides the influence of the
seeds, the rate of the actual target image is influenced also by the
images already rated. The results presented here have been obtained
after experiments conducted on the Wang database for one iteration
and utilizing color moments on the RGB space. This compact
descriptor, Color Moments, is adequate for the efficiency purposes
needed in the case of interactive systems. The results obtained allow
us to claim that the proposed algorithm proves good results; it even
outperforms a wide range of techniques available in the literature.
Abstract: The rapid expansion of the web is causing the
constant growth of information, leading to several problems such as
increased difficulty of extracting potentially useful knowledge. Web
content mining confronts this problem gathering explicit information
from different web sites for its access and knowledge discovery.
Query interfaces of web databases share common building blocks.
After extracting information with parsing approach, we use a new
data mining algorithm to match a large number of schemas in
databases at a time. Using this algorithm increases the speed of
information matching. In addition, instead of simple 1:1 matching,
they do complex (m:n) matching between query interfaces. In this
paper we present a novel correlation mining algorithm that matches
correlated attributes with smaller cost. This algorithm uses Jaccard
measure to distinguish positive and negative correlated attributes.
After that, system matches the user query with different query
interfaces in special domain and finally chooses the nearest query
interface with user query to answer to it.
Abstract: Although the level crossing concept has been the subject of intensive investigation over the last few years, certain problems of great interest remain unsolved. One of these concern is distribution of threshold levels. This paper presents a new threshold level allocation schemes for level crossing based on nonuniform sampling. Intuitively, it is more reasonable if the information rich regions of the signal are sampled finer and those with sparse information are sampled coarser. To achieve this objective, we propose non-linear quantization functions which dynamically assign the number of quantization levels depending on the importance of the given amplitude range. Two new approaches to determine the importance of the given amplitude segment are presented. The proposed methods are based on exponential and logarithmic functions. Various aspects of proposed techniques are discussed and experimentally validated. Its efficacy is investigated by comparison with uniform sampling.
Abstract: Application of Information Technology (IT) has
revolutionized the functioning of business all over the world. Its
impact has been felt mostly among the information of dependent
industries. Tourism is one of such industry. The conceptual
framework in this study represents an innovation of travel
information searching system on mobile devices which is used as
tools to deliver travel information (such as hotels, restaurants, tourist
attractions and souvenir shops) for each user by travelers
segmentation based on data mining technique to segment the tourists-
behavior patterns then match them with tourism products and
services. This system innovation is designed to be a knowledge
incremental learning. It is a marketing strategy to support business to
respond traveler-s demand effectively.
Abstract: Ethnicity identification of face images is of interest in
many areas of application, but existing methods are few and limited.
This paper presents a fusion scheme that uses block-based uniform
local binary patterns and Haar wavelet transform to combine local
and global features. In particular, the LL subband coefficients of the
whole face are fused with the histograms of uniform local binary
patterns from block partitions of the face. We applied the principal
component analysis on the fused features and managed to reduce the
dimensionality of the feature space from 536 down to around 15
without sacrificing too much accuracy. We have conducted a number
of preliminary experiments using a collection of 746 subject face
images. The test results show good accuracy and demonstrate the
potential of fusing global and local features. The fusion approach is
robust, making it easy to further improve the identification at both
feature and score levels.