Abstract: Several trillion cigarettes produced worldwide annually lead to many thousands of kilograms of toxic waste. Cigarette butts (CBs) accumulate in the environment due to the poor biodegradability of the cellulose acetate filters. This paper presents some of the results from a continuing study on recycling CBs into fired clay bricks. Physico-mechanical properties of fired clay bricks manufactured with different percentages of CBs are reported and discussed. The results show that the density of fired bricks was reduced by up to 30 %, depending on the percentage of CBs incorporated into the raw materials. Similarly, the compressive strength of bricks tested decreased according to the percentage of CBs included in the mix. The thermal conductivity performance of bricks was improved by 51 and 58 % for 5 and 10 % CBs content respectively. Leaching tests were carried out to investigate the levels of possible leachates of heavy metals from the manufactured clay-CB bricks. The results revealed trace amounts of heavy metals.
Abstract: Sandwich panels are widely used in the construction
industry for their ease of assembly, light weight and efficient thermal
performance. They are composed of two RC thin outer layers
separated by an insulating inner layer. In this research the inner
insulating layer is made of lightweight Autoclaved Aerated Concrete
(AAC) blocks which has good thermal insulation properties and yet
possess reasonable mechanical strength. The shear strength of the
AAC infill is relied upon to replace the traditionally used insulating
foam and to provide the shear capacity of the panel. A
comprehensive experimental program was conducted on full scale
sandwich panels subjected to bending. In this paper, detailed
numerical modeling of the tested sandwich panels is reported. Nonlinear
3-D finite element modeling of the composite action of the
sandwich panel is developed using ANSYS. Solid elements with
different crashing and cracking capabilities and different constitutive
laws were selected for the concrete and the AAC. Contact interface
elements are used in this research to adequately model the shear
transfer at the interface between the different layers. The numerical
results showed good correlation with the experimental ones
indicating the adequacy of the model in estimating the loading
capacity of panels.
Abstract: This paper presents the findings of an
experimental investigation to study the effect of alkali content
in geopolymer mortar specimens exposed to sulphuric acid.
Geopolymer mortar specimens were manufactured from Class F fly
ash by activation with a mixture of sodium hydroxide and sodium
silicate solution containing 5% to 8% Na2O. Durability of specimens
were assessed by immersing them in 10% sulphuric acid solution and
periodically monitoring surface deterioration and depth of
dealkalization, changes in weight and residual compressive strength
over a period of 24 weeks. Microstructural changes in the specimens
were studied with Scanning electron microscopy (SEM) and EDAX.
Alkali content in the activator solution significantly affects the
durability of fly ash based geopolymer mortars in sulphuric acid.
Specimens manufactured with higher alkali content performed better
than those manufactured with lower alkali content. After 24 weeks in
sulphuric acid, specimen with 8% alkali still recorded a residual
strength as high as 55%.
Abstract: Neighborhood Rough Sets (NRS) has been proven to
be an efficient tool for heterogeneous attribute reduction. However,
most of researches are focused on dealing with complete and noiseless
data. Factually, most of the information systems are noisy, namely,
filled with incomplete data and inconsistent data. In this paper, we
introduce a generalized neighborhood rough sets model, called
VPTNRS, to deal with the problem of heterogeneous attribute
reduction in noisy system. We generalize classical NRS model with
tolerance neighborhood relation and the probabilistic theory.
Furthermore, we use the neighborhood dependency to evaluate the
significance of a subset of heterogeneous attributes and construct a
forward greedy algorithm for attribute reduction based on it.
Experimental results show that the model is efficient to deal with noisy
data.
Abstract: Soils are normally dried in either a convection oven or stove. Laboratory moisture content testing indicated that the typical drying durations for a convection oven were, 24 hours. The purpose of this study was to determine the accuracy and soil drying duration of both, moisture content and liquid limit using microwave radiation. The soils were tested with both, convection and microwave ovens. The convection oven was considered to produce the true values for both, natural moisture content and liquid limit of soils; it was, therefore, used as a basis for comparison for the results of the microwave ovens. The samples used in this study were obtained from different projects of Consulting Engineering Bureau of College of Engineering of Sulaimani University. These samples were collected from different locations and at the different depths and consist mostly of brown and light brown clay and silty clay. A total of 102 samples were prepared. 26 of them were tested for natural moisture determination, while the other 76 were used for liquid limits determination
Abstract: Image synthesis is an important area in image processing.
To synthesize images various systems are proposed in
the literature. In this paper, we propose a bio-inspired system to
synthesize image and to study the generating power of the system, we
define the class of languages generated by our system. We call image
as array in this paper. We use a primitive called iso-array to synthesize
image/array. The operation is double splicing on iso-arrays. The
double splicing operation is used in DNA computing and we use
this to synthesize image. A comparison of the family of languages
generated by the proposed self restricted double splicing systems on
iso-arrays with the existing family of local iso-picture languages is
made. Certain closure properties such as union, concatenation and
rotation are studied for the family of languages generated by the
proposed model.
Abstract: The paper describes a new approach for fingerprint
classification, based on the distribution of local features (minute
details or minutiae) of the fingerprints. The main advantage is that
fingerprint classification provides an indexing scheme to facilitate
efficient matching in a large fingerprint database. A set of rules based
on heuristic approach has been proposed. The area around the core
point is treated as the area of interest for extracting the minutiae
features as there are substantial variations around the core point as
compared to the areas away from the core point. The core point in a
fingerprint has been located at a point where there is maximum
curvature. The experimental results report an overall average
accuracy of 86.57 % in fingerprint classification.
Abstract: A new approach for facial expressions recognition based on face context and adaptively weighted sub-pattern PCA (Aw-SpPCA) has been presented in this paper. The facial region and others part of the body have been segmented from the complex environment based on skin color model. An algorithm has been proposed to accurate detection of face region from the segmented image based on constant ratio of height and width of face (δ= 1.618). The paper also discusses on new concept to detect the eye and mouth position. The desired part of the face has been cropped to analysis the expression of a person. Unlike PCA based on a whole image pattern, Aw-SpPCA operates directly on its sub patterns partitioned from an original whole pattern and separately extracts features from them. Aw-SpPCA can adaptively compute the contributions of each part and a classification task in order to enhance the robustness to both expression and illumination variations. Experiments on single standard face with five types of facial expression database shows that the proposed method is competitive.
Abstract: Rarefied gas flows are often occurred in micro electro
mechanical systems and classical CFD could not precisely anticipate
the flow and thermal behavior due to the high Knudsen number.
Therefore, the heat transfer and the fluid dynamics characteristics of
rarefied gas flows in both a two-dimensional simple microchannel
and geometry similar to single Knudsen compressor have been
investigated with a goal of increasing performance of a actual
Knudsen compressor by using a particle simulation method. Thermal
transpiration and thermal creep, which are rarefied gas dynamic
phenomena, that cause movement of the flow from less to higher
temperature is generated by using two different longitude temperature
gradients (Linear, Step) along the walls of the flow microchannel. In
this study the influence of amount of temperature gradient and
governing pressure in various Knudsen numbers and length-to-height
ratios have been examined.
Abstract: Timetabling problems are often hard and timeconsuming
to solve. Most of the methods of solving them concern
only one problem instance or class. This paper describes a universal
method for solving large, highly constrained timetabling problems
from different domains. The solution is based on evolutionary
algorithm-s framework and operates on two levels – first-level
evolutionary algorithm tries to find a solution basing on given set of
operating parameters, second-level algorithm is used to establish
those parameters. Tabu search is employed to speed up the solution
finding process on first level. The method has been used to solve
three different timetabling problems with promising results.
Abstract: In this paper, the discrete-time fuzzy BAM neural network with delays and impulses is studied. Sufficient conditions are obtained for the existence and global stability of a unique equilibrium of this class of fuzzy BAM neural networks with Lipschitzian activation functions without assuming their boundedness, monotonicity or differentiability and subjected to impulsive state displacements at fixed instants of time. Some numerical examples are given to demonstrate the effectiveness of the obtained results.
Abstract: In this paper we considered the Neumann problem for
the fourth order differential equation. First we define the weighted Sobolev space
2 Wα and generalized solution for this equation. Then we consider the existence and uniqueness of the generalized solution,
as well as give the description of the spectrum and of the domain of definition of the corresponding operator.
Abstract: Obtaining labeled data in supervised learning is often
difficult and expensive, and thus the trained learning algorithm tends
to be overfitting due to small number of training data. As a result,
some researchers have focused on using unlabeled data which may
not necessary to follow the same generative distribution as the labeled
data to construct a high-level feature for improving performance on
supervised learning tasks. In this paper, we investigate the impact of
the relationship between unlabeled and labeled data for classification
performance. Specifically, we will apply difference unlabeled data
which have different degrees of relation to the labeled data for
handwritten digit classification task based on MNIST dataset. Our
experimental results show that the higher the degree of relation
between unlabeled and labeled data, the better the classification
performance. Although the unlabeled data that is completely from
different generative distribution to the labeled data provides the lowest
classification performance, we still achieve high classification performance.
This leads to expanding the applicability of the supervised
learning algorithms using unsupervised learning.
Abstract: In this article a modification of the algorithm of the fuzzy ART network, aiming at returning it supervised is carried out. It consists of the search for the comparison, training and vigilance parameters giving the minimum quadratic distances between the output of the training base and those obtained by the network. The same process is applied for the determination of the parameters of the fuzzy ARTMAP giving the most powerful network. The modification consist in making learn the fuzzy ARTMAP a base of examples not only once as it is of use, but as many time as its architecture is in evolution or than the objective error is not reached . In this way, we don-t worry about the values to impose on the eight (08) parameters of the network. To evaluate each one of these three networks modified, a comparison of their performances is carried out. As application we carried out a classification of the image of Algiers-s bay taken by SPOT XS. We use as criterion of evaluation the training duration, the mean square error (MSE) in step control and the rate of good classification per class. The results of this study presented as curves, tables and images show that modified fuzzy ARTMAP presents the best compromise quality/computing time.
Abstract: This article attempts to analyze functionally graded beam thermal buckling along with piezoelectric layers applying based on the third order shearing deformation theory considering various boundary conditions. The beam properties are assumed to vary continuously from the lower surface to the upper surface of the beam. The equilibrium equations are derived using the total potential energy equations, Euler equations, piezoelectric material constitutive equations and third order shear deformation theory assumptions. In order to fulfill such an aim, at first functionally graded beam with piezoelectric layers applying the third order shearing deformation theory along with clamped -clamped boundary conditions are thoroughly analyzed, and then following making sure of the correctness of all the equations, the very same beam is analyzed with piezoelectric layers through simply-simply and simply-clamped boundary conditions. In this article buckling critical temperature for functionally graded beam is derived in two different ways, without piezoelectric layer and with piezoelectric layer and the results are compared together. Finally, all the conclusions obtained will be compared and contrasted with the same samples in the same and distinguished conditions through tables and charts. It would be noteworthy that in this article, the software MAPLE has been applied in order to do the numeral calculations.
Abstract: There are many kinds of metal borates found not only
in nature but also synthesized in the laboratory such as magnesium
borates. Due to its excellent properties, as remarkable ceramic
materials, they have also application areas in anti-wear and friction
reducing additives as well as electro-conductive treating agents. The
synthesis of magnesium borate powders can be fulfilled simply with
two different methods, hydrothermal and thermal synthesis.
Microwave assisted method, also another way of producing
magnesium borate, can be classified into thermal synthesis because of
using the principles of solid state synthesis. It also contributes
producing particles with small size and high purity in nano-size
material synthesize. In this study the production of magnesium
borates, are aimed using MgCl2.6H2O and H3BO3. The identification
of both starting materials and products were made by the equipments
of, X-Ray Diffraction (XRD) and Fourier Transform Infrared
Spectroscopy (FT-IR). After several synthesis steps magnesium
borates were synthesized and characterized by XRD and FT-IR, as
well.
Abstract: Domineering is a classic two-player combinatorial
game usually played on a rectangular board. Three-player Domineering
is the three-player version of Domineering played on a three
dimensional board. Experimental results are presented for x×y ×z
boards with x + y + z < 10 and x, y, z ≥ 2. Also, some theoretical
results are shown for 2 × 2 × n board with n even and n ≥ 4.
Abstract: Sparse representation which can represent high dimensional
data effectively has been successfully used in computer vision
and pattern recognition problems. However, it doesn-t consider the
label information of data samples. To overcome this limitation,
we develop a novel dimensionality reduction algorithm namely
dscriminatively regularized sparse subspace learning(DR-SSL) in this
paper. The proposed DR-SSL algorithm can not only make use of
the sparse representation to model the data, but also can effective
employ the label information to guide the procedure of dimensionality
reduction. In addition,the presented algorithm can effectively deal
with the out-of-sample problem.The experiments on gene-expression
data sets show that the proposed algorithm is an effective tool for
dimensionality reduction and gene-expression data classification.
Abstract: A learning management system (commonly
abbreviated as LMS) is a software application for the administration,
documentation, tracking, and reporting of training programs,
classroom and online events, e-learning programs, and training
content (Ellis 2009). (Hall 2003) defines an LMS as \"software that
automates the administration of training events. All Learning
Management Systems manage the log-in of registered users, manage
course catalogs, record data from learners, and provide reports to
management\". Evidence of the worldwide spread of e-learning in
recent years is easy to obtain. In April 2003, no fewer than 66,000
fully online courses and 1,200 complete online programs were listed
on the TeleCampus portal from TeleEducation (Paulsen 2003). In the
report \" The US market in the Self-paced eLearning Products and
Services:2010-2015 Forecast and Analysis\" The number of student
taken classes exclusively online will be nearly equal (1% less) to the
number taken classes exclusively in physical campuses. Number of
student taken online course will increase from 1.37 million in 2010 to
3.86 million in 2015 in USA. In another report by The Sloan
Consortium three-quarters of institutions report that the economic
downturn has increased demand for online courses and programs.
Abstract: This paper proposes an improvement method of classification
efficiency in a classification model. The model is used
in a risk search system and extracts specific labels from articles
posted at bulletin board sites. The system can analyze the important
discussions composed of the articles. The improvement method
introduces ensemble learning methods that use multiple classification
models. Also, it introduces expressions related to the specific labels
into generation of word vectors. The paper applies the improvement
method to articles collected from three bulletin board sites selected
by users and verifies the effectiveness of the improvement method.