Abstract: The impact force of a rockfall is mainly determined by
its moving behavior and velocity, which are contingent on the rock
shape, slope gradient, height, and surface roughness of the moving
path. It is essential to precisely calculate the moving path of the
rockfall in order to effectively minimize and prevent damages caused
by the rockfall. By applying the Colorado Rockfall Simulation
Program (CRSP) program as the analysis tool, this research studies the
influence of three shapes of rock (spherical, cylindrical and discoidal)
and surface roughness on the moving path of a single rockfall. As
revealed in the analysis, in addition to the slope gradient, the geometry
of the falling rock and joint roughness coefficient ( JRC ) of the slope
are the main factors affecting the moving behavior of a rockfall. On a
single flat slope, both the rock-s bounce height and moving velocity
increase as the surface gradient increases, with a critical gradient value
of 1:m = 1 . Bouncing behavior and faster moving velocity occur more
easily when the rock geometry is more oval. A flat piece tends to cause
sliding behavior and is easily influenced by the change of surface
undulation. When JRC
Abstract: Brassinosteroids (BRs) regulate cell elongation,
vascular differentiation, senescence, and stress responses. BRs signal
through the BES1/BZR1 family of transcription factors, which
regulate hundreds of target genes involved in this pathway. In this
research a comprehensive genome-wide analysis was carried out in
BES1/BZR1 gene family in Arabidopsis thaliana, Cucumis sativus,
Vitis vinifera, Glycin max and Brachypodium distachyon.
Specifications of the desired sequences, dot plot and hydropathy plot
were analyzed in the protein and genome sequences of five plant
species. The maximum amino acid length was attributed to protein
sequence Brdic3g with 374aa and the minimum amino acid length
was attributed to protein sequence Gm7g with 163aa. The maximum
Instability index was attributed to protein sequence AT1G19350
equal with 79.99 and the minimum Instability index was attributed to
protein sequence Gm5g equal with 33.22. Aliphatic index of these
protein sequences ranged from 47.82 to 78.79 in Arabidopsis
thaliana, 49.91 to 57.50 in Vitis vinifera, 55.09 to 82.43 in Glycin
max, 54.09 to 54.28 in Brachypodium distachyon 55.36 to 56.83 in
Cucumis sativus. Overall, data obtained from our investigation
contributes a better understanding of the complexity of the
BES1/BZR1 gene family and provides the first step towards directing
future experimental designs to perform systematic analysis of the
functions of the BES1/BZR1 gene family.
Abstract: Biological sequences from different species are called or-thologs if they evolved from a sequence of a common ancestor species and they have the same biological function. Approximations of Kolmogorov complexity or entropy of biological sequences are already well known to be useful in extracting similarity information between such sequences -in the interest, for example, of ortholog detection. As is well known, the exact Kolmogorov complexity is not algorithmically computable. In prac-tice one can approximate it by computable compression methods. How-ever, such compression methods do not provide a good approximation to Kolmogorov complexity for short sequences. Herein is suggested a new ap-proach to overcome the problem that compression approximations may notwork well on short sequences. This approach is inspired by new, conditional computations of Kolmogorov entropy. A main contribution of the empir-ical work described shows the new set of entropy-based machine learning attributes provides good separation between positive (ortholog) and nega-tive (non-ortholog) data - better than with good, previously known alter-natives (which do not employ some means to handle short sequences well).Also empirically compared are the new entropy based attribute set and a number of other, more standard similarity attributes sets commonly used in genomic analysis. The various similarity attributes are evaluated by cross validation, through boosted decision tree induction C5.0, and by Receiver Operating Characteristic (ROC) analysis. The results point to the conclu-sion: the new, entropy based attribute set by itself is not the one giving the best prediction; however, it is the best attribute set for use in improving the other, standard attribute sets when conjoined with them.
Abstract: A novel physico-chemical route to produce few layer graphene nanoribbons with atomically smooth edges is reported, via acid treatment (H2SO4:HNO3) followed by characteristic thermal shock processes involving extremely cold substances. Samples were studied by scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), Raman spectroscopy and X-ray photoelectron spectroscopy. This method demonstrates the importance of having the nanotubes open ended for an efficient uniform unzipping along the nanotube axis. The average dimensions of these nanoribbons are approximately ca. 210 nm wide and consist of few layers, as observed by transmission electron microscopy. The produced nanoribbons exhibit different chiralities, as observed by high resolution transmission electron microscopy. This method is able to provide graphene nanoribbons with atomically smooth edges which could be used in various applications including sensors, gas adsorption materials, composite fillers, among others.
Abstract: In this study, we used shape memory alloys as
actuators to build a biomorphic robot which can imitate the motion of
an earthworm. The robot can be used to explore in a narrow space.
Therefore we chose shape memory alloys as actuators. Because of the
small deformation of a wire shape memory alloy, spiral shape memory
alloys are selected and installed both on the X axis and Y axis (each
axis having two shape memory alloys) to enable the biomorphic robot
to do reciprocating motion. By the mechanism we designed, the robot
can increase the distance as it moves in a duty cycle. In addition, two
shape memory alloys are added to the robot head for controlling right
and left turns. By sending pulses through the I/O card from the
controller, the signals are then amplified by a driver to heat the shape
memory alloys in order to make the SMA shrink to pull the mechanism
to move.
Abstract: Neural processors have shown good results for
detecting a certain character in a given input matrix. In this paper, a
new idead to speed up the operation of neural processors for character
detection is presented. Such processors are designed based on cross
correlation in the frequency domain between the input matrix and the
weights of neural networks. This approach is developed to reduce the
computation steps required by these faster neural networks for the
searching process. The principle of divide and conquer strategy is
applied through image decomposition. Each image is divided into
small in size sub-images and then each one is tested separately by
using a single faster neural processor. Furthermore, faster character
detection is obtained by using parallel processing techniques to test the
resulting sub-images at the same time using the same number of faster
neural networks. In contrast to using only faster neural processors, the
speed up ratio is increased with the size of the input image when using
faster neural processors and image decomposition. Moreover, the
problem of local subimage normalization in the frequency domain is
solved. The effect of image normalization on the speed up ratio of
character detection is discussed. Simulation results show that local
subimage normalization through weight normalization is faster than
subimage normalization in the spatial domain. The overall speed up
ratio of the detection process is increased as the normalization of
weights is done off line.
Abstract: In this paper, we are going to determine the threshold levels of adaptive modulation in a burst by burst CDMA system by a suboptimum method so that the above method attempts to increase the average bit per symbol (BPS) rate of transceiver system by switching between the different modulation modes in variable channel condition. In this method, we choose the minimum values of average bit error rate (BER) and maximum values of average BPS on different values of average channel signal to noise ratio (SNR) and then calculate the relative threshold levels of them, so that when the instantaneous SNR increases, a higher order modulation be employed for increasing throughput and vise-versa when the instantaneous SNR decreases, a lower order modulation be employed for improvement of BER. In transmission step, by this adaptive modulation method, in according to comparison between obtained estimation of pilot symbols and a set of above suboptimum threshold levels, above system chooses one of states no transmission, BPSK, 4QAM and square 16QAM for modulation of data. The expected channel in this paper is a slow Rayleigh fading.
Abstract: In this paper a genetic algorithms approach for solving the linear and quadratic fuzzy equations Ãx̃=B̃ and Ãx̃2 + B̃x̃=C̃ , where Ã, B̃, C̃ and x̃ are fuzzy numbers is proposed by genetic algorithms. Our genetic based method initially starts with a set of random fuzzy solutions. Then in each generation of genetic algorithms, the solution candidates converge more to better fuzzy solution x̃b . In this proposed method the final reached x̃b is not only restricted to fuzzy triangular and it can be fuzzy number.
Abstract: The main aim of this study is to describe and introduce a method of numerical analysis in obtaining approximate solutions for the SIR-SI differential equations (susceptible-infectiverecovered for human populations; susceptible-infective for vector populations) that represent a model for dengue disease transmission. Firstly, we describe the ordinary differential equations for the SIR-SI disease transmission models. Then, we introduce the numerical analysis of solutions of this continuous time, discrete space SIR-SI model by simplifying the continuous time scale to a densely populated, discrete time scale. This is followed by the application of this numerical analysis of solutions of the SIR-SI differential equations to the estimation of relative risk using continuous time, discrete space dengue data of Kuala Lumpur, Malaysia. Finally, we present the results of the analysis, comparing and displaying the results in graphs, table and maps. Results of the numerical analysis of solutions that we implemented offers a useful and potentially superior model for estimating relative risks based on continuous time, discrete space data for vector borne infectious diseases specifically for dengue disease.
Abstract: A new Meta heuristic approach called "Randomized gravitational emulation search algorithm (RGES)" for solving vertex covering problems has been designed. This algorithm is found upon introducing randomization concept along with the two of the four primary parameters -velocity- and -gravity- in physics. A new heuristic operator is introduced in the domain of RGES to maintain feasibility specifically for the vertex covering problem to yield best solutions. The performance of this algorithm has been evaluated on a large set of benchmark problems from OR-library. Computational results showed that the randomized gravitational emulation search algorithm - based heuristic is capable of producing high quality solutions. The performance of this heuristic when compared with other existing heuristic algorithms is found to be excellent in terms of solution quality.
Abstract: This paper addresses the controller synthesis problem of discrete-time switched positive systems with bounded time-varying delays. Based on the switched copositive Lyapunov function approach, some necessary and sufficient conditions for the existence of state-feedback controller are presented as a set of linear programming and linear matrix inequality problems, hence easy to be verified. Another advantage is that the state-feedback law is independent on time-varying delays and initial conditions. A numerical example is provided to illustrate the effectiveness and feasibility of the developed controller.
Abstract: The work presents a development of EN338 strength classes for Strombosia pustulata, Pterygotama crocarpa, Nauclea diderrichii and Entandrophragma cyclindricum Nigerian timber species. The specimens for experimental measurements were obtained from the timber-shed at the famous Panteka market in Kaduna in the northern part of Nigeria. Laboratory experiments were conducted to determine the physical and mechanical properties of the selected timber species in accordance with EN 13183-1 and ASTM D193. The mechanical properties were determined using three point bending test. The generated properties were used to obtain the characteristic values of the material properties in accordance with EN384. The selected timber species were then classified according to EN 338. Strombosia pustulata, Pterygotama crocarpa, Nauclea diderrichii and Entandrophragma cyclindricum were assigned to strength classes D40, C14, D40 and D24 respectively. Other properties such as tensile and compressive strengths parallel and perpendicular to grains, shear strength as well as shear modulus were obtained in accordance with EN 338.
Abstract: Sufficient linear matrix inequalities (LMI) conditions for regularization of discrete-time singular systems are given. Then a new class of regularizing stabilizing controllers is discussed. The proposed controllers are the sum of predictive and memoryless state feedbacks. The predictive controller aims to regularizing the singular system while the memoryless state feedback is designed to stabilize the resulting regularized system. A systematic procedure is given to calculate the controller gains through linear matrix inequalities.
Abstract: In most study fields, a phenomenon may not be
studied directly but it will be examined indirectly by phenomenon
model. Making an accurate model of system, there is attained new
information from modeled phenomenon without any charge, danger,
etc... there have been developed more solutions for describing and
analyzing the recent complicated systems but few of them have
analyzed the performance in the range of system description. Petri
nets are of limited solutions which may make such union. Petri nets
are being applied in problems related to modeling and designing the
systems. Theory of Petri nets allow a system to model
mathematically by a Petri net and analyzing the Petri net can then
determine main information of modeled system-s structure and
dynamic. This information can be used for assessing the performance
of systems and suggesting corrections in the system. In this paper,
beside the introduction of Petri nets, a real case study will be studied
in order to show the application of generalized stochastic Petri nets in
modeling a resource sharing production system and evaluating the
efficiency of its machines and robots. The modeling tool used here is
SHARP software which calculates specific indicators helping to
make decision.
Abstract: The study of morphometric and histologic evolutions
of the Bursa of Fabricus during 27 weeks of post-hashing age,
realized on 88 subjects of broiler chicken they permitted to collect
information about the morpho-histological aspect according to their
post-hashing age; showed the size and the weight of the Bursa of
Fabricius which reach their maximum between the 10th and the 11th
week of age and the physiologic involution phenomena. These
variations are in close relationship to the sexual maturity. These
results can be used in the diagnosis of viral disease such as the
Gumboro disease, Marek disease.
Abstract: The control of oxygen flow rate during growth of
titanium dioxide by mass flow controller in DC plasma sputtering
growth system is studied. The impedance of TiO2 films for inductance
effect is influenced by annealing time and oxygen flow rate. As
annealing time is increased, the inductance of TiO2 film is the more.
The growth condition of optimum and maximum inductance for TiO2
film to serve as sensing device are oxygen flow rate of 15 sccm and
large annealing time. The large inductance of TiO2 film will be
adopted to fabricate the biosensor to obtain the high sensitivity of
sensing in biology.
Abstract: This paper describes reactive neural control used to
generate phototaxis and obstacle avoidance behavior of walking
machines. It utilizes discrete-time neurodynamics and consists of
two main neural modules: neural preprocessing and modular neural
control. The neural preprocessing network acts as a sensory fusion
unit. It filters sensory noise and shapes sensory data to drive the
corresponding reactive behavior. On the other hand, modular neural
control based on a central pattern generator is applied for locomotion
of walking machines. It coordinates leg movements and can generate
omnidirectional walking. As a result, through a sensorimotor loop this
reactive neural controller enables the machines to explore a dynamic
environment by avoiding obstacles, turn toward a light source, and
then stop near to it.
Abstract: The aim of this paper is the analysis and preservation of lime kilns, focusing on the structure, construction, and functionality of vertical shaft lime kilns of the Cap Corse in Corsica. Plans and sections of two lime kilns are presented in detail, providing an overall picture of this specific industrial heritage. The potential damage areas are identified performing structural analysis of a lime kiln using the finite element method. A restoration and strengthening technique that satisfies the directions of the Charter of Venice is presented using post-tensioning tendons. Recommendations are given to preserve and promote these important historical structures integrating them into the custom footpath.
Abstract: The H.264/AVC video coding standard contains a number of advanced features. Ones of the new features introduced in this standard is the multiple intramode prediction. Its function exploits directional spatial correlation with adjacent block for intra prediction. With this new features, intra coding of H.264/AVC offers a considerably higher improvement in coding efficiency compared to other compression standard, but computational complexity is increased significantly when brut force rate distortion optimization (RDO) algorithm is used. In this paper, we propose a new fast intra prediction mode decision method for the complexity reduction of H.264 video coding. for luma intra prediction, the proposed method consists of two step: in the first step, we make the RDO for four mode of intra 4x4 block, based the distribution of RDO cost of those modes and the idea that the fort correlation with adjacent mode, we select the best mode of intra 4x4 block. In the second step, we based the fact that the dominating direction of a smaller block is similar to that of bigger block, the candidate modes of 8x8 blocks and 16x16 macroblocks are determined. So, in case of chroma intra prediction, the variance of the chroma pixel values is much smaller than that of luma ones, since our proposed uses only the mode DC. Experimental results show that the new fast intra mode decision algorithm increases the speed of intra coding significantly with negligible loss of PSNR.
Abstract: since in natural accidents, facilities that relate to this vita element are underground so, it is difficult to find quickly some right, exact and definite information about water utilities. There fore, this article has done operationally in Boukan city in Western Azarbaijan of Iran and it tries to represent operation and capabilities of Geographical Information system (GIS) in urban water management at the time of natural accidents. Structure of this article is that firstly it has established a comprehensive data base related to water utilities by collecting, entering, saving and data management, then by modeling water utilities we have practically considered its operational aspects related to water utility problems in urban regions.