Abstract: In this research paper we have presented control
architecture for robotic arm movement and trajectory planning using
Fuzzy Logic (FL) and Genetic Algorithms (GAs). This architecture is
used to compensate the uncertainties like; movement, friction and
settling time in robotic arm movement. The genetic algorithms and
fuzzy logic is used to meet the objective of optimal control
movement of robotic arm. This proposed technique represents a
general model for redundant structures and may extend to other
structures. Results show optimal angular movement of joints as result
of evolutionary process. This technique has edge over the other
techniques as minimum mathematics complexity used.
Abstract: The aim of this research is to use artificial neural networks computing technology for estimating the net heating value (NHV) of crude oil by its Properties. The approach is based on training the neural network simulator uses back-propagation as the learning algorithm for a predefined range of analytically generated well test response. The network with 8 neurons in one hidden layer was selected and prediction of this network has been good agreement with experimental data.
Abstract: The purpose of this study is to identify ideal urban
design elements of waterfronts and to analyze the differences in users-
cognition among these elements. This study follows three steps as
following: first is identifying the urban design elements of waterfronts
from literature review and second is evaluating intended users-
cognition of urban design elements in urban waterfronts. Lastly, third
is analyzing the users- cognition differences. As the result, evaluations
of waterfront areas by users show similar features that non-waterfront
urban design elements contain the highest degree of importance. This
indicates the difference of users- cognition has dimensions of
frequency and distance, and demonstrates differences in the aspect of
importance than of satisfaction. Multi-Dimensional Scaling Method
verifies differences among their cognition. This study provides
elements to increase satisfaction of users from differences of their
cognition on design elements for waterfronts. It also suggests
implications on elements when waterfronts are built.
Abstract: Load forecasting has always been the essential part of
an efficient power system operation and planning. A novel approach
based on support vector machines is proposed in this paper for annual
power load forecasting. Different kernel functions are selected to
construct a combinatorial algorithm. The performance of the new
model is evaluated with a real-world dataset, and compared with two
neural networks and some traditional forecasting techniques. The
results show that the proposed method exhibits superior performance.
Abstract: Rice husk is one of the alternative fuels for Thailand because of its high potential and environmental benefits. Nonetheless, the environmental profile of the electricity production from rice husk must be assessed to ensure reduced environmental damage. A 10 MW pilot plant using rice husk as feedstock is the study site. The environmental impacts from rice husk power plant are evaluated by using the Life Cycle Assessment (LCA) methodology. Energy, material and carbon balances have been determined for tracing the system flow. Carbon closure has been used for describing of the net amount of CO2 released from the system in relation to the amount being recycled between the power plant and the CO2 adsorbed by rice husk. The transportation of rice husk to the power plant has significant on global warming, but not on acidification and photo-oxidant formation. The results showed that the impact potentials from rice husk power plant are lesser than the conventional plants for most of the categories considered; except the photo-oxidant formation potential from CO. The high CO from rice husk power plant may be due to low boiler efficiency and high moisture content in rice husk. The performance of the study site can be enhanced by improving the combustion efficiency.
Abstract: Average current analysis checking the impact of
current flow is very important to guarantee the reliability of
semiconductor systems. As semiconductor process technologies
improve, the coupling capacitance often become bigger than self
capacitances. In this paper, we propose an analytic technique for
analyzing average current on interconnects in multi-conductor
structures. The proposed technique has shown to yield the acceptable
errors compared to HSPICE results while providing computational
efficiency.
Abstract: The balanced Hamiltonian cycle problemis a quiet new topic of graph theorem. Given a graph G = (V, E), whose edge set can be partitioned into k dimensions, for positive integer k and a Hamiltonian cycle C on G. The set of all i-dimensional edge of C, which is a subset by E(C), is denoted as Ei(C).
Abstract: This paper demonstrates the application of craziness based particle swarm optimization (CRPSO) technique for designing the 8th order low pass Infinite Impulse Response (IIR) filter. CRPSO, the much improved version of PSO, is a population based global heuristic search algorithm which finds near optimal solution in terms of a set of filter coefficients. Effectiveness of this algorithm is justified with a comparative study of some well established algorithms, namely, real coded genetic algorithm (RGA) and particle swarm optimization (PSO). Simulation results affirm that the proposed algorithm CRPSO, outperforms over its counterparts not only in terms of quality output i.e. sharpness at cut-off, pass band ripple, stop band ripple, and stop band attenuation but also in convergence speed with assured stability.
Abstract: By means of the extended homoclinic test approach (shortly EHTA) with the aid of a symbolic computation system such as Maple, some complexiton type solutions for the (3+1)-dimensional Jimbo-Miwa equation are presented.
Abstract: We present a new intuitionistic fuzzy aggregation
operator called the intuitionistic fuzzy ordered weighted
averaging-weighted average (IFOWAWA) operator. The main
advantage of the IFOWAWA operator is that it unifies the OWA
operator with the WA in the same formulation considering the degree
of importance that each concept has in the aggregation. Moreover, it is
able to deal with an uncertain environment that can be assessed with
intuitionistic fuzzy numbers. We study some of its main properties and
we see that it has a lot of particular cases such as the intuitionistic
fuzzy weighted average (IFWA) and the intuitionistic fuzzy OWA
(IFOWA) operator. Finally, we study the applicability of the new
approach on a financial decision making problem concerning the
selection of financial strategies.
Abstract: The precision of heat flux simulation influences the
temperature field and test aberration for TB test and also reflects the
test level for spacecraft development. This paper describes TB tests for
a small satellite using solar simulator, electric heaters, calrod heaters
to evaluate the difference of the three methods. Under the same
boundary condition, calrod heaters cases were about 6oC higher than
solar simulator cases and electric heaters cases for
non-external-heat-flux cases (extreme low temperature cases). While
calrod heaters cases and electric heaters cases were 5~7oC and 2~3oC
lower than solar simulator cases respectively for high temperature
cases. The results show that the solar simulator is better than calrod
heaters for its better collimation, non-homogeneity and stability.
Abstract: The POD-assisted projective integration method based on the equation-free framework is presented in this paper. The method is essentially based on the slow manifold governing of given system. We have applied two variants which are the “on-line" and “off-line" methods for solving the one-dimensional viscous Bergers- equation. For the on-line method, we have computed the slow manifold by extracting the POD modes and used them on-the-fly along the projective integration process without assuming knowledge of the underlying slow manifold. In contrast, the underlying slow manifold must be computed prior to the projective integration process for the off-line method. The projective step is performed by the forward Euler method. Numerical experiments show that for the case of nonperiodic system, the on-line method is more efficient than the off-line method. Besides, the online approach is more realistic when apply the POD-assisted projective integration method to solve any systems. The critical value of the projective time step which directly limits the efficiency of both methods is also shown.
Abstract: This paper presents a technical speaker adaptation
method called WMLLR, which is based on maximum likelihood linear
regression (MLLR). In MLLR, a linear regression-based transform
which adapted the HMM mean vectors was calculated to maximize the
likelihood of adaptation data. In this paper, the prior knowledge of the
initial model is adequately incorporated into the adaptation. A series of
speaker adaptation experiments are carried out at a 30 famous city
names database to investigate the efficiency of the proposed method.
Experimental results show that the WMLLR method outperforms the
conventional MLLR method, especially when only few utterances
from a new speaker are available for adaptation.
Abstract: In this paper electrical characteristics of various kinds
of multiple-gate silicon nanowire transistors (SNWT) with the
channel length equal to 7 nm are compared. A fully ballistic quantum
mechanical transport approach based on NEGF was employed to
analyses electrical characteristics of rectangular and cylindrical
silicon nanowire transistors as well as a Double gate MOS FET. A
double gate, triple gate, and gate all around nano wires were studied
to investigate the impact of increasing the number of gates on the
control of the short channel effect which is important in nanoscale
devices. Also in the case of triple gate rectangular SNWT inserting
extra gates on the bottom of device can improve the application of
device. The results indicate that by using gate all around structures
short channel effects such as DIBL, subthreshold swing and delay
reduces.
Abstract: Current image-based individual human recognition
methods, such as fingerprints, face, or iris biometric modalities
generally require a cooperative subject, views from certain aspects,
and physical contact or close proximity. These methods cannot
reliably recognize non-cooperating individuals at a distance in the
real world under changing environmental conditions. Gait, which
concerns recognizing individuals by the way they walk, is a relatively
new biometric without these disadvantages. The inherent gait
characteristic of an individual makes it irreplaceable and useful in
visual surveillance.
In this paper, an efficient gait recognition system for human
identification by extracting two features namely width vector of
the binary silhouette and the MPEG-7-based region-based shape
descriptors is proposed. In the proposed method, foreground objects
i.e., human and other moving objects are extracted by estimating
background information by a Gaussian Mixture Model (GMM) and
subsequently, median filtering operation is performed for removing
noises in the background subtracted image. A moving target classification
algorithm is used to separate human being (i.e., pedestrian)
from other foreground objects (viz., vehicles). Shape and boundary
information is used in the moving target classification algorithm.
Subsequently, width vector of the outer contour of binary silhouette
and the MPEG-7 Angular Radial Transform coefficients are taken as
the feature vector. Next, the Principal Component Analysis (PCA)
is applied to the selected feature vector to reduce its dimensionality.
These extracted feature vectors are used to train an Hidden Markov
Model (HMM) for identification of some individuals. The proposed
system is evaluated using some gait sequences and the experimental
results show the efficacy of the proposed algorithm.
Abstract: To evaluate the ability to predict xerostomia after
radiotherapy, we constructed and compared neural network and
logistic regression models. In this study, 61 patients who completed a
questionnaire about their quality of life (QoL) before and after a full
course of radiation therapy were included. Based on this questionnaire,
some statistical data about the condition of the patients’ salivary
glands were obtained, and these subjects were included as the inputs of
the neural network and logistic regression models in order to predict
the probability of xerostomia. Seven variables were then selected from
the statistical data according to Cramer’s V and point-biserial
correlation values and were trained by each model to obtain the
respective outputs which were 0.88 and 0.89 for AUC, 9.20 and 7.65
for SSE, and 13.7% and 19.0% for MAPE, respectively. These
parameters demonstrate that both neural network and logistic
regression methods are effective for predicting conditions of parotid
glands.
Abstract: In this paper, Tobephobia (TBP) alludes to the fear of
failure experienced by teachers to manage curriculum change. TBP is
an emerging concept and it extends the boundaries of research in
terms of how we view achievement and failure in education.
Outcomes-based education (OBE) was introduced fifteen years ago
in South African schools without simultaneously upgrading teachers-
professional competencies. This exploratory research, therefore
examines a simple question: What is the impact of TBP and OBE on
teachers? Teacher ineptitude to cope with the OBE curriculum in the
classroom is a serious problem affecting large numbers of South
African teachers. This exploratory study sought to determine the
perceived negative impact of OBE and TBP on teachers. A survey
was conducted amongst 311 teachers in Port Elizabeth and Durban,
South Africa. The results confirm the very negative impact of TBP
and OBE on teachers. This exploratory study authenticates the
existence of TBP.
Abstract: Freeways are originally designed to provide high
mobility to road users. However, the increase in population and
vehicle numbers has led to increasing congestions around the world.
Daily recurrent congestion substantially reduces the freeway capacity
when it is most needed. Building new highways and expanding the
existing ones is an expensive solution and impractical in many
situations. Intelligent and vision-based techniques can, however, be
efficient tools in monitoring highways and increasing the capacity of
the existing infrastructures. The crucial step for highway monitoring
is vehicle detection. In this paper, we propose one of such
techniques. The approach is based on artificial neural networks
(ANN) for vehicles detection and counting. The detection process
uses the freeway video images and starts by automatically extracting
the image background from the successive video frames. Once the
background is identified, subsequent frames are used to detect
moving objects through image subtraction. The result is segmented
using Sobel operator for edge detection. The ANN is, then, used in
the detection and counting phase. Applying this technique to the
busiest freeway in Riyadh (King Fahd Road) achieved higher than
98% detection accuracy despite the light intensity changes, the
occlusion situations, and shadows.
Abstract: Waste corn pulp was investigated as a potential feedstock during vermicomposting using Eisenia fetida. Corn pulp is the major staple food in Southern Africa and constitutes about 25% of the total organic waste. Wastecooked corn pulp was blended with cow dung in the ratio 6:1 respectively to optimize the vermicomposting process. The feedstock was allowed to vermicompost for 30 days. The vermicomposting took place in a 3- tray plastic worm bin. Moisture content, temperature, pH, and electrical conductivity were monitoreddaily. The NPK content was determined at day 30. During vermicomposting, moisture content increased from 27.68% to 52.41%, temperature ranged between 19- 25◦C, pH increased from 5.5 to 7.7, and electrical conductivity decreased from 80000μS/cm to 60000μS/cm. The ash content increased from 11.40% to 28.15%; additionally the volatile matter increased from 1.45% to 10.02%. An odorless, dark brown vermicompost was obtained. The vermicompost NPK content was 4.19%, 1.15%, and 6.18% respectively.
Abstract: Rice, which is the staple food in Sierra Leone, is
consumed on a daily basis. It is the most imperative food crop
extensively grown by farmers across all ecologies in the country.
Though much attention is now given to rice grain production through
the small holder commercialization programme (SHCP), however, no
attention has been given in investigating the limitations faced by rice
producers. This paper will contribute to attempts to overcome the
development challenges caused by food insecurity. The objective of
this paper is thus, to analysis the relationship between rice production
and the domestic retail price of rice. The study employed a log linear
model in which, the quantity of rice produced is the dependent
variable, quantity of rice imported, price of imported rice and price of
domestic rice as explanatory variables. Findings showed that, locally
produced rice is even more expensive than the imported rice per ton,
and almost all the inhabitants in the capital city which hosts about
65% of the entire population of the country favor imported rice, as it
is free from stones with other impurities. On the other hand, to
control price and simultaneously increase rice production, the
government should purchase the rice from the farmers and then sell to private retailers.