Abstract: Applicability of tuning the controller gains for Stewart manipulator using genetic algorithm as an efficient search technique is investigated. Kinematics and dynamics models were introduced in detail for simulation purpose. A PD task space control scheme was used. For demonstrating technique feasibility, a Stewart manipulator numerical-model was built. A genetic algorithm was then employed to search for optimal controller gains. The controller was tested onsite a generic circular mission. The simulation results show that the technique is highly convergent with superior performance operating for different payloads.
Abstract: The use of the oncologic index ISTER allows for a more effective planning of the radiotherapic facilities in the hospitals. Any change in the radiotherapy treatment, due to unexpected stops, may be adapted by recalculating the doses to the new treatment duration while keeping the optimal prognosis. The results obtained in a simulation model on millions of patients allow the definition of optimal success probability algorithms.
Abstract: Radio-frequency identification has entered as a beneficial means with conforming GS1 standards to provide the best solutions in the manufacturing area. It competes with other automated identification technologies e.g. barcodes and smart cards with regard to high speed scanning, reliability and accuracy as well. The purpose of this study is to improve production line-s performance by implementing RFID system in the manufacturing area on the basis of radio-frequency identification (RFID) system by 3D modeling in the program Cinema 4D R13 which provides obvious graphical scenes for users to portray their applications. Finally, with regard to improving system performance, it shows how RFID appears as a well-suited technology in a comparison of the barcode scanner to handle different kinds of raw materials in the production line base on logical process.
Abstract: Nowadays, the challenge in hydraulic turbine design is
the multi-objective design of turbine runner to reach higher
efficiency. The hydraulic performance of a turbine is strictly depends
on runner blades shape. The present paper focuses on the application
of the multi-objective optimization algorithm to the design of a small
Francis turbine runner. The optimization exercise focuses on the
efficiency improvement at the best efficiency operating point (BEP)
of the GAMM Francis turbine. A global optimization method based
on artificial neural networks (ANN) and genetic algorithms (GA)
coupled by 3D Navier-Stokes flow solver has been used to improve
the performance of an initial geometry of a Francis runner. The
results show the good ability of optimization algorithm and the final
geometry has better efficiency with initial geometry. The goal was to
optimize the geometry of the blades of GAMM turbine runner which
leads to maximum total efficiency by changing the design parameters
of camber line in at least 5 sections of a blade. The efficiency of the
optimized geometry is improved from 90.7% to 92.5%. Finally,
design parameters and the way of selection have been considered and
discussed.
Abstract: In this study we applied thermal lens (TL) technique
to study the effect of size on thermal diffusivity of cadmium sulphide
(CdS) nanofluid prepared by using γ-radiation method containing
particles with different sizes. In TL experimental set up a diode laser
of wavelength 514 nm and intensity stabilized He-Ne laser were used
as the excitation source and the probe beam respectively,
respectively. The experimental results showed that the thermal
diffusivity value of CdS nanofluid increases when the of particle size
increased.
Abstract: Laboratory activities have produced benefits in
student learning. With current drives of new technology resources
and evolving era of education methods, renewal status of learning
and teaching in laboratory methods are in progress, for both learners
and the educators. To enhance learning outcomes in laboratory works
particularly in engineering practices and testing, learning via handson
by instruction may not sufficient. This paper describes and
compares techniques and implementation of traditional (expository)
with open-ended laboratory (problem-based) for two consecutive
cohorts studying environmental laboratory course in civil engineering
program. The transition of traditional to problem-based findings and
effect were investigated in terms of course assessment student
feedback survey, course outcome learning measurement and student
performance grades. It was proved that students have demonstrated
better performance in their grades and 12% increase in the course
outcome (CO) in problem-based open-ended laboratory style than
traditional method; although in perception, students has responded
less favorable in their feedback.
Abstract: The growing influence of service industries has
prompted greater attention being paid to service operations
management. However, service managers often have difficulty
articulating the veritable effects of their service innovation. Especially,
the performance evaluation process of service innovation problems
generally involves uncertain and imprecise data. This paper presents a
2-tuple fuzzy linguistic computing approach to dealing with
heterogeneous information and information loss problems while the
processes of subjective evaluation integration. The proposed method
based on group decision-making scenario to assist business managers
in measuring performance of service innovation manipulates the
heterogeneity integration processes and avoids the information loss
effectively.
Abstract: The paper is devoted to stochastic analysis of finite
dimensional difference equation with dependent on ergodic Markov
chain increments, which are proportional to small parameter ". A
point-form solution of this difference equation may be represented
as vertexes of a time-dependent continuous broken line given on the
segment [0,1] with "-dependent scaling of intervals between vertexes.
Tending " to zero one may apply stochastic averaging and diffusion
approximation procedures and construct continuous approximation of
the initial stochastic iterations as an ordinary or stochastic Ito differential
equation. The paper proves that for sufficiently small " these
equations may be successfully applied not only to approximate finite
number of iterations but also for asymptotic analysis of iterations,
when number of iterations tends to infinity.
Abstract: This paper employs a new approach to regulate the
blood glucose level of type I diabetic patient under an intensive
insulin treatment. The closed-loop control scheme incorporates
expert knowledge about treatment by using reinforcement learning
theory to maintain the normoglycemic average of 80 mg/dl and the
normal condition for free plasma insulin concentration in severe
initial state. The insulin delivery rate is obtained off-line by using Qlearning
algorithm, without requiring an explicit model of the
environment dynamics. The implementation of the insulin delivery
rate, therefore, requires simple function evaluation and minimal
online computations. Controller performance is assessed in terms of
its ability to reject the effect of meal disturbance and to overcome the
variability in the glucose-insulin dynamics from patient to patient.
Computer simulations are used to evaluate the effectiveness of the
proposed technique and to show its superiority in controlling
hyperglycemia over other existing algorithms
Abstract: This paper offers a case study, in which
methodological aspects of cell design for transformation the
production process are applied. The cell redesign in this work is
tightly focused to reach optimization of material flows under real
manufacturing conditions. Accordingly, more individual techniques
were aggregated into compact methodical procedure with aim to built
one-piece flow production. Case study was concentrated on relatively
typical situation of transformation from batch production to cellular
manufacturing.
Abstract: In this paper stress and strain for two rotating thin
wall cylinder fitted together with initial interference and overlap are
computed. Also stress value for variation of initial interference is
calculated.
At first problem is considered without rotation and next angular
velocity increased from 0 to 50000 rev/min and stress in each stage
is calculated. The important point is that when stress become very
small in magnitude the angular velocity is critical and two cylinders
will separate. The critical speed i.e. speed of separation is calculated
in each step.
Abstract: Traffic Management and Information Systems, which rely on a system of sensors, aim to describe in real-time traffic in urban areas using a set of parameters and estimating them. Though the state of the art focuses on data analysis, little is done in the sense of prediction. In this paper, we describe a machine learning system for traffic flow management and control for a prediction of traffic flow problem. This new algorithm is obtained by combining Random Forests algorithm into Adaboost algorithm as a weak learner. We show that our algorithm performs relatively well on real data, and enables, according to the Traffic Flow Evaluation model, to estimate and predict whether there is congestion or not at a given time on road intersections.
Abstract: In recent years there has been renewal of interest in the
relation between Green IT and Cloud Computing. The growing use of
computers in cloud platform has caused marked energy consumption,
putting negative pressure on electricity cost of cloud data center. This
paper proposes an effective mechanism to reduce energy utilization in
cloud computing environments. We present initial work on the
integration of resource and power management that aims at reducing
power consumption. Our mechanism relies on recalling virtualization
services dynamically according to user-s virtualization request and
temporarily shutting down the physical machines after finish in order
to conserve energy. Given the estimated energy consumption, this
proposed effort has the potential to positively impact power
consumption. The results from the experiment concluded that energy
indeed can be saved by powering off the idling physical machines in
cloud platforms.
Abstract: Primary barrier of membrane type LNG containment system consist of corrugated 304L stainless steel. This 304L stainless steel is austenitic stainless steel which shows different material behaviors owing to phase transformation during the plastic work. Even though corrugated primary barriers are subjected to significant amounts of pre-strain due to press working, quantitative mechanical behavior on the effect of pre-straining at cryogenic temperatures are not available. In this study, pre-strain level and pre-strain temperature dependent tensile tests are carried to investigate mechanical behaviors. Also, constitutive equations with material parameters are suggested for a verification study.
Abstract: In this paper, we propose an energy efficient cluster
based communication protocol for wireless sensor network. Our
protocol considers both the residual energy of sensor nodes and the
distance of each node from the BS when selecting cluster-head. This
protocol can successfully prolong the network-s lifetime by 1)
reducing the total energy dissipation on the network and 2) evenly
distributing energy consumption over all sensor nodes. In this
protocol, the nodes with more energy and less distance from the BS
are probable to be selected as cluster-head. Simulation results with
MATLAB show that proposed protocol could increase the lifetime of
network more than 94% for first node die (FND), and more than 6%
for the half of the nodes alive (HNA) factor as compared with
conventional protocols.
Abstract: Utilities use operating reserve for frequency regulation.To ensure that the operating frequency and system security are well maintained, the operating grid codes always specify that the reserve quantity and response rate should meet some prescribed levels. This paper proposes a methodology to evaluate system's contingency reserve for an isolated power network. With the presented algorithm to estimate system's frequency response characteristic, an online allocation of contingency reserve would be feasible to meet the grid codes for contingency operation. Test results from the simulated conditions, and from the actual operating data verify the merits of the proposed methodology to system's frequency control, and security.
Abstract: The world's population continues to grow at a quarter of a million people per day, increasing the consumption of energy. This has made the world to face the problem of energy crisis now days. In response to the energy crisis, the principles of renewable energy gained popularity. There are much advancement made in developing the wind and solar energy farms across the world. These energy farms are not enough to meet the energy requirement of world. This has attracted investors to procure new sources of energy to be substituted. Among these sources, extraction of energy from the waves is considered as best option. The world oceans contain enough energy to meet the requirement of world. Significant advancements in design and technology are being made to make waves as a continuous source of energy. One major hurdle in launching wave energy devices in a developing country like Pakistan is the initial cost. A simple, reliable and cost effective wave energy converter (WEC) is required to meet the nation-s energy need. This paper will present a novel design proposed by team SAS for harnessing wave energy. This paper has three major sections. The first section will give a brief and concise view of ocean wave creation, propagation and the energy carried by them. The second section will explain the designing of SAS-2. A gear chain mechanism is used for transferring the energy from the buoy to a rotary generator. The third section will explain the manufacturing of scaled down model for SAS-2 .Many modifications are made in the trouble shooting stage. The design of SAS-2 is simple and very less maintenance is required. SAS-2 is producing electricity at Clifton. The initial cost of SAS-2 is very low. This has proved SAS- 2 as one of the cost effective and reliable source of harnessing wave energy for developing countries.
Abstract: Wheat gluten hydrolyzates (WGHs) and anchovy fine
powder hydrolyzates (AFPHs) were produced at 300 MPa using
combinations of Flavourzyme 500MG (F), Alcalase 2.4L (A),
Marugoto E (M) and Protamex (P), and then were compared to those
produced at ambient pressure concerning the contents of soluble solid
(SS), soluble nitrogen and electrophoretic profiles. The contents of SS
in the WGHs and AFPHs increased up to 87.2% according to the
increase in enzyme number both at high and ambient pressure. Based
on SS content, the optimum enzyme combinations for one-, two-,
three- and four-enzyme hydrolysis were determined as F, FA, FAM
and FAMP, respectively. Similar trends were found for the contents of
total soluble nitrogen (TSN) and TCA-soluble nitrogen (TCASN). The
contents of SS, TSN and TCASN in the hydrolyzates together with
electrophoretic mobility maps indicates that the high-pressure
treatment of this study accelerated protein hydrolysis compared to
ambient-pressure treatment.
Abstract: The goal of this project is to design a system to
recognition voice commands. Most of voice recognition systems
contain two main modules as follow “feature extraction" and “feature
matching". In this project, MFCC algorithm is used to simulate
feature extraction module. Using this algorithm, the cepstral
coefficients are calculated on mel frequency scale. VQ (vector
quantization) method will be used for reduction of amount of data to
decrease computation time. In the feature matching stage Euclidean
distance is applied as similarity criterion. Because of high accuracy
of used algorithms, the accuracy of this voice command system is
high. Using these algorithms, by at least 5 times repetition for each
command, in a single training session, and then twice in each testing
session zero error rate in recognition of commands is achieved.
Abstract: Multi-agent system approach has proven to be an effective and appropriate abstraction level to construct whole models of a diversity of biological problems, integrating aspects which can be found both in "micro" and "macro" approaches when modeling this type of phenomena. Taking into account these considerations, this paper presents the important computational characteristics to be gathered into a novel bioinformatics framework built upon a multiagent architecture. The version of the tool presented herein allows studying and exploring complex problems belonging principally to structural biology, such as protein folding. The bioinformatics framework is used as a virtual laboratory to explore a minimalist model of protein folding as a test case. In order to show the laboratory concept of the platform as well as its flexibility and adaptability, we studied the folding of two particular sequences, one of 45-mer and another of 64-mer, both described by an HP model (only hydrophobic and polar residues) and coarse grained 2D-square lattice. According to the discussion section of this piece of work, these two sequences were chosen as breaking points towards the platform, in order to determine the tools to be created or improved in such a way to overcome the needs of a particular computation and analysis of a given tough sequence. The backwards philosophy herein is that the continuous studying of sequences provides itself important points to be added into the platform, to any time improve its efficiency, as is demonstrated herein.