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: 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: The speech signal conveys information about the
identity of the speaker. The area of speaker identification is
concerned with extracting the identity of the person speaking the
utterance. As speech interaction with computers becomes more
pervasive in activities such as the telephone, financial transactions
and information retrieval from speech databases, the utility of
automatically identifying a speaker is based solely on vocal
characteristic. This paper emphasizes on text dependent speaker
identification, which deals with detecting a particular speaker from a
known population. The system prompts the user to provide speech
utterance. System identifies the user by comparing the codebook of
speech utterance with those of the stored in the database and lists,
which contain the most likely speakers, could have given that speech
utterance. The speech signal is recorded for N speakers further the
features are extracted. Feature extraction is done by means of LPC
coefficients, calculating AMDF, and DFT. The neural network is
trained by applying these features as input parameters. The features
are stored in templates for further comparison. The features for the
speaker who has to be identified are extracted and compared with the
stored templates using Back Propogation Algorithm. Here, the
trained network corresponds to the output; the input is the extracted
features of the speaker to be identified. The network does the weight
adjustment and the best match is found to identify the speaker. The
number of epochs required to get the target decides the network
performance.
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: 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: 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.
Abstract: Perspective of food security in 21 century showed
shortage of food that production is faced to vital problem. Food
security strategy is applied longtime method to assess required food.
Meanwhile, nanotechnology revolution changes the world face.
Nanotechnology is adequate method utilize of its characteristics to
decrease environmental problems and possible further access to food
for small farmers. This article will show impact of production and
adoption of nanocrops on food security. Population is researchers of
agricultural research center of Esfahan province. The results of study
show that there was a relationship between uses, conversion,
distribution, and production of nanocrops, operative human
resources, operative circumstance, and constrains of usage of
nanocrops and food security. Multivariate regression analysis by
enter model shows that operative circumstance, use, production and
constrains of usage of nanocrops had positive impact on food security
and they determine in four steps 20 percent of it.
Abstract: Mathematical, graphical and intuitive models are often
constructed in the development process of computational systems.
The Unified Modeling Language (UML) is one of the most popular
modeling languages used by practicing software engineers. This
paper critically examines UML models and suggests an augmented
use case view with the addition of new constructs for modeling
software. It also shows how a use case diagram can be enhanced. The
improved modeling constructs are presented with examples for
clarifying important design and implementation issues.
Abstract: Ren et al. presented an efficient carrier frequency offset
(CFO) estimation method for orthogonal frequency division multiplexing
(OFDM), which has an estimation range as large as the
bandwidth of the OFDM signal and achieves high accuracy without
any constraint on the structure of the training sequence. However,
its detection probability of the integer frequency offset (IFO) rapidly
varies according to the fractional frequency offset (FFO) change. In
this paper, we first analyze the Ren-s method and define two criteria
suitable for detection of IFO. Then, we propose a novel method for
the IFO estimation based on the maximum-likelihood (ML) principle
and the detection criteria defined in this paper. The simulation results
demonstrate that the proposed method outperforms the Ren-s method
in terms of the IFO detection probability irrespective of a value of
the FFO.
Abstract: The aim of this paper is to present a methodology in
three steps to forecast supply chain demand. In first step, various data
mining techniques are applied in order to prepare data for entering
into forecasting models. In second step, the modeling step, an
artificial neural network and support vector machine is presented
after defining Mean Absolute Percentage Error index for measuring
error. The structure of artificial neural network is selected based on
previous researchers' results and in this article the accuracy of
network is increased by using sensitivity analysis. The best forecast
for classical forecasting methods (Moving Average, Exponential
Smoothing, and Exponential Smoothing with Trend) is resulted based
on prepared data and this forecast is compared with result of support
vector machine and proposed artificial neural network. The results
show that artificial neural network can forecast more precisely in
comparison with other methods. Finally, forecasting methods'
stability is analyzed by using raw data and even the effectiveness of
clustering analysis is measured.
Abstract: The turbulent mixing of coolant streams of different
temperature and density can cause severe temperature fluctuations in
piping systems in nuclear reactors. In certain periodic contraction
cycles these conditions lead to thermal fatigue. The resulting aging
effect prompts investigation in how the mixing of flows over a sharp
temperature/density interface evolves. To study the fundamental
turbulent mixing phenomena in the presence of density gradients,
isokinetic (shear-free) mixing experiments are performed in a square
channel with Reynolds numbers ranging from 2-500 to 60-000.
Sucrose is used to create the density difference. A Wire Mesh Sensor
(WMS) is used to determine the concentration map of the flow in the
cross section. The mean interface width as a function of velocity,
density difference and distance from the mixing point are analyzed
based on traditional methods chosen for the purposes of
atmospheric/oceanic stratification analyses. A definition of the
mixing layer thickness more appropriate to thermal fatigue and based
on mixedness is devised. This definition shows that the thermal
fatigue risk assessed using simple mixing layer growth can be
misleading and why an approach that separates the effects of large
scale (turbulent) and small scale (molecular) mixing is necessary.
Abstract: Mobile agent has motivated the creation of a new
methodology for parallel computing. We introduce a methodology
for the creation of parallel applications on the network. The proposed
Mobile-Agent parallel processing framework uses multiple Javamobile
Agents. Each mobile agent can travel to the specified
machine in the network to perform its tasks. We also introduce the
concept of master agent, which is Java object capable of
implementing a particular task of the target application. Master agent
is dynamically assigns the task to mobile agents. We have developed
and tested a prototype application: Mobile Agent Based Parallel
Computing. Boosted by the inherited benefits of using Java and
Mobile Agents, our proposed methodology breaks the barriers
between the environments, and could potentially exploit in a parallel
manner all the available computational resources on the network.
This paper elaborates performance issues of a mobile agent for
parallel computing.
Abstract: This paper presents the results of the preliminary investigation of microwave (MW) irradiation pretreatments on the anaerobic digestion of food residues using biochemical methane potential (BMP) assays. Low solids systems with a total solids (TS) content ranging from 5.0-10.0% were analyzed. The inoculum to bulk mass of substrates to water ratio was 1:2:2 (mass basis). The experimental conditions for pretreatments were as follows: a control (no MW irradiation), two runs with MW irradiation for 15 and 30 minutes at 320 W, and another two runs with MW irradiation at 528 W for 30 and 60 minutes. The cumulative biogas production were 6.3 L and 8.7 L for 15min/320 W and 30min/320 W MW irradiation conditions, respectively, and 10.5 L and 11.4 L biogas for 30min/528 W and 60min/528 W, respectively, as compared to the control giving 5.8 L biogas. Both an increase in exposure time of irradiation and power of MW had increased the rate and yield of biogas. Singlefactor ANOVA tests (p
Abstract: The advent of multi-million gate Field Programmable
Gate Arrays (FPGAs) with hardware support for multiplication opens
an opportunity to recreate a significant portion of the front end of a
human cochlea using this technology. In this paper we describe the
implementation of the cochlear filter and show that it is entirely
suited to a single device XC3S500 FPGA implementation .The filter
gave a good fit to real time data with efficiency of hardware usage.
Abstract: While the problem based learning (PBL) approach promotes unsupervised self-directed learning (SDL), many students experience difficulty juggling the role of being an information recipient and information seeker. Logbooks have been used to assess trainee doctors but not in other areas. This study aimed to determine the effectiveness of logbook for assessing SDL during PBL sessions in first year medical students. The log book included a learning checklist and knowledge and skills components. Comparisons with the baseline assessment of student performance in PBL and that at semester end after logbook intervention showed significant improvements in student performance (31.5 ± 8 vs. 17.7 ± 4.4; p
Abstract: Modeling of a heterogeneous industrial fixed bed
reactor for selective dehydrogenation of heavy paraffin with Pt-Sn-
Al2O3 catalyst has been the subject of current study. By applying
mass balance, momentum balance for appropriate element of reactor
and using pressure drop, rate and deactivation equations, a detailed
model of the reactor has been obtained. Mass balance equations have
been written for five different components. In order to estimate
reactor production by the passage of time, the reactor model which is
a set of partial differential equations, ordinary differential equations
and algebraic equations has been solved numerically.
Paraffins, olefins, dienes, aromatics and hydrogen mole percent as
a function of time and reactor radius have been found by numerical
solution of the model. Results of model have been compared with
industrial reactor data at different operation times. The comparison
successfully confirms validity of proposed model.
Abstract: An ultrasound-assisted activation method for
electroless silver plating is presented in this study. When the
ultrasound was applied during the activation step, the amount of the Pd
species adsorbed on substrate surfaces was higher than that of sample
pretreated with a conventional activation process without ultrasound
irradiation. With this activation method, it was also shown that the
adsorbed Pd species with a size of about 5 nm were uniformly
distributed on the surfaces, thus a smooth and uniform coating on the
surfaces was obtained by subsequent electroless silver plating. The
samples after each step were characterized by AFM, XPS, FIB, and
SEM.
Abstract: Fats and oils are made of esterified hydrocarbons
(RCOOR-) and this work demonstrates the substitution of R by
multi-walled CNTs (MWNTs). The resultant materials are fluidic, oily,
electrically conducting and excellent lubricants. Esterified MWNTs
can also respond to magnetic field when tubules contain long segments
of Fe
Abstract: The paper reviews the relationship between spatial
and transportation planning in the Southern African Development
Community (SADC) region of Sub-Saharan Africa. It argues that
most urbanisation in the region has largely occurred subsequent to
the 1950s and, accordingly, urban development has been
profoundly and negatively affected by the (misguided) spatial and
institutional tenets of modernism. It demonstrates how a
considerable amount of the poor performance of these settlements
can be directly attributed to this. Two factors in particular about the
planning systems are emphasized: the way in which programmatic
land-use planning lies at the heart of both spatial and transportation
planning; and the way on which transportation and spatial planning
have been separated into independent processes. In the final
section, the paper identifies ways of improving the planning
system. Firstly, it identifies the performance qualities which
Southern African settlements should be seeking to achieve.
Secondly, it focuses on two necessary arenas of change: the need to
replace programmatic land-use planning practices with structuralspatial
approaches; and it makes a case for making urban corridors
a spatial focus of integrated planning, as a way of beginning the
restructuring and intensification of settlements which are currently
characterised by sprawl, fragmentation and separation