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 users are now expecting higher level of
DSP(Digital Signal Processing) software quality than ever before.
Prevention and detection of defect are critical elements of software
quality assurance. In this paper, principles and rules for prevention and
detection of defect are suggested, which are not universal guidelines,
but are useful for both novice and experienced DSP software
developers.
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.
Abstract: Investment in a constructed facility represents a cost in
the short term that returns benefits only over the long term use of the
facility. Thus, the costs occur earlier than the benefits, and the owners
of facilities must obtain the capital resources to finance the costs of
construction. A project cannot proceed without an adequate
financing, and the cost of providing an adequate financing can be
quite large. For these reasons, the attention to the project finance is an
important aspect of project management. Finance is also a concern to
the other organizations involved in a project such as the general
contractor and material suppliers. Unless an owner immediately and
completely covers the costs incurred by each participant, these
organizations face financing problems of their own. At a more
general level, the project finance is the only one aspect of the general
problem of corporate finance. If numerous projects are considered
and financed together, then the net cash flow requirements constitute
the corporate financing problem for capital investment. Whether
project finance is performed at the project or at the corporate level
does not alter the basic financing problem .In this paper, we will first
consider facility financing from the owner's perspective, with due
consideration for its interaction with other organizations involved in a
project. Later, we discuss the problems of construction financing
which are crucial to the profitability and solvency of construction
contractors. The objective of this paper is to present the steps utilized
to determine the best combination of minimum project financing.
The proposed model considers financing; schedule and maximum net
area .The proposed model is called Project Financing and Schedule
Integration using Genetic Algorithms "PFSIGA". This model
intended to determine more steps (maximum net area) for any project
with a subproject. An illustrative example will demonstrate the
feature of this technique. The model verification and testing are put
into consideration.
Abstract: The group mutual exclusion (GME) problem is an
interesting generalization of the mutual exclusion problem. In the
group mutual exclusion, multiple processes can enter a critical
section simultaneously if they belong to the same group. In the
extended group mutual exclusion, each process is a member of
multiple groups at the same time. As a result, after the process by
selecting a group enter critical section, other processes can select the
same group with its belonging group and can enter critical section at
the moment, so that it avoids their unnecessary blocking. This paper
presents a quorum-based distributed algorithm for the extended
group mutual exclusion problem. The message complexity of our
algorithm is O(4Q ) in the best case and O(5Q) in the worst case,
where Q is a quorum size.
Abstract: This paper explains a project based learning method where autonomous mini-robots are developed for research, education and entertainment purposes. In case of remote systems wireless sensors are developed in critical areas, which would collect data at specific time intervals, send the data to the central wireless node based on certain preferred information would make decisions to turn on or off a switch or control unit. Such information transfers hardly sums up to a few bytes and hence low data rates would suffice for such implementations. As a robot is a multidisciplinary platform, the interfacing issues involved are discussed in this paper. The paper is mainly focused on power supply, grounding and decoupling issues.
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: The technical realization of data transmission using
glass fiber began after the development of diode laser in year 1962.
The erbium doped fiber amplifiers (EDFA's) in high speed networks
allow information to be transmitted over longer distances without
using of signal amplification repeaters. These kinds of fibers are
doped with erbium atoms which have energy levels in its atomic
structure for amplifying light at 1550nm. When a carried signal wave
at 1550nm enters the erbium fiber, the light stimulates the excited
erbium atoms which pumped with laser beam at 980nm as additional
light. The wavelength and intensity of the semiconductor lasers
depend on the temperature of active zone and the injection current.
The present paper shows the effect of the diode lasers temperature
and injection current on the optical amplification. From the results of
in- and output power one may calculate the max. optical gain by
erbium doped fiber amplifier.
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: This study aims to demonstrate the quantification of
peptides based on isotope dilution surface enhanced Raman
scattering (IDSERS). SERS spectra of phenylalanine (Phe), leucine
(Leu) and two peptide sequences TGQIFK (T13) and
YSFLQNPQTSLCFSESIPTPSNR (T6) as part of the 22-kDa
human growth hormone (hGH) were obtained on Ag-nanoparticle
covered substrates. On the basis of the dominant Phe and Leu
vibrational modes, precise partial least squares (PLS) prediction
models were built enabling the determination of unknown T13 and
T6 concentrations. Detection of hGH in its physiological
concentration in order to investigate the possibility of protein
quantification has been achieved.
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 main aim of this research is to investigate a novel technique for implementing a more natural and intelligent conversation system. Conversation systems are designed to converse like a human as much as their intelligent allows. Sometimes, we can think that they are the embodiment of Turing-s vision. It usually to return a predetermined answer in a predetermined order, but conversations abound with uncertainties of various kinds. This research will focus on an integrated natural language processing approach. This approach includes an integrated knowledge-base construction module, a conversation understanding and generator module, and a state manager module. We discuss effectiveness of this approach based on an experiment.
Abstract: An advanced composite flywheel rotor consisting of
intra and inter hybrid rims was designed to optimally increase the energy capacity, and was manufactured using filament winding with
in-situ curing. The flywheel has recently attracted considerable attention from many investigators since it possesses great potential in
many energy storage applications, including electric utilities, hybrid or
electric automobiles, and space vehicles. In this investigation, a comprehensive study was conducted with the intent to implement
composites in high performance flywheel applications.The inner two
intra-hybrid rims (rims 1 and 2) were manufactured as a whole part
through continuous filament winding under in-situ curing conditions,
and so were the outer two rims (rims 3 and 4). The outer surface of rim
2 and the inner surface of rim 3 were CNC-tapered for press-fitting. Machined rims were finally press-fitted using a hydraulic press with a
maximum compressive force of approximately 1000 ton.
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: 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: In the literature of fuzzy measures, there exist many
well known parametric and non-parametric measures, each with its
own merits and limitations. But our main emphasis is on
applications of these measures to a variety of disciplines. To extend
the scope of applications of these fuzzy measures to geometry, we
need some special fuzzy measures. In this communication, we have
introduced two new fuzzy measures involving trigonometric
functions and simultaneously provided their applications to obtain
the basic results already existing in the literature of geometry.
Abstract: Saudi Arabia is an arid country which depends on
costly desalination plants to satisfy the growing residential water
demand. Prediction of water demand is usually a challenging task
because the forecast model should consider variations in economic
progress, climate conditions and population growth. The task is
further complicated knowing that Mecca city is visited regularly by
large numbers during specific months in the year due to religious
occasions. In this paper, a neural networks model is proposed to
handle the prediction of the monthly and yearly water demand for
Mecca city, Saudi Arabia. The proposed model will be developed
based on historic records of water production and estimated visitors-
distribution. The driving variables for the model include annuallyvarying
variables such as household income, household density, and
city population, and monthly-varying variables such as expected
number of visitors each month and maximum monthly temperature.