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: The entropy of intuitionistic fuzzy sets is used to indicate the degree of fuzziness of an interval-valued intuitionistic fuzzy set(IvIFS). In this paper, we deal with the entropies of IvIFS. Firstly, we propose a family of entropies on IvIFS with a parameter λ ∈ [0, 1], which generalize two entropy measures defined independently by Zhang and Wei, for IvIFS, and then we prove that the
new entropy is an increasing function with respect to the parameter λ. Furthermore, a new multiple attribute decision making (MADM) method using entropy-based attribute weights is proposed to deal with the decision making situations where the alternatives on attributes are expressed by IvIFS and the attribute weights information is unknown. Finally, a numerical example is given to illustrate the applications of the proposed method.
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: 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: 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: This paper presents a reliability-based approach to select appropriate wind turbine types for a wind farm considering site-specific wind speed patterns. An actual wind farm in the northern region of Iran with the wind speed registration of one year is studied in this paper. An analytic approach based on total probability theorem is utilized in this paper to model the probabilistic behavior of both turbines- availability and wind speed. Well-known probabilistic reliability indices such as loss of load expectation (LOLE), expected energy not supplied (EENS) and incremental peak load carrying capability (IPLCC) for wind power integration in the Roy Billinton Test System (RBTS) are examined. The most appropriate turbine type achieving the highest reliability level is chosen for the studied wind farm.
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 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: Today, the Internet based communication has widen
the opportunity of event monitoring system in the medical field.
There is always a need of analyzing and designing secure and reliable
mobile communication between the hospital and biomedical
engineers mobile units. This study has been carried out to find
possible solution using SIP-based event notification for alerting the
technical staff about the Biomedical Device (BMD) status and
Patients treatment session. The Session Initiation Protocol (SIP) can
be used to create a medical event notification system. SIP can work
on a variety of devices. Its adoption as the protocol of choice for third
generation wireless networks allows for a robust and scalable
environment. One of the advantages of SIP is that it supports personal
mobility through the separation of user addressing and device
addressing. The solution for Telemed alert notification system is
based on SIP - Specific Event Notification. The aim of this project is
to extend mobility service to the hospital technicians who are using
Telemedicine system.
Abstract: To improve the classification rate of the face
recognition, features combination and a novel non-linear kernel are
proposed. The feature vector concatenates three different radius of
local binary patterns and Gabor wavelet features. Gabor features are
the mean, standard deviation and the skew of each scaling and
orientation parameter. The aim of the new kernel is to incorporate
the power of the kernel methods with the optimal balance between
the features. To verify the effectiveness of the proposed method,
numerous methods are tested by using four datasets, which are
consisting of various emotions, orientations, configuration,
expressions and lighting conditions. Empirical results show the
superiority of the proposed technique when compared to other
methods.