Abstract: Pigeon pea (Cajanus cajan) blanched for 20min was dehulled and milled into flour. The flour was incorporated into dried whole fermented maize (Ogi) at five levels. The resultant products were analyzed for chemical and pasting properties. The fortified Ogi samples were also assessed for sensory attributes: appearance, color, flavor, mouth feel and overall acceptability. The protein content in the whole Ogi fortified samples was in the range of 11.2-16.6% and crude fibre 3.22-3.46%. Fortified whole Ogi with pigeon pea at 30%, 40% and 50% of inclusion with pigeon pea flour has higher protein, crude fibre and ash content. Varying range of pasting quality was recorded for the blends, pasting temperature for fortified Obi was in the range of 45.3-49.50C and peak time 5.05-5.210C. The sensory acceptability of the whole Ogi fortified blends prepared into gruel has higher acceptability for various qualities in comparison with the traditional Ogi gruel.
Abstract: In this paper, we propose improved versions of DVHop
algorithm as QDV-Hop algorithm and UDV-Hop algorithm for
better localization without the need for additional range measurement
hardware. The proposed algorithm focuses on third step of DV-Hop,
first error terms from estimated distances between unknown node and
anchor nodes is separated and then minimized. In the QDV-Hop
algorithm, quadratic programming is used to minimize the error to
obtain better localization. However, quadratic programming requires
a special optimization tool box that increases computational
complexity. On the other hand, UDV-Hop algorithm achieves
localization accuracy similar to that of QDV-Hop by solving
unconstrained optimization problem that results in solving a system
of linear equations without much increase in computational
complexity. Simulation results show that the performance of our
proposed schemes (QDV-Hop and UDV-Hop) is superior to DV-Hop
and DV-Hop based algorithms in all considered scenarios.
Abstract: The Address Resolution Protocol (ARP) is used by
computers to map logical addresses (IP) to physical addresses
(MAC). However ARP is an all trusting protocol and is stateless
which makes it vulnerable to many ARP cache poisoning attacks
such as Man-in-the-Middle (MITM) and Denial of service (DoS)
attacks. These flaws result in security breaches thus weakening the
appeal of the computer for exchange of sensitive data. In this paper
we describe ARP, outline several possible ARP cache poisoning
attacks and give the detailed of some attack scenarios in network
having both wired and wireless hosts. We have analyzed each of
proposed solutions, identify their strengths and limitations. Finally
get that no solution offers a feasible solution. Hence, this paper
presents an efficient and secure version of ARP that is able to cope
up with all these types of attacks and is also a feasible solution. It is a
stateful protocol, by storing the information of the Request frame in
the ARP cache, to reduce the chances of various types of attacks in
ARP. It is more efficient and secure by broadcasting ARP Reply
frame in the network and storing related entries in the ARP cache
each time when communication take place.
Abstract: The performance of sensor-less controlled induction
motor drive depends on the accuracy of the estimated speed.
Conventional estimation techniques being mathematically complex
require more execution time resulting in poor dynamic response. The
nonlinear mapping capability and powerful learning algorithms of
neural network provides a promising alternative for on-line speed
estimation. The on-line speed estimator requires the NN model to be
accurate, simpler in design, structurally compact and computationally
less complex to ensure faster execution and effective control in real
time implementation. This in turn to a large extent depends on the
type of Neural Architecture. This paper investigates three types of
neural architectures for on-line speed estimation and their
performance is compared in terms of accuracy, structural
compactness, computational complexity and execution time. The
suitable neural architecture for on-line speed estimation is identified
and the promising results obtained are presented.
Abstract: Monitoring and control of cane sugar crystallization
processes depend on the stability of the supersaturation (σ ) state.
The most widely used information to represent σ is the electrical
conductivity κ of the solutions. Nevertheless, previous studies point
out the shortcomings of this approach: κ may be regarded as
inappropriate to guarantee an accurate estimation of σ in impure
solutions. To improve the process control efficiency, additional
information is necessary. The mass of crystals in the solution ( c m )
and the solubility (mass ratio of sugar to water / s w m m ) are relevant
to complete information. Indeed, c m inherently contains information
about the mass balance and / s w m m contains information about the
supersaturation state of the solution. The main problem is that c m
and / s w m m are not available on-line. In this paper, a model based
soft-sensor is presented for a final crystallization stage (C sugar).
Simulation results obtained on industrial data show the reliability of
this approach, c m and the crystal content ( cc ) being estimated with
a sufficient accuracy for achieving on-line monitoring in industry
Abstract: The study of soil for agriculture purposes has
remained the main focus of research since the beginning of civilization as humans- food related requirements remained closely linked with the soil. The study of soil has generated an interest
among the researchers for very similar other reasons including transmission, reflection and refraction of signals for deploying
wireless underground sensor networks or for the monitoring of objects on (or in ) soil in the form of better understanding of soil
electromagnetic characteristics properties. The moisture content has
been very instrumental in such studies as it decides on the resistance of the soil, and hence the attenuation on signals traveling through soil
or the attenuation the signals may suffer upon their impact on soil. This work is related testing and characterizing a measurement circuit
meant for the detection of moisture level content in soil.
Abstract: Creation of information society, or in other words, a
society based on knowledge, has wide consequences, both on
individual and complete society, and in general – on a economy of
one country. Development and implementation of ICT represents a
stimulant for economic growth. On individual level, knowledge,
skills and information gathered using ICT, are expanding individual
possibilities of persons, enabling them to have access to timely
sensitive information, such as market prices or investment
conditions, possibilities to access Government-s or private
development funds, etc. By doing so, productivity is increased both
on individual and national level and therefore social wellbeing in
general. In one word, creation of information society - a knowledge
society is happening.
This work will describe challenges and strategies that will follow
the development as well as obstacles in creating information society
– knowledge society in Montenegro.
Abstract: This paper presents a study of laminar to turbulent transition on a profile specifically designed for wind turbine blades, the DU91-W2-250, which belongs to a class of wind turbine dedicated airfoils, developed by Delft University of Technology. A comparison between the experimental behavior of the airfoil studied at Delft wind tunnel and the numerical predictions of the commercial CFD solver ANSYS FLUENT® has been performed. The prediction capabilities of the Spalart-Allmaras turbulence model and of the γ-θ Transitional model have been tested. A sensitivity analysis of the numerical results to the spatial domain discretization has also been performed using four different computational grids, which have been created using the mesher GAMBIT®. The comparison between experimental measurements and CFD results have allowed to determine the importance of the numerical prediction of the laminar to turbulent transition, in order not to overestimate airfoil friction drag due to a fully turbulent-regime flow computation.
Abstract: This paper has two main ideas. Firstly, it describes Evans and Wurster-s concepts “the trade-off between reach and richness", and relates them to the impact of technology on the virtual markets. Authors Evans and Wurster see the transfer of information as a 'trade'off between richness and reach-. Reach refers to the number of people who share particular information, with Richness ['Rich'] being a more complex concept combining: bandwidth, customization, interactivity, reliability, security and currency. Traditional shopping limits the number of shops the shopper is able to visit due to time and other cost constraints; the time spent traveling consequently leaves the shopper with less time to evaluate the product. The paper concludes that although the Web provides Reach, offering Richness and the sense of community required for creating and sustaining relationships with potential clients could be difficult.
Abstract: Data gathering is an essential operation in wireless
sensor network applications. So it requires energy efficiency
techniques to increase the lifetime of the network. Similarly,
clustering is also an effective technique to improve the energy
efficiency and network lifetime of wireless sensor networks. In this
paper, an energy efficient cluster formation protocol is proposed with
the objective of achieving low energy dissipation and latency without
sacrificing application specific quality. The objective is achieved by
applying randomized, adaptive, self-configuring cluster formation
and localized control for data transfers. It involves application -
specific data processing, such as data aggregation or compression.
The cluster formation algorithm allows each node to make
independent decisions, so as to generate good clusters as the end.
Simulation results show that the proposed protocol utilizes minimum
energy and latency for cluster formation, there by reducing the
overhead of the protocol.
Abstract: In order to answer the general question: “What does a simple agent with a limited life-time require for constructing a useful representation of the environment?" we propose a robot platform including the simplest probabilistic sensory and motor layers. Then we use the platform as a test-bed for evaluation of the navigational capabilities of the robot with different “brains". We claim that a protocognitive behavior is not a consequence of highly sophisticated sensory–motor organs but instead emerges through an increment of the internal complexity and reutilization of the minimal sensory information. We show that the most fundamental robot element, the short-time memory, is essential in obstacle avoidance. However, in the simplest conditions of no obstacles the straightforward memoryless robot is usually superior. We also demonstrate how a low level action planning, involving essentially nonlinear dynamics, provides a considerable gain to the robot performance dynamically changing the robot strategy. Still, however, for very short life time the brainless robot is superior. Accordingly we suggest that small organisms (or agents) with short life-time does not require complex brains and even can benefit from simple brain-like (reflex) structures. To some extend this may mean that controlling blocks of modern robots are too complicated comparative to their life-time and mechanical abilities.
Abstract: Emotions are related with learning processes and
physiological signals can be used to detect them for the
personalization of learning resources and to control the pace of
instruction. A model of relevant emotions has been developed, where
specific combinations of emotions and cognition processes are
connected and integrated with the concept of 'flow', in order to
improve learning. The cardiac pulse is a reliable signal that carries
useful information about the subject-s emotional condition; it is
detected using a classroom chair adapted with non invasive EMFi
sensor and an acquisition system that generates a ballistocardiogram
(BCG), the signal is processed by an algorithm to obtain
characteristics that match a specific emotional condition. The
complete chair system is presented in this work, along with a
framework for the personalization of learning resources.
Abstract: Airbag deployment has been known to be responsible
for huge death, incidental injuries and broken bones due to low crash
severity and wrong deployment decisions. Therefore, the authorities
and industries have been looking for more innovative and intelligent
products to be realized for future enhancements in the vehicle safety
systems (VSSs). Although the VSSs technologies have advanced
considerably, they still face challenges such as how to avoid
unnecessary and untimely airbag deployments that can be hazardous
and fatal. Currently, most of the existing airbag systems deploy
without regard to occupant size and position. As such, this paper will
focus on the occupant and crash sensing performances due to frontal
collisions for the new breed of so called smart airbag systems. It
intends to provide a thorough discussion relating to the occupancy
detection, occupant size classification, occupant off-position
detection to determine safe distance zone for airbag deployment,
crash-severity analysis and airbag decision algorithms via a computer
modeling. The proposed system model consists of three main
modules namely, occupant sensing, crash severity analysis and
decision fusion. The occupant sensing system module utilizes the
weight sensor to determine occupancy, classify the occupant size,
and determine occupant off-position condition to compute safe
distance for airbag deployment. The crash severity analysis module is
used to generate relevant information pertinent to airbag deployment
decision. Outputs from these two modules are fused to the decision
module for correct and efficient airbag deployment action. Computer
modeling work is carried out using Simulink, Stateflow,
SimMechanics and Virtual Reality toolboxes.
Abstract: An optimal mean-square fusion formulas with scalar
and matrix weights are presented. The relationship between them is
established. The fusion formulas are compared on the continuous-time
filtering problem. The basic differential equation for cross-covariance
of the local errors being the key quantity for distributed fusion is
derived. It is shown that the fusion filters are effective for multi-sensor
systems containing different types of sensors. An example
demonstrating the reasonable good accuracy of the proposed filters is
given.
Abstract: In this paper, zigbee communication based wireless energy surveillance system is presented. The proposed system consists of multiple energy surveillance devices and an energy surveillance monitor. Each different standby power-off value of electric device is set automatically by using learning function of energy surveillance device. Thus adaptive standby power-off function provides user convenience and it maximizes the energy savings. Also, power consumption monitoring function is helpful to reduce inefficient energy consumption in home. The zigbee throughput simulator is designed to evaluate minimum transmission power and maximum allowable information quantity in the proposed system. The test result of prototype has been satisfied all the requirements. The proposed system has confirmed that can be used as an intelligent energy surveillance system for energy savings in home or office.
Abstract: Recently, much research has been conducted for
security for wireless sensor networks and ubiquitous computing.
Security issues such as authentication and data integrity are major
requirements to construct sensor network systems. Advanced
Encryption Standard (AES) is considered as one of candidate
algorithms for data encryption in wireless sensor networks. In this
paper, we will present the hardware architecture to implement low
power AES crypto module. Our low power AES crypto module has
optimized architecture of data encryption unit and key schedule unit
which could be applicable to wireless sensor networks. We also details
low power design methods used to design our low power AES crypto
module.
Abstract: The seeds of cotton (Gossypium hirsutum) fall among the lesser known oil seeds. Cottonseeds are not normally consumed in their natural state due to their gossypol content, an antinutrient. The effect of processing on the sensory characteristics and chemical composition of cottonseed and its extract was studied by subjecting the cottonseed extract to heat treatment (boiling) and the cottonseed to fermentation. The cottonseed extract was boiled using the open pot and the pressure pot for 30 minutes respectively. The fermentation of the cottonseed was carried out for 6 days with samples withdrawn at intervals of 2 days. The extract and fermented samples were subjected to chemical analysis and sensory evaluated for colour, aroma, taste, mouth feel, appearance and overallacceptability. The open pot sample was more preferred. Fermentation for 6 days resulted into a significant reduction in gossypol level of the cottonseed; however, sample fermented for 2 days was most preferred.
Abstract: For identifying the discriminative sequence features between exons and introns, a new paradigm, rescaled-range frameshift analysis (RRFA), was proposed. By RRFA, two new
sequence features, the frameshift sensitivity (FS) and the accumulative
penta-mer complexity (APC), were discovered which
were further integrated into a new feature of larger scale, the persistency in anti-mutation (PAM). The feature-validation experiments
were performed on six model organisms to test the power
of discrimination. All the experimental results highly support that FS, APC and PAM were all distinguishing features between exons
and introns. These identified new sequence features provide new insights into the sequence composition of genes and they have
great potentials of forming a new basis for recognizing the exonintron boundaries in gene sequences.
Abstract: Candida spp. are common and aggressive pathogens. Because of the growing resistance of Candida spp. to current antifungals, novel targets, found in Candida spp. but not in humans or other flora, have to be identified. The alternative oxidase (AOX) is one such possibility. This enzyme is insensitive to cyanide, but is sensitive to compounds such as salicylhydroxamic acid (SHAM), disulfiram and n-alkyl gallates. The growth each of six Candida spp. was inhibited significantly by ~13 mM SHAM or 2 mM cyanide, albeit to differing extents. In C. dubliniensis, C. krusei and C. tropicalis the rate of O2 uptake was inhibited by 18-36% by 25 mM SHAM, but this had little or no effect on C. glabrata, C. guilliermondii or C. parapsilosis. Although SHAM substantially inhibited the growth of Candida spp., it is unlikely that the inhibition of AOX was the cause. Salicylhydroxamic acid is used therapeutically in the treatment of urinary tract infections and urolithiasis, but it also has some potential in the treatment of Candida spp. infection.
Abstract: We propose a method for discrimination and
classification of ovarian with benign, malignant and normal tissue
using independent component analysis and neural networks. The
method was tested for a proteomic patters set from A database, and
radial basis functions neural networks. The best performance was
obtained with probabilistic neural networks, resulting I 99% success
rate, with 98% of specificity e 100% of sensitivity.