Abstract: In this paper, we argue the security protocols of
ZigBee wireless sensor network in MAC layer. AES 128-bit
encryption algorithm in CCM* mode is secure transferred data;
however, AES-s secret key will be break within nearest future.
Efficient public key algorithm, ECC has been mixed with AES to
rescue the ZigBee wireless sensor from cipher text and replay attack.
Also, the proposed protocol can parallelize the integrity function to
increase system performance.
Abstract: The paper provides a literature review of the STEPNC
compliant research around the world. The first part of this paper
focuses on projects based on STEP compliance followed by research
and development in this area based on machining operations. Review
the literature relating to relevant STEP standards and application in
the area of turning centers. This research will review the various
research work, carried out from the evolution of STEP-NC of the
CNC manufacturing activities. The paper concludes with discussion
of the applications in this particular area.
Abstract: Certain tRNA synthetases have developed highly accurate molecular machinery to discriminate their cognate amino acids. Those aaRSs achieve their goal via editing reaction in the Connective Polypeptide 1 (CP1). Recently mutagenesis studies have revealed the critical importance of residues in the CP1 domain for editing activity and X-ray structures have shown binding mode of noncognate amino acids in the editing domain. To pursue molecular mechanism for amino acid discrimination, molecular modeling studies were performed. Our results suggest that aaRS bind the noncognate amino acid more tightly than the cognate one. Finally, by comparing binding conformations of the amino acids in three systems, the amino acid binding mode was elucidated and a discrimination mechanism proposed. The results strongly reveal that the conserved threonines are responsible for amino acid discrimination. This is achieved through side chain interactions between T252 and T247/T248 as well as between those threonines and the incoming amino acids.
Abstract: SEMG (Surface Electromyogram) is one of the
bio-signals and is generated from the muscle. And there are many
research results that use forearm EMG to detect hand motions. In this
paper, we will talk about our developed the robot hand system that can
control grasping power by SEMG. In our system, we suppose that
muscle power is proportional to the amplitude of SEMG. The power is
estimated and the grip power of a robot hand is able to be controlled
using estimated muscle power in our system. In addition, to perform a
more precise control can be considered to build a closed loop feedback
system as an object to a subject to pressure from the edge of hand. Our
objectives of this study are the development of a method that makes
perfect detection of the hand grip force possible using SEMG patterns,
and applying this method to the man-machine interface.
Abstract: The IEEE 802.11e which is an enhanced version of the 802.11 WLAN standards incorporates the Quality of Service (QoS) which makes it a better choice for multimedia and real time applications. In this paper we study various aspects concerned with 802.11e standard. Further, the analysis results for this standard are compared with the legacy 802.11 standard. Simulation results show that IEEE 802.11e out performs legacy IEEE 802.11 in terms of quality of service due to its flow differentiated channel allocation and better queue management architecture. We also propose a method to improve the unfair allocation of bandwidth for downlink and uplink channels by varying the medium access priority level.
Abstract: Faced with social and health system capacity
constraints and rising and changing demand for welfare services,
governments and welfare providers are increasingly relying on
innovation to help support and enhance services. However, the
evidence reported by several studies indicates that the realization of
that potential is not an easy task. Innovations can be deemed
inherently complex to implement and operate, because many of them
involve a combination of technological and organizational renewal
within an environment featuring a diversity of stakeholders. Many
public welfare service innovations are markedly systemic in their
nature, which means that they emerge from, and must address, the
complex interplay between political, administrative, technological,
institutional and legal issues. This paper suggests that stakeholders
dealing with systemic innovation in welfare services must deal with
ambiguous and incomplete information in circumstances of
uncertainty. Employing a literature review methodology and case
study, this paper identifies, categorizes and discusses different
aspects of the uncertainty of systemic innovation in public welfare
services, and argues that uncertainty can be classified into eight
categories: technological uncertainty, market uncertainty,
regulatory/institutional uncertainty, social/political uncertainty,
acceptance/legitimacy uncertainty, managerial uncertainty, timing
uncertainty and consequence uncertainty.
Abstract: Water hyacinth has been used in aquatic systems for
wastewater purification in many years worldwide. The role of water
hyacinth (Eichhornia crassipes) species in polishing nitrate and
phosphorus concentration from municipal wastewater treatment plant
effluent by phytoremediation method was evaluated. The objective
of this project is to determine the removal efficiency of water
hyacinth in polishing nitrate and phosphorus, as well as chemical
oxygen demand (COD) and ammonia. Water hyacinth is considered
as the most efficient aquatic plant used in removing vast range of
pollutants such as organic matters, nutrients and heavy metals. Water
hyacinth, also referred as macrophytes, were cultivated in the
treatment house in a reactor tank of approximately 90(L) x 40(W) x
25(H) in dimension and built with three compartments. Three water
hyacinths were placed in each compartments and water sample in
each compartment were collected in every two days. The plant
observation was conducted by weight measurement, plant uptake and
new young shoot development. Water hyacinth effectively removed
approximately 49% of COD, 81% of ammonia, 67% of phosphorus
and 92% of nitrate. It also showed significant growth rate at starting
from day 6 with 0.33 shoot/day and they kept developing up to 0.38
shoot/day at the end of day 24. From the studies conducted, it was
proved that water hyacinth is capable of polishing the effluent of
municipal wastewater which contains undesirable amount of nitrate
and phosphorus concentration.
Abstract: As the Internet continues to grow at a rapid pace as
the primary medium for communications and commerce and as
telecommunication networks and systems continue to expand their
global reach, digital information has become the most popular and
important information resource and our dependence upon the
underlying cyber infrastructure has been increasing significantly.
Unfortunately, as our dependency has grown, so has the threat to the
cyber infrastructure from spammers, attackers and criminal
enterprises. In this paper, we propose a new machine learning based
network intrusion detection framework for cyber security. The
detection process of the framework consists of two stages: model
construction and intrusion detection. In the model construction stage,
a semi-supervised machine learning algorithm is applied to a
collected set of network audit data to generate a profile of normal
network behavior and in the intrusion detection stage, input network
events are analyzed and compared with the patterns gathered in the
profile, and some of them are then flagged as anomalies should these
events are sufficiently far from the expected normal behavior. The
proposed framework is particularly applicable to the situations where
there is only a small amount of labeled network training data
available, which is very typical in real world network environments.
Abstract: In this paper, we propose a reversible watermarking
scheme based on histogram shifting (HS) to embed watermark bits
into the H.264/AVC standard videos by modifying the last nonzero
level in the context adaptive variable length coding (CAVLC) domain.
The proposed method collects all of the last nonzero coefficients (or
called last level coefficient) of 4×4 sub-macro blocks in a macro
block and utilizes predictions for the current last level from the
neighbor block-s last levels to embed watermark bits. The feature of
the proposed method is low computational and has the ability of
reversible recovery. The experimental results have demonstrated that
our proposed scheme has acceptable degradation on video quality and
output bit-rate for most test videos.
Abstract: The use of machine vision to inspect the outcome of
surgical tasks is investigated, with the aim of incorporating this
approach in robotic surgery systems. Machine vision is a non-contact
form of inspection i.e. no part of the vision system is in direct contact
with the patient, and is therefore well suited for surgery where
sterility is an important consideration,. As a proof-of-concept, three
primary surgical tasks for a common neurosurgical procedure were
inspected using machine vision. Experiments were performed on
cadaveric pig heads to simulate the two possible outcomes i.e.
satisfactory or unsatisfactory, for tasks involved in making a burr
hole, namely incision, retraction, and drilling. We identify low level
image features to distinguish the two outcomes, as well as report on
results that validate our proposed approach. The potential of using
machine vision in a surgical environment, and the challenges that
must be addressed, are identified and discussed.
Abstract: This work presents the results of a study carried out to
determine the sliding wear behavior and its effect on the process
parameters of components manufactured by direct metal laser
sintering (DMLS). A standard procedure and specimen had been used
in the present study to find the wear behavior. Using Taguchi-s
experimental technique, an orthogonal array of modified L8 had been
developed. Sliding wear testing using pin-on-disk machine was
carried out and analysis of variance (ANOVA) technique was used to
investigate the effect of process parameters and to identify the main
process parameter that influences the properties of wear behavior on
the DMLS components. It has been found that part orientation, one
of the selected process parameter had more influence on wear as
compared to other selected process parameters.
Abstract: In this paper presented initial design of Low Speed
Axial Flux Permanent Magnet (AFPM) Machine with Non-Slotted
TORUS topology type by use of certain algorithm (Appendix).
Validation of design algorithm studied by means of selected data of
an initial prototype machine. Analytically design calculation carried
out by means of design algorithm and obtained results compared with
results of Finite Element Method (FEM).
Abstract: In highly competitive environments, a growing
number of companies must regularly launch new products speedily
and successfully. A company-s success is based on the systematic,
conscious product designing method which meets the market
requirements and takes risks as well as resources into consideration.
Research has found that developing and launching new products are
inherently risky endeavors. Hence in this research, we aim at
introducing a risk evaluation framework for the new product
innovation process. Our framework is based on the fuzzy analytical
hierarchy process (FAHP) methodology. We have applied all the
stages of the framework on the risk evaluation process of a
pharmaceuticals company.
Abstract: An analytical solution for dispersion of a solute in the
peristaltic motion of a couple stress fluid in the presence of magnetic
field with both homogeneous and heterogeneous chemical reactions is
presented. The average effective dispersion coefficient has been found
using Taylor-s limiting condition and long wavelength approximation.
The effects of various relevant parameters on the average effective
coefficient of dispersion have been studied. The average effective
dispersion coefficient tends to decrease with magnetic field parameter,
homogeneous chemical reaction rate parameter and amplitude ratio
but tends to increase with heterogeneous chemical reaction rate
parameter.
Abstract: This paper discusses coordinated reactive power -
voltage (Q-V) control in a multi machine steam power plant. The
drawbacks of manual Q-V control are briefly listed, and the design
requirements for coordinated Q-V controller are specified.
Theoretical background and mathematical model of the new
controller are presented next followed by validation of developed
Matlab/Simulink model through comparison with recorded
responses in real steam power plant and description of practical
realisation of the controller. Finally, the performance of
commissioned controller is illustrated on several examples of
coordinated Q-V control in real steam power plant and compared
with manual control.
Abstract: This paper presents a systematic procedure for modelling and simulation of a power system installed with a power system stabilizer (PSS) and a flexible ac transmission system (FACTS)-based controller. For the design purpose, the model of example power system which is a single-machine infinite-bus power system installed with the proposed controllers is developed in MATLAB/SIMULINK. In the developed model synchronous generator is represented by model 1.1. which includes both the generator main field winding and the damper winding in q-axis so as to evaluate the impact of PSS and FACTS-based controller on power system stability. The model can be can be used for teaching the power system stability phenomena, and also for research works especially to develop generator controllers using advanced technologies. Further, to avoid adverse interactions, PSS and FACTS-based controller are simultaneously designed employing genetic algorithm (GA). The non-linear simulation results are presented for the example power system under various disturbance conditions to validate the effectiveness of the proposed modelling and simultaneous design approach.
Abstract: The amount of the information being churned out by the field of biology has jumped manifold and now requires the extensive use of computer techniques for the management of this information. The predominance of biological information such as protein sequence similarity in the biological information sea is key information for detecting protein evolutionary relationship. Protein sequence similarity typically implies homology, which in turn may imply structural and functional similarities. In this work, we propose, a learning method for detecting remote protein homology. The proposed method uses a transformation that converts protein sequence into fixed-dimensional representative feature vectors. Each feature vector records the sensitivity of a protein sequence to a set of amino acids substrings generated from the protein sequences of interest. These features are then used in conjunction with support vector machines for the detection of the protein remote homology. The proposed method is tested and evaluated on two different benchmark protein datasets and it-s able to deliver improvements over most of the existing homology detection methods.
Abstract: The deterministic quantum transfer-matrix (QTM)
technique and its mathematical background are presented. This
important tool in computational physics can be applied to a class of
the real physical low-dimensional magnetic systems described by the
Heisenberg hamiltonian which includes the macroscopic molecularbased
spin chains, small size magnetic clusters embedded in some
supramolecules and other interesting compounds. Using QTM, the
spin degrees of freedom are accurately taken into account, yielding
the thermodynamical functions at finite temperatures.
In order to test the application for the susceptibility calculations to
run in the parallel environment, the speed-up and efficiency of
parallelization are analyzed on our platform SGI Origin 3800 with
p = 128 processor units. Using Message Parallel Interface (MPI)
system libraries we find the efficiency of the code of 94% for
p = 128 that makes our application highly scalable.
Abstract: This paper presents a recognition system for isolated
words like robot commands. It’s carried out by Time Delay Neural
Networks; TDNN. To teleoperate a robot for specific tasks as turn,
close, etc… In industrial environment and taking into account the
noise coming from the machine. The choice of TDNN is based on its
generalization in terms of accuracy, in more it acts as a filter that
allows the passage of certain desirable frequency characteristics of
speech; the goal is to determine the parameters of this filter for
making an adaptable system to the variability of speech signal and to
noise especially, for this the back propagation technique was used in
learning phase. The approach was applied on commands pronounced
in two languages separately: The French and Arabic. The results for
two test bases of 300 spoken words for each one are 87%, 97.6% in
neutral environment and 77.67%, 92.67% when the white Gaussian
noisy was added with a SNR of 35 dB.
Abstract: In this study, the use of silicon NAM (Non-Audible
Murmur) microphone in automatic speech recognition is presented.
NAM microphones are special acoustic sensors, which are attached
behind the talker-s ear and can capture not only normal (audible)
speech, but also very quietly uttered speech (non-audible murmur).
As a result, NAM microphones can be applied in automatic speech
recognition systems when privacy is desired in human-machine communication.
Moreover, NAM microphones show robustness against
noise and they might be used in special systems (speech recognition,
speech conversion etc.) for sound-impaired people. Using a small
amount of training data and adaptation approaches, 93.9% word
accuracy was achieved for a 20k Japanese vocabulary dictation
task. Non-audible murmur recognition in noisy environments is also
investigated. In this study, further analysis of the NAM speech has
been made using distance measures between hidden Markov model
(HMM) pairs. It has been shown the reduced spectral space of NAM
speech using a metric distance, however the location of the different
phonemes of NAM are similar to the location of the phonemes
of normal speech, and the NAM sounds are well discriminated.
Promising results in using nonlinear features are also introduced,
especially under noisy conditions.