Abstract: This paper proposes a solution to the motion planning
and control problem of a point-mass robot which is required to move
safely to a designated target in a priori known workspace cluttered
with fixed elliptical obstacles of arbitrary position and sizes. A
tailored and unique algorithm for target convergence and obstacle
avoidance is proposed that will work for any number of fixed
obstacles. The control laws proposed in this paper also ensures that
the equilibrium point of the given system is asymptotically stable.
Computer simulations with the proposed technique and applications
to a planar (RP) manipulator will be presented.
Abstract: Study on suppression of interference in time domain equalizers is attempted for high data rate impulse radio (IR) ultra wideband communication system. The narrow band systems may cause interference with UWB devices as it is having very low transmission power and the large bandwidth. SRAKE receiver improves system performance by equalizing signals from different paths. This enables the use of SRAKE receiver techniques in IRUWB systems. But Rake receiver alone fails to suppress narrowband interference (NBI). A hybrid SRake-MMSE time domain equalizer is proposed to overcome this by taking into account both the effect of the number of rake fingers and equalizer taps. It also combats intersymbol interference. A semi analytical approach and Monte-Carlo simulation are used to investigate the BER performance of SRAKEMMSE receiver on IEEE 802.15.3a UWB channel models. Study on non-line of sight indoor channel models (both CM3 and CM4) illustrates that bit error rate performance of SRake-MMSE receiver with NBI performs better than that of Rake receiver without NBI. We show that for a MMSE equalizer operating at high SNR-s the number of equalizer taps plays a more significant role in suppressing interference.
Abstract: In this paper, an experimentation to enhance the
visibility of hot objects in a thermal image acquired with ordinary
digital camera is reported, after the applications of lowpass and
median filters to suppress the distracting granular noises. The
common thresholding and slicing techniques were used on the
histogram at different gray levels, followed by a subjective
comparative evaluation. The best result came out with the threshold
level 115 and the number of slices 3.
Abstract: In this paper, the trajectory tracking problem for carlike mobile robots have been studied. The system comprises of a leader and a follower robot. The purpose is to control the follower so that the leader-s trajectory is tracked with arbitrary desired clearance to avoid inter-robot collision while navigating in a terrain with obstacles. A set of artificial potential field functions is proposed using the Direct Method of Lyapunov for the avoidance of obstacles and attraction to their designated targets. Simulation results prove the efficiency of our control technique.
Abstract: Tracing and locating the geographical location of users (Geolocation) is used extensively in todays Internet. Whenever we, e.g., request a page from google we are - unless there was a specific configuration made - automatically forwarded to the page with the relevant language and amongst others, dependent on our location identified, specific commercials are presented. Especially within the area of Network Security, Geolocation has a significant impact. Because of the way the Internet works, attacks can be executed from almost everywhere. Therefore, for an attribution, knowledge of the origination of an attack - and thus Geolocation - is mandatory in order to be able to trace back an attacker. In addition, Geolocation can also be used very successfully to increase the security of a network during operation (i.e. before an intrusion actually has taken place). Similar to greylisting in emails, Geolocation allows to (i) correlate attacks detected with new connections and (ii) as a consequence to classify traffic a priori as more suspicious (thus particularly allowing to inspect this traffic in more detail). Although numerous techniques for Geolocation are existing, each strategy is subject to certain restrictions. Following the ideas of Endo et al., this publication tries to overcome these shortcomings with a combined solution of different methods to allow improved and optimized Geolocation. Thus, we present our architecture for improved Geolocation, by designing a new algorithm, which combines several Geolocation techniques to increase the accuracy.
Abstract: The effect of gamma irradiation on micro-hardness of polymer blends of poly (ethyl methacrylate)(PEMA) and poly (ethylene oxide) (PEO) has been investigated to detect the radiation induced crosslinking. The blend system comprises a noncrystallizable polymer, PEMA and a crystallizable polymer, PEO. On irradiation, the overall hardness of the blend specimens for different dose levels infers occurrence of a crosslinking process. The radiation-induced crosslinking was greater for blends having lower concentration of PEO. However, increase in radiation dose causes softening of blend system due to radiation induced scissioning of the chains
Abstract: The necessity of ever-increasing use of distributed
data in computer networks is obvious for all. One technique that is
performed on the distributed data for increasing of efficiency and
reliablity is data rplication. In this paper, after introducing this
technique and its advantages, we will examine some dynamic data
replication. We will examine their characteristies for some overus
scenario and the we will propose some suggestion for their
improvement.
Abstract: This paper proposes a new approach for image encryption
using a combination of different permutation techniques.
The main idea behind the present work is that an image can be
viewed as an arrangement of bits, pixels and blocks. The intelligible
information present in an image is due to the correlations among the
bits, pixels and blocks in a given arrangement. This perceivable information
can be reduced by decreasing the correlation among the bits,
pixels and blocks using certain permutation techniques. This paper
presents an approach for a random combination of the aforementioned
permutations for image encryption. From the results, it is observed
that the permutation of bits is effective in significantly reducing the
correlation thereby decreasing the perceptual information, whereas
the permutation of pixels and blocks are good at producing higher
level security compared to bit permutation. A random combination
method employing all the three techniques thus is observed to be
useful for tactical security applications, where protection is needed
only against a casual observer.
Abstract: A new topology of unified power quality conditioner
(UPQC) is proposed for different power quality (PQ) improvement in
a three-phase four-wire (3P-4W) distribution system. For neutral
current mitigation, a star-hexagon transformer is connected in shunt
near the load along with three-leg voltage source inverters (VSIs)
based UPQC. For the mitigation of source neutral current, the uses of
passive elements are advantageous over the active compensation due
to ruggedness and less complexity of control. In addition to this, by
connecting a star-hexagon transformer for neutral current mitigation
the over all rating of the UPQC is reduced. The performance of the
proposed topology of 3P-4W UPQC is evaluated for power-factor
correction, load balancing, neutral current mitigation and mitigation
of voltage and currents harmonics. A simple control algorithm based
on Unit Vector Template (UVT) technique is used as a control
strategy of UPQC for mitigation of different PQ problems. In this
control scheme, the current/voltage control is applied over the
fundamental supply currents/voltages instead of fast changing APFs
currents/voltages, thereby reducing the computational delay.
Moreover, no extra control is required for neutral source current
compensation; hence the numbers of current sensors are reduced. The
performance of the proposed topology of UPQC is analyzed through
simulations results using MATLAB software with its Simulink and
Power System Block set toolboxes.
Abstract: Knowing about the customer behavior in a grocery has
been a long-standing issue in the retailing industry. The advent of
RFID has made it easier to collect moving data for an individual
shopper's behavior. Most of the previous studies used the traditional
statistical clustering technique to find the major characteristics of
customer behavior, especially shopping path. However, in using the
clustering technique, due to various spatial constraints in the store,
standard clustering methods are not feasible because moving data such
as the shopping path should be adjusted in advance of the analysis,
which is time-consuming and causes data distortion. To alleviate this
problem, we propose a new approach to spatial pattern clustering
based on the longest common subsequence. Experimental results using
real data obtained from a grocery confirm the good performance of the
proposed method in finding the hot spot, dead spot and major path
patterns of customer movements.
Abstract: Gas Metal Arc Welding (GMAW) processes is an
important joining process widely used in metal fabrication
industries. This paper addresses modeling and optimization of this
technique using a set of experimental data and regression analysis.
The set of experimental data has been used to assess the influence
of GMAW process parameters in weld bead geometry. The
process variables considered here include voltage (V); wire feed
rate (F); torch Angle (A); welding speed (S) and nozzle-to-plate
distance (D). The process output characteristics include weld bead
height, width and penetration. The Taguchi method and regression
modeling are used in order to establish the relationships between
input and output parameters. The adequacy of the model is
evaluated using analysis of variance (ANOVA) technique. In the
next stage, the proposed model is embedded into a Simulated
Annealing (SA) algorithm to optimize the GMAW process
parameters. The objective is to determine a suitable set of process
parameters that can produce desired bead geometry, considering
the ranges of the process parameters. Computational results prove
the effectiveness of the proposed model and optimization
procedure.
Abstract: Variable channel conditions in underwater networks,
and variable distances between sensors due to water current, leads to
variable bit error rate (BER). This variability in BER has great
effects on energy efficiency of error correction techniques used. In
this paper an efficient energy adaptive hybrid error correction
technique (AHECT) is proposed. AHECT adaptively changes error
technique from pure retransmission (ARQ) in a low BER case to a
hybrid technique with variable encoding rates (ARQ & FEC) in a
high BER cases. An adaptation algorithm depends on a precalculated
packet acceptance rate (PAR) look-up table, current BER,
packet size and error correction technique used is proposed. Based
on this adaptation algorithm a periodically 3-bit feedback is added to
the acknowledgment packet to state which error correction technique
is suitable for the current channel conditions and distance.
Comparative studies were done between this technique and other
techniques, and the results show that AHECT is more energy
efficient and has high probability of success than all those
techniques.
Abstract: We apply a particle tracking technique to track the motion of individual pathogenic Leptospira. We observe and capture images of motile Leptospira by means of CCD and darkfield microscope. Image processing, statistical theories and simulations are used for data analysis. Based on trajectory patterns, mean square displacement, and power spectral density characteristics, we found that the motion modes are most likely to be directed motion mode (70%) and the rest are either normal diffusion or unidentified mode. Our findings may support the fact that why leptospires are very well efficient toward targeting internal tissues as a result of increase in virulence factor.
Abstract: Data mining can be called as a technique to extract
information from data. It is the process of obtaining hidden
information and then turning it into qualified knowledge by statistical
and artificial intelligence technique. One of its application areas is
medical area to form decision support systems for diagnosis just by
inventing meaningful information from given medical data. In this
study a decision support system for diagnosis of illness that make use
of data mining and three different artificial intelligence classifier
algorithms namely Multilayer Perceptron, Naive Bayes Classifier and
J.48. Pima Indian dataset of UCI Machine Learning Repository was
used. This dataset includes urinary and blood test results of 768
patients. These test results consist of 8 different feature vectors.
Obtained classifying results were compared with the previous studies.
The suggestions for future studies were presented.
Abstract: This paper is a review on the aspects and approaches of design an image cryptosystem. First a general introduction given for cryptography and images encryption and followed by different techniques in image encryption and related works for each technique surveyed. Finally, general security analysis methods for encrypted images are mentioned.
Abstract: The gases generated in oil filled transformers can be
used for qualitative determination of incipient faults. The Dissolved
Gas Analysis has been widely used by utilities throughout the world
as the primarily diagnostic tool for transformer maintenance. In this
paper, various Artificial Intelligence Techniques that have been used
by the researchers in the past have been reviewed, some conclusions
have been drawn and a sequential hybrid system has been proposed.
The synergy of ANN and FIS can be a good solution for reliable
results for predicting faults because one should not rely on a single
technology when dealing with real–life applications.
Abstract: This paper deals with condition monitoring of electric switch machine for railway points. Point machine, as a complex electro-mechanical device, switch the track between two alternative routes. There has been an increasing interest in railway safety and the optimal management of railway equipments maintenance, e.g. point machine, in order to enhance railway service quality and reduce system failure. This paper explores the development of Kolmogorov- Smirnov (K-S) test to detect some point failures (external to the machine, slide chairs, fixing, stretchers, etc), while the point machine (inside the machine) is in its proper condition. Time-domain stator Current signatures of normal (healthy) and faulty points are taken by 3 Hall Effect sensors and are analyzed by K-S test. The test is simulated by creating three types of such failures, namely putting a hard stone and a soft stone between stock rail and switch blades as obstacles and also slide chairs- friction. The test has been applied for those three faults which the results show that K-S test can effectively be developed for the aim of other point failures detection, which their current signatures deviate parametrically from the healthy current signature. K-S test as an analysis technique, assuming that any defect has a specific probability distribution. Empirical cumulative distribution functions (ECDF) are used to differentiate these probability distributions. This test works based on the null hypothesis that ECDF of target distribution is statistically similar to ECDF of reference distribution. Therefore by comparing a given current signature (as target signal) from unknown switch state to a number of template signatures (as reference signal) from known switch states, it is possible to identify which is the most likely state of the point machine under analysis.
Abstract: Requirement engineering has been the subject of large
volume of researches due to the significant role it plays in the
software development life cycle. However, dynamicity of software
industry is much faster than advances in requirements engineering
approaches. Therefore, this paper aims to systematically review and
evaluate the current research in requirement engineering and identify
new research trends and direction in this field. In addition, various
research methods associated with the Evaluation-based techniques
and empirical study are highlighted for the requirements engineering
field. Finally, challenges and recommendations on future directions
research are presented based on the research team observations
during this study.
Abstract: The aim of this research is to determine how preservice Turkish teachers perceive themselves in terms of problem solving skills. Students attending Department of Turkish Language Teaching of Gazi University Education Faculty in 2005-2006 academic year constitute the study group (n= 270) of this research in which survey model was utilized. Data were obtained by Problem Solving Inventory developed by Heppner & Peterson and Personal Information Form. Within the settings of this research, Cronbach Alpha reliability coefficient of the scale was found as .87. Besides, reliability coefficient obtained by split-half technique which splits odd and even numbered items of the scale was found as r=.81 (Split- Half Reliability). The findings of the research revealed that preservice Turkish teachers were sufficiently qualified on the subject of problem solving skills and statistical significance was found in favor of male candidates in terms of “gender" variable. According to the “grade" variable, statistical significance was found in favor of 4th graders.
Abstract: Wireless sensor networks are consisted of hundreds or
thousands of small sensors that have limited resources.
Energy-efficient techniques are the main issue of wireless sensor
networks. This paper proposes an energy efficient agent-based
framework in wireless sensor networks. We adopt biologically
inspired approaches for wireless sensor networks. Agent operates
automatically with their behavior policies as a gene. Agent aggregates
other agents to reduce communication and gives high priority to nodes
that have enough energy to communicate. Agent behavior policies are
optimized by genetic operation at the base station. Simulation results
show that our proposed framework increases the lifetime of each node.
Each agent selects a next-hop node with neighbor information and
behavior policies. Our proposed framework provides self-healing,
self-configuration, self-optimization properties to sensor nodes.