Abstract: Two multisensor system architectures for navigation
and guidance of small Unmanned Aircraft (UA) are presented and
compared. The main objective of our research is to design a compact,
light and relatively inexpensive system capable of providing the
required navigation performance in all phases of flight of small UA,
with a special focus on precision approach and landing, where Vision
Based Navigation (VBN) techniques can be fully exploited in a
multisensor integrated architecture. Various existing techniques for
VBN are compared and the Appearance-Based Navigation (ABN)
approach is selected for implementation. Feature extraction and
optical flow techniques are employed to estimate flight parameters
such as roll angle, pitch angle, deviation from the runway centreline
and body rates. Additionally, we address the possible synergies of
VBN, Global Navigation Satellite System (GNSS) and MEMS-IMU
(Micro-Electromechanical System Inertial Measurement Unit)
sensors, and the use of Aircraft Dynamics Model (ADM) to provide
additional information suitable to compensate for the shortcomings of
VBN and MEMS-IMU sensors in high-dynamics attitude
determination tasks. An Extended Kalman Filter (EKF) is developed
to fuse the information provided by the different sensors and to
provide estimates of position, velocity and attitude of the UA
platform in real-time. The key mathematical models describing the
two architectures i.e., VBN-IMU-GNSS (VIG) system and VIGADM
(VIGA) system are introduced. The first architecture uses VBN
and GNSS to augment the MEMS-IMU. The second mode also
includes the ADM to provide augmentation of the attitude channel.
Simulation of these two modes is carried out and the performances of
the two schemes are compared in a small UA integration scheme (i.e.,
AEROSONDE UA platform) exploring a representative cross-section
of this UA operational flight envelope, including high dynamics
manoeuvres and CAT-I to CAT-III precision approach tasks.
Simulation of the first system architecture (i.e., VIG system) shows
that the integrated system can reach position, velocity and attitude
accuracies compatible with the Required Navigation Performance
(RNP) requirements. Simulation of the VIGA system also shows
promising results since the achieved attitude accuracy is higher using
the VBN-IMU-ADM than using VBN-IMU only. A comparison of
VIG and VIGA system is also performed and it shows that the
position and attitude accuracy of the proposed VIG and VIGA
systems are both compatible with the RNP specified in the various
UA flight phases, including precision approach down to CAT-II.
Abstract: The groundwater quality was assessed nearby places of Nagalkeni, Chennai, Tamil Nadu, India. The selected physico-chemical parameters were pH, EC, TDS, total hardness (TH), anions like Ca, Mg, Na and K, and cations like SO4, NO3, Cl2, HCO3, and CO3, and Cr(VI). In order to suit the groundwater for drinking and irrigation purposes, compared the value of selected parameters with the value of selected parameters from BIS drinking water quality standard and irrigation water quality indices. The physico-chemical study of the groundwater systems of selected sites of nearby places of Nagalkeni showed that the groundwater is nearly acidic and mostly oxidizing in nature and hence, water is not suitable for drinking purpose directly. The results of the irrigation indices indicated that the groundwater samples in the study area found to be brackish water, results, groundwater from the study area is also not suitable for irrigation purpose directly, but the groundwater may be used after implementing some suitable treatment techniques.
Abstract: The advances in technology in the last five years
allowed an improvement in the educational area, as the increasing in
the development of educational software. One of the techniques that
emerged in this lapse is called Gamification, which is the utilization of
video game mechanics outside its bounds. Recent studies involving
this technique provided positive results in the application of these
concepts in many areas as marketing, health and education. In the last
area there are studies that covers from elementary to higher education,
with many variations to adequate to the educators methodologies.
Among higher education, focusing on IT courses, data structures are
an important subject taught in many of these courses, as they are
base for many systems. Based on the exposed this paper exposes
the development of an interactive web learning environment, called
DSLEP (Data Structure Learning Platform), to aid students in higher
education IT courses. The system includes basic concepts seen on
this subject such as stacks, queues, lists, arrays, trees and was
implemented to ease the insertion of new structures. It was also
implemented with gamification concepts, such as points, levels, and
leader boards, to engage students in the search for knowledge and
stimulate self-learning.
Abstract: This paper discusses on power spectral density (PSD) characteristics which are extracted from three-dimensional (3D) electroencephalogram (EEG) models. The EEG signal recording was conducted on 150 healthy subjects. Development of 3D EEG models involves pre-processing of raw EEG signals and construction of spectrogram images. Then, the values of maximum PSD were extracted as features from the model. These features are analyzed using mean relative power (MRP) and different mean relative power (DMRP) technique to observe the pattern among different brain balancing indexes. The results showed that by implementing these techniques, the pattern of brain balancing indexes can be clearly observed. Some patterns are indicates between index 1 to index 5 for left frontal (LF) and right frontal (RF).
Abstract: This paper presents advances in pulse width modulation techniques which refers to a method of carrying information on train of pulses and the information be encoded in the width of pulses. Pulse Width Modulation is used to control the inverter output voltage. This is done by exercising the control within the inverter itself by adjusting the ON and OFF periods of inverter. By fixing the DC input voltage we get AC output voltage. In variable speed AC motors the AC output voltage from a constant DC voltage is obtained by using inverter. Recent developments in power electronics and semiconductor technology have lead improvements in power electronic systems. Hence, different circuit configurations namely multilevel inverters have became popular and considerable interest by researcher are given on them. A fast space-vector pulse width modulation (SVPWM) method for five-level inverter is also discussed. In this method, the space vector diagram of the five-level inverter is decomposed into six space vector diagrams of three-level inverters. In turn, each of these six space vector diagrams of three-level inverter is decomposed into six space vector diagrams of two-level inverters. After decomposition, all the remaining necessary procedures for the three-level SVPWM are done like conventional two-level inverter. The proposed method reduces the algorithm complexity and the execution time. It can be applied to the multilevel inverters above the five-level also. The experimental setup for three-level diode-clamped inverter is developed using TMS320LF2407 DSP controller and the experimental results are analyzed.
Abstract: Medical image analysis is one of the great effects of computer image processing. There are several processes to analysis the medical images which the segmentation process is one of the challenging and most important step. In this paper the segmentation method proposed in order to segment the dental radiograph images. Thresholding method has been applied to simplify the images and to morphologically open binary image technique performed to eliminate the unnecessary regions on images. Furthermore, horizontal and vertical integral projection techniques used to extract the each individual tooth from radiograph images. Segmentation process has been done by applying the level set method on each extracted images. Nevertheless, the experiments results by 90% accuracy demonstrate that proposed method achieves high accuracy and promising result.
Abstract: Photovoltaic (PV) energy is one of the most important renewable energy sources. Maximum Power Point Tracking (MPPT) techniques should be used in photovoltaic systems to maximize the PV panel output power by tracking continuously the maximum power point which depends on panel’s temperature and on irradiance conditions. Incremental conductance control method has been used as MPPT algorithm. The methodology is based on connecting a pulse width modulated dc/dc SEPIC converter, which is controlled by a microprocessor based unit. The SEPIC converter is one of the buck-boost converters which maintain the output voltage as constant irrespective of the solar isolation level. By adjusting the switching frequency of the converter the maximum power point has been achieved. The main difference between the method used in the proposed MPPT systems and other technique used in the past is that PV array output power is used to directly control the dc/dc converter thus reducing the complexity of the system. The resulting system has high efficiency, low cost and can be easily modified. The tracking capability has been verified experimentally with a 10 W solar panel under a controlled experimental setup. The SEPIC converter and their control strategies has been analyzed and simulated using Simulink/Matlab software.
Abstract: This paper presents a set of artificial potential field functions that improves upon, in general, the motion planning and posture control, with theoretically guaranteed point and posture stabilities, convergence and collision avoidance properties of the general3-trailer system in a priori known environment. We basically design and inject two new concepts; ghost walls and the distance optimization technique (DOT) to strengthen point and posture stabilities, in the sense of Lyapunov, of our dynamical model. This new combination of techniques emerges as a convenient mechanism for obtaining feasible orientations at the target positions with an overall reduction in the complexity of the navigation laws. Simulations are provided to demonstrate the effectiveness of the controls laws.
Abstract: Microarray gene expression data play a vital in biological processes, gene regulation and disease mechanism. Biclustering in gene expression data is a subset of the genes indicating consistent patterns under the subset of the conditions. Finding a biclustering is an optimization problem. In recent years, swarm intelligence techniques are popular due to the fact that many real-world problems are increasingly large, complex and dynamic. By reasons of the size and complexity of the problems, it is necessary to find an optimization technique whose efficiency is measured by finding the near optimal solution within a reasonable amount of time. In this paper, the algorithmic concepts of the Particle Swarm Optimization (PSO), Shuffled Frog Leaping (SFL) and Cuckoo Search (CS) algorithms have been analyzed for the four benchmark gene expression dataset. The experiment results show that CS outperforms PSO and SFL for 3 datasets and SFL give better performance in one dataset. Also this work determines the biological relevance of the biclusters with Gene Ontology in terms of function, process and component.
Abstract: This paper presents a set of artificial potential field functions that improves upon, in general, the motion planning and posture control, with theoretically guaranteed point and posture stabilities, convergence and collision avoidance properties of 3-trailer systems in a priori known environment. We basically design and inject two new concepts; ghost walls and the distance optimization technique (DOT) to strengthen point and posture stabilities, in the sense of Lyapunov, of our dynamical model. This new combination of techniques emerges as a convenient mechanism for obtaining feasible orientations at the target positions with an overall reduction in the complexity of the navigation laws. The effectiveness of the proposed control laws were demonstrated via simulations of two traffic scenarios.
Abstract: In this paper, together with some improved
Lyapunov-Krasovskii functional and effective mathematical
techniques, several sufficient conditions are derived to guarantee the
error system is globally asymptotically stable with H∞
performance, in which both the time-delay and its time variation
can be fully considered. In order to get less conservative results of
the state estimation condition, zero equalities and reciprocally
convex approach are employed. The estimator gain matrix can be
obtained in terms of the solution to linear matrix inequalities. A
numerical example is provided to illustrate the usefulness and
effectiveness of the obtained results.
Abstract: The generalized Higham matrix is a complex symmetric matrix A = B + iC, where both B ∈ Cn×n and C ∈ Cn×n are Hermitian positive definite, and i = √−1 is the imaginary unit. The growth factor in Gaussian elimination is less than 3√2 for this kind of matrices. In this paper, we give a new brief proof on this result by different techniques, which can be understood very easily, and obtain some new findings.
Abstract: The continuous growth in the size of the World Wide Web has resulted in intricate Web sites, demanding enhanced user skills and more sophisticated tools to help the Web user to find the desired information. In order to make Web more user friendly, it is necessary to provide personalized services and recommendations to the Web user. For discovering interesting and frequent navigation patterns from Web server logs many Web usage mining techniques have been applied. The recommendation accuracy of usage based techniques can be improved by integrating Web site content and site structure in the personalization process.
Herein, we propose semantically enriched Web Usage Mining method for Personalization (SWUMP), an extension to solely usage based technique. This approach is a combination of the fields of Web Usage Mining and Semantic Web. In the proposed method, we envisage enriching the undirected graph derived from usage data with rich semantic information extracted from the Web pages and the Web site structure. The experimental results show that the SWUMP generates accurate recommendations and is able to achieve 10-20% better accuracy than the solely usage based model. The SWUMP addresses the new item problem inherent to solely usage based techniques.
Abstract: Microfibrous palygorskite and tubular halloysite clay mineral combined with nanocrystalline TiO2 are incorporating in the preparation of nanocomposite films on glass substrates via sol-gel route at 450oC. The synthesis is employing nonionic surfactant molecule as pore directing agent along with acetic acid-based sol-gel route without addition of water molecules. Drying and thermal treatment of composite films ensure elimination of organic material lead to the formation of TiO2 nanoparticles homogeneously distributed on the palygorskite or halloysite surfaces. Nanocomposite films without cracks of active anatase crystal phase on palygorskite and halloysite surfaces are characterized by microscopy techniques, UV-Vis spectroscopy, and porosimetry methods in order to examine their structural properties.
The composite palygorskite-TiO2 and halloysite-TiO2 films with variable quantities of palygorskite and halloysite were tested as photocatalysts in the photo-oxidation of Basic Blue 41 azo dye in water. These nanocomposite films proved to be most promising photocatalysts and highly effective to dye’s decoloration in spite of small amount of palygorskite-TiO2 or halloysite-TiO2 catalyst immobilized onto glass substrates mainly due to the high surface area and uniform distribution of TiO2 on clay minerals avoiding aggregation.
Abstract: Some of the key aspects of vulnerability—discovery, dissemination, and disclosure—have received some attention recently. However, the role of interaction among the vulnerability discoverers and vulnerability acquirers has not yet been adequately addressed. Our study suggests that a major percentage of discoverers, a majority in some cases, are unaffiliated with the software developers and thus are free to disseminate the vulnerabilities they discover in any way they like. As a result, multiple vulnerability markets have emerged. In some of these markets, the exchange is regulated, but in others, there is little or no regulation. In recent vulnerability discovery literature, the vulnerability discoverers have remained anonymous individuals. Although there has been an attempt to model the level of their efforts, information regarding their identities, modes of operation, and what they are doing with the discovered vulnerabilities has not been explored.
Reports of buying and selling of the vulnerabilities are now appearing in the press; however, the existence of such markets requires validation, and the natures of the markets need to be analyzed. To address this need, we have attempted to collect detailed information. We have identified the most prolific vulnerability discoverers throughout the past decade and examined their motivation and methods. A large percentage of these discoverers are located in Eastern and Western Europe and in the Far East. We have contacted several of them in order to collect firsthand information regarding their techniques, motivations, and involvement in the vulnerability markets. We examine why many of the discoverers appear to retire after a highly successful vulnerability-finding career. The paper identifies the actual vulnerability markets, rather than the hypothetical ideal markets that are often examined. The emergence of worldwide government agencies as vulnerability buyers has significant implications. We discuss potential factors that can impact the risk to society and the need for detailed exploration.
Abstract: The results of dissertation research "Preventing and
combating corruption in public procurement" are presented in this
publication. The study was conducted 2011 till 2013 in a Member
State of the European Union– in the Republic of Latvia.
Goal of the thesis is to explore corruption prevention and
combating issues in public procurement sphere, to identify the
prevalence rates, determinants and contributing factors and
prevention opportunities in Latvia.
In the first chapter the author analyzes theoretical aspects of
understanding corruption in public procurement, with particular
emphasis on corruption definition problem, its nature, causes and
consequences. A separate section is dedicated to the public
procurement concept, mechanism and legal framework. In the first
part of this work the author presents cognitive methodology of
corruption in public procurement field, based on which the author has
carried out an analysis of corruption situation in public procurement
in Republic of Latvia.
In the second chapter of the thesis, the author analyzes the
problem of corruption in public procurement, including its historical
aspects, typology and classification of corruption subjects involved,
corruption risk elements in public procurement and their
identification. During the development of the second chapter author's
practical experience in public procurements was widely used.
The third and fourth chapter deals with issues related to the
prevention and combating corruption in public procurement, namely
the operation of the concept, principles, methods and techniques,
subjects in Republic of Latvia, as well as an analysis of foreign
experience in preventing and combating corruption. The fifth chapter
is devoted to the corruption prevention and combating perspectives
and their assessment. In this chapter the author has made the
evaluation of corruption prevention and combating measures
efficiency in Republic of Latvia, assessment of anti-corruption
legislation development stage in public procurement field in Latvia.
Abstract: Supersymmetric Quantum Mechanics is an interesting
framework to analyze nonrelativistic quantal problems. Using these
techniques, we construct a family of strictly isospectral Hulth´en
potentials. Isospectral wave functions are generated and plotted for
different values of the deformation parameter.
Abstract: The proposed method is to study and analyze Electrocardiograph (ECG) waveform to detect abnormalities present with reference to P, Q, R and S peaks. The first phase includes the acquisition of real time ECG data. In the next phase, generation of signals followed by pre-processing. Thirdly, the procured ECG signal is subjected to feature extraction. The extracted features detect abnormal peaks present in the waveform Thus the normal and abnormal ECG signal could be differentiated based on the features extracted. The work is implemented in the most familiar multipurpose tool, MATLAB. This software efficiently uses algorithms and techniques for detection of any abnormalities present in the ECG signal. Proper utilization of MATLAB functions (both built-in and user defined) can lead us to work with ECG signals for processing and analysis in real time applications. The simulation would help in improving the accuracy and the hardware could be built conveniently.
Abstract: This paper deals with the problem of stability of
neural networks with leakage, discrete and distributed delays. A
new Lyapunov functional which contains some new double integral
terms are introduced. By using appropriate model transformation
that shifts the considered systems into the neutral-type time-delay
system, and by making use of some inequality techniques,
delay-dependent criteria are developed to guarantee the stability of
the considered system. Finally, numerical examples are provided to
illustrate the usefulness of the proposed main results.
Abstract: Information Security is the most describing problem in present times. To cop up with the security of the information, the passwords were introduced. The alphanumeric passwords are the most popular authentication method and still used up to now. However, text based passwords suffer from various drawbacks such as they are easy to crack through dictionary attacks, brute force attacks, keylogger, social engineering etc. Graphical Password is a good replacement for text password. Psychological studies say that human can remember pictures better than text. So this is the fact that graphical passwords are easy to remember. But at the same time due to this reason most of the graphical passwords are prone to shoulder surfing. In this paper, we have suggested a shoulder-surfing resistant graphical password authentication method. The system is a combination of recognition and pure recall based techniques. Proposed scheme can be useful for smart hand held devices (like smart phones i.e. PDAs, iPod, iPhone, etc) which are more handy and convenient to use than traditional desktop computer systems.