Abstract: This paper focuses on the integration of hybrid renewable energy resources available in remote isolated islands of Sundarban-24 Parganas-South of Eastern part of India to National Grid of conventional power supply to give a Smart-Grid scenario. Before grid-integration, feasibility of optimization of hybrid renewable energy system is monitored through an Intelligent Controller proposed to be installed at Moushuni Island of Sundarban. The objective is to ensure the reliability and efficiency of the system to optimize the utilization of the hybrid renewable energy sources and also a proposition of how theses isolated Hybrid Renewable Energy Systems at remote islands can be grid-connected is analyzed towards vision of green smart-grid.
Abstract: This paper focuses on a critical component of the situational awareness (SA), the neural control of autonomous constant depth flight of an autonomous underwater vehicle (AUV). Autonomous constant depth flight is a challenging but important task for AUVs to achieve high level of autonomy under adverse conditions. The fundamental requirement for constant depth flight is the knowledge of the depth, and a properly designed controller to govern the process. The AUV, named VORAM, is used as a model for the verification of the proposed hybrid control algorithm. Three neural network controllers, named NARMA-L2 controllers, are designed for fast and stable diving maneuvers of chosen AUV model. This hybrid control strategy for chosen AUV model has been verified by simulation of diving maneuvers using software package Simulink and demonstrated good performance for fast SA in real-time searchand- rescue operations.
Abstract: In this paper, the effect of transmission codes on the
performance of coherent square M-ary quadrature amplitude
modulation (CSMQAM) under hybrid selection/maximal-ratio
combining (H-S/MRC) diversity is analysed. The fading channels are
modeled as frequency non-selective slow independent and identically
distributed Rayleigh fading channels corrupted by additive white
Gaussian noise (AWGN). The results for coded MQAM are
computed numerically for the case of (24,12) extended Golay code
and compared with uncoded MQAM under H-S/MRC diversity by
plotting error probabilities versus average signal to noise ratio (SNR)
for various values L and N in order to examine the improvement in
the performance of the digital communications system as the number
of selected diversity branches is increased. The results for no
diversity, conventional SC and Lth order MRC schemes are also
plotted for comparison. Closed form analytical results derived in this
paper are sufficiently simple and therefore can be computed
numerically without any approximations. The analytical results
presented in this paper are expected to provide useful information
needed for design and analysis of digital communication systems
over wireless fading channels.
Abstract: This paper deals with the application of artificial
neural network (ANN) and fuzzy based Adaptive Neuro Fuzzy
Inference System(ANFIS) approach to Load Frequency Control
(LFC) of multi unequal area hydro-thermal interconnected power
system. The proposed ANFIS controller combines the advantages of
fuzzy controller as well as quick response and adaptability nature of
ANN. Area-1 and area-2 consists of thermal reheat power plant
whereas area-3 and area-4 consists of hydro power plant with electric
governor. Performance evaluation is carried out by using intelligent
controller like ANFIS, ANN and Fuzzy controllers and conventional
PI and PID control approaches. To enhance the performance of
intelligent and conventional controller sliding surface is included.
The performances of the controllers are simulated using
MATLAB/SIMULINK package. A comparison of ANFIS, ANN,
Fuzzy, PI and PID based approaches shows the superiority of
proposed ANFIS over ANN & fuzzy, PI and PID controller for 1%
step load variation.
Abstract: A different concept for designing and detailing of
reinforced concrete precast frame structures is analyzed in this paper.
The new detailing of the joints derives from the special hybrid
moment frame joints. The special reinforcements of this alternative
detailing, named modified special hybrid joint, are bondless with
respect to both column and beams. Full scale tests were performed on
a plan model, which represents a part of 5 story structure, cropped in
the middle of the beams and columns spans. Theoretical approach
was developed, based on testing results on twice repaired model,
subjected to lateral seismic type loading. Discussion regarding the
modified special hybrid joint behavior and further on widening
research needed concludes the presentation.
Abstract: Recently, malware attacks have become more serious
over the Internet by e-mail, denial of service (DoS) or distributed
denial of service (DDoS). The Botnets have become a significant part
of the Internet malware attacks. The traditional botnets include three
parts – botmaster, command and control (C&C) servers and bots. The
C&C servers receive commands from botmaster and control the
distributions of computers remotely. Bots use DNS to find the
positions of C&C server. In this paper, we propose an advanced hybrid
peer-to-peer (P2P) botnet 2.0 (AHP2P botnet 2.0) using web 2.0
technology to hide the instructions from botmaster into social sites,
which are regarded as C&C servers. Servent bots are regarded as
sub-C&C servers to get the instructions from social sites. The AHP2P
botnet 2.0 can evaluate the performance of servent bots, reduce DNS
traffics from bots to C&C servers, and achieve harder detection bots
actions than IRC-based botnets over the Internet.
Abstract: Caching was suggested as a solution for reducing bandwidth utilization and minimizing query latency in mobile environments. Over the years, different caching approaches have been proposed, some relying on the server to broadcast reports periodically informing of the updated data while others allowed the clients to request for the data whenever needed. Until recently a hybrid cache consistency scheme Scalable Asynchronous Cache Consistency Scheme SACCS was proposed, which combined the two different approaches benefits- and is proved to be more efficient and scalable. Nevertheless, caching has its limitations too, due to the limited cache size and the limited bandwidth, which makes the implementation of cache replacement strategy an important aspect for improving the cache consistency algorithms. In this thesis, we proposed a new cache replacement strategy, the Least Unified Value strategy (LUV) to replace the Least Recently Used (LRU) that SACCS was based on. This paper studies the advantages and the drawbacks of the new proposed strategy, comparing it with different categories of cache replacement strategies.
Abstract: The Neuro-Fuzzy hybridization scheme has become
of research interest in pattern classification over the past decade. The
present paper proposes a novel Modified Adaptive Fuzzy Inference
Engine (MAFIE) for pattern classification. A modified Apriori
algorithm technique is utilized to reduce a minimal set of decision
rules based on input output data sets. A TSK type fuzzy inference
system is constructed by the automatic generation of membership
functions and rules by the fuzzy c-means clustering and Apriori
algorithm technique, respectively. The generated adaptive fuzzy
inference engine is adjusted by the least-squares fit and a conjugate
gradient descent algorithm towards better performance with a
minimal set of rules. The proposed MAFIE is able to reduce the
number of rules which increases exponentially when more input
variables are involved. The performance of the proposed MAFIE is
compared with other existing applications of pattern classification
schemes using Fisher-s Iris and Wisconsin breast cancer data sets and
shown to be very competitive.
Abstract: This paper presents two different sequential switching hybrid-modulation strategies and implemented for cascaded multilevel inverters. Hybrid modulation strategies represent the combinations of Fundamental-frequency pulse width modulation (FFPWM) and Multilevel sinusoidal-modulation (MSPWM) strategies, and are designed for performance of the well-known Alternative Phase opposition disposition (APOD), Phase shifted carrier (PSC). The main characteristics of these modulations are the reduction of switching losses with good harmonic performance, balanced power loss dissipation among the devices with in a cell, and among the series-connected cells. The feasibility of these modulations is verified through spectral analysis, power loss analysis and simulation.
Abstract: For the past thirty years the Malaysian economy has been said to contribute well to the progress of the nations. However, the intensification of global economy activity and the extensive use of Information Communication Technologies (ICTs) in recent years are challenging government-s effort to further develop Malaysian society. The competition posed by the low wage economies such as China and Vietnam have made the government realise the importance of engaging in high-skill and high technology industries. It is hoped this will be the basis of attracting more foreign direct investment (FDI) in order to help the country to compete in globalised world. Using Vision 2020 as it targeted vision, the government has decided to engage in the use of ICTs and introduce many policies pertaining to it. Mainly based on the secondary analysis approach, the findings show that policy pertaining to ICTs in Malaysia contributes to economic growth, but the consequences of this have resulted in greater division within society. Although some of the divisions such as gender and ethnicity are narrowing down, the gap in important areas such as regions and class differences is becoming wider. The widespread use of ICTs might contribute to the further establishment of democracy in Malaysia, but the increasing number of foreign entities such as FDI and foreign workers, cultural hybridisation and to some extent cultural domination are contributing to neocolonialism in Malaysia. This has obvious consequences for the government-s effort to create a Malaysian national identity. An important finding of this work is that there are contradictions within ICT policy between the effort to develop the economy and society.
Abstract: The charnockitic and associated granitic rocks of Akure area were studied for their field and petrographic relationship's. The outcrops locations were plotted in Surfer 8. The granitic rock exhibits a porphyritic texture and outcrops in the north-eastern side of the study area while the charnockitics outcrop in the central/western part. An essentially dark coloured and fine grained intrusive exhibiting xenoliths and xenocrysts (plagioclase phenocrysts) of the granite outcrops between the granitic and charnockitic rocks. Mineralogically, the central rock combines the content of the other two indicating that it is most likely a product of their hybridization. The charnockitic magma is believed to have intruded and assimilated the granite substantially thereby contaminating itself and consequently emplacing the hybrid. The presented model of emplacement elucidates the hybridization proposal. Conclusively, the charnockitics are believed to be (a) younger than the granite, (b) of Pan-African age and (c) of igneous origin.
Abstract: This paper shows the results obtained in the analysis
of the impact of distributed generation (DG) on distribution losses
and presents a new algorithm to the optimal allocation of distributed
generation resources in distribution networks. The optimization is
based on a Hybrid Genetic Algorithm and Particle Swarm
Optimization (HGAPSO) aiming to optimal DG allocation in
distribution network. Through this algorithm a significant
improvement in the optimization goal is achieved. With a numerical
example the superiority of the proposed algorithm is demonstrated in
comparison with the simple genetic algorithm.
Abstract: The Far From Most Strings Problem (FFMSP) is to obtain a string which is far from as many as possible of a given set of strings. All the input and the output strings are of the same length, and two strings are said to be far if their hamming distance is greater than or equal to a given positive integer. FFMSP belongs to the class of sequences consensus problems which have applications in molecular biology. The problem is NP-hard; it does not admit a constant-ratio approximation either, unless P = NP. Therefore, in addition to exact and approximate algorithms, (meta)heuristic algorithms have been proposed for the problem in recent years. On the other hand, in the recent years, hybrid algorithms have been proposed and successfully used for many hard problems in a variety of domains. In this paper, a new metaheuristic algorithm, called Constructive Beam and Local Search (CBLS), is investigated for the problem, which is a hybridization of constructive beam search and local search algorithms. More specifically, the proposed algorithm consists of two phases, the first phase is to obtain several candidate solutions via the constructive beam search and the second phase is to apply local search to the candidate solutions obtained by the first phase. The best solution found is returned as the final solution to the problem. The proposed algorithm is also similar to memetic algorithms in the sense that both use local search to further improve individual solutions. The CBLS algorithm is compared with the most recent published algorithm for the problem, GRASP, with significantly positive results; the improvement is by order of magnitudes in most cases.
Abstract: The paper presents a new hybridization methodology involving Neural, Fuzzy and Rough Computing. A Rough Sets based approximation technique has been proposed based on a certain Neuro – Fuzzy architecture. A New Rough Neuron composition consisting of a combination of a Lower Bound neuron and a Boundary neuron has also been described. The conventional convergence of error in back propagation has been given away for a new framework based on 'Output Excitation Factor' and an inverse input transfer function. The paper also presents a brief comparison of performances, of the existing Rough Neural Networks and ANFIS architecture against the proposed methodology. It can be observed that the rough approximation based neuro-fuzzy architecture is superior to its counterparts.
Abstract: In this paper, four carbazole-based D-D-π-A organic
dyes code as CCT2A, CCT3A, CCT1PA and CCT2PA were reported.
A series of these organic dyes containing identical donor and
acceptor group but different π-system. The effect of replacing of
thiophene by phenyl thiophene as π-system on the physical
properties has been focused. The structural, energetic properties and
absorption spectra were theoretically investigated by means of
Density Functional Theory (DFT) and Time-Dependent Density
Functional Theory (TD-DFT). The results show that nonplanar
conformation due to steric hindrance in donor part (cabazolecarbazole
unit) of dye molecule can prevent unfavorable dye
aggregation. By means of the TD-DFT method, the absorption
spectra were calculated by B3LYP and BHandHLYP to study the
affect of hybrid functional on the excitation energy (Eg). The results
revealed the increasing of thiophene units not only resulted in
decreasing of Eg, but also found the shifting of absorption spectra to
higher wavelength. TD-DFT/BHandHLYP calculated results are
more strongly agreed with the experimental data than B3LYP
functions. Furthermore, the adsorptions of CCT2A and CCT3A on the
TiO2 anatase (101) surface were carried out by mean of the chemical
periodic calculation. The result exhibit the strong adsorption energy.
The calculated results provide our new organic dyes can be
effectively used as dye for Dye Sensitized Solar Cell (DSC).
Abstract: Selecting the routes and the assignment of link flow in a computer communication networks are extremely complex combinatorial optimization problems. Metaheuristics, such as genetic or simulated annealing algorithms, are widely applicable heuristic optimization strategies that have shown encouraging results for a large number of difficult combinatorial optimization problems. This paper considers the route selection and hence the flow assignment problem. A genetic algorithm and simulated annealing algorithm are used to solve this problem. A new hybrid algorithm combining the genetic with the simulated annealing algorithm is introduced. A modification of the genetic algorithm is also introduced. Computational experiments with sample networks are reported. The results show that the proposed modified genetic algorithm is efficient in finding good solutions of the flow assignment problem compared with other techniques.
Abstract: Aspheric optical components are an alternative to the use of conventional lenses in the implementation of imaging systems for the visible range. Spherical lenses are capable of producing aberrations. Therefore, they are not able to focus all the light into a single point. Instead, aspherical lenses correct aberrations and provide better resolution even with compact lenses incorporating a small number of lenses.
Metrology of these components is very difficult especially when the resolution requirements increase and insufficient or complexity of conventional tools requires the development of specific approaches to characterization.
This work is part of the problem existed because the objectives are the study and comparison of different methods used to measure surface rays hybrid aspherical lenses.
Abstract: In this paper, a novel corner detection method is
presented to stably extract geometrically important corners.
Intensity-based corner detectors such as the Harris corner can detect
corners in noisy environments but has inaccurate corner position and
misses the corners of obtuse angles. Edge-based corner detectors such
as Curvature Scale Space can detect structural corners but show
unstable corner detection due to incomplete edge detection in noisy
environments. The proposed image-based direct curvature estimation
can overcome limitations in both inaccurate structural corner detection
of the Harris corner detector (intensity-based) and the unstable corner
detection of Curvature Scale Space caused by incomplete edge
detection. Various experimental results validate the robustness of the
proposed method.
Abstract: Low-density parity-check (LDPC) codes have been shown to deliver capacity approaching performance; however, problematic graphical structures (e.g. trapping sets) in the Tanner graph of some LDPC codes can cause high error floors in bit-error-ratio (BER) performance under conventional sum-product algorithm (SPA). This paper presents a serial concatenation scheme to avoid the trapping sets and to lower the error floors of LDPC code. The outer code in the proposed concatenation is the LDPC, and the inner code is a high rate array code. This approach applies an interactive hybrid process between the BCJR decoding for the array code and the SPA for the LDPC code together with bit-pinning and bit-flipping techniques. Margulis code of size (2640, 1320) has been used for the simulation and it has been shown that the proposed concatenation and decoding scheme can considerably improve the error floor performance with minimal rate loss.
Abstract: The recognition of human faces, especially those with
different orientations is a challenging and important problem in image
analysis and classification. This paper proposes an effective scheme
for rotation invariant face recognition using Log-Polar Transform and
Discrete Cosine Transform combined features. The rotation invariant
feature extraction for a given face image involves applying the logpolar
transform to eliminate the rotation effect and to produce a row
shifted log-polar image. The discrete cosine transform is then applied
to eliminate the row shift effect and to generate the low-dimensional
feature vector. A PSO-based feature selection algorithm is utilized to
search the feature vector space for the optimal feature subset.
Evolution is driven by a fitness function defined in terms of
maximizing the between-class separation (scatter index).
Experimental results, based on the ORL face database using testing
data sets for images with different orientations; show that the
proposed system outperforms other face recognition methods. The
overall recognition rate for the rotated test images being 97%,
demonstrating that the extracted feature vector is an effective rotation
invariant feature set with minimal set of selected features.