Abstract: In this paper we present the design of a new encryption scheme. The scheme we propose is a very exible encryption and authentication primitive. We build this scheme on two relatively new design principles: t-functions and fast pseudo hadamard transforms. We recapitulate the theory behind these principles and analyze their security properties and efficiency. In more detail we propose a streamcipher which outputs a message authentication tag along with theencrypted data stream with only little overhead. Moreover we proposesecurity-speed tradeoffs. Our scheme is faster than other comparablet-function based designs while offering the same security level.
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: Data security in u-Health system can be an important
issue because wireless network is vulnerable to hacking. However, it is
not easy to implement a proper security algorithm in an embedded
u-health monitoring because of hardware constraints such as low
performance, power consumption and limited memory size and etc. To
secure data that contain personal and biosignal information, we
implemented several security algorithms such as Blowfish, data
encryption standard (DES), advanced encryption standard (AES) and
Rivest Cipher 4 (RC4) for our u-Health monitoring system and the
results were successful. Under the same experimental conditions, we
compared these algorithms. RC4 had the fastest execution time.
Memory usage was the most efficient for DES. However, considering
performance and safety capability, however, we concluded that AES
was the most appropriate algorithm for a personal u-Health monitoring
system.
Abstract: This paper explores the issues that influence online retailing in Saudi Arabia. Retailers in Saudi Arabia have been reserved in their adoption of electronically delivered aspects of their business. Despite the fact that Saudi Arabia has the largest and fastest growth of ICT marketplaces in the Arab region, e-commerce activities are not progressing at the same speed. Only very few Saudi companies, mostly medium and large companies from the manufacturing sector, are involved in e-commerce implementation. Based on qualitative data collected by conducting interviews with 16 retailers and 16 potential customers in Saudi Arabia, several factors influencing online retailing diffusion in Saudi Arabia are identified. However, government support comes the highest and most influencing factor for online retailing growth as identified by both parties; retailers and potential customers in Saudi Arabia.
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: In this paper, we apply a semismooth active set method to image inpainting. The method exploits primal and dual features of a proposed regularized total variation model, following after the technique presented in [4]. Numerical results show that the method is fast and efficient in inpainting sufficiently thin domains.
Abstract: Some fast exact algorithms for the maximum weight clique problem have been proposed. Östergard’s algorithm is one of them. Kumlander says his algorithm is faster than it. But we confirmed that the straightforwardly implemented Kumlander’s algorithm is slower than O¨ sterga˚rd’s algorithm. We propose some improvements on Kumlander’s algorithm.
Abstract: This paper describes about the process of recognition and classification of brain images such as normal and abnormal based on PSO-SVM. Image Classification is becoming more important for medical diagnosis process. In medical area especially for diagnosis the abnormality of the patient is classified, which plays a great role for the doctors to diagnosis the patient according to the severeness of the diseases. In case of DICOM images it is very tough for optimal recognition and early detection of diseases. Our work focuses on recognition and classification of DICOM image based on collective approach of digital image processing. For optimal recognition and classification Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Support Vector Machine (SVM) are used. The collective approach by using PSO-SVM gives high approximation capability and much faster convergence.
Abstract: This paper deals with efficient computation of
probability coefficients which offers computational simplicity as
compared to spectral coefficients. It eliminates the need of inner
product evaluations in determination of signature of a combinational
circuit realizing given Boolean function. The method for computation
of probability coefficients using transform matrix, fast transform
method and using BDD is given. Theoretical relations for achievable
computational advantage in terms of required additions in computing
all 2n probability coefficients of n variable function have been
developed. It is shown that for n ≥ 5, only 50% additions are needed
to compute all probability coefficients as compared to spectral
coefficients. The fault detection techniques based on spectral
signature can be used with probability signature also to offer
computational advantage.
Abstract: Steganography meaning covered writing. Steganography includes the concealment of information within computer files [1]. In other words, it is the Secret communication by hiding the existence of message. In this paper, we will refer to cover image, to indicate the images that do not yet contain a secret message, while we will refer to stego images, to indicate an image with an embedded secret message. Moreover, we will refer to the secret message as stego-message or hidden message. In this paper, we proposed a technique called RGB intensity based steganography model as RGB model is the technique used in this field to hide the data. The methods used here are based on the manipulation of the least significant bits of pixel values [3][4] or the rearrangement of colors to create least significant bit or parity bit patterns, which correspond to the message being hidden. The proposed technique attempts to overcome the problem of the sequential fashion and the use of stego-key to select the pixels.
Abstract: Electro Discharge Sawing is a hybrid process
combining the features of SEDM and ECM. Its major characteristic is
extremely fast erosion rate compare to either of the above processes.
This paper brings out its relative feature of SEDM and EDS about
their erosion rates, surface roughness, and morphology of machined
surfaces.
Abstract: A strip domain decomposition parallel algorithm for fast direct Poisson solver is presented on a 3D Cartesian staggered grid. The parallel algorithm follows the principles of sequential algorithm for fast direct Poisson solver. Both Dirichlet and Neumann boundary conditions are addressed. Several test cases are likewise addressed in order to shed light on accuracy and efficiency in the strip domain parallelization algorithm. Actually the current implementation shows a very high efficiency when dealing with a large grid mesh up to 3.6 * 109 under massive parallel approach, which explicitly demonstrates that the proposed algorithm is ready for massive parallel computing.
Abstract: Defense and Aerospace environment is continuously
striving to keep up with increasingly sophisticated Information
Technology (IT) in order to remain effective in today-s dynamic and
unpredictable threat environment. This makes IT one of the largest
and fastest growing expenses of Defense. Hundreds of millions of
dollars spent a year on IT projects. But, too many of those millions
are wasted on costly mistakes. Systems that do not work properly,
new components that are not compatible with old ones, trendy new
applications that do not really satisfy defense needs or lost through
poorly managed contracts.
This paper investigates and compiles the effective strategies that
aim to end exasperation with low returns and high cost of
Information Technology acquisition for defense; it tries to show how
to maximize value while reducing time and expenditure.
Abstract: The genetic algorithm (GA) based solution techniques
are found suitable for optimization because of their ability of
simultaneous multidimensional search. Many GA-variants have been
tried in the past to solve optimal power flow (OPF), one of the
nonlinear problems of electric power system. The issues like
convergence speed and accuracy of the optimal solution obtained
after number of generations using GA techniques and handling
system constraints in OPF are subjects of discussion. The results
obtained for GA-Fuzzy OPF on various power systems have shown
faster convergence and lesser generation costs as compared to other
approaches. This paper presents an enhanced GA-Fuzzy OPF (EGAOPF)
using penalty factors to handle line flow constraints and load
bus voltage limits for both normal network and contingency case
with congestion. In addition to crossover and mutation rate
adaptation scheme that adapts crossover and mutation probabilities
for each generation based on fitness values of previous generations, a
block swap operator is also incorporated in proposed EGA-OPF. The
line flow limits and load bus voltage magnitude limits are handled by
incorporating line overflow and load voltage penalty factors
respectively in each chromosome fitness function. The effects of
different penalty factors settings are also analyzed under contingent
state.
Abstract: A fast adaptive Tomlinson Harashima (T-H) precoder structure is presented for indoor wireless communications, where the channel may vary due to rotation and small movement of the mobile terminal. A frequency-selective slow fading channel which is time-invariant over a frame is assumed. In this adaptive T-H precoder, feedback coefficients are updated at the end of every uplink frame by using system identification technique for channel estimation in contrary with the conventional T-H precoding concept where the channel is estimated during the starting of the uplink frame via Wiener solution. In conventional T-H precoder it is assumed the channel is time-invariant in both uplink and downlink frames. However assuming the channel is time-invariant over only one frame instead of two, the proposed adaptive T-H precoder yields better performance than conventional T-H precoder if the channel is varied in uplink after receiving the training sequence.
Abstract: Since IEC61850 substation communication standard represents the trend to develop new generations of Substation Automation System (SAS), many IED manufacturers pursue this technique and apply for KEMA. In order to put on the market to meet customer demand as fast as possible, manufacturers often apply their products only for basic environment standard certification but claim to conform to IEC61850 certification. Since verification institutes generally perform verification tests only on specific IEDs of the manufacturers, the interoperability between all certified IEDs cannot be guaranteed. Therefore the interoperability between IEDs from different manufacturers needs to be tested. Based upon the above reasons, this study applies the definitions of the information models, communication service, GOOSE functionality and Substation Configuration Language (SCL) of the IEC61850 to build the concept of communication protocols, and build the test environment. The procedures of the test of the data collection and exchange of the P2P communication mode and Client / Server communication mode in IEC61850 are outlined as follows. First, test the IED GOOSE messages communication capability from different manufacturers. Second, collect IED data from each IED with SCADA system and use HMI to display the SCADA platform. Finally, problems generally encountered in the test procedure are summarized.
Abstract: In these days, multimedia data is transmitted and
processed in compressed format. Due to the decoding procedure and
filtering for edge detection, the feature extraction process of MPEG-7
Edge Histogram Descriptor is time-consuming as well as
computationally expensive. To improve efficiency of compressed
image retrieval, we propose a new edge histogram generation
algorithm in DCT domain in this paper. Using the edge information
provided by only two AC coefficients of DCT coefficients, we can get
edge directions and strengths directly in DCT domain. The
experimental results demonstrate that our system has good
performance in terms of retrieval efficiency and effectiveness.
Abstract: State-of-the-art methods for secondary structure (Porter, Psi-PRED, SAM-T99sec, Sable) and solvent accessibility (Sable, ACCpro) predictions use evolutionary profiles represented by the position specific scoring matrix (PSSM). It has been demonstrated that evolutionary profiles are the most important features in the feature space for these predictions. Unfortunately applying PSSM matrix leads to high dimensional feature spaces that may create problems with parameter optimization and generalization. Several recently published suggested that applying feature extraction for the PSSM matrix may result in improvements in secondary structure predictions. However, none of the top performing methods considered here utilizes dimensionality reduction to improve generalization. In the present study, we used simple and fast methods for features selection (t-statistics, information gain) that allow us to decrease the dimensionality of PSSM matrix by 75% and improve generalization in the case of secondary structure prediction compared to the Sable server.
Abstract: Waiting times and queues are a daily problem for theme parks. Fast lines or priority queues appear as a solution for a specific segment of customers, that is, tourists who are willing to pay to avoid waiting. This paper analyzes the fast line system and explores the factors that affect the decision to purchase a fast line pass. A greater understanding of these factors may help companies to design appropriate products and services. This conceptual paper was based on a literature review in marketing and consumer behavior. Additional research was identified in related disciplines such as leisure studies, psychology, and sociology. A conceptual framework of the factors influencing the decision to purchase a fast line pass is presented.
Abstract: The use of statistical data and of the neural networks, capable of elaborate a series of data and territorial info, have allowed the making of a model useful in the subdivision of urban places into homogeneous zone under the profile of a social, real estate, environmental and urbanist background of a city. The development of homogeneous zone has fiscal and urbanist advantages. The tools in the model proposed, able to be adapted to the dynamic changes of the city, allow the application of the zoning fast and dynamic.