Welcome to Journal of Theoretical and Applied Information Technology

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This paper presents the current status of PET/CT brain image registration. Registration of brain images is a more complex problem, Automatic registration, based on computer programs, might, however, offer better accuracy and repeatability and save time. Computed Tomography (CT) is used for the attenuation correction of Positron Emission Tomography (PET) to enhance the efficiency of data acquisition process and to improve the quality of the reconstructed PET data in the brain. Due to the use of two different modalities, chances of misalignment between PET and CT images are quite significant. The main cause of this misregistration is the motion of the patient during the PET scan and between the PET and CT scans. This misalignment produces an erroneous CT attenuation map that can project the bone and water attenuation parameters onto the brain, thereby under- or over-estimating the attenuation. Template matching is used for applications in image processing. Cross Correlation is the basic statistical approach to image registration. It is used for template matching or pattern recognition. Template can be considered a sub-image from the reference image, and the image can be considered as a sensed image. The objective is to establish the correspondence between the reference image and sensed image. It gives the measure of the degree of similarity between an image and template. This paper describes medical image registration by template matching based on Normalized Cross-Correlation (NCC) using Cauchy-Schwartz inequality.

Positron Emission Tomography (PET), Computed Tomography (CT), Magnetic Resonance (MR), Normalized Cross-Correlation (NCC)

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 This paper proposes general and specific modeling and simulation for Schott ASE-300-DGF PV panel for Smart Grid applications. This is done, with the aid of MATLAB environment and Artificial Neural Network (ANN). First modeling of PV cell module at nominal conditions at 25C, and 1KW/m2 with I-V curves at (0C, 25C, 50C, 75C), also power and irradiance. Then, we propose general modeling and simulation at more probable situations for variable values of temperature and irradiance. The simulation results at each irradiance value with various temperature values and corresponding characteristics are well depicted in 3-D figures. Later, the ANN model for the proposed range of irradiance and temperature as model inputs, with the corresponding values of voltages, currents, and power as outputs is presented. Finally, algebraic equations for the ANN model are deduced.

Modeling, Simulation, Smart Grid, MATLAB, Neural Network, PV Cell.

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Building fault tolerance into a system cannot be an afterthought or add on approach. Design for fault tolerance needs to begin with the early stages of system conceptualization, requirement, specification and system design. The ultimate goals of a computer system affect its design philosophy and design tradeoffs. The cost of fault tolerance must be weighed against the cost of error or failure. This paper gives the design methodology for fault tolerant systems. Identify class of expected faults over the life time of the system.

Res_Code, Circuit, FPGA,Fault, System, System, Clock, Model

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It is well known that an interleaver with random properties, quite often generated by pseudo-random algorithms, is one of the essential building blocks of turbo codes, however, randomly generated interleavers has a lack of a compact representation that leads to a simple implementation. Especially for satellite application, we avoid using memories to save a look-up table, but the best way to do is to generate these interleavers on the fly from simple algorithms. One of those algorithmic interleavers is used by CCSDS (Consultative Committee for Space Data Systems). In this paper, several deterministic interleavers will be suggested of length matched with CCSDS standards to be used in the satellite applications and their performances were compared with CCSDS interleaver performance. The minimum Hamming distance and their multiplicities are the criteria for comparison. The simulation results show a larger minimum distance which leads to decrease the error floor to be applicable in satellite new missions. Moreover, the results give a larger minimum distance by factor of 1.12dB compared with the CCSDS interleaver. The suggested deterministic interleaver can be used in turbo code systems without any encoder/decoder configurations change or adding any system complexity. The simulation is applied for frame length 1784, and code rate 1/2.

Turbo Codes, CCSDS,Algorithmic Interleaver

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Mоrphоlоgiсаl оpenings аnd сlоsings аre useful fоr the smооthing оf grауsсаle images. However, their use fоr imаge nоise reduсtiоn is limited bу their tendenсу tо remоve impоrtаnt, thin features from аn imаge аlоng with the nоise. This pаper is а desсriptiоn аnd аnаlуsis оf а new mоrphоlоgiсаl imаge nоise reduсtiоn аnd соmpressiоn (INRС) thаt preserves thin feаtures while remоving nоise. INRС is useful fоr grауsсаle imаges соrrupted bу dense, lоw-аmplitude, rаndоm оr pаtterned nоise. Suсh nоise is tуpiсаl оf sсаnned оr still-videо imаges. INRС differs frоm previоus mоrphоlоgiсаl nоise filters in thаt it mаnipulаtes residuаl imаges – the differenсes between the оriginаl imаge аnd mоrphоlоgiсаllу smооthed versiоns. It саlсulаtes residuаls оn а number оf different sсаles viа а mоrphоlоgiсаl size distributiоn. It disсаrds regiоns in the vаriоus residuаls thаt it judges tо соntаin nоise. INRС сreаtes а сleаned imаge bу reсоmbining the prосessed residuаl imаges with а smооthed versiоn.

Mоrphоlоgiсаl Openings, Smооthing оf Grауsсаle Images,  INRС, Nоise Flters

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The extraction of text in an image is a classical problem in the computer vision. Extraction involves detection, localization, tracking, extraction, enhancement and recognition of the text from the given image. However variation of text due to difference in size, style, orientation, alignment, low image contrast and complex background make the problem of automatic text extraction extremely challenging. Text extraction requires binarization which leads to loss of significant information contained in gray scale images. The images may contain noise and have complex structure which makes the extraction more difficult. This paper proposes an algorithm which is insensitive to noise, skew and text orientation. It is free from artifacts that are usually introduced by thresholding using morphological operators. Examples are presented to illustrate the performance of proposed method. The text extraction system has been attempted over a corpus of three kinds of images and promising precision has been obtained.

Mathematical Morphology, Morphological Operators, Edge Detection, Localization, Connected Component

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The Big Bang–Big Crunch (BB–BC) optimization algorithm is a new optimization method that relies on the Big Bang and Big Crunch theory, one of the theories of the evolution of the universe. In this paper, a Big Bang–Big Crunch algorithm is presented for solving optimal power flow (OPF) problems with valve-point effects. The proposed algorithm has been tested with the IEEE 30-bus system with different fuel cost characteristics, quadratic cost curve model, and quadratic cost curve with valve-point effects model. Numerical results demonstrate the efficiency of the BB–BC algorithm compared to other heuristic algorithms.

Big Bang–Big Crunch, optimal power flow, Economic Dispatch, Valve-point effect

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Recently, the urge for e-voting has been described to be the inevitable future of electioneering in most countries of the world. Despite all its good features, like the other voting systems it has been seen to also be susceptible to rigging and fraud. Some of its undesirable features include not allowing recounting of votes after election in case of a protest like the others. Another issue is that of erroneous software which can greatly affect the result of the election. All these is further compounded by the fact that voting systems deals with very large amount of data that is collected from a distributed population source hence the raw data are extremely difficult to comprehend and therefore monitor. This paper attempts to solve this problem using a TreeMap based visualization technique to monitor in real-time the distributed balloting and voting processes. The paper proved that TreeMap algorithms can be configured and deployed on the central server to monitor effectively the voting transactions in real-time and hence enable transparency.

E-voting,Treemap Algorithm, Visualization, Results,Real-Time, Balloting, Nigeria

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The minimum spanning tree clustering algorithm is capable of detecting clusters with irregular boundaries. In this paper we propose a novel minimum spanning tree based clustering algorithm. The algorithm produces k clusters with center and guaranteed intra-cluster similarity. The algorithm uses divisive approach to produce k number of clusters. The center points are considered as representative points for each cluster. These center points are connected and again minimum spanning tree is constructed. Using eccentricity of points the central cluster is identified from k number of clusters

Euclidean minimum spanning tree, Subtree, Eccentricity, Center, Hierarchical clustering, Central Cluster

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This paper presents the novel approach in protection and detection techniques of Alternator stator winding from the earth faults which are simulated between 2% to 10% distance point from the alternator neutral, since the impedence at that distance is very high we can not detect or protect by normal methods. The transient produced is analyzed in discreet Wavelet transforms. The potential of using discreet wavelet transforms in protection relay is examined and model of relay using transient phenomenon to fault in the winding in alternator stator is proposed and next integrated into ATP integration program.

Wavelet Transforms, Faults, Fault Transient, Digital Relay, Arc Model