Solve Nokia Ovi suite Update problem | Solve Nokia Mobile Software Update Problem

While Nokia Mobile updating time sea following error.

"There seems to be a with connecting to the nokia ovi suite update service. Make sure that your firewall and virus protection settings are correct.Also,make sure that the menu option for working offline is not selected in Internet Explorer. If you still cannot connect, the service may be unavailable.Please Try again later"

Problem solves following Steps

goto -> control panel -> administrative tools -> service - >goto windows firewall/Internet Connection Sharing service,Then right click and stop.

Then restart your Nokia ovi suite .Then Update your software.Finally your mobile software update successfully.

Fuzzy Logic Examples using Matlab,Fuzzy Logic Modeling with Matlab,Introduction to Fuzzy Logic using MATLAB

Fuzzy Logic, which used in Artificial intelligence.It contain logical think of rules and member input and output functions. Three steps are taken to generate a fuzzy control engine:

1)Fuzzification(Using membership functions to graphically illustrate a situation)
2)Rule evaluation(purpose of fuzzy rules)
3)Defuzzification(find the crunchy or actual results)

Here we provide the examples of Fuzzy Logic and design it.In below one way you easy create the Fuzzy project using matlab tool.

In Matlab contain a fuzzy Toolbox.it simple to create an Fuzzy Logic.
1.Type fuzzy in matlab command prompt.

2.Add a input and output variables.

in coding as follows

a = newfis('my_fis');
a = addvar(a,'input','service',[0 10]);
a = addmf(a,'input',1,'poor','gaussmf',[1.5 0]);
a = addmf(a,'input',1,'good','gaussmf',[1.5 5]);
a = addmf(a,'input',1,'excellent','gaussmf',[1.5 10]);

3.Set the input variable range and corresponding input membership function ranges,same thing do in output also.

4.choose type of Mf functions.

5.Double click the mamdani for adding a rules.

in coding

ruleList=[1 1 1 1 1
1 2 2 1 1];

a = addrule(a,ruleList);

In ruleList 1st row is 1st rule.in first 3 ones are input range and output range.in 4 is and /or 5 th one is weight of the rule.

6.Finaly save that fuzzy file name on your hard disk.

Testing a Fuzzy

1. Load a my_fis.fis in matlab command window using following commands.

my_fis_mat = readfis('my_fis'); % reading fis file

2.Give the inputs.

If you have two input means give two values in one vector array.
test_data is

my_fis_mat = readfis('my_fis');
my_test = [2 1; 4 9];
out = evalfis(my_test,my_fis_mat)

in out variable contain your result of your fuzzy. Finally you got the answer.

Object Detection Project and Finding similler Images,CBIR Example

Here we Give the project of Object Detection.Here we using recognition and segmentation techniques.both technique used to find out the object in an Image.

This Projects use to code book.xml to Finding the region and finding the edges to predict the image.If you give more code-book xml for object edges position for finding a object.This Project Worked mainly used to Live Cameras. Coodbook xml used For best extracting of Object.In feature this technique used in CBVR and CBIR.

FUTURE ENHANCEMENT

1. Extraction of identified Object from the image.
2. Extraction of identified Object from the Videos.
3. Also Supported to CBVR and CBIR to extract Images and Videos.
4. Recognizing related Objects.
5. Identifying and retrieving information about the person whose face was detected.

PROJECT SCREEN SHOTS

This project screen shots are below there.If you need this project Code means email to us.

Matlab plot tips and tricks,Matlab Plot with Color and Line width

MATLAB plotting commands are best show by example. I have used to make the examples compact, while avoiding the insignificant. The examples build on each other so it is advisable to at least read quickly through the presentation in order. In Matlab plotting has more types and more properties are there. This properties are differ in different Matlab versions.

Plot(xdata,ydata) %normal plot in matlab

Matlab has a lot of parameters with plot. that properties are

1. Xdata
2. Ydata
3. Outliers
4. OutlierLineSpec and etc
   

Example as follows,

>> xdata = [1 2 3 4 5];
>> ydata = [6 7 8 9 10];

>> plot(xdata,ydata);

This plot is normal plot of line. if you have set any color and any properties then you use single quotes and use their properties and values .In below example shows a matlab plot with color and line width and set grid option.

>>x = -pi:.1:pi;
>>y = sin(x);
>>plot(x,y,'color','red','LineWidth',2)
>>grid on %set a grid on figure

Matlab Plot 3D:

Matlab 3D plot as follow example.

>> t = 0:pi/50:10*pi;
>>plot3(sin(t),cos(t),t)
>>grid on % show the grid option on figure

>>axis square %set access as square shape

Matlab Scatter Plot Example | Use Scatter Plot in Matlab

Scatter plot is one of the plot in matlab. scatter(x,y) this is the syntax on matlab for plotting scatter plot.This plot displays the colored circle in specified location of x,y.here x and y are vector,this vector must be same length.this plot use the parameters(properties) like as plot function.Properties are color,circle width and ect. Properties use as scatter(...,'PropertyName',propertyvalue) this syntax.

This plot mainly use in cluster grouping and cluster spiting also use in classification section also.

syntax : scatter(X,Y)


X,Y must be same length vector ,following example shows the scatter plot.

>> x = rand(10,1);
>> y = rand(10,1);
>> scatter(x,y);

x and y variables are generate randomly, that size is 10 row with 1 columns, finally we use plot function "Scatter" used to plot the x and y values. the output as below,

Matlab Bar chart Example, Matlab 3D Bar chart Example

Bar chart is one of best and stylish plot in matlab.Bar chart mainly used in comparison and Histogram operation.in bar chart can supported 2d and 3d matrix data's,While bar char displays choose different colors of bars generated.This color choose randomly in bar chart function,In this chart use different properties like as normal plot properties.The basic syntax as follows.

>>bar(x,Y)% for 2d bar chart
>>bar(x,Y,z)% for 3d bar chart

In bar chat example as follows.

>> x = rand(10,1);
>> y = rand(10,1);
>> data = [x y];
>> bar(data)
>> legend('X data','Y data')

In this example x and y has two different data s,This data s must same length of size,data variable to combine two classes of data s.Then we plot the data use bar function.Finally we set the legend of our classes.We got finally follows output

In 3d bar chart as following example to use plot.

>> x = rand(10,1);
>> y = rand(10,1);
>> z = rand(10,1);

>> data = [x y z];

>> bar3(data)

Here we generate random data s of x,y and z ,then all of them combine one single data s then we plot the data s .Here also we use legend,we get the result as follow.

Matlab Random Number Generation Example | Random Number Generate between two Numbers in Matlab

Matlab random number generation using rand() function.This function generate random number with floating points. if you want int number means,you round function used to round the values.Random number only generate between 0 to 1.Random number generate as following command.

>>rand

ans =

0.6557

Matlab generate random number with some vector size.If you want random number generate 5 row with 3 then use following command,

>> rand(5,3)

ans =

0.3816 0.4456 0.6797

0.7655 0.6463 0.6551

0.7952 0.7094 0.1626

0.1869 0.7547 0.1190

0.4898 0.2760 0.4984

Matlab random number generate between two int point means use following command

>> startpnt = 10;

>> endpnt = 20;

>> startpnt+(endpnt-startpnt)*rand(5,2)

ans =

12.5108 15.8526

16.1604 15.4972

14.7329 19.1719

13.5166 12.8584

18.3083 17.5720

Here generate random rumber between 10 to 20 values.If you want real number means you have used to round function.round(startpnt+(endpnt-startpnt)*rand(5,2)) get real numbers between 10 to 20.

Matlab Basic fitting Example | Curve Fitting matlab Example

Cure Fitting is one of the Toolbox in matlab .Curve fitting used to draw our data points in different types of fittings.In curve fitting contain following fittings.

1. Spline Interpolant
2. Space-preserving Interpolant
3. Quadratic
4. Cubic
5. 4th Degree Polynomial
6. 5th Degree Polynomial
7. 6th Degree Polynomial
8. 7th Degree Polynomial
9. 8th Degree Polynomial
10. 9th Degree Polynomial
11. 10th Degree Polynomial

The above type of polyfiting are there in matlab.

In below example to use the poly fitting in our data s.

>> xdata1 = 1:10;
>> ydata1 = rand(1,10);
>> axesLimits1 = [min(xdata1) max(xdata1)];

>> xplot1 = linspace(axesLimits1(1), axesLimits1(2));
>> fitResults1 = polyfit(xdata1, ydata1, 1);

>> yplot1 = polyval(fitResults1, xplot1);

>> figure;plot(xplot1,yplot1,'color','red')

>> hold on;

>> drawnow;
>> plot(xdata1,ydata1);

Here we getting xdata and ydata,then we find minimum limit and maximum limit of xdata,then find out linspace ,then find the polyfitting use 1.1 means linear fitting,if You have change that number you get different poly fitting.The out put as follows.

Matlab Subplot Example | Simple matlab Subplot example.

Subplot is the group of plots in one figure item.This type of plotting used to comparisons.While in your result shows maximum amount of figures shows that time you have use this type of plots.Subplot shows multiple plots in same Figure window.This subplot syntax as follows

>>subplot(row,columns,plot index) ;

row -> Represent you choose the row amount of plot
columns -> Represent you choose the columns of plot
plot-index -> Plot index

Following example shows the subplot best and simple example.

>> x1 = rand(10,1);
>> x2 = rand(10,1);
>> x3 = rand(10,1);
>> x4 = rand(10,1);
>> subplot(2,2,1);plot(x1);
>> subplot(2,2,2);plot(x2);
>> subplot(2,2,3);plot(x3);
>> subplot(2,2,4);plot(x4);

here total 4 plots used so we split subplot 2,2,This split we choose and split,we also use following types of spiting plot,4,1, and 1,4,

Two subplot index has used in one subplot example as follows,

>>x1 = rand(10,1);

>>x2 = rand(10,1);

>>x3 = rand(10,1);

>>subplot(2,2,1);plot(x1);

>>subplot(2,2,2);plot(x2);

>>subplot(2,2,[3 4]);plot(x3);

here last one subplot used two subplot indexes.That indexes are 3 and 4.This output as follows.

Matlab Mutiplot in Same Plot Window I Matlab Hold on drawnow Example used To Plotting

Some times you want to many plots in same plots window with legend, at that time you have use this type of examples.Here we have used hold on command and also use drawnow used to plot two are more plot in same plot window.That example as follows

>> xdata = rand(10,1);

>> ydata = rand(10,1);

>> figure;
>> plot(xdata);

>> hold on

>> drawnow

>> xdata

>> plot(ydata,'color','red');
>> legend('Xdata','Ydata');

In above code used to mutiplots in same plot window.Here we used two datas xdata and ydata.xdata plot in blue color,Ydata plot in red color.The out put as follows

Matlab Function creation | Matlab make Function with arguments and without arguments | Matlab function example

In Matlab toolbox ,we make a function very easy. You have use following steps to make a new function in matlab.

1. Goto Matlab Editor window
2. Press new M-File
3. Type the function coding.
4. Finally you have save the function as function name.

In matlab function contain 4 types

1. Function with arguments
2. Function without arguments
3. No return values.
4. Return Values.

Following example are explain these types.

Function with arguments

function add(a,b)

c = a+b;

display([Added values is : num2str(c)]);

add(10,12);% call a function

Function without arguments

function add()

a = 10;

b=20;

c = a+b;

display([Added values is : num2str(c)]);

simply call add();

No return values

This type of functions using both Function with arguments and without arguments.

Return Values

function c = add(a,b)

c = a+b;

display([Added values is : num2str(c)]);

c = add(10,20);% calling a function...

Matlab data types | Matlab Datatype examples | Matlab Cell, Structure example

In Matlab data types are following

1. Matrix/Vector
2. Cell
3. Structure

Matrix:

Matrix contain row and columns values .if one row/columns means that is vector.This vector also matrix.if you assign string values in one variable means that string variable also one matrix.for example

>> a = 'Matlab';

>> a(1)

ans =

M

>> a(2)

ans =

a

Cell

cell is one of the datatype in matlab.cell is also an array .This cell array stores vector/matrix in one cell.for example you have different size of matrix values means you have store a two matrix in one cell array variables.

>> a = [11 2 32 45 43543];

>> b = [23 34 34 34 34 4 34 34 34 34 341 32434];

>> my_cell{1} = a;

>> my_cell{2} = b;

>> my_cell

my_cell =

[1x5 double] [1x12 double]

Structure

Structure is one of the datatype in matlab .This structure like C,C++ structure concept.Structure store different type of values.it stores matrix,vector,string and cell array.Structure like a class also.for example

make a image structure as given below

>> my_image.name = 'matlab.jpg';

>> my_image.row = 100;

>> my_image.columns = 100;

>> my_image

my_image =

name: 'matlab.jpg'

row: 100

columns: 100

Matlab toolboxes | List of Toolboxes in Matlab

In Matlab contain lot of toolboxes,Every toolboxes used different research domains.For example power system researches used in power system toolbox. Matlab also contain different type of algorithm are include.These algorithm are predefined function in matlab. we use the predefined functions and make the program for research.

here we attach the Screen shot of List of Matlab toolboxes.

In matlab contain many algorithms,Ex genetic algorithm,Kmeans,FCm,SVM and ect.

Features of Image in Research | List Of Features in Image | CBIR Image Features

Image is photo it contain row number pixels and column number of pixels.Image features are use for object detection,object classification,object recognition,content based video retrieval and content based video retrievals.In below we mention following features are may extract form image.

1. Color features using color Histogram
2. Color moment using texture of image
3. Shape feature
4. Edge feature
5. Wavelet feature
6. SHIFT(Scale-invariant feature transform) feature .This feature finding the geometric distortion of image. like scale,translation and rotation of images.
7. GIST feature of Segmented Objects
8. Cluster feature for image segments.

These feature are available in a Image.In latest, Google Image search using 1st one feature.If you know more features means please comments it.

Examples of neural network using matlab | Neural network matlab Code | Neural Network Matlab Example

Neural Network tool is one of the toolbox in matlab.Neural Network operates Artificial intelligence approch. Most research works are used this concept.This concept mostly working in pattern recognition,classification and prediction.We give some notes, how to use neural network in matlab.

Matlab is Research tool ,mainly used for research and researchers.you have use following operations for study the Neural Network.

Neural Network contain Three layers.

1. Input Layer
2. Hidden Layer
3. Output Layer

Use following operation in Matlab for train the data on NeuralNetwork.

1. Goto matlab command window.
2. Type nftool (nftool is keyword, for load the Neural network Toolbox on matlab).
3. Then you sea following screen.

4. Load The data s from work space.

5.Set The hidden layers of neural network.

5.Then goto Next.Then press Train button train your data.

6.Then goto 2 Next Button then press generate m file.This m file is your training file.

This method for directly using Neural Network Toolbox.

In below create Neural network with using NN toolbox codes and syntax's.

1. Training use as following code

>> input_data = [1 2;2 3;2 2;4 2;6 6]; % Input matrix

>> output_data = [3;5;4;6;12]; %output vector

>> net = newff(input_data',output_data',20); % design a NN Structure

>> net = train(net,input_data',output_data');% Train the data's

2. Test the data's on NN.

>> pred = sim(net,[2;3]) % test the data's on neural network

pred =

4.95

This "sim" is a function ,for test the data's on networks.you may have use large amount of data's to train and test on neural network

Dicom Image Viewer in ImageJ Tool | ImageJ Dicom viewer

ImageJ is the one of the image processing tool.Developed in java platform.This software views dicom image directly.Dicom images are medical images,like CT scanned images.This images mainly communicate in medical fields.

here we mention followings.

dicom image dataset - http://pubimage.hcuge.ch:8080/

ImageJ Tool download from - http://rsbweb.nih.gov/ij/download.html

Dicom dataset contain large amount of images their in a link.so please download it.Then you have download imageJ tool and run it. Finally you open your dicom image easily.

This imageJ tool provide 3D view also.This is very simple to show your imageJ tool.Add your dicom images in ImageJ stack.then go ImageJ plugin menu->go 3D->go volume viewer.Then you see in Dicom images in 3D view.

Anna Univ Database System Concepts Book | Database System Concepts PDF Books Download Online

Here We sharing the link for download the e-book as "Database System Concepts" .This Book version is 4th .This book used for anna university computer science students.Many universities are used for this books syllabus,This book type is PDF .So you have study on offline easily.so download and enjoy to study.

4shared - http://www.4shared.com/file/axak_IzV/Database_System_Concepts.html

Database System Concepts books are available on Internet .we put the 4shared link for students

Ann University Operating system concepts 6th and 7th edition Book | Operating system concepts 6th and 7th edition Book PDF

Here We sharing the link for download the e-book as "Operating system concepts" .This Book version is 6th and 7th.his book used for anna university computer science students and use many universities.we provide two links 6th and 7th edition books.6th edition book contain 7 part with 22 chapters.Book types are PDF.Download it stydy offline.

Download

6th Version : http://www.4shared.com/file/xWwOpTxm/OperatingSystemConcepts6thEdit.html

7th Version : http://www.4shared.com/document/FmtyiTOk/Operating_System_Concepts_7_th.html

Ann University Digital Signal Processing E-Book | Download Ann University Digital Signal Processing E-Book | Ann University Digital Signal Processing

Here We sharing the link for download the e-book as "Digital Signal Processing" .This Book version is 3rd .This book used for anna university computer science students and ECC students,This book is copywriter-ed book.Book contain 12 chapter available.This book gives some matlab functions in last.Please download it ,study offline.This Book type as PDF.So you can study easily.

Download

MediaFire (Compressed Version) : http://www.mediafire.com/?r41rnmzzqkr

4shared(PDF) : http://www.mediafire.com/?r41rnmzzqkr

Radial basis function Neural network Example | RBF Neural Network code | Matlab example of RBF

In Neural Network one of the type is '(RBF) Radial basis function' network.This neural network is also one of the classifier in research area.More than tools are build this network.RBF network are used in Matlab and Weka tools.In this networks operates radial basis functions , like distance and centers.It easy to compute linear and time series data prediction.This network contain three layers.That layers are

1. Input Layer
2. Hidden Layer
3. Output layer(may be linear)

This network generate random weight to map the Input to output using radial basis function.This weight are hidden neurons.

here we put the example Matlab code of RBF neural network Training and Testing.

Training Process:

>> input = [1 2 3 4 5 6 7 8 9];

>> target = [2.0 4.1 5.9 6.8 7.4 8.4 9.4 10.3 11.9];

>> net = newrb(input,target,20);

NEWRB, neurons = 0, MSE = 8.47802

Testing :

>> test_input = 1.5;

>> Y = sim(net,test_input) % output value in Y.

Y =

3.9

above example giving a linear data we predict in interval of input data.

SVM Train the Data in Matlab | Matlab SVM code for training and Testing | Matlab svm data train and test

In Support Vector machine uses predict the supervised learning data's.In beginning SVM uses two class features only.Now we modifies that algorithm used more class data's in Muti-SVM concept.It supports following type of functions run inside the SVM.

1. Linear data's
2. Quadratic data's
3. Radial Basis Function data's
4. Multi-layer Perception data's

These above are developed kernel function's.These are predefined develop codes in matlab.In below mention SVM main properties.

1. Input (Training data's) .
2. Output(Groups).
3. Kernel functions.

In svm use more domain's to analyse the datas's and predict the patterns.It used most major domain's like Data-mining,image processing,medical Imaging and ect.Below we give some example code for SVM Example.It use svmtrain and svmclassify function's.

1. svmtrain for train the data's.
2. svmclassify for test the data's.

below example contain two classes of 9 data's.

>> data = [1 1;2 1;3 1;4 1;5 2;6 2;7 2;8 2;9 2];

>> data

data =

1 1

2 1

3 1

4 1

5 2

6 2

7 2

8 2

9 2

>> my_svm_struct = svmtrain(data(:,1),data(:,2));

>> out = svmclassify(my_svm_struct,1)

out =

1

>> out = svmclassify(my_svm_struct,1.5)

out =

1

Finally predict the data's using svmclassify function.

Non Linear Extended Kalman filter Matlab Example code | Extended Kalman filter Matlab Code

In filters one type is Kalman filter.Filter are used to remove the noise from signal,data or images.In Extended Kalman filter are used to remove the nose in different method.This technique to remove the noise using present observation and past observation.This one is non linear kalman filter type.This filters are used GPS system ,control systems and communication systems.

Three steps are used to design a filter

1. Design a filter model .
2. Predicted state using state equations.
3. Update state using measurement equation.

In this filter use main 3 functions.

1. Create 'F' function for predicted data using present observation from past observation.
2. Create 'H' function for estimate co-variance using computed measurement from past observation.
3. Update the observation.

In below give matlab sample output for EKF Filter .download here

Matlab Animation Plot | Matlab Moving Object Plots | Drawnow hold on Matlab Command Example

While Plot the data's on matlab you not see the figure window.You only sea the after plot the data.If you use drawnow command you have easy to see while plot the data's.here we give some example for plot the data with animation.Here we use plot data with style of star '*' with hold on and drawnow functions command.

1. hold on used for continuous plot the data with update the current data axis.
2. drawnow command used for No refresh the current window screen.
   

Below example mainly helpful to you for Matlab animation plot.Here we randomly generate continuous position and pot the data's for 100 iterations with some delay.Matlab pause command used for delay operation.

clc

clear all

close all

warning off

x = 1;

y =1;

figure;

for iter = 1:150

plot(x,y,'*');

hold on

drawnow

y = y+1;

randnum_chk = round(rand*2);

if randnum_chk==1

x = x+1;

else

x = x-1;

end

if x<=0

x =x+1;

end

pause(0.01);

axis([0 150 0 150]);

end

In above program output as follows.

Matlab Image Patch Extraction Code | Patch Extraction from an Image matlab code

In Image patch extraction mainly used for Content Based Image Retrieval (CBIR) and Patter recognition systems.Here we give the code for patch extraction from an Image.In patch extraction also get the features from each patches in CBIR system. It also used segmentation computation.Patches also used to Recognize Face Synthesis process and detect Nose, eyes,mouth.Patches also support improve the image quality and remove the noise from an images.You have apply the filters on each patches then you get quality images.

In below code used for Patch extraction from an Image.

clc

clear all

close all

input = rgb2gray(imread('041078.JPG')); %converted into RGB color

patchsize = 10; %10*10 path size

imsize = 10*25;

input = imresize(input,[imsize imsize]);

figure;imshow(input);

image_out = [];

for i = 1:patchsize:imsize

image_out_tmp = [];

for j = 1:patchsize:imsize

tmp_img = input((i+1-1):i+patchsize-1,(j+1-1):j+patchsize-1);

tmp_img = [ones(patchsize,1) tmp_img ones(patchsize,1)];

tmp_img = [ones(1,patchsize+2);tmp_img;ones(1,patchsize+2)];

image_out_tmp = [image_out_tmp tmp_img];

end

image_out = [image_out;image_out_tmp];

end

figure;imshow(image_out);

This script out put as follows..

In above output for patch extraction.Here we give the patch sizes is 10.Then we extract the 10x10 patches from an Image.

Bresenham 3d line Drawing algorithm | Matlab 3D Line Drawing Algorithm Source code | Matlab Line Drawing Algorithm code

Bresenham 3d line Drawing algorithm is one of the algorithm in Computer graphics,It find out the points of 'N' Dimensional Axis area Lines.Here below we put the matlab code of this algorithm .Here we give and use three dimensional data points and plot that point in Axis areas.

More graphics libraries are used this one algorithm. This algorithm Linear functions are used to draw the Lines.It draw the lines any number of dimensions.This algorithm are mainly used in computer graphics domains.

Here below give the code of "Bresenham 3d line Drawing algorithm"

Point1 = [10 33 8];

Point2 = [39 25 67];

These two points with three dimensional data points are used to draw the Lines.

Function:

bresenham_line3d_algorithm.m is matlab function please download this function from Hackchina.com

Function Calling:

Point1 = [10 33 8];

Point2 = [39 25 67];

[Xpnt,Ypnt,Zpnt] =bresenham_line3d_algorithm(Point1, Point2);

figure;plot3(Xpnt,Ypnt,Zpnt,'s','markerface','b');

The output as follows

Tips For Research Scholars | Pre-PhD Tips | Publishing Research Papers Tips

Most of the research peoples struggle in them research.Here we put some simple tips for Research scholar.Please note this points for all per-research scholars.Very simple points for Research.

Select your Research Area

This is your most important things of your research.you have choose most like,interested and well knows domain areas.If you choose well know research area means you can easy to complete your PhD.Research area's are like networking,cloud computing or any area.

Find problem

Here you Find out the any one problem of your selected research area.You must implement and solve this problem on your research.Refer more tools and paper (most recent) for solve the find-out problem on your domain.You may use Google scholar and Microsoft research site for help your research works.you have easy to pick the research papers from these sites.

Problem Solving

In this section you must implement your research work and solve the problem  itself..then you have do comparison with old algorithm and proposed algorithms.then you put the more intermediate result on your research paper.


Publishing Papers

This one is main important for you research.Most universities are want to publishing papers on best journals.so you careful to choose the Journal. if your papers accepted on Journals then Reviewer may give some tips for improve the quality of your research papers or ask some doubts of your research works,If they have any doubts then you must clarify all of doubts.If you solve all problems then your papers publishing on that Journal. otherwise may be rejected.

Matlab Save the Figure Window Example Code | Saveas Function For Save the Figure in Matlab

Matlab is one of research toolbox,It contain large amount of Tools.Some times you want to save the figure file at that situation it mainly helpful.Matlab different way to save the figures.We give one of the option to save the figure in run time.We use saveas function for save the figure window.This way most helpful for save the figure.Please use following operation for save the figures in matlab.

1. In figure window must use the handle object.ex (h1 = figure;plot(x,y));
2. Then this handle object save in your work space using saveas function.

This saveas function contain three major Parameters.

1. Handle object
2. Name of the fileName
3. Final parameter is Filename type, like(Jpeg,Png,Tiff);

Syntax as follows

saveas(handle,'filename','filetype')

Example code and output as follows

>> x = rand(10,1);

>> y = rand(10,1);

>> h1 = figure;plot(x,y);

>> saveas(h1,'my_figure','jpg');

output is

Matlab uint8 addition, subtraction and division Example | Matlab Image addition,addition subtraction and division Example

Here we explain uint8 data variable addition , subtraction and division.This uint8 is one of the data type in matlab. It stores the values up '0' to '255'.Your normal addition/subtraction/division not supported for this type of variables in matlab.This variable are also called as Image variable.

Here addition,subtraction and division's are used following commands

1. Addition using 'imadd' function.
2. Division using 'imdivide' function.
3. Multiplication using 'immultiply' function.

This above functions only used this type of variable.This function also support for Image.Read two images after convert uint8 format variable then add the two variables.then you got two added image in one image.

Here below we give the example of this Uint8 type variables addition and subtraction.

>> b = uint8(round(rand(1,10)*255))

b =

180 8 71 12 25 210 177 81 242 9

>> a = uint8(round(rand(1,10)*255))

a =

112 97 195 203 48 125 114 165 181 192

>> imadd(a,b)

ans =

255 105 255 215 73 255 255 246 255 201

Here we use two random variables 'a' and 'b'.Then these two uint8 variables add using imadd function.These added result we finally shown.Here added values not grater than 255*.Please check it.While using subtraction result not lesser than 0.Like division function also.

Download KDD Cup dataset | KDD Cup dataset for free Download | Data mining KDD Cup dataset

KDD Cup data set is one of the standard research data set in worldwide.This KDD full-form(abbreviation) is Knowledge Discovery and Data Mining.It support more research works in data mining and more domains.This data set contain 14 classes of data set ,This data sets taken from 1997 to 2010.This data set support classification, regression,clustering and more research algorithm approach.

You have use these data set for you research.If you have use these data set means your research paper get more points.So please use these data on you research.

Here we put the link of KDD cup data set.So visit that link and download that data set.This data set is totally free Download for research. Click and download the data set.

http://www.sigkdd.org/kddcup

In above link contain KDDcup datasets.This link contain 14 classes of data set and their description.So please visit.

Matlab Notebook setup example | Matlab Notebook publishing on word | Matlab function execute on Ms-word

Some matlab tips for publishing a matlab content on word.It made easily.Only you have enable 'm-book.bot' template on word.This process like a MS-Word to connect the matlab with macros then execte the commands on matlab the result displays on word. Here we give matlab tips for publishing a notebook matlab content on word.Here we give some steps used for publishing content on word.This Notebook used for publishing matlab commands and function on word.It made easy to execute on word.

Please use following steps to publishing matlab content on word.

1. Open matlab,then goto command prompt then type "notebook -setup".

Then you sea following screen on matlab command prompt.

2.Then open word.Then goto New->Then click 'My template' -> then choose 'm-book.dot';

Then you type matlab function and press "ctrl+enter" ,then the matlab function execute on word.here we give some examples of Matlab function execution on word.Please note it.If you have any doubt means please comment it.

Retinal Image dataset download | Standard dataset of Retinal Image

Here we give some description of Retinal Image.We put the data set link of Retinal Image.This images are used for research in Medical Image processing Processing.Retinal images are used to detect the blood vessels for find normal or abnormal disease in human body.This images are used for research in following operational functions.

1. Retinal Image Segmentation.
2. Retinal Image classification (Normal/Ab-normal).
3. Detect the disc and hub area.

Segmentation apply to detect the part of disc and hub area of retinal image .In classification area,classified the images into normal /ab-normal.

These Retinal Images contain two main features.

1. Optic disc measurements for detection of Vessels
2. Retinal waves feature.

Here we give the STARE data-set description

DATASET Link : http://www.ces.clemson.edu/~ahoover/stare/

Images : 20Images

STARE data-set is standard one of the best data-set in Medical Imaging research.In STARE Data-set include 20 images,10 for normal another 10 for abnormal images.More research scholars are used this data-set for research.

***if you have done any research works in this data-set means give more comments.Thank you.***

Matlab Find Dictionary word or not Example code | Matlab Extract Synonyms of the word

Here we give some example code of extract Synonym word from corresponding word and find the word is dictionary word or not.It very simple.Following operations are used to extract Synonym word from corresponding word in matlab.

1. Create The activex object to the word.(Note:you have must install word on your PC).This creation using actxserver function.
2. Invoke these object on matlab with "SynonymInfo" properties using on invoke function.In invoke function give another one Input is Finding Synonym word.
3. Finally we extract Synonym words on Invoke object using get function.

In below example explain these above notions.

clc

clear all

close all

warning off

text = 'language';

Doc = actxserver('Word.Application');

X = invoke(Doc,'SynonymInfo',text);

Synonyms = get(X,'MeaningList');

if in above Synonyms variable is empty then give word is not a dictionary word. Here Input text is language out put synonyms are 'verbal communication', 'tongue', 'words'.Below we attach these output.

Create symbolic variable in matlab | Matlab symbolic variable expression addition,multiplication examples | Evaluate symbolic variables in Matlab

Here we give some notes for matlab symbolic variable creation,expression and evaluation.Symbolic variable are used to design a Mathematical expression with some variables.if you can create Symbolic variable means you must use sym or syms function on Matlab.

Syntax : syms ('var1','var2'........'varn');

above syntax for symbolic variable creation. In below example represent symbolic variable creation and expression with evaluation.

>> syms s % symbolic object name is 's'

>> a = (1+2)/s^2 %symbolic equation generation

a =

3/s^2

>> b = (1+s)/s^2

b =

(1+s)/s^2

Two symbolic variable are addition into one varaible as 'c'.

>> c = a+b;

>> c

c =

3/s^2+(1+s)/s^2

>> subs(c,10)

ans =

0.1400

Finally two symbolic variables added and evaluated.In symbolic variable evaluation using subs function.This function evaluate the object on matlab.finally we got the result.

Matlab Accuracy ,Precision ,Recall ,F-measure Calculation example code

Here we discuss with following things....

1. Accuracy
2. Precision
3. Recall
4. F-measure

In above things are used in more research domains.This things are used in classification section, it find out the accuracy of your algorithms.If you have design the algorithm for classification means you have must use these calculation and results.If Research scholars choose classification area means you put these result on your paper.

Below we give some example for this approach.For example you have contain two classes,like Negative sample and Positive sample data means.you have must us following steps for accuracy calculation.

FP rate = False Positive / N; N is the number of negative samples

TP rate = True Positive / P; P is the number of positive samples

Accuracy = (True Positive+ False Positive) / (P + N); / / we generally use

Precision = TP / (True Positive+ False Positive)

Recall = TP / P;

F-score = Precision * Recall;

Accuracy is one of the most frequently used, in some areas, Precision and Recall is also very frequent.

In below we give the matlab code for finding Accuracy ,Precision ,Recall and F-measure Calculation.

FP rate = FP / N;

TP rate = TP / P;

above rates are results of your classes.

function [Accuracy,Precision,Recall,F-measure] = accuracy_calc(FP,TP,N,P)

TN = abs(TP-P);

Accuracy = (TP + FP) / (P + N);

Precision = TP / (TP + FP);

Recall = TP / P;

F-measure = Precision * Recall;