Understanding DBMS

DBMS is Database Management System sigkatan of Indonesian interpreted in a database management system (DBMS). DBMS is the software provided by the database provision for:

 
- Manage and maintain data.
- Moving data to and from the required physical data files.
- Managing concurrent data access by multiple users.
- Oversee the renewal data and prevent conflict data changes.
- Managing the transaction so that data changes occur in full or no change if the transaction canceled.
- Supports query language.
- Monitoring database backup and recovery from errors.
- Security mechanism.
 DBMS is used to store data in a file and write code for the particular application set.
Examples of DBMS is Oracle, MySQL, SQL server 2000/2003, MS Access, and others.
The stored data illustrate various aspects such as:
- Entities (for example: students, subjects).
- Relationships between entities / relationships (eg: Andi took a course Database).
With a database management system (DBMS) allows a user mempu define, create, maintain and provide controlled access to the data.

news source:http://temukanpengertian.blogspot.com/2013/07/pengertian-dbms.html

Understanding Hackers

The term hacker is a familiar term in the computer world, you know what is a Hacker?? Hacker is one who has the desire to learn in depth about the work of a system, a computer or computer network, thus becoming an expert in the field of control systems, computer or computer network. While Hacking the attitude and ability to learn on their own basically.
The term hacker is often misunderstood us about the things that destroy / hack like facebook hack, hack email, hack network dall. But actually Hacking is the art of science, art, computer network security, not all hackers are bad some are good. Hacker definition according to the "working area" they are:

- Black Hat Hacker
Often called a cracker is a kind of hackers who use their skills to do things that damage is considered unlawful.

- White Hat Hacker
Is the opposite of Balack Hat Hackers, White Hat Hacker is a hacker who uses his ability on the right path to face the Black Hat Hacker. White Hat Hackers usually is a professional who works in the company such as a security analyst at security, security consultants, and others.

- Grey Hat Hacker
Is a kind of hacker who moves diarea gray between good and evil, they are White Hat Hacker but they can also turn into a Black Hat Hacker

- Suicide Hacker
Suicide Hacker is a hacker called myths, as cyber terrorism has not been so visible.

That's the definition of a Hacker, not all hackers are evil and destructive but there is also a good hacker and there are gray.

news source: http://temukanpengertian.blogspot.com/2013/06/pengertian-hacker.html

Hacker (computer security)

                In the computer security context, a hacker is someone who seeks and exploits weaknesses in a computer system or computer network. Hackers may be motivated by a multitude of reasons, such as profit, protest, or challenge. The subculture that has evolved around hackers is often referred to as the computer underground and is now a known community. While other uses of the word hacker exist that are not related to computer security, such as referring to someone with an advanced understanding of computers and computer networks,they are rarely used in mainstream context.

They are subject to the long standing hacker definition controversy about the true meaning of the term hacker.computer programmers who argue that someone breaking into computers is better called a cracker,not making a difference between computer criminals (black hats) and computer security experts (white hats).Some white hat hackers claim that they also deserve the title hacker, and that only black hats should be called crackers.

In this controversy, the term hacker is reclaimed by Bruce Sterling traces part of the roots of the computer underground to the Yippies, a 1960s counterculture movement which published the Technological Assistance Program (TAP) newsletter.[citation needed] TAP was a phone phreaking newsletter that taught the techniques necessary for the unauthorized exploration of the phone network. Many people from the phreaking community are also active in the hacking community even today, and vice versa

     Several subgroups of the computer underground with different attitudes use different terms to demarcate themselves from each other, or try to exclude some specific group with which they do not agree.

Eric S. Raymond (author of The New Hacker's Dictionary) advocates that members of the computer underground should be called crackers. Yet, those people see themselves as hackers and even try to include the views of Raymond in what they see as one wider hacker culture, a view harshly rejected by Raymond himself. Instead of a hacker/cracker dichotomy, they give more emphasis to a spectrum of different categories, such as white hat, grey hat, black hat and script kiddie. In contrast to Raymond, they usually reserve the term cracker for more malicious activity.

     According to (Clifford R.D. 2006) a cracker or cracking is to "gain unauthorized access to a computer in order to commit another crime such as destroying information contained in that system". These subgroups may also be defined by the legal status of their activities.

A white hat hacker breaks security for non-malicious reasons, perhaps to test their own security system or while working for a security company which makes security software. The term "white hat" in Internet slang refers to an ethical hacker. This classification also includes individuals who perform penetration tests and vulnerability assessments within a contractual agreement. The EC-Council, also known as the International Council of Electronic Commerce Consultants, is one of those organizations that have developed certifications, course-ware, classes, and online training covering the diverse arena of Ethical Hacking. A "black hat" hacker is a hacker who "violates computer security for little reason beyond maliciousness or for personal gain" (Moore, 2005). Black hat hackers form the stereotypical, illegal hacking groups often portrayed in popular culture, and are "the epitome of all that the public fears in a computer criminal".Black hat hackers break into secure networks to destroy data or make the network unusable for those who are authorized to use the network.

A grey hat hacker is a combination of a black hat and a white hat hacker. A grey hat hacker may surf the internet and hack into a computer system for the sole purpose of notifying the administrator that their system has a security defect, for example. Then they may offer to correct the defect for a fee

      A social status among hackers, elite is used to describe the most skilled. Newly discovered exploits will circulate among these hackers. Elite groups such as Masters of Deception conferred a kind of credibility on their members. A script kiddie (also known as a skid or skiddie) is a non-expert who breaks into computer systems by using pre-packaged automated tools written by others, usually with little understanding of the underlying concept—hence the term script (i.e. a prearranged plan or set of activities) kiddie (i.e. kid, child—an individual lacking knowledge and experience, immature). A neophyte, "n00b", or "newbie" is someone who is new to hacking or phreaking and has almost no knowledge or experience of the workings of technology, and hacking

     A blue hat hacker is someone outside computer security consulting firms who is used to bug test a system prior to its launch, looking for exploits so they can be closed. Microsoft also uses the term BlueHat to represent a series of security briefing events

     A hacktivist is a hacker who utilizes technology to announce a social, ideological, religious, or political message. In general, most hacktivism involves website defacement or denial-of-service attacks. Intelligence agencies and cyberwarfare operatives of nation states. Criminal activity carried on for profil. Bots are automated software tools, some freeware, that are available for the use of any type of hacker.

news source: http://en.wikipedia.org/wiki/Hacker

E-commerce

         Electronic commerce, commonly known as e-commerce or eCommerce, is a type of industry where the buying and selling of products or services is conducted over electronic systems such as the Internet and other computer networks. Electronic commerce draws on technologies such as mobile commerce, electronic funds transfer, supply chain management, Internet marketing, online transaction processing, electronic data interchange (EDI), inventory management systems, and automated data collection systems. Modern electronic commerce typically uses the World Wide Web at least at one point in the transaction's life-cycle, although it may encompass a wider range of technologies such as e-mail, mobile devices social media, and telephones as well.

 Electronic commerce is generally considered to be the sales aspect of e-business. It also consists of the exchange of data to facilitate the financing and payment aspects of business transactions. This is an effective and efficient way of communicating within an organization and one of the most effective and useful ways of conducting business.
E-commerce can be divided into:

• E-tailing or "virtual storefronts" on websites with online catalogs, sometimes gathered into a "virtual mall"
• Buying or Selling on various websites
• The gathering and use of demographic data through Web contacts and social media
• Electronic Data Interchange (EDI), the business-to-business exchange of data
• E-mail and fax and their use as media for reaching prospective and established customers (for example, with newsletters)
• Business-to-business buying and selling
• The security of business transactions
  
  news source:http://en.wikipedia.org/wiki/E-commerce

A Brief History of E Commerce

 electronic commerce began in the early 1970s with the kind of innovative electronic fund transfer (EFT). current levels of application are limited to large corporations, financial institutions, and small companies that nekat.lalu segelincir appear Electronic Data Interchage (EDI), which evolved from the financial transaction to another transaction processing as well as increase the number of participating companies, financial institutions began to institute until perusahaanmanufaktur, retail, service and so on.

Applications other apps followed, which has Jangakauan from stock trading to a travel reservation system. at the time the system is referred to as the strategic value of telecom applications are known in general. with the commercialization of the Internet in the early 1990s, and the rapid growth of yanhg reach millions of potential customers, hence the term electronic commerce (e-commerce), the application ssegera growing rapidly. e-commerce research center at the University of Texas who studies the Internet company in 2000, so it is the fastest growing e-Commerce, which rose to 72% from $ 99.8 billion to $ 171.5 billion. in 2002 over a trillion dollars in revenue generated from the internet. 

One reason for the rapid development of these technologies is the development of networks, protocols, software perangakat, and specifications. Another reason is the increasing competition and a variety of other business pressures 

From 1995 to 1999 we have seen a variety of innovative applications, ranging up to auction advertising and virtual reality experiences. almost every medium and large organizations in the U.S. have their own web site. there is a very large, eg, in 1998, General Motors Corporation (www.gm.com) offers 18,000 pages of information covering 98,000 links to various products, services and dealer dealership. 

news source: M.Suyanto

Journal nueral network cancer

International Journal of Computer Applications (0975 – 8887)
Volume 10– No.3, November 2010

Parallel Approach for Diagnosis of Breast Cancer
using Neural Network Technique
Dr. K. Usha Rani
Dept. of Computer Science
Sri Padmavathi Mahila isvavidyalayam (Women’s University)
Tirupati , Andhra Pradesh

ABSTRACT

Classification is perhaps the most familiar and popular data mining technique. Inspired by biological neural networks, Artificial Neural Networks are developed to mimic the characteristics such as robustness and fault tolerance. To perform classification task of medical data, the neural network is trained. To speed up the training process parallel approach is adopted. In this paper a parallel approach by using neural network technique is proposed to help in the diagnosis of breast cancer. The neural network is trained with breast cancer data base by using feed forward neural network model and backpropagation learning algorithm with momentum and variable learning rate. The performance of the network is evaluated. The experimental result shows that by applying parallel approach in neural network model yields efficient result.

Keywords
Classification, Neural Networks, Parallelism, feed forward, backpropagation, Breast Cancer.

1. INTRODUCTION

Data mining is an essential step in the process of knowledge discovery in databases in which intelligent methods are applied in order to extract patterns. Parallelism offers a natural and
promising approach to cope with the problem of efficient data mining in large databases. There has been considerable interest in parallel processing of data mining algorithms [1,2]. Classification is an important problem in the rapidly emerging field of data mining. It has been studied extensively by the machine learning community as a possible solution to the knowledge acquisition or knowledge extraction problem. The input to a classifier is a training set of records, each of which is tagged with a class label. A set of attribute values defines each record. Attributes with discrete domain are referred to as categorical, while those with ordered domains are referred to as numeric. The goal is to induce a model or description for each class in terms of the attributes. The model is then used to classify future records whose classes are unknown. Among the techniques developed for classification, popular ones include Bayesian classification, Neural Networks, Generic Algorithms and Decision Trees. The decision tree approach is most useful in classification problems. With this technique, a tree is constructed to model the classification process. Once the tree is built, it is applied to each tuple in the database and results in a classification for that tuple. Disadvantages of decision trees are, they do not easily handle continuous data. Handling missing data is difficult because correct branches in the tree could not be taken. Correlation among attributes in the database are ignored by the decision tree process. Neural network is one of the most used data mining method to extract patterns in an intelligent and reliable way and has been greatly used to find models that describe data relationship [3,4]. Neural networks, Fuzzy sets and Genetic algorithm applications in data mining are discussed in the survey of data mining using soft computing [5]. In this paper a neural network technique is proposed to detect breast cancer. To fasten the process parallel computation also adopted.
 

2. NEURAL NETWORK FOR CLASSIFICATION
Another technique that is commonly applied for solving data mining problem is the Artificial Neural Networks (ANN). Originally inspired by biological models of mammalian brains, ANN have emerged as a powerful technique for data analysis. Neural Networks consists of compositions of single, non linear processing units that are organized in a densely inter connected graph. A set of parameters, called weights, are assigned to each of the edges of the graph [6]. These parameters are adapted through the local interactions of processing units in the network. By repeatedly adjusting these parameters, the neural network is able to construct a representation of a given data set. This adaptation process is known as training. Neural Network is able to solve highly complex problems due to the non linear processing capabilities of its neurons. In addition, the inherent modularity of the neural network structure makes it adaptable to a wide range of applications. One of the main limitations of applying neural networks to analyze massive data mining databases is the excessive processing that is required. It is not uncommon for a data mining neural networks to take weeks or months to complete its task. This time constraint is infeasible for most real work applications. However, processing time can be substantially reduced by distributing the load of computation among multiple processors. Thus, parallelism presents a logical approach to managing the computation costs of data mining applications. 

 

2.1 Neural Networks Parallelization Strategies
There are a variety of different parallelization strategies which have been considered for Artificial Neural Networks [7]. Due to the modularity of the Neural Network structure, there are several levels at which Neural Network processing can be divided into concurrently executable components. The following are thesome of the ways of parallelism that can be implemented in Neural Networks.

2.1.1 Exemplar Parallelism (EP)

This approach uses the existence of a large number of data examples as the source of parallelism. The work of Neural Networks training is reduced by distributing an equal size partition of the data set to each processor. Each processor trains an identical network on its local set of data examples.
 

2.1.2 Block parallelism
This approach partitions the network into blocks of adjacent neurons that are distributed among the processors.
 

2.1.3 Neuron Parallelism
For this approach , each individual neuron is treated as a concurrent process and is randomly distributed among the processors in a parallel machine.
The figures 1 to 3 illustrates each of the above Parallelism strategies [7].
1. Distributed Examples
2. Compute local gradients
3. Globally exchange weight updates
4. Update network
weight
Figure 1: The Block diagram of Exemplar Parallelism
Figure 2: Block diagram of Block parallelism
Figure 3: Block diagram of Neuron parallelism
There are two other levels of neural Parallelism that are in practice. The first one is training- session parallelism which entails the simultaneous training of independent Neural Networks on different processors. The other approach is weight parallelism in which the weights connected to every neuron in the network are distributed among several processors i.e, this approach parallelizes the weighted sum computation for each
neuron.
 

2.2 Advantages of Neural Networks for Classification
• Neural Networks are more robust than decision trees because of the weights
• The Neural Networks improves its performance by learning. This may continue even after the training set has been applied.
• The use of Neural Networks can be parallelized as specified above for better performance.
• There is a low error rate and thus a high degree of accuracy once the appropriate training has been performed.
• Neural Networks are more robust than decision trees in noisy environment.
 

2.3 Neural Network Models
There are three aspects involved in the construction of a Neural Networks.
1. Structure : The architecture and topology of Neural Networks.
2. Encoding : The method of changing weights (Training ).
3. Recall : The method and capacity to retrieve information.
Various Neural Networks models exist and among these Feed Forward Neural Network is considered in this study for the construction of neural network. Because, this model, besides being popular and simple, is easy to implement and appropriate for classification applications.
 

2.3.1 Feed Forward Networks with Backpropagation
The feed forward backpropagation network is a very popular model in neural network. It does not have feedback connections, but the errors are back propagated during training. Backpropagation learning consists of two passes through the different layers of the network: a forward pass and backward pass. In forward pass, input vector is applied to the sensory nodes of the network and its effect propagates through the network layer by layer. Finally, a set of outputs is produced as the actual response of the network. During the forward pass the synaptic weights of the network are all fixed. During the backward pass, the synaptic weights are all adjusted in accordance with an error correction rule. The actual response of the network is subtracted from a desired (target) response to produce an error signal. This error signal is then backpropogated through the network, against the direction of synaptic connections[8]. Backpropagation algorithm can be improved by considering momentum and variable learning rate. Momentum allows a network to respond not only to the local gradient, but also to the recent trends in error surface. Acting like a low pass filter, momentum allows the network to ignore small features in the error surface. Without momentum, a network may get struck in a Ishallow local minimum. In backpropagation with momentum, the weight change is in a direction that is a combination of the current and previous gradients. This is a modification of gradient descent whose advantages arise chiefly when some training data are very different from the majority of the data. Convergence is sometimes faster if a momentum term is added to the weight update formulas. The performance of algorithm is very sensitive to the proper setting of the learning rate. If the learning rate is set too high, the algorithm may oscillate and become unstable. If the learning rate too small, the algorithm will take too long to converge. It is not practical to determine the optimal setting for the learning rate before training and in fact the optimal learning rate changes during the training process, as the algorithm moves across the performance surface. Performance of the backpropogation can be improved by allowing the learning rate to change during the training process. An adaptive learning rate will attempt to keep the learning step size as large as possible while keeping the learning process stable. The learning rate is made responsive to the complexity of the local error surface.
 

3. NEURAL NETWORKS IN MEDICAL FIELD
Keeping in view of the significant characteristics of NN and its advantages for the implementation of the classification problem, Neural Network technique is considered for the classification of data related to medical field in this study. Owing to their wide range of applicability and their ability to learn complex and non linear relationships including noisy or less precise information Neural Networks are very well suited to
solve problems in biomedical engineering. By their nature, Neural Networks are capable of high-speed parallel signal processing in real time. They have an advantage over conventional technologies because they can solve problems that are too complex-problems that do not have an algorithmic solution or for which an algorithmic solution is too complex. Neural Networks are trained by examples instead of rules and are automated. This is one of the major advantages of neural networks over traditional expert systems [9,10]. When NN is used in medical diagnosis they are not affected by factors such as human fatigue, emotional states and habituation. They are capable of rapid identification, analyses of conditions, and diagnosis in real time. With the spread of Neural Networks in almost all fields of science and engineering, it has found extensive application in biomedical engineering field also. The applications of neural networks in biomedical computing are numerous. Various applications of ANN techniques in medical field like medical expert system, cardiology, neurology, rheumatology, mammography and pulmonology were studied [11,12]. In this study medical data related to Breast Cancer is considered for classification purpose to identify the disease. As the Neural Networks are inherently parallel in nature, this technique is considered in this study to implement parallelism for calculating the output at each node in different layers of the network. The basic unit of modularity in a network is neuron. Every neuron operates independently, processing the input receives, adjusting weights, and propagating its computed output thus a neuron is a natural level of parallelization for neural networks. Every neuron is treated as a parallel process. For example a layer other than the input layer consists of m neurons and assume that processing time ‘t units’ to calculate the output at each neuron is similar. If the parallel concept is not adopted in neural network ‘mt units’ of time is needed to calculate the output. The needed time can be reduced by m times, if parallel concept is implemented at neuron level. If the
network consists of many hidden layers, the processing time can be reduced at each layer in the network and thus the overall training time of the network can be reduced drastically. Hence, we adopted the above said parallel concept in this thesis to speedup the training process of the net to perform the classification task.
 

3.1 Experiment - Classification of Cancer Dataset
One of the leading causes of death of women is breast cancer. Mammography has been proved to be an effective diagnostic procedure for early detection of breast cancer. An important sign in its detection is the identification of micro calcification of mammograms, especially when they form clusters. In this experiment the medical data related to breast cancer is considered. This database was obtained from the university of Wisconsin hospital, Madison from Dr. William H. Wolberg. This is publicly available dataset in the Internet.
Descriptions of Database:
• Number of instances 699
• Number of attributes: 10 plus the class attribute
• Attributes 2 through 10 will be used to represent instances
• Each instance has one of 2 possible classes: benign or malignant
• Class distribution: Benign : 458 (65.5%)
Malignant : 241 (34.5%)
Attribute information:
Attribute Domain
1. Sample code number id number
2. Clump thickness 1-10
3. Uniformity of cell size 1-10
4. Uniformity of cell shape 1-10
5. Marginal adhesion 1-10
6. Single epithelial cell size 1-10
7. Bare nuclei 1-10
8. Bland chromatin 1-10
9. Normal nucleoli 1-10
10. Mitosis 1-10
11. Class (2 for benign, 4 for malignant)
Data Representation Scheme:
The original data is present in the form of analog values with values ranging from 0-10. The given data sets are converted to their equivalent digital form. Scaling has the advantage of mapping the desired range of variables ranging between minimum and maximum range of network input. conversion of the given data sets into binary is done based on certain ranges, which are defined for each attribute. There are totally 10 attributes (1 class and 9 numeric features). The 9 numerical attributes are in the analog form scaled in the range between 0 and 1. First from the given range of inputs, the minimum and maximum value is picked up and this scaling is done by the following formula. 

New value (after scaling) = (current value – Min value) / (Max - Min)
The new values obtained after truncating are converted into binary from by the following scaling. The values, which are in the range 0 to 5 are converted to 0 and 6 to 10 are converted to 1.
 

3.2 Training the Neural Network
In this experiment the neural network is trained with Breast Cancer database by using feed forward neural network model and backpropagation learning algorithm with momentum and variable learning rate. The cancer database consists 9 attributes. The input layer of the network consists of 9 neurons to represent each attribute as the cancer database consists of 9 attributes. The number of classes are 2, one Benign and another is Malignant. So one neuron in the output layer is sufficient to represent these two classes. The description of the backpropagation algorithm is specified in the above is used to train the neural network during the training process. Several neural networks are constructed with and without hidden layers i.e, single and multi layer networks and trained with cancer dataset. Relationship between the number of epochs and the sum of squares of errors during training process for various networks can be observed from the Figures 4 and 5.
Figure 4: Training the Single Layer Network with Cancer Dataset
Figure 5: Training the Multi Layer Network with Cancer Dataset

3.3 Performance of the Network
The various phases in the classification problems solved by neural network techniques are construction, training and testing. Construction and training of the neural network are explained in the previous section. The classification of the test data and the performance of the network are discussed in this section. Various samples are collected as test data. The test data is given as the input to the trained network and the output of the net is calculated with the adjusted weights. Since we know the target output, the output of net is compared with this target output to study the learning ability of the network for classifying the cancer data. We observed that 92% test data are correctly classified and 8% are misclassified may be because of the analog conversion to digital conversion of dataset.
Table 1: Experimental Results of Cancer Dataset:

4. CONCLUSION
To classify the medical data set a neural network approach is adopted. Neural Networks are inherently parallel in nature. This technique is adopted to implement parallelism to calculate the output at each node in different layers for the classification of medical dataset such as Breast Cancer. The experiment is conducted with this dataset by considering the single and multi layer neural network models. Backpropogation algorithm with momentum and variable learning rate is used to train the networks. To analyze performance of the network various test data are given as input to the network. To speed up the learning process, parallelism is implemented at each neuron in all hidden and output layers. The results show that the multilayer neural network is trained quickly than single layer neural network and the classification efficiency is also high. The experimental results proved that neural networks technique provides satisfactory results for the classification task. 

5. REFERENCES
[1] A.A Freitas & S.H. Lavington. Mining Very Large Databases with Parallel Processing. Kulwer Academic Publishers, 1998. ISBN 0-7923-8048-7.
[2] R. J. Bayardo. Efficiently mining long patterns from databases. In ACM SIGMOD Conf. Management of Data, June 1998.
[3] John Shafer, Rakesh Agarwal, and Manish Mehta. SPRINT:A scalable parallel classifier for data mining. In Proc. Of the VLDB Conference, Bombay, India, Sep 1996.
[4] Sunghwan Sohn and Cihan H. Dagli. Ensemble of Evolving Neural Networks in classification. Neural Processing Letters 19: 191-203, Kulwer Publishers, 2004
[5] Sushmita Mitra. Datamining in Soft Computing Framework: A Survey. IEEE Transactions on Neural Networks, Vol 13, No. 1, Jan 2002.
[6] R. Rojas. Neural Networks: a systematic introduction. Springer-Verlag, 1996
[7] R. Owen Rigers. A framework for parallel data mining using neural networks. Technical report , Queen’s
University, Canada, 1997.
[8] Simon Haykin. Neural Networks – A Comprehensive Foundation. Pearson Education, 2001.
[9] K. Anil Jain, Jianchang Mao and K.M. Mohiuddin. Artificial Neural Networks: A Tutorial. IEEE Computers, 1996, pp.31-44.
[10] George Cybenko. Neural Networks in Computational Science and Engineering. IEEE Computational Science and Engineering, 1996, pp.36-42.
[11] Dr. A. Kandaswamy, Applications of Artificial Neural Networks in Bio Medical Engineering. The Institute of Electronics and Telecommunicatio Engineers, Proceedings of the Zonal Seminar on Neural Networks, Nov 20-21, 1997.
[12] A. Kusiak, K.H. Kernstine, J.A. Kern, K>A. McLaughlin and T.L. Tseng, Data mining: Medical and Engineering Case Studies, Proceedings of the Industrial Rngineering Research 2000 Conference, Cleveland, Ohio, May21- 23,pp.1-7,2000

PHP Tutorial Part 2 - Displaying Information & Variables

Introduction

In the last part of the tutorial I explained some of the advantages of PHP as a scripting language and showed you how to test your server for PHP. In this part I will show you the basics of showing information in the browser and how you can use variables to hold information.

Printing Text

To output text in your PHP script is actually very simple. As with most other things in PHP, you can do it in a variety of different ways. The main one you will be using, though, is print. Print will allow you to output text, variables or a combination of the two so that they display on the screen.

The print statement is used in the following way:

print("Hello world!");

I will explain the above line:

print is the command and tells the script what to do. This is followed by the information to be printed, which is contained in the brackets. Because you are outputting text, the text is also enclosed instide quotation marks. Finally, as with nearly every line in a PHP script, it must end in a semicolon. You would, of course, have to enclose this in your standard PHP tags, making the following code:

print("Hello word");

Which will display:

Hello world!

on the screen.

Variables

As with other programming languages, PHP allows you to define variables. In PHP there are several variable types, but the most common is called a String. It can hold text and numbers. All strings begin with a $ sign. To assign some text to a string you would use the following code:

$welcome_text = "Hello and welcome to my website.";

This is quite a simple line to understand, everything inside the quotation marks will be assigned to the string. You must remember a few rules about strings though:

Strings are case sensetive so $Welcome_Text is not the same as $welcome_text
String names can contain letters, numbers and underscores but cannot begin with a number or underscore
When assigning numbers to strings you do not need to include the quotes so:

$user_id = 987

would be allowed.

Outputting Variables

To display a variable on the screen uses exactly the same code as to display text but in a slightly different form. The following code would display your welcome text:

As you can see, the only major difference is that you do not need the quotation marks if you are printing a variable.

Formatting Your Text

Unfortunately, the output from your PHP programs is quite boring. Everything is just output in the browser's default font. It is very easy, though, to format your text using HTML. This is because, as PHP is a server side language, the code is executed before the page is sent to the browser. This means that only the resulting information from the script is sent, so in the example above the browser would just be sent the text:

Hello and welcome to my website.

This means, though, that you can include standard HTML markup in your scripts and strings. The only problem with this is that many HTML tags require the " sign. You may notice that this will clash with the quotation marks used to print your text. This means that you must tell the script which quotes should be used (the ones at the beginning and end of the output) and which ones should be ignored (the ones in the HTML code).

For this example I will change the text to the Arial font in red. The normal code for this would be:




As you can see this code contains 4 quotation marks so would confuse the script. Because of this you must add a backslash before each quotation mark to make the PHP script ignore it. The code would chang
e to:




You can now include this in your print statement:

print("Hello and welcome to my website.");

which will make the browser display:

Hello and welcome to my website.

because it has only been sent the code:

Hello and welcome to my website.

This does make it quite difficult to output HTML code into the browser but later in this tutorial I will show you another way of doing this which can make it a bit easier.

Part 3

In part 3 I will introduce If statements.
news sources from : www.freewebmasterhelp.com

PHP Tutorial Part 1 - Introduction

Introduction

Up until recently, scripting on the internet was something which very few people even attempted, let alone mastered. Recently though, more and more people have been building their own websites and scripting languages have become more important. Because of this, scripting languages are becomming easier to learn and PHP is one of the easiest and most powerful yet.

What Is PHP?

PHP stands for Hypertext Preprocessor and is a server-side language. This means that the script is run on your web server, not on the user's browser, so you do not need to worry about compatibility issues. PHP is relatively new (compared to languages such as Perl (CGI) and Java) but is quickly becomming one of the most popular scripting languages on the internet.

Why PHP?

You may be wondering why you should choose PHP over other languages such as Perl or even why you should learn a scripting language at all. I will deal with learning scripting languages first. Learning a scripting language, or even understanding one, can open up huge new possibilities for your website. Although you can download pre-made scripts from sites like Hotscripts, these will often contain advertising for the author or will not do exactly what you want. With an understanding of a scripting language you can easily edit these scripts to do what you want, or even create your own scripts.

Using scripts on your website allows you to add many new 'interactive' features like feedback forms, guestbooks, message boards, counters and even more advanced features like portal systems, content management, advertising managers etc. With these sort of things on your website you will find that it gives a more professional image. As well as this, anyone wanting to work in the site development industry will find that it is much easier to get a job if they know a scripting language.

What Do I Need?

As mentioned earlier, PHP is a server-side scripting language. This means that, although your users will not need to install new software, you web host will need to have PHP set up on their server. It should be listed as part of your package but if you don't know if it is installed you can find out using the first script in this tutorial. If you server does not support PHP you can ask your web host to install it for you as it is free to download and install. If you need a low cost web host which supports PHP I would recommmend HostRocket.





Writing PHP

Writing PHP on your computer is actually very simple. You don't need any specail software, except for a text editor (like Notepad in Windows). Run this and you are ready to write your first PHP script.

Declaring PHP

PHP scripts are always enclosed in between two PHP tags. This tells your server to parse the information between them as PHP. The three different forms are as follows:








All of these work in exactly the same way but in this tutorial I will be using the first option (). There is no particular reason for this, though, and you can use either of the options. You must remember, though, to start and end your code with the same tag (you can't start with for example).

Your First Script

The first PHP script you will be writing is very basic. All it will do is print out all the information about PHP on your server. Type the following code into your text editor:



As you can see this actually just one line of code. It is a standard PHP function called phpinfo which will tell the server to print out a standard table of information giving you information on the setup of the server.

One other thing you should notice in this example is th
at the line ends in a semicolon. This is very important. As with many other scripting and programming languages nearly all lines are ended with a semicolon and if you miss it out you will get an error.

Finishing and Testing Your Script

Now you have finished your script save it as phpinfo.php and upload it to your server in the normal way. Now, using your browser, go the the URL of the script. If it has worked (and if PHP is installed on your server) you should get a huge page full of the information about PHP on your server.

If your script doesn't work and a blank page displays, you have either mistyped your code or your server does not support this function (although I have not yet found a server that does not). If, instead of a page being displayed, you are prompted to download the file, PHP is not installed on your server and you should either serach for a new web host or ask your current host to install PHP.

It is a good idea to keep this script for future reference.

Part 2

In this part I have introduced you to the basics of writing and running PHP. By this time you should now know if your host supports PHP and should have a basic understanding of how PHP scripts are structured. In part 2 I will show you how to print out information to the browser

news sources from : www.freewebmasterhelp.com

Penetrating TM PC Security Protection

If you're a fan of software protection for windows, you must be familiar with this software. PC Security is a software protection for files, system, boot and others equipped with protective fiture fiture-interesting. To be able to enter and modify proteksinya settings, you must ident as an administrator for PC security and it will be asked for a password.

So you can login without a password through, how search sdeamon.exe file name and file winwd.exe which is innate PC Security TM, dihidden file from windows, so go through DOS. Usually located in the directory c: \ windows or c: \ windows \ system. Delete these two files and you will be able to enter the PC Security TM easily and without being asked to change password settingnya. Good luck

Protect files

Protect files or folders in a way nge-rename the file or folder by using alt + 255 (or with other characters is a combination of alt + number) has a flaw that the file can still be seen in windows 9x environment as that will make people who see the curious atawa want to know.

In order not to be seen or be hidden files how to change the name of the file (eg file name is try it from DOS type: "ren, try (alt +255) new locker with hidden attribute from DOS (not windows). To open the back or cut through with ease can be used Norton Commander ..... ie when it entered the NC press the F6 and change the file name that wrote he did not look earlier....

Enabling Computer Lock Features

If you are using Windows XP but only menggandalakan password from screen saver, do not expect a high level of security from it. therefore, if you activate the checkbox On resuma, display welcome screen on screen saver, the computer can still be used by someone else who has an account on that computer. for that, you who want a higher security in Windows XP can use the Lock Computer feature in Windows XP.

So when you leave the computer, but you and the administrator, no one else can use the computer. How to enable this feature:
1. Click [Start] -> [Control Panel], then select User Accounts.
2. In the User Accounts window, select Change the way users log on or off, remove the check mark in the checkbox Use the Welcome Screen.
3. Then click [Apply Options].
4. Furthermore, if you want to lock the computer, press [Ctrl + Alt + Del] and select Lock Computer

Hide user account in Windows XP

Assessment of user: / 0
Poor Excellent
Hide user account in Windows XP
When you start the computer using the welcome screen will appear and will show all the user accounts on the computer. With the tips below you can hide the user account you want.
Click Start -> Run ---> Regedit

Key -> HKEY_LOCAL_MACHINE \ SOFTWARE \ Microsoft \ Windows NT \ CurrentVersion \ Policies \ SpecialAccounts \ Userlist
Value Name (name of user account that will be hidden
Data Type REG_DWORD (DWORD Value)
Data 0 to 1 to hide and show again.
Although the user account does not appear on the welcome screen, but you can still log in with user account, the way by pressing the Ctrl + Alt + Del two times

Search for a file system or Hidden Files

By default, Search does not search for hidden files or system files, so you can munkin not menumukan these files even though there is in the drive.
To find these, click Start, click Search, click All Files and Folders, then click on more
advanced options, Cetang Search box and Search system folders and hidden folders.

You do not need to set the Options dialog box folder in Explorer windows to show the files tesembunyi Search Companion sharing option hide protected operating system files (which hides files and system files are hidden) The Options dialog box in Windows Eplorer.

Flash disk size was not as originally

If you use a USB disk, you may have experienced irregularities in the remaining space. Say your flash disk size is 128Mb and contains half the alias 64MB. Strangely the rest of the space should still only 67MB was 20MB.Menggapa demikin. Flash disk empty actions also cause peculiarities which sometimes filled the room only to be informed of 128MB smaller. Only 50-60 MB for example. How do I get the missing space.

Flash dist is often experienced "lost space" like this after repeatedly used the data store. Actually this is not a problem, but we should get the maximum capacity of a flash disk. To try to restore full capacity to move data from flash disk to your hard dist, then re-do the format. select a quick format just after it should have been dist-capacity flash back to normal.
good luckl.
good luck

Accelerating Windows

Click Start -> Run -> type "regedit
Sign in to each section below:
[HKEY_CURRENT_USERControl PanelDesktop] -> Change the following match ..
"AutoEndTasks" = "1"
"HungAppTimeout" = "3000"
"MenuShowDelay" = "0"
"WaitToKillAppTimeout" = "3000"

[HKEY_CURRENT_USERSoftwareMicrosoftWindowsCurrentVersionExplorer]
-> Right click add a DWORD value "DesktopProcess"
-> Right click on the item "DesktopProcess" modify this turn into a "1"
[HKEY_CURRENT_USERSoftwareMicrosoftWindowsCurrentVersionRun]
[HKEY_LOCAL_MACHINESoftwareMicrosoftWindowsCurrentVersionRun]
-> Delete unneeded registers (the register contained therein is the startup process that will run every time windows login)
[HKEY_LOCAL_MACHINESOFTWAREMicrosoftWindows NTCurrentVersionWinlogon]
-> Right click add a DWORD value "EnableQuickReboot"
-> Right click on the item "EnableQuickReboot" modify this turn into a "1"
[HKEY_LOCAL_MACHINESYSTEMControlSet001Control]
-> Change the following as ...
"WaitToKillServiceTimeout" = "3000"
Good Try