Retail Management

A process of promoting greater sales and customer satisfaction by gaining a better understanding of the consumers of goods and services produced by a company. A typical retail management strategy for a manufacturing business might research the retail process that distributes the finished products created by the business to consumers to determine and satisfy what buyers want and require.

Intrusion Detection System Research Based on Data Mining for IPv6

IPv6 will inevitably take the place of IPv4 as the next generation of the Internet Protocol. Despite IPv6 has better security than IPv4, but there still have some security issues. So it is an urgent problem to requirement of IDS for IPv6 networks.
Many intelligent information processing methods, data mining technology and so on have been applied to improve detection accuracy for IPv4 network. At first IPv6 security issues has been analysis in this project, secondly discussed the IPv6 intrusion detection model, then we in accordance with such a model present an intrusion detection model realization for IPv6 network, and we propose a strategy for the system achieve and optimization. The system can work well for intrusion detection for IPv6 network.

Network Intrusion Detection:            
         Modern computer networks must be equipped with appropriate security mechanisms in order to protect the information resources maintained by them. Intrusion detection systems (IDSs) are integral parts of any well configured and managed computer network systems. An IDS is a combination of software and hardware components, capable of monitoring different activities in a network and analyze them for signs of security threats. There are two major approaches to intrusion detection: anomaly detection and misuse detection. Misuse detection uses patterns of well known intrusions to match and identify unlabeled data sets. In fact, many commercial and open source intrusion detection systems are misuse based. Anomaly detection, on the other hand, consists of building models from normal data which can be used to detect variations in the observed data from the normal model. The advantage with anomaly detection algorithms is that they can detect new forms of attacks which might deviate from the normal behaviour . In this project, various supervised learning algorithms, particularly decision trees based on ID3, J48, and Naïve Bayes algorithms are explored for network intrusion.Intrusion detection is the art of detecting the break-ins of malicious attackers. Today, computer security has grown in importance with the widespread use of the Internet. Firewalls are commonly used to prevent attacks from occurring. Antivirus and anti-spyware programs can help people to remove already existing automated attacks from their computer. Access control limits physical and networked use of a computer. However, an important component of setting up a secure system is to have some way to analyze the activity on the computer and determine whether an attack has been launched against the computer. Such a system is called an intrusion detection system. This project uses Naive Bayes, a Decision Tree algorithms to determine the relative strengths and weaknesses of using these approaches. The purpose is to give an evaluation of the performance of these algorithms that will allow someone who wishes to use one of these approaches to understand how accurate the approach is and under what conditions it works well. In addition, a novel evaluation technique will be considered. Accuracy can be evaluated effectively by using Receiver Operating Characteristic (ROC) curves. Cost curves  can indicate the conditions under which the algorithm works well.
           A requirement is a feature that the system must have or a constraint that it must satisfy to be accepted by client. Requirements engineering aims at defining the requirements for the system under construction. It includes two main activities: Requirements Elicitation and Analysis.
         Requirements elicitation is about communication among developers, clients, and users for defining a new system. It focuses on describing the purpose of the system. Such a definition is called system  specification. Requirement elicitation is the more challenging of the two because it requires the collaboration of several groups of participants with different backgrounds. On the one hand, the client and the users are experts in their domain and have a general idea of what the system should do, but they often have little experience in software development. On the other hand, the developers have experience in building systems, but often have  little knowledge of everyday environment of the users

Intrusion Detection and Attack Classification Using Feed-Forward Neural Network

THE rapid development and expansion of World Wide Web and local network systems have changed the computing world in the last decade. The highly connected computing world has also equipped the intruders and hackers with new facilities for their
destructive purposes. The costs of temporary or permanent damages caused by unauthorized access of the intruders to computer systems have urged different organizations to increasingly implement various systems to monitor data flow in their networks These systems are generally referred to as Intrusion Detection Systems (IDSs).
Network security is becoming an issue of paramount importance in the information technology era The survey conducted in Australia reveals that while 98% of organizations experienced some form of broader computer crime or abuse, 67% suffered a computer security incident National and international infrastructure is heavily network based across all sectors. As we increasingly rely on information infrastructures to support critical operations in defense, banking, telecommunication, transportation, electric power, e-governance, and many other systems, intrusions into information systems have become a significant threat to our society with potentially severe consequences .
 An intrusion compromises the security (e.g. availability, integrity, and confidentiality) of an information system through various means. Computer systems have become so large, complex, and have assumed many important tasks that when things go wrong, it is extremely difficult to implement fixes fast enough to avoid mission critical problems. The fast growing data transfer rate, proliferation of networks, and the Internet’s unpredictability have added even more problems. Researchers are working hard to develop more efficient, reliable and self-monitoring systems, which detect problems and continue to operate fixing without human interaction. This type of approach tries to reduce catastrophic failures of sensitive systems.
There are two main approaches to the design of IDSs. In a misuse detection based IDS, intrusions are detected by looking for activities that correspond to known signatures of intrusions or vulnerabilities. On the other hand, an anomaly detection based IDS detects intrusions by searching for abnormal network traffic. The abnormal  traffic pattern can be defined either as the violation of accepted thresholds for frequency of events in a connection or as a user’s violation of the legitimate profile developed for his/her normal behavior. One of the most commonly used approaches in expert system based intrusion detection systems is rule-based analysis using  profile model. Rule-based
analysis relies on sets of predefined rules that are provided by an administrator or created by the system. Unfortunately, expert systems require frequent updates to remain current. This design approach usually results in an inflexible detection system that is unable to detect an attack if the sequence of events is even slightly different from the predefined profile. The problem may lie in the fact that the intruder is an intelligent and flexible agent while the rulebased IDSs obey fixed rules. This problem can be tackled by the application of soft computing techniques in IDSs. Soft computing is a general term for describing a set of optimization and processing techniques that are tolerant of imprecision and uncertainty. The principal constituents of soft computing techniques are Fuzzy Logic (FL), Artificial Neural Networks (ANNs), Probabilistic Reasoning (PR), and Genetic Algorithms (GAs).

There are two general categories of attacks which intrusion detection technologies attempt to identify - anomaly detection and misuse detection. Anomaly detection identifies activities that vary from established patterns for users, or groups of users. Anomaly detection typically involves the creation of knowledge bases that contain the profiles of the monitored activities. The second general approach to intrusion detection is misuse detection. This technique involves the comparison of a user's activities with the known behaviors of attackers attempting to penetrate a system. While anomaly detection typically utilizes threshold monitoring to indicate when a certain established metric has been reached, misuse detection techniques frequently utilize a rule-based approach. When applied to misuse detection, the rules become scenarios for network attacks. The intrusion detection mechanism identifies a potential attack if a user's activities are found to be consistent with the established rules. The use of comprehensive rules is critical in the application of expert systems for intrusion detection.
There are four major categories of networking attacks. Every attack on a network can be placed into one of these groupings.

Data Mining

As on discovering the web usage patterns of websites from the server log files. The Web is a huge, explosive, diverse, dynamic and mostly unstructured data repository, which supplies incredible amount of information, and also raises the complexity of how to deal with the information from the different perspectives of view, users, web service providers, business analysts. The users want to have the effective search tools to find relevant information easily and precisely. The Web service providers want to find the way to predict the users’ behaviors and personalize information to reduce the traffic load and design the Website suited for the different group of users. The business analysts want to have tools to learn the user/consumers’ needs. All of them are expecting tools or techniques to help them satisfy their demands and/or solve the problems encountered on the Web. Therefore, Web mining becomes a popular active area and is taken as the research topic for this investigation. Web Usage Mining is the application of data mining techniques to discover interesting usage patterns from Web data, in order to understand and better serve the needs of Web-based applications. Usage data captures the   identity or origin of Web users along with their browsing behavior at a Web site.
Web usage mining itself can be classified further depending on the kind of usage data considered. They are web server data, application server data and application level data. Web server data correspond to the user logs that are collected at Web server. Some of the typical data collected at a Web server include IP addresses, page references, and access time of the users and is the main input to the present Research. This Research work concentrates on web usage mining and in particular focuse

ANGEL: Enhancing the Utility of Generalization for Privacy Preserving Publication

Generalization is a well-known method for privacy reserving data publication. Despite its vast popularity, it has several drawbacks such as heavy information loss, difficulty of supporting marginal publication, and so on. To overcome these drawbacks, we develop ANGEL,1 a new anonymization technique that is as effective as generalization in privacy protection, but is able to retain significantly more information in the microdata. ANGEL is applicable to any monotonic principles (e.g., l-diversity, t-closeness, etc.), with its superiority (in correlation preservation) especially obvious when tight privacy control must be enforced. We show that ANGEL lends itself elegantly to the hard problem of marginal publication. In particular, unlike generalization that can release only restricted marginals, our technique can be easily used to publish any marginals with strong privacy guarantees.

Congestion-Aware Routing

SENSOR network deployments may include hundreds or thousands of nodes. Since deploying such large-scale networks has a high cost, it is increasingly likely that sensors will be shared by multiple applications and gather various types of data: temperature, the presence of lethal chemical gases, audio and/or video feeds, etc. Therefore, data generated in a sensor network may not all be equally important. With large deployment sizes, congestion becomes an important problem. Congestion may lead to indiscriminate dropping of data (i.e., high-priority (HP) packets may be dropped while low-priority (LP) packets are delivered). It also results in an increase in energy consumption to route packets that will be dropped downstream as links become saturated. As nodes along optimal routes are depleted of energy, only nonoptimal routes remain, further compounding the problem. To ensure that data with higher priority is received in the presence of congestion due to LP packets, differentiated service must be provided. In this work, we are interested in congestion that results from excessive competition for the wireless medium. Existing schemes detect congestion while considering all data to be equally important. We characterize congestion as the degradation of service to HP data due to competing LP traffic. In this case, congestion detection is reduced to identifying competition for medium access between HP and LP traffic. Congestion becomes worse when a particular area is generating data at a high rate. This may occur in deployments in which sensors in one area of interest are requested to gather and transmit data at a higher rate than others (similar to bursty converge cast [25]). In this case, routing dynamics can lead to congestion on specific paths. These paths are usually close to each other, which lead to an entire zone in the network facing congestion. We refer to this zone, essentially an extended hotspot, as the congestion zone (Conzone). In this paper, we examine data delivery issues in the presence of congestion. We propose the use of data prioritization and a differentiated routing protocol and/or a prioritized medium access scheme to mitigate its effects on HP traffic. We strive for a solution that accommodates both LP and HP traffic when the network is static or near static and enables fast recovery of LP traffic in networks with mobile HP data sources. Our solution uses a differentiated routing approach to effectively separate HP traffic from LP traffic in the sensor network. HP traffic has exclusive use of nodes along its shortest path to the sink, whereas LP traffic is routed over un-congested nodes in the network but may traverse longer paths. Our contributions in this work are listed as follows:

Design of Congestion-Aware Routing (CAR):
 CAR   is a network-layer solution to provide differentiated service in congested sensor networks. CAR also prevents severe degradation of service to LP data by utilizing un congested parts of the network.


Modules:
1 Network Formation
2 Conzone Discovery

3 Routing Data via Differentiated paths

predicting report

The primary task of association mining is to detect frequently co-occurring groups of items in transactional databases. The intention is to use this knowledge for prediction purposes: if bread, butter, and milk often appear in the same transactions, then the presence of butter and milk in a shopping cart suggests that the customer may also buy bread. More generally, knowing which items a shopping cart contains, we want to predict other items that the customer is likely to add before proceeding to the checkout counter. This paradigm can be exploited in diverse applications. For example, in the domain discussed in each “shopping cart” contained a set of hyperlinks pointing to a Web page in medical applications, the shopping cart may contain a patient’s symptoms, results of lab tests, and diagnoses; in a financial domain, the cart may contain companies held in the same portfolio; and Bollmann-Sdorra et al. proposed a framework that employs frequent itemsets in the field of information retrieval.

In all these databases, prediction of unknown items can play a very important role. For instance, a patient’s symptoms are rarely due to a single cause; two or more diseases usually conspire to make the person sick. Having identified one, the physician tends to focus on how to treat this single disorder, ignoring others that can meanwhile deteriorate the patient’s condition. Such unintentional neglect can be prevented by subjecting the patient to all possible lab tests. However, the number of tests one can undergo is limited by such practical factors as time, costs, and the patient’s discomfort.

Applications of Data Mining Techniques in Healthcare and Prediction of Heart Attacks

Information Technology offer health care industry significant potential to improve productivity and quality of patient care. The area of Data mining in health care is growing rapidly because of strong need for analyzing the vast amount of clinical data bases stored in hospitals. The huge amounts of data generated by healthcare transactions are too complex and voluminous to be processed and analyzed by traditional methods. Data mining provides the methodology and technology to transform these volumes of data into useful information for decision making. In this paper ,the potential use of classification based data mining techniques such as Decision tree, Naïve Bayes are applied to massive volume of healthcare data.Experimental results predicts the hearthattack results for efficient decision making purpose.

Association Rules Technique

Data mining involves the use of sophisticated data analysis tools to discover previously unknown, valid patterns and relationships in large data sets. These tools can include statistical models, mathematical algorithms, and machine learning methods (algorithms that improve their performance automatically through experience, such as neural networks, Association Rules or decision trees). Consequently, data mining consists of more than collecting and managing data, it also includes analysis and prediction. 
Association Rules is an approach that analyzes the characteristics between sets of data in order to find out those similar patterns or relationships that have been highly relied on in merchandising. By analyzing the patterns of the customers’ purchase behaviors, association rules are able to reveal the preferences of products, correlations between each purchase and further predict the consumers’ choices. For example, when one product is often purchased with another one, there is an association. This technique is frequently used by retail stores to assist in areas such as marketing, advertising, product promotion, and product placement.



Components of customer relationship management

Customer relationship management is a combination of several components. Before the process can begin, the firm must first possess customer information. Companies can learn about their customers through internal customer data or they can purchase data from outside sources. There are several sources of internal data:
_ summary tables that describe customers (e.g., billing records)
_ customer surveys of a subset of customers who answer detailed questions
_ behavioral data contained in transactions systems (web logs, credit card records,
etc).
An enterprise data warehouse is a critical component of a successful CRM strategy. Most firms have massive databases that contain marketing, HR, and financial information. However, the data required for CRM can be limited to a marketing data mart with limited feeds from other corporate systems.

CRM system must analyze the data using statistical tools, OLAP, and data mining. Whether the firm uses traditional statistical techniques or one of the data mining software tools, marketing professionals need to understand the customer data and business imperatives.
The term “customer lifecycle” refers to the stages in the relationship between a customer and a business. It is important to understand customer lifecycle because it relates directly to customer revenue and customer profitability. Marketers say there are three ways to increase a customer’s value: (1) increase their use (or purchases) of products they already have; (2) sell them more or higher-margin products; and (3) keep the customers for a longer period of time.


The customer lifecycle provides a good framework for applying data mining to CRM. On the “input” side of data mining, the customer lifecycle tells what information is available. On the “output” side, the customer lifecycle tells what is likely to be interesting

Telecommunications

Telecommunication companies around the world face escalating competition which is forcing them to aggressively market special pricing programs aimed at retaining existing customers and attracting new ones. Knowledge discovery in telecommunications include the following
Call detail record analysis—Telecommunication companies accumulate detailed call records. By identifying customer segments with similar use patterns, the companies can develop attractive pricing and feature promotions.
_ Customer loyalty—Some customers repeatedly switch providers, or “churn”, to take advantage of attractive incentives by competing companies. The companies can use data mining to identify the characteristics of customers who are likely to remain loyal once they switch, thus enabling the companies to target their spending on customers who will produce the most profit.
 Knowledge discovery applications are emerging in a variety of industries :
 _ Customer segmentation—All industries can take advantage of data mining to discover discrete segments in their customer bases by considering additional variables beyond traditional analysis.
_ Manufacturing—Through choice boards, manufacturers are beginning to customize products for customers; therefore they must be able to predict which features should be bundled to meet customer demand.
_ Warranties—Manufacturers need to predict the number of customers who will submit warranty claims and the average cost of those claims.
_ Frequent flier incentives—Airlines can identify groups of customers that can be given incentives to fly more.

Customer Relationship Management is defined by four elements of a simple framework:
 CRM requires the firm to know and understand its markets and customers. This involves detailed customer intelligence in order  to select the most profitable customers and identify those no longer worth targeting.

CRM also entails development of the offer: which products to sell to which customers and through which channel. In selling, firms use campaign management to increase the marketing department’s effectiveness. Finally, CRM seeks to retain its customers through services such as call centers and help desks.

CRM is essentially a two-stage concept. The task of the first stage is to master the basics of building customer focus. This means moving from a product orientation to a customer orientation and defining market strategy from outside-in and not from inside-out. The focus should be on customer needs rather than product features. Companies in the second stage are moving beyond the basics; they do not rest on their laurels but push their development of customer orientation by integrating CRM across the entire customer experience chain, by leveraging technology to achieve real-time customer management, and by constantly innovating their value proposition to customers


e-commerce

With the rapid expansion of e-commerce, more and more products are sold on the Web, and more and more people are also buying products online. In order to enhance customer satisfaction and shopping experience, it has become a common practice for online merchants to enable their customers to review or to express opinions on the products that they have purchased. With more and more common users becoming comfortable with the Web, an increasing number of people are writing reviews. As a result, the number of reviews that a product receives grows rapidly. Some popular products can get hundreds of reviews at some large merchant sites. Furthermore, many reviews are long and have only a few sentences containing opinions on the product. This makes it hard for a potential customer to read them to make an informed decision on whether to purchase the product. If he/she only reads a few reviews, he/she may get a biased view. The large number of reviews also makes it hard for product manufacturers to keep track of customer opinions of their products. For a product manufacturer, there are additional difficulties because many merchant sites may sell its products, and the manufacturer may (almost always) produce many kinds of products.


security

Existing work on security-enhanced data transmission includes the designs of cryptography algorithms and system infrastructures and security-enhanced routing methods. Their common objectives are often to defeat various threats over the Internet, including eavesdropping, spoofing, session hijacking, etc. Among many well-known designs for cryptography based systems, the IP Security (IPSec) and the Secure Socket Layer (SSL) are popularly supported and implemented in many systems and platforms. Although IPSec and SSL do greatly improve the security level for data transmission, they unavoidably introduce substantial overheads, especially on gateway/host performance and effective network bandwidth. For example, the data transmission overhead is 5 cycles/byte over an Intel Pentium II with the Linux IP stack alone, and the overhead increases to 58 cycles/byte when Advanced Encryption Standard (AES) is adopted for encryption/decryption for IPSec.

The Man...

A man always lives for himself,
yet claims to be the harbinger of a peaceful society
Off the shelf of comforts from the outside of the door of unseeing eyes,
Living in luxury with in the concealed thoughts !

Wearing a rope of trust across to hold the gown called Love
dipped in the sweat of toiled hearts !
Greedy eyes with false tears drawn at will from the
well of non-existent well of Pity...
Name the soul that has ever witnessed the truth behind those empty eyes !

Wake up from the sleep oh my soul !
My dear blood that holds the heart and mind together,
Find your true self, embrace the beauty of suffering...
Find the answers in the desolate desperation to Change !

The Betrayal...

There is a thin line that separates the Trust from Betrayal
As think as the speck of doubt in the core of a faithful heart
Stretching all over till the Yes and No are separated
The heart walking on the thin rope between the Yes and No
Where sanity of mind tries to unlock the closed Doors...
The key vanishing between the Question and An Answer !
Thin line yet thick in its very existence,
Eyes that see the Kite flying high in the Sky and the breaking Manja,
A think line that divides the Mind in to two different Worlds,
A void and Crowd seen together with the eyes that conceive a tear of joy and pain,
Thought that diverges somewhere down the lane
Where The Light transforms into Dark Loop and The Dark path shines as bright as the inferno !
Seeds of honesty sprouting in to Weeds segregating Unseen from the Seen...

Its the Door that the Old self chooses that makes all the difference,
From the past to present till future,
The thin line was, is and will be the necklace around the Man s neck,
Dancing close to heart till the being is divided between Life and Death !

I You Point A Race !!!

Pain is the mother carrying the artist in her womb
If spirits were to kill pain, there will be no artist born in to the world
and The world would be a desolate painting that the Artist unseen forgot to finish
The magic of writing is one doesn't have to worry about what people think
Because the ink and words are the writers blood and soul

Shred the words till the desire to do so speaks of its inability to reason with its thoughts
There is a magic in words that's a one time contract
enables us to connect what we see and what we feel,
What others couldn't see or feel!
The freedom from all that comes from Earth and said to be formed somewhere in the deep dark blues

Words that can turn a smile and a tear in to a song
A lullaby to put the baby with in to sleep till the dreams consume the eyes
Until they see the World the words reside in !
Solitude is a long cry with words around to make sail.

LDIAGRHKT, SSAIINNT, WWOORRLDDS, crazy yet if one can read between the lines,
The magic of words can be felt !

The Poet's Song...

Long gone is The Sun in to the deep clouds,
Never to show up in the shallow eyes...
To shine and spread joy across the Silver Line,
Distant home and lonely bird flying against the Winds
Winds flowing hand in hand with Words,
Neither the nest nor the wind seem to appear
A question spread across the oceans of heart
Or is it an entire nation of Questions conquering the little guild of Answers ?

Words that stumble as they walk,
Widowed trust which disagrees to marry the future !
Rock standing no  more still, trying to find a way to find the flow,
Never to know that flow of time is designed to make things fall along...
Hope standing in the back streets shouting at the Lost Sun,
To shine and show the broken path,
Will the wings ever get tired of Flying ?
What the shallow eyes feel but can't see is the truth...
Truth burning on the pyre along with honesty...
What can measure the depth of the dreams the spread under the world of Answers?
What answer can ever tell the truth... What light can ever shun the darkness...

All the breathe of the soul and The World smells the same as long as the love for  the soul is knotted with souls...
The same stinks when souls smell rotten.
The home the bird longs for is a temporary nest,
That evening when the Sun goes down will last forever...
Till the honesty is corrupted till it takes on the new face !
Rolling stone will eventually shatter the temple of dreams,
Depth of the sound of falling will defeat the Kingdom of questions!

Thats when hope will awake from it nightmare... To look at a new dream and a new face...
With new wings that care about nothing but tearing the winds to FLY !
The Sun will shine on the new World !

Cry of The Man...

When a man cries... he pours out all his pain, pain of separation from self or a dream
When he smiles with pain inside, it makes him strong...
But if the smile were never to wear off, it never means that he s forgotten the time
Might he just take a leap from the moments where the heart tends to grow weak,
To smile... to see the smiles alive !
Why doesn't he cry? Afraid or strong?
What hold him back from crying loud? Till all the pain vanishes...
A shoulder to lean on to... a trust that stands by the side when heart tends to choose the dark path...
Anger, hatred compressed by fate that holds back the heart from melting...
To act strong yet feeble inside...
How long can a person fool people around?
What is a man if He can't find a heart that can contain his Pain yet be able to cry and smile...
Whats the purpose of making magical bonds with the dreams if they were to wreck its casters trust...
What eyes will wet when the words in its form vanish?
A man is strong when he cries...
What if He cant? As good as a rotten soul !

The Prayer...

Light my path piercing the crouching dark
Find the lost path, defaced in the storms,
Conceive the marooned strength from the past
Relieve me from the misery of the lost battles
Strengthen the broken trust.

Let not the heart fall into temptation
But make it firm not to incline towards the dual facet
Open the doors for the Lost Pride
Let the fire inside the conscience burn bright till
The hatred of memories is consumed,
Glory of the temple within, let the glory return
Clear the questions conquering the maker of thoughts,
Let not the answers find their way to the tombs,
Let the Sound and Sane heart defeat the Silence
Till the Eyes see the truth.

Where the valorous mind can let the defeat flow with the rivers of time,
Until the reflection of the smile looks the same in the mirror with in,
Till the hidden self comes out in to the clearing
To play with the Light !!!
Till the Heart's feathers recover,
To Fly High Again... In to the open Blues...
Feel the free air... Honest and Transparent !!!

She Sings...

At the brink of the dreams she sings...
The song of defeat, composed by the Fallen King...
As the Sun crawls in to the Depths of His vision,
Sunk in to the other worlds to shine bright again
while the Fallen King squirms in the cozy dust embroidered with the Blood...
The song is echoed all over the Kingdom drunk by the defeat
While the foes celebrate the victory of Kings pain...
The pain that grows dark with the darkness of the world when the Light vanishes in to the depths
She sings the song of pain...
Till all the fallen soldiers are lost in the memories
Of the past and of the future unseen with eyes but by dreams
As the song echoes in the ears drenched in blood...
The life itself seems to be crying making the blood dilute...
Dilute till the Life vanishes in to thin air...
Cries of the fallen dominated by the cries of joy...
Fallen in blood while wine springs out in joy...

What does the Fallen King dream of before the final breathe of life finds its way...
To travel in to skies, never to return to the grave of its temporary container...
Does he dream of seeing the Sun again? To shine bright in his eyes
Till it obscures all the darkness...
till the life of the Soldiers to return from the corners of the Earths...
To see the Kingdom standing firm and tall into the Blues...
While the Wine overflowing meets the Blood on the other side...
 
Till the scarlet covers both the grounds...
Till the dream binds the Final Breathe with Hope...
She sings the song of Death while the Fallen sink in to the Depths...
As the song echoes over the souls, The Sun still shines on the other side not knowing
That the warmth has lost its meaning on the other side !!!