Available Balance
Beauty & Style – IS BEAUTY REALLY SKIN DEEP?

28. If you can wear them, consider switching to contact lenses. Make sure you remember to remove them when swimming. You can easily
lose them in the pool or worse, if you wear soft lenses you could contract a cornea infection that comes from a parasite found in water. The chlorine
won’t kill it and the result of this nasty little dude is not pleasant. You are inviting painful corneal infection that could cause partial or total blindness.

29. Try buying different colored lenses. You might discover a whole new you behind blue eyes!

30. Better yet, check out lasik. If you are a candidate it might give you a whole new lease on life. Of course, it’s a treatment for nearsightedness only, but if that’s your reason for wearing eyeglasses or contact lenses you might want to look into it. Just remember, even though the procedure is done with a laser, it is still a surgical procedure. Take your time and investigate to make certain that you visit a skilled surgeon who has completed many lasik procedures.

31. Take vitamin C, vitamin E and beta-carotene to improve your sight and overall health of your eyes.

32. Avoid caffeine. It negatively impacts the system that they eyes use for focusing. That includes coffee, tea and chocolate. Well, okay, if you can’t quit, at least cut back!

33. Do not over use eye drops. You may just make your eye sredder. Artificial tears are okay, but you should limit or avoid using vasoconstrictors. They will shrink the blood vessels on the surface of your eye. Check with your doctor if you need further explanation on the differences.

Did you know. . . that eye makeup worn by the ancient Egyptians served more than just a cosmetic purpose? It was worn by men and women alike.
It was decorative for certain but they also wore it for medicinal purposes as well as magical reasons. The Egyptian word for eye-palette is a derivative
from their word for “protect.” An eye that wore no makeup was considered to be “unprotected.” An unprotected eye was therefore at risk from the Evil
Eye. The next time you are standing in front of the mirror applying your eye makeup just remember that it is a rite of protection passed along from
Cleopatra to Betty Boop!

Rate This Content
Beauty & Style – IS BEAUTY REALLY SKIN DEEP?

20. Maybe you would prefer something a bit less abrasive, pardon the pun. If so, you might consider a deep peel. This process is
accomplished using an acid and are for moderately deep wrinkles. There are some risks associated with the acid procedure. It isn’t as stable as the
laser resurfacing because there is less control of the acid solution.

21. Have a glycolic or beta peel. This process won’t do much for your wrinkles, but if you are only looking to improve general skin tone, this is the one for you.

22. Try Retin A. If you want to see a smoothing of fine wrinkles and an overall healthy glow that will remove mottling and give your skin a youthful blush, then this is the route to go.

23. You can avoid all the nastiness of the previous treatments by choosing collagen injections. The biggest challenge with this choice is it’s temporary lasting just a few months so you have to repeat the procedure frequently.

24. Stop shaving your legs and use hot wax. Much gentler on your skin.

25. Mix up a tablespoon of brandy along with a smashed up peach and apply to your face for twenty minutes then rinse. Makes for a great summer facial hey don’t call them the “windows to the soul” for nothing! The eyes never lie. If you’re feeling and looking great your eyes will shine and sparkle. If you’re sad and lonely your eyes will give you away every time.

26. If you have red, watery eyes due to allergies, deal with them! There are plenty of medications available to eliminate allergy symptoms. Nothing will detract from your appearance faster than red eyes.

27. If you wear eyeglasses make certain that they do not detract from your appearance. Eyeglasses should complement your eyes,
not cover them. If your frames are unattractive it means you had the wrong sales person. Try again.

Rate This Content
Linked Lists – Traversing the list in reverse order, Doubly Linked List

Traversing a singly linked list in a forward manner (i.e. left to right) is simple as demonstrated in x2.1.4. However, what if we wanted to traverse the nodes in
the linked list in reverse order for some reason? The algorithm to perform such a traversal is very simple, and just like demonstrated in x2.1.3 we will need to
acquire a reference to the predecessor of a node, even though the fundamental characteristics of the nodes that make up a singly linked list make this an
expensive operation. For each node, ¯nding its predecessor is an O(n) operation, so over the course of traversing the whole list backwards the cost becomes O(n2). Figure 2.3 depicts the following algorithm being applied to a linked list with the integers 5, 10, 1, and 40.

1) algorithm ReverseTraversal(head, tail)
2) Pre: head and tail belong to the same list
3) Post: the items in the list have been traversed in reverse order
4) if tail 6= ; 5) curr à tail
6) while curr 6= head
7) prev à head
8) while prev.Next 6= curr
9) prev à prev.Next
10) end while
11) yield curr.Value
12) curr à prev
13) end while
14) yield curr.Value
15) end if
16) end ReverseTraversal

This algorithm is only of real interest when we are using singly linked lists, as you will soon see that doubly linked lists (de¯ned in x2.2) make reverse list traversal simple and e±cient, as shown in x2.2.3.

Doubly Linked List

Doubly linked lists are very similar to singly linked lists. The only di®erence is that each node has a reference to both the next and previous nodes in the list.

The following algorithms for the doubly linked list are exactly the same as
those listed previously for the singly linked list:
1. Searching (de¯ned in x2.1.2)
2. Traversal (de¯ned in x2.1.4)

Insertion

The only major di®erence between the algorithm in x2.1.1 is that we need to
remember to bind the previous pointer of n to the previous tail node if n was
not the ¯rst node to be inserted into the list.
1) algorithm Add(value)
2) Pre: value is the value to add to the list
3) Post: value has been placed at the tail of the list
4) n à node(value)
5) if head = ; 6) head à n
7) tail à n
8) else
9) n.Previous à tail
10) tail.Next à n
11) tail à n
12) end if
13) end Add
Figure 2.5 shows the doubly linked list after adding the sequence of integers
de¯ned in x2.1.1.

Rate This Content
Linked Lists – Deletion, Traversing the list

Deleting a node from a linked list is straightforward but there are a few cases
we need to account for:
1. the list is empty; or
2. the node to remove is the only node in the linked list; or
3. we are removing the head node; or
4. we are removing the tail node; or
5. the node to remove is somewhere in between the head and tail; or
6. the item to remove doesn’t exist in the linked list

The algorithm whose cases we have described will remove a node from any-where within a list irrespective of whether the node is the head etc. If you know
that items will only ever be removed from the head or tail of the list then you can create much more concise algorithms. In the case of always removing from
the front of the linked list deletion becomes an O(1) operation.

1) algorithm Remove(head, value)
2) Pre: head is the head node in the list
3) value is the value to remove from the list
4) Post: value is removed from the list, true; otherwise false
5) if head = ; 6) // case 1
7) return false
8) end if
9) n à head
10) if n.Value = value
11) if head = tail
12) // case 2
13) head à ; 14) tail à ; 15) else
16) // case 3
17) head à head.Next
18) end if
19) return true
20) end if
21) while n.Next 6= ; and n.Next.Value 6= value
22) n à n.Next
23) end while
24) if n.Next 6= ; 25) if n.Next = tail
26) // case 4
27) tail à n
28) end if
29) // this is only case 5 if the conditional on line 25 was false
30) n.Next à n.Next.Next
31) return true
32) end if
33) // case 6
34) return false
35) end Remove

 

Traversing the list

Traversing a singly linked list is the same as that of traversing a doubly linked
list (de¯ned in x2.2). You start at the head of the list and continue until you
come across a node that is ;. The two cases are as follows:
1. node = ;, we have exhausted all nodes in the linked list; or
2. we must update the node reference to be node.Next.
The algorithm described is a very simple one that makes use of a simple
while loop to check the ¯rst case.

1) algorithm Traverse(head)
2) Pre: head is the head node in the list
3) Post: the items in the list have been traversed
4) n à head
5) while n 6= 0
6) yield n.Value
7) n à n.Next
8) end while
9) end Traverse

Rate This Content
Linked Lists – Insertion , Searching and more

In general when people talk about insertion with respect to linked lists of any form they implicitly refer to the adding of a node to the tail of the list. When
you use an API like that of DSA and you see a general purpose method that adds a node to the list, you can assume that you are adding the node to the tail
of the list not the head.

Adding a node to a singly linked list has only two cases:
1. head = ; in which case the node we are adding is now both the head and
tail of the list; or
2. we simply need to append our node onto the end of the list updating the
tail reference appropriately.

1) algorithm Add(value)
2) Pre: value is the value to add to the list
3) Post: value has been placed at the tail of the list
4) n à node(value)
5) if head = ; 6) head à n
7) tail à n
8) else
9) tail.Next à n
10) tail à n
11) end if
12) end Add
As an example of the previous algorithm consider adding the following se-
quence of integers to the list: 1, 45, 60, and 12, the resulting list is that of

Figure 2.2.

 

Searching

Searching a linked list is straightforward: we simply traverse the list checking
the value we are looking for with the value of each node in the linked list. The
algorithm listed in this section is very similar to that used for traversal in x2.1.4.

1) algorithm Contains(head, value)
2) Pre: head is the head node in the list
3) value is the value to search for
4) Post: the item is either in the linked list, true; otherwise false
5) n à head
6) while n 6= ; and n.Value 6= value
7) n à n.Next
8) end while
9) if n = ; 10) return false
11) end if
12) return true
13) end Contains

guys for study about physics so let’s join my post and support

physics – http://literacybase.com/physics-study-electric-charges-and-fields/

If you want to for more accounting for begging

so let’s join our accounting post – Introduction to Accounting – Definition, Meaning

Rate This Content
The Good and Bad of Social Networking. Be careful…
November 12, 2017
0

Social Networking

The Good and Bad of Social Networking

A piece highlighting the good and bad things about using social networking websites. Includes helpful tips on how to stay safe when online.

The good

Social networking sites have madecommunication much easier. Friends’ and family now have a quicker, cheaper way of keeping in touch, making important relationships easier to maintain.
Not only does a social networking site help you keep in touch with friends you already have, but they also help you form new relationships. People can find others who share the same interests or hobbies and form friendships with them. These sites help bring together people from all different cultures and races: breaking down boundaries that may otherwise exist in everyday life. People are able to make friends with people they would never have even met without using a networking site.

The bad

Even those who see life from the rosiest of spectacles have to admit there are drawbacks to using social networking websites. People can use these sites to prey on the naive and vunerable. This can be done in a number of ways including grooming and identity fraud.

Just think about all of the sensitive information that people post on these websites. Details commonly found include: dates of birth, addressees, marital statuses, and jobs. All of this can be used against you by a fraudster.

It is also easier for people to harass, stalk and bully you through these sites.

Not only this but people aren’t always who they say they are. This could mean someone befriending you only to gain as much personal and sensitive information as they can. This too can be used against you.

Although it is true that legitimate businesses uses sites such as MySpace and facebook, it is also true that people could invent fake businesses or products and advertise them on social networking sites, in a bid to take your money.

Keeping safe

There are very real dangers surrounding social networking and so when using these sites people should take precautions. Below are some of the things people are advised to do when using social networking:

Restrict access to your profile or page to people that you know face to face, such as family and friends.

Don’t use a username that reveals anything about you. Stay clear from using your real name or age.

Keep personal information to yourself. Don’t post things such as: addresses, dates of birth, phone numbers, credit and debit card numbers or the name of your school or work.Remember that not everyone is trustworthy. Keep in mind that people lie.Avoid meeting people you have only met online.

Trust your own instincts if you are suspicious or feel uncomfortable when talking to someone.

What’s There For Girls On Social Networking Websites
Social networking websites have become major parts of our lives and I belong to that thought of mind set that believes that these websites are beneficial for everyone if used with the right spirit. For boy’s privacy on these websites in not an issue but for girls it can mean a lot of difference. Therefore on one side after encouraging the fact that people especially girls should use the website I declare that they should use it by taking the necessary important steps.

First of all if possible don’t put up your own picture over any social networking website. It’s one of first and the foremost precautions that need to be taken care of. This is very important because from your pictures can stem problems that you can never imagine of. If you still really want to put up picture than be sure that it’s accessible to only your friends and not everyone over the networking website. Next is the issue of which people to add and which people not to add. The issue has a very simple solution and that solution is that add only those people on the internet that you know in person. Add boys who are you colleges or class fellows but put them in proper privacy.

The bottom line however is that the social networking websites have become the part and parcel of life and it’s a good thing that one uses this facility but only when proper precautionary measures have been taken.

Final judgment

Although the dangers with using social networking sites are very serious, in my opinion they are good for our society as long as the correct precautions are taken. However, when it comes down to whether social networking is right for you that is something only you can decide, using your own judgment and past experiences. Before becoming a member of a social networking website do your homework on what they have to offer but also find out about the risks involved.

______________________________________________________________________

Stop Thinking Sales. Start Thinking Relationships

The sale is neither here nor there until the relationship is established.

The problem when you’re faking that relationship – like, after you make the sale – is that the friendly emails suddenly stop. When the relationship is fake, the client detects that. In fact, we all do.

But if the relationship is real, you will do the best for your client. When that happens, you’ll begin to see all those negative responses vanish. Why? You just became a friend, and friends look out for one another. A short-term sales person or marketer sees only the number they’ve been given to hit.

People are suspicious of marketing. If they see that you are actively trying to sell them something they will resist your offers. Direct marketing strategies are also useless in this new trust economy and institutional info has become the symbol of fake, untrustable company communication.

Customers want friendly, sincere, credible and unpartial suggestions, passionate recommendations by someone who cares about their needs and not only about extracting money from them.

Start building a following of passionate, true fans and followers who love your advice, suggestions and ideas. Let them be your best marketing agents. Help them realize their dreams and they will in turn do the best word-of-mouth marketing job you could ever buy, for free.

Privacy Protection Issue on Social Networking Sites

Social networking sites (SNS) are built for all, old, youngsters and kids equally enjoy these social networking sites. During the past few years, these SNS have earned great popularity among people of all ages and regions. Major reason behind this popularity is that these sites provide individuals a plat form to express their own interests and find out people of the similar interests and individuality. Though this is a great way to make a chain among individuals of different backgrounds and welfares to meet, make discussions, share unique ideas and conclude useful information from across the world.

Where these social networking sites are broadcasting the modern lives of people at large, there are also some threats attached with these networks. Privacy issue arises when you are not willing all your contacts to see particular peace of your live data, like profile information, threads, display images or links of your account. Some features provided by these sites are totally out of user control and go by default. At the same time, some people are still unconscious of the identity theft and threats, and are unaware of the way to make privacy setting of their SNS accounts. Though many of people may be using fake identities, but the risks exist when they publish a sensitive kind of links or videos, or it becomes sensitive with the comments made on it. Such situations can be more dangerous for kids using SNS who are not fully conscious of the gravity of the wide reach of their data online. A little comment made on a post can turn a serious issue into a joke and even a joke video can lead to the life threats to a user. This is the biggest disadvantage of SNS that users are unable to control others viewing and making comments on their live data.

A report says that many people, especially parents, are getting more conscious about their privacy on these social networks for little kids. Generally kids may not be completely aware of the sensitivity of a topic where they make comment or post new data about. Sometimes, they broadcast too much account information data online that may lead to vulnerability of their privacy. Definitely there is a need of an appropriate framework to identify and cope with these privacy issues to make social networking more secure and safe

Rate This Content
Linked Lists – Data Structures and Algorithms

Linked lists can be thought of from a high level perspective as being a series of nodes. Each node has at least a single pointer to the next node, and in the last node’s case a null pointer representing that there are no more nodes in the

linked list.

In DSA our implementations of linked lists always maintain head and tail pointers so that insertion at either the head or tail of the list is a constant time operation. Random insertion is excluded from this and will be a linear operation. As such, linked lists in DSA have the following characteristics:

Insertion is O(1)
2. Deletion is O(n)
3. Searching is O(n)

Out of the three operations the one that stands out is that of insertion. In DSA we chose to always maintain pointers (or more aptly references) to the node(s) at the head and tail of the linked list and so performing a traditional insertion to either the front or back of the linked list is an O(1) operation. An exception to this rule is performing an insertion before a node that is neither the head nor tail in a singly linked list. When the node we are inserting before is somewhere in the middle of the linked list (known as random insertion) the complexity is O(n). In order to add before the designated node we need to traverse the linked list to ¯nd that node’s current predecessor. This traversal yields an O(n) run time.

This data structure is trivial, but linked lists have a few key points which at times make them very attractive:
1. the list is dynamically resized, thus it incurs no copy penalty like an array or vector would eventually incur; and
2. insertion is O(1).

Singly Linked List

Singly linked lists are one of the most primitive data structures you will ¯nd in this book. Each node that makes up a singly linked list consists of a value, and a reference to the next node (if any) in the list.

Rate This Content
Linked Lists – Data Structures and Algorithms

Linked lists can be thought of from a high level perspective as being a series
of nodes. Each node has at least a single pointer to the next node, and in the
last node’s case a null pointer representing that there are no more nodes in the
linked list.
In DSA our implementations of linked lists always maintain head and tail
pointers so that insertion at either the head or tail of the list is a constant
time operation. Random insertion is excluded from this and will be a linear
operation. As such, linked lists in DSA have the following characteristics:

Insertion is O(1)
2. Deletion is O(n)
3. Searching is O(n)

Out of the three operations the one that stands out is that of insertion. In
DSA we chose to always maintain pointers (or more aptly references) to the
node(s) at the head and tail of the linked list and so performing a traditional
insertion to either the front or back of the linked list is an O(1) operation. An
exception to this rule is performing an insertion before a node that is neither
the head nor tail in a singly linked list. When the node we are inserting before
is somewhere in the middle of the linked list (known as random insertion) the
complexity is O(n). In order to add before the designated node we need to
traverse the linked list to ¯nd that node’s current predecessor. This traversal
yields an O(n) run time.

This data structure is trivial, but linked lists have a few key points which at
times make them very attractive:
1. the list is dynamically resized, thus it incurs no copy penalty like an array
or vector would eventually incur; and
2. insertion is O(1).

In the next study w Singly Linked List

so let’s chek out my post freinds we will explain with diagram for DSA

 

for motivational visit my post
Thinking, Fast and Slow – The Best selling book published in 2011

Thinking, Fast and Slow – The Best selling book published in 2011

Top 10 Quotes for Thinking, Fast & Slow – I promises Never Forget

Top 10 Quotes for Thinking, Fast & Slow – I promises Never Forget

Rate This Content
Introduction of Data Structures and Algorithms

Testing

All the data structures and algorithms have been tested using a minimised test
driven development style on paper to °esh out the pseudocode algorithm. We
then transcribe these tests into unit tests satisfying them one by one. When
all the test cases have been progressively satis¯ed we consider that algorithm
suitably tested.
For the most part algorithms have fairly obvious cases which need to be
satis¯ed. Some however have many areas which can prove to be more complex
to satisfy. With such algorithms we will point out the test cases which are tricky
and the corresponding portions of pseudocode within the algorithm that satisfy
that respective case.
As you become more familiar with the actual problem you will be able to
intuitively identify areas which may cause problems for your algorithms imple-
mentation. This in some cases will yield an overwhelming list of concerns which
will hinder your ability to design an algorithm greatly. When you are bom-
barded with such a vast amount of concerns look at the overall problem again
and sub-divide the problem into smaller problems. Solving the smaller problems
and then composing them is a far easier task than clouding your mind with too
many little details.
The only type of testing that we use in the implementation of all that is
provided in this book are unit tests. Because unit tests contribute such a core
piece of creating somewhat more stable software we invite the reader to view
Appendix D which describes testing in more depth.

In This topic we study about some New topic for DSA

1st we study Data Structures and Algorithms – Big Oh notation

For run time complexity analysis we use big Oh notation extensively so it is vital that you are familiar with the general concepts to determine which is the best algorithm for you in certain scenarios. We have chosen to use big Oh notation for a few reasons, the most important of which is that it provides an abstract measurement by which we can judge the performance of algorithms without using mathematical proofs.

2nd we study Data Structures and Algorithms – Imperative programming language

In The last lecture we study about – Big Oh notation
Figure 1.1 shows some of the run times to demonstrate how important it is to choose an efficient algorithm. For the sanity of our graph we have omitted cubic O(n 3 ), and exponential O(2n) run times. Cubic and exponential algorithms should only ever be used for very small problems (if ever!); avoid them if feasibly possible.
The following list explains some of the most common big Oh notations:
O(1) constant: the operation doesn’t depend on the size of its input, e.g. adding a node to the tail of a linked list where we always maintain a pointer to the tail node.
O(n) linear: the run time complexity is proportionate to the size of n.

 

3rd we study about Introduction of Data Structures and Algorithms – Object oriented concepts, Pseudo code

Object oriented concepts
For the most part this book does not use features that are speci¯c to any one
language. In particular, we never provide data structures or algorithms that
work on generic types|this is in order to make the samples as easy to follow
as possible. However, to appreciate the designs of our data structures you will
need to be familiar with the following object oriented (OO) concepts

And we will study in the next topic for DSA
Linked Lists

Rate This Content
Introduction of Data Structures and Algorithms – Object oriented concepts, Pseudo code

Object oriented concepts

For the most part this book does not use features that are speci¯c to any one
language. In particular, we never provide data structures or algorithms that
work on generic types|this is in order to make the samples as easy to follow
as possible. However, to appreciate the designs of our data structures you will
need to be familiar with the following object oriented (OO) concepts:

1. Inheritance
2. Encapsulation
3. Polymorphism

This is especially important if you are planning on looking at the C# target
that we have implemented (more on that in x1.7) which makes extensive use
of the OO concepts listed above. As a ¯nal note it is also desirable that the
reader is familiar with interfaces as the C# target uses interfaces throughout
the sorting algorithms.

Pseudocode

Throughout this book we use pseudocode to describe our solutions. For the
most part interpreting the pseudocode is trivial as it looks very much like a
more abstract C++, or C#, but there are a few things to point out:

1. Pre-conditions should always be enforced
2. Post-conditions represent the result of applying algorithm a to data struc-
ture d
3. The type of parameters is inferred
4. All primitive language constructs are explicitly begun and ended

If an algorithm has a return type it will often be presented in the post-
condition, but where the return type is su±ciently obvious it may be omitted
for the sake of brevity.
Most algorithms in this book require parameters, and because we assign no
explicit type to those parameters the type is inferred from the contexts in which
it is used, and the operations performed upon it. Additionally, the name of
the parameter usually acts as the biggest clue to its type. For instance n is a
pseudo-name for a number and so you can assume unless otherwise stated that
n translates to an integer that has the same number of bits as a WORD on a
32 bit machine, similarly l is a pseudo-name for a list where a list is a resizeable
array (e.g. a vector).
The last major point of reference is that we always explicitly end a language
construct. For instance if we wish to close the scope of a for loop we will
explicitly state end for rather than leaving the interpretation of when scopes
are closed to the reader. While implicit scope closure works well in simple code,
in complex cases it can lead to ambiguity.
The pseudocode style that we use within this book is rather straightforward.
All algorithms start with a simple algorithm signature, e.g.

1) algorithm AlgorithmName(arg1, arg2, …, argN)
2) …
n) end AlgorithmName
Immediately after the algorithm signature we list any Pre or Post condi-
tions.
1) algorithm AlgorithmName(n)
2) Pre: n is the value to compute the factorial of
3) n ¸ 0
4) Post: the factorial of n has been computed
5) // …
n) end AlgorithmName

The example above describes an algorithm by the name of AlgorithmName,
which takes a single numeric parameter n. The pre and post conditions follow
the algorithm signature; you should always enforce the pre-conditions of an
algorithm when porting them to your language of choice.
Normally what is listed as a pre-conidition is critical to the algorithms opera-
tion. This may cover things like the actual parameter not being null, or that the
collection passed in must contain at least n items. The post-condition mainly
describes the e®ect of the algorithms operation. An example of a post-condition
might be \The list has been sorted in ascending order”
Because everything we describe is language independent you will need to
make your own mind up on how to best handle pre-conditions. For example,
in the C# target we have implemented, we consider non-conformance to pre-
conditions to be exceptional cases. We provide a message in the exception to
tell the caller why the algorithm has failed to execute normally.

Rate This Content