E-mail security (CSE Department @ LAQSHYA)

E-mail security

Most people don’t have CBI/IB sniffing through their personal emails, but people grossly underestimate how transparent their digital communications have become.

Anyone can read your emails because its so easy to do. What people realize is that hacking and spying went main stream a decade ago.

To secure your email

1.      Hide your location

v  You can mask your IP address using TOR (TOOL).

v  You can also use a virtual private network which adds a layer of security to public Wi-Fi networks.

v  Email providers like Google and yahoo keep login records, which reveal IP addresses, for 18 months during which they can easily be asked for data legally.

v  A letter on the letterhead of DCP/SP of the police to network service providers can reveal lot of individual data.

2.      Go off the record

v  At bare minimum, choose, “off the record” feature on Google talk, Google instant messaging client, which ensures that nothing  typed is saved or searchable in either person’s Gmail account.

3.      Encrypt your messages

v  Email encryption services like GPG, help protect digital secrets from eavesdroppers without an encryption key, any message stored in an inbox, or reached from cloud, with look like gibberish.

v  Wickr, a mobile app, performs a similar service for smart phones.

4.      Set your self-destruct timer

v  Services like 10 minute mail allows users to open an Email addresses and send a message, and the address self-destructs 10 minutes later.

v  Wickr also allows users to set a self destruct timer for mobile communications.

5.      Don’t mess-up

v  It is hard to pull of one of these steps let alone all of them all the time. It takes just one mistake forgetting to use TOR, leaving your encryption keys. Where someone can find them, connecting to an airport  Wi-Fi just once to ruin you.

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CSE Departement

LAQSHYA Institute of Technology & Sciences             

Binary Search Trees (IT Department @ LAQSHYA)

Binary Search Trees

• Lets look at trees that are (1) binary and (2) ordered.
• We will use these trees to store some values (in a computer's memory, I assume).
• Each vertex will contain one of whatever data we're storing.
• I'm assuming we're organizing our data by one value: its key.
• The keys must be totally-ordered.
• Let's assume all the keys are distinct for simplicity.
• The key might be something like a student number or name: the thing we want to search by.
• That is, it will look like this:

typedef struct bst_node {     struct bst_node *leftchild;     struct bst_node *rightchild;     char *key;     char *otherdata; } bst_node;

• We'll make a few rules about how we arrange the values in the tree:
• The keys in the left subtree must be less than the key of the root.
• The keys in the right subtree must be greater than the key of the root.
• Those must also be true for each subtree.
• A tree like this is called a binary search tree or BST.
• For example, this is a binary search tree containing some words (ordered by dictionary ordering):
• This is another BST containing the same values:
• We haven't made any assertions about the BST being balanced or full.
• It is fairly straightforward to insert a new value into a BST and maintain the rules of the tree.
• The idea: look at the keys to decide if we go to the left or right.
• If the child spot is free, put it there.
• If not, recurse down the tree.

procedure bst_insert(bst_root, newnode)

if newnode.key < bst_root.key  // insert on the left

if bst_root.leftchild = null

bst_root.leftchild = newnode

else

 bst_insert(bst_root.leftchild, newnode)

else  // insert on the right

if bst_root.rightchild = null

bst_root.leftchild = newnode

else

bst_insert(bst_root.rightchild, newnode)       

• For example, if we start with the first BST above:
• … and insert “eggplant”, then we call the function with the root of the tree and…
• “eggplant” > “date”, and the right child is non-null. Recurse on the right child, “grape”.
• “eggplant” < “grape”, and the left child is non-null. Recurse on the left child, “fig”.
• “eggplant” < “fig”, but the right child is null. Insert the new node as the right child.
• After that, we get this:
• Still a BST.
• Still balanced, but that's not always going to be true.
• If we now insert “elderberry”, it will be unbalanced
• The running time of the insertion?
• We do constant work and recurse (at most) once per level of the tree.
• Running time is \(O(h)\).
• So, it would be nice to keep \(h\) under control.
• We know that if we have a binary tree with \(n\) vertices that is full and balanced, it has height of \(\Theta(\log_2 n)\).
• But that insertion algorithm doesn't get us balanced trees.
• For example, if we start with an empty tree and insert the values in-order, we build the trees like this:
• Those are as unbalanced as they can be: \(h=n\).
• So, further insertions take a long time.
• Any other algorithms that traverse the height of the tree will be slow too.
• One solution that will probably work: insert the values in a random order.
• For example, I randomly permuted the words and got: date, fig, apple, grape, banana, eggplant, cherry, honeydew.
• Inserting in that order gives us this tree:
• \(h=3\) is pretty good.
• Of course, we could have been unlucky and got a large \(h\).
• But for large \(n\), the probability of getting a really-unbalanced tree is quite small.
• Once we have a BST, we can search for values in the collection easily:

   procedure bst_search(bst_root, key)

 if bst_root = null  // it's not there

   return null

 else if key = bst_root.key  // found it

 return bst_root

   else if key < bst_root.key  // look on the left

   return bst_search(bst_root.leftchild, key)

 else  // look on the right

return bst_search(bst_root.rightchild, key)

• Like insertion, running time is \(O(h)\) for the search.
• It's looking even more important that we keep \(h\) as close to \(\log_2 n\) as we can.
• Another solution to imbalanced trees: be more clever in the insertion and re-balance the tree if it gets too out-of-balance.
• But that's tricky.
• If we have a badly-balanced BST, we can do something to re-balance.
• We can “pivot” around an edge to make one side higher/shorter than it was:
• There, \(A,B,C\) represent subtrees.
• Both before and after, the tree represents values with \(A<1<B<2<C\).
• So, if it was a BST before, it will be after.
• If \(A\) was too short or \(C\) too tall on the left, they will be better on the right.
• The problem is that we might have to do a lot of these to get the BST back in-balance.
• … making insertion slow because of the maintenance work.
• How to overcome that is a problem for another course.
• But if we do keep our tree mostly-balanced (\(h=O(\log n)\)) then we can search in \(\log n\) time.
• As long as we don't take too long to insert, it starts to sound better than a sorted list.
• In a sorted list, we can search in \(O(\log n)\) (binary search) but insertion takes \(O(n)\) since we have to make space in the array.
• Remember the problem you're trying to solve with data structures like this: we want to store some values so that we can quickly…

1.      insert a new value into the collection;

2.      look up a value by its key (and get the other data in the structure);

3.      delete values from the collection.

                        A sorted list is fast at 2, but slow at 1 and 3.

                        The BST is usually fast at all three, but slow at all three if the tree is unbalanced.

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IT Departement

LAQSHYA Institute of Technology & Sciences             

Slicers and its Working (ECE Department @ LAQSHYA)

Slicers

Clipping circuits are also referred to as voltage (or current) limiters, amplitude Selectors or slicers. They are used to select for transmission that part of an arbitrary waveform which lies above or below some particular reference voltage level.

A clipping circuit comprises of linear elements like resistors and non-linear elements like junction diodes or transistors, but it does not contain energy storage elements like capacitors.

A clipper circuit can remove certain portion of an arbitrary wave form near the positive or negative peaks. Clipping may be achieved either at one level or at two levels.

fig : Clippers Classification

In shunt clippers, the diode is connected in series with reference voltage across the output terminals. In series clippers, the diode forms a series path connecting the input and output terminals.

·         The analysis of any clipper circuit has the following three stages.

    (i) Study of working of the diode.

    (ii) Formulation of the transfer characteristic equations and

    (iii) Plotting of the transfer characteristic curves

Now we discuss about the principle and working of CLIPPING ABOVE THE REFERENCE LEVEL circuit. The shunt clipper (CLIPPING ABOVE THE REFERENCE LEVEL) circuit diagram is as shown below.

Working :  It is seen that, for V_i<V_R+V_γ, the diode D is OFF  because it is reverse biased and hence  it does not conduct therefore no current flows, hence there is no voltage drop across R.

                                            V_O=V_i         for         V_i< V_R+V_γ.

 For V_i>V_R+V_γ, the diode D is ON because it is forward biased and the potential barrier is overcome hence it conducts, therefore the output voltage is equal to the reference voltage

                                                                V_O=V_R                              for           V_i> V_R+V_γ.

From the above discussion we can conclude that the transfer characteristic equations are

                                                                V_o =V_i           for   V_i<V_R+V_γ and,

                                                                V_o =V_R+V_γ    for    V_i>V_R+V_γ,

 Transfer Characteristic Curve: It is graph between input and output voltages. When Vo =V_i=> Vo/V_i= 1 i.e. slope=1 and When Vo=V_R+V_γ i.e. Vo is constant since both V_R and V_γ are of fixed magnitude hence Slope=0                     When D is OFF, V_O=V_i, there is no clipping action and the input signal is transmitted without any alteration of the wave shape.

    However, when D is ON, it is seen that Vo is constant whatever the instantaneous magnitude of Vi. Hence there is clipping action. The portion of the input signal greater than (V_R+V_γ) is not transmitted. This is clearly shown in the following fig.

Fig: Transfer Characteristic curve for clipping above the reference level.

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Article By

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Mr.A.Ravi Shankar                        

Assistant Professor

ECE Departement

LAQSHYA Institute of Technology & Sciences              

Power Factor (EEE Department @ LAQSHYA)

Definition:-         

Power factor is the ratio between the KW and the KVA drawn by an electrical load where the KW is the actual load power and the KVA is the apparent load power.

Simply, it is a measure of how efficiently the load current is being converted into useful work output and more particularly is a good indicator of the effect of the load current on the efficiency of the supply system.

Consider this:

When you buy fuel for a vehicle, the manufacturer makes in it in litres, the pump dispenses it in litres and you pay for it in litres. Rs/litre – simple!

When you buy potatoes, the supplier bags them in kilos the shop sells them in kilos and you pay for them in kilos. Rs/kg – simple!

When you buy electricity, the “manufacturer” (electricity generator) makes KVA (kilo volt amperes) and you pay for it in KWh (kilowatt hours) or maybe on your bill (Units) – not so simple! Maybe we all should have KVA meters to make life simple. So what is the kilowatt hour (or unit) we get on our bills? Simply, 1000 watts of electricity being used for 1 hour.

Example: 10 x 100 watt lamps x 1 hour=1000 watts/hr divided by 1000=1kWh – simple!

Now here comes the problem: In an alternating current (AC) electrical supply, a mysterious thing called “Power Factor” comes into play. Power Factor is simply the measure of the efficiency of the power being used, so, a power factor of 1 would mean 100% of the supply is being used efficiently. A power factor of 0.5 means the use of the power is very inefficient or wasteful.

 What causes Power Factor to change?

In the real world of industry and commerce, a power factor of 1 is not obtainable because equipment such as electric motors, welding sets, fluorescent and high bay lighting creates what is called an “inductive load” which in turn causes the amps in the supply to lag the volts. The resulting lag is called Power Factor.

For a 3 phase power supply: KVA, which the electricity generator makes=Line Volts x Amps x 1.73÷ 1000. This is converted to kilowatts KW by the formula: Line Volts x Amps x 1.73 ÷ 1000 x Power Factor=KW (V x A x 1.73÷ 1000 x pf) or KVA x pf=KW (N.B. 1.73 is the square root of 3) so as the power factor worsens from say 0.98 to 0.5, the generator has to supply more KVA for each kW you are using.

For example, a large electric motor will typically have a Power Factor of about 0.85 at full load. If we have a hypothetical electric motor rated at 100kW, then ignoring the inherent inefficiency of the motor, when running at full load the electricity supplier would have to supply 100÷0.85=118KVA to provide the 100KW to run the motor.

Or put the other way they would be supplying 18% more electricity than they are charging you for. If the same motor was operating “off load” at say 50kW or being used on a cyclic duty then the power factor may go as low as 0.5. In this case the supplier would have to supply “double” the KVA to match the 50kW duty point. (50÷0.5=100kVA)

How this power is wasted can be shown graphically since in 3 phase power supplies "power" can be represented and measured as a triangle. ACTIVE Power is the base line and is the “real” usable power measured and paid for in KW. REACTIVE power is the vertical or that part of the supply which causes the inductive load. The reactive power in is measured in KVAR (kilo volt-amperes reactive). APPARENT Power is the hypotenuse. This is the component the electricity generator must supply and it is the resultant of the other two components, measured in KVA. Mathematically the power can be calculated by Pythagoras or trigonometry whereby Power Factor is expressed as COS Ø (The angle between Apparent Power and Active power)

But we want a simple explanation so consider a barge being pulled by a horse:

Since the horse cannot walk on water its pulling effort is reduced by the “angle” of the two ropes. If the horse could walk on water then the angle Ø would be zero and COS Ø=1. Meaning all the horse power is being used to pull the load.

However the relative position of the horse influences the power. As the horse gets closer to the barge, angle Ø₁ increases and power is wasted, but, as the horse is positioned further away, then angle Ø₂ gets closer to zero and less power is wasted

So, by improving Power Factor (reducing the angle), the reactive power component is reduced, what does it do to my electricity bill?

As stated above in a 3 phase power supply, KW consumed is 3 phase VOLTS x AMPS x 1.73 x Power Factor. The Electricity Company supply you VOLTS x AMPS and they have to supply extra to make up for the loss caused by poor Power Factor. When the power factor falls below a set figure, the electricity supply companies charge a premium on the KW being consumed, or, charge for the whole supply as KVA by adding reactive power charges (KVAR) to the bill.

How does Power Factor Correction work?

By installing suitably sized switched capacitors into the power distribution circuit, the Power Factor is improved and the value becomes nearer to 1 thus minimizing wasted energy, improving the efficiency of a plant, liberating more KW from the available supply and saving you money! The purchase cost of the installation is usually repaid in less than 1 year’s electricity savings.

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Article By

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Mr.D.Narasimha Rao,                        

M.Tech , Assistant Professor

EEE Departement

LAQSHYA Institute of Technology & Sciences              

LAQSHYA Group of Colleges 

Bloom Energy (EEE Department @ LAQSHYA)

Bloom Energy

What is an Energy Server?

Built with our patented solid oxide fuel cell technology, Bloom's Energy Server™ is a new

class of distributed power generator, producing clean, reliable, affordable electricity at the

customer site. Fuel cells are devices that convert fuel into electricity through a clean

electro-chemical process rather than dirty combustion. They are like batteries except that

they always run. Our particular type of fuel cell technology is different than legacy

"hydrogen" fuel cells in three main ways:

1. Low cost materials – our cells use a common sand-like powder instead of precious

metals like platinum or corrosive materials like acids.

2. High electrical efficiency – we can convert fuel into electricity at nearly twice the

rate of some legacy technologies

3. Fuel flexibility – our systems are capable of using either renewable or fossil fuels

Each Bloom Energy Server provides 200kW of power, enough to meet the baseload needs

of 160 average homes or an office building... day and night, in roughly the footprint of a

standard parking space. For more power simply add more energy servers.

Energy Server Architecture

At the heart of every Energy Server™ is Bloom's patented solid oxide fuel cell technology.

Each Energy Server consists of thousands of Bloom's fuel cells. Each cell is a flat solid

ceramic square made from a common sand-like "powder." Each Bloom Energy fuel cell is

capable of producing about 25W... enough to power a light bulb. For more power, the cells

are sandwiched, along with metal interconnect plates into a fuel cell "stack". A few stacks,

together about the size of a loaf of bread, is enough to power an average home. In an

Energy Server, multiple stacks are aggregated together into a "power module", and then

multiple power modules, along with a common fuel input and electrical output are

Aassembled as a complete system.

For more power, multiple Energy Server systems can be

In addition to Bloom's unmatched performance, this modular architecture offers...

· easy and fast deployment

· inherent redundancy for fault tolerance

· high availability (one power module can be serviced while all others continue to

operate)

· mobility

The Benefits of Bloom Energy

Bloom Energy is a Distributed Generation solution that is clean and reliable and affordable

all at the same time. Bloom's Energy Servers

, assembled deployed side by side.

can produce clean energy 24 hours pe

per day,

365 days per year, generating more electrons than intermittent solutions, and delivering

faster payback and greater environmental benefits for the customer. And while other DG

systems may require lengthy installations, sunny locations, or demand for consistent

24/7/365 heat load, Bloom's systems are easy and fast to install, practically anywhere.

Article By

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Mr.Shiva Kishore                                

Assistant Professor

EEE Departement

LAQSHYA Institute of Technology & Sciences              

Binray Trees Applications (IT Department @ LAQSHYA)

Binary Trees Applications

• Binary Search Tree - Used in many search applications where data is constantly entering/leaving, such as the map and set objects in many languages' libraries.
• Binary Space Partition - Used in almost every 3D video game to determine what objects need to be rendered.
• Binary Tries - Used in almost every high-bandwidth router for storing router-tables.
• Hash Trees - used in p2p programs and specialized image-signatures in which a hash needs to be verified, but the whole file is not available.
• Heaps - Used in implementing efficient priority-queues, which in turn are used for scheduling processes in many operating systems, Quality-of-Service in routers, and A* (path-finding algorithm used in AI applications, including robotics and video games). Also used in heap-sort.
• Huffman Coding Tree - used in compression algorithms, such as those used by the .jpeg and .mp3 file-formats.
• GGM Trees - Used in cryptographic applications to generate a tree of pseudo-random numbers.
• Syntax Tree - Constructed by compilers and (implicitly) calculators to parse expressions.
• Treap - Randomized data structure used in wireless networking and memory allocation.
• T-tree - Though most databases use some form of B-tree to store data on the drive, databases which keep all (most) their data in memory often use T-trees to do so.

·         The reason that binary trees are used more often than n-ary trees for searching is that n-ary trees are more complex, but usually provide no real speed advantage.

·         In a (balanced) binary tree with m nodes, moving from one level to the next requires one comparison, and there are log_2(m) levels, for a total of log_2(m) comparisons.

·         In contrast, an n-ary tree will it will require log_2(n) comparisons (using a binary search) to move to the next level. Since there are log_n(m) total levels, the search will require log_2(n)*log_n(m) = log_2(m) comparisons total. So, though n-ary trees are more complex, they provide no advantage in terms of total comparisons necessary.

·         (However, n-ary trees are still useful in niche-situations. The examples that come immediately to mind are quad-trees and other space-partitioning trees, where divisioning space using only two nodes per level would make the logic unnecessarily complex; and B-trees used in many databases, where the limiting factor is not how many comparisons are done at each level but how many nodes can be loaded from the hard-drive at once)

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IT Department
LAQSHYA Institute of Technology & Sciences

                                                                                                             

ENGINEERING CHEMISTRY (B.Tech I year Model Paper)

LAQSHYA INSTITUTE OF TECHNOLOGY & SCIENCES

B.Tech I year Model Paper  Examinations, May 2014

Name of the Subject: ENGINEERING CHEMISTRY  

ENGINEERING DRAWING(MECHANICAL - B.Tech I year)

LAQSHYA INSTITUTE OF TECHNOLOGY & SCIENCES

B.Tech I year model paper  Examinations, May 2014

Name of the Subject: ENGINEERING DRAWING

      BRANCH: MECHANICAL                           

ENGINEERING DRAWING ( BRANCH: ECE-B & EEE )

LAQSHYA INSTITUTE OF TECHNOLOGY & SCIENCES

B.Tech I year Model Paper  Examinations, May 2014

Name of the Subject: ENGINEERING DRAWING

BRANCH: ECE-B&EEE