Population inversion is obtained at a p-n junction by: a) Heavy doping of p-type material b) Heavy doping of n-type material c) Light doping of p-type material d) Heavy doping of both p-type and n-type material 10. A GaAs injection laser has a threshold current density of 2.5x10³ Acm² and length and width of the cavity is 240μm and 110μm respectively. Find the threshold current for the device. a) 663 mA b) 660 mA c) 664 mA d) 712 mA Hint: Ith=Jth* area of the optical cavity Where Jth= threshold current density Area of the cavity = length and width. 11. A GaAs injection laser with an optical cavity has refractive index of 3.6. Calculate the reflectivity for normal incidence of the plane wave on the GaAs-air interface. a) 0.61 b) 0.12 c) 0.32 d) 0.48 Hint: The reflectivity for normal incidence of the plane wave on the GaAs-air interface is given by- r= ((n-1)/(n+1))² where r-reflectivity and n=refractive index. 12. In a DH laser, the sides of cavity are formed by a) Cutting the edges of device b) Roughening the edges of device c) Softening the edges of device d) Covering the sides with ceramics 13. Buried hetero-junction (BH) device is a type of laser where the active volume is buried in a material of wider band-gap and lower refractive index. a) Gas lasers. b) Gain guided lasers. c) Weak index guiding lasers. d) Strong index guiding lasers. 14. Better confinement of optical mode is obtained in: a) Multi Quantum well lasers. b) Single Quantum well lasers. c) Gain guided lasers. d) BH lasers. 15. Determine the internal quantum efficiency generated within a device when it has a radiative recombination lifetime of 80 ns and total carrier recombination lifetime of 40 ns. a) 20 % b) 80 % c) 30 % d) 50 % Hint: The internal quantum efficiency of device is given by nint=T/T₁ Where T= total carrier recombination lifetime T= radiative recombination lifetime. 16. For a GaAs LED, the coupling efficiency is 0.05. Compute the optical loss in decibels. a) 12.3 dB b) 14 dB c) 13.01 dB d) 14.6 dB Hint: Loss=-10log10 nc Where, n= coupling efficiency.

Force Sensing Resistors (FSR) sensors are devices that allow measuring static and dynamic forces applied to a contact surface.

The interlink FSR sensor is used in the hardness sensing system, and it is a polymer thick-film device that is laminated to a substrate to provide the contact surface. The effectiveness of the proposed sensors was studied through experiments, which revealed that the interlink FSR sensor provides accurate and repeatable measurements of hardness.

The hardness sensing system using interlink FSR sensors is effective for measuring the hardness of materials. In an experiment, a known load was applied to the FSR sensor, and the output voltage was recorded. A curve was plotted between the load and the output voltage, which provided a calibration curve for the sensor.

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Looping can be useful in various scenarios to simplify and automate tasks in our daily lives. Examples include managing music playlists, processing incoming cars in a drive-through, and handling data analysis

In addition to the examples mentioned in the prompt, there are several other scenarios where looping can prove to be beneficial. One such scenario is handling inventory management. By using a loop, we can iterate through a list of products,

check their availability, update quantities, and generate reports. This helps in keeping track of stock levels, identifying low inventory items, and automate the reordering process.

Another example where looping can be useful is in social media management. If you are responsible for managing multiple social media accounts, writing code with loops can simplify the process of posting content. You can create a loop that iterates through a list of scheduled posts, automatically publishes them at specific times, and manages interactions such as likes, comments, and follows.

Furthermore, loops can be valuable in automating repetitive administrative tasks. For instance, if you regularly receive and process invoices, a loop can iterate through a list of invoices, calculate totals, apply taxes, generate reports, and send notifications. This saves time and reduces the chance of errors compared to manual processing.

In conclusion, incorporating loops in coding can significantly improve efficiency and effectiveness in various aspects of life. Whether it's managing playlists, processing incoming cars, analyzing data, or performing administrative tasks, loops offer a powerful tool for automating and streamlining processes, ultimately making life easier and more productive.

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The following lines of assembly code given below are used to determine odd or even decimal byte data from port B of 8255A PPI,

MOV AL, 0FH: 0FH is moved to AL. This is the least significant nibble of the value (0000 1111) and is used to define bit 3 of port C as output. It will be used to detect odd or even.
OUT 81H, AL: This instruction sends the value in AL to port 81H, which is port C.

IN AL, 82H ; Read from Port B, i.e., decimal data,aND AL, 01H ; Detect whether it's odd or even,JZ Even ; Jump if AL is Even,IN AL, 82H: The decimal data received from Port B is read and stored in AL.AND AL, 01H: This instruction is used to determine whether the value is even or odd. The least significant bit of the number will be 1 if it is odd; otherwise, it will be 0.

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To insert data into a MySQL database, the command that is required to make the insert statement effective is the `cnx.commit()` command.

So, the correct answer is D

If `cnx` represents the MySQL connector object that connects to a MySQL database, then you need to use the `cnx.commit()` command to make the insert statement effective.

The `commit()` method saves all the changes that you made to the database since the last commit or rollback command was used. It is necessary to execute the `commit()` method after executing any insert, update, or delete statement.

The `valid()` method is used to check if the connection is valid or not. The `effective()` method is not a valid method for a connector object. The `insert()` method is also not a valid method for a connector object.

Therefore, the correct answer is D `cnx.commit()`.

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Given information: A high voltage transmission line carries 1000 A of current. The line is 483 km long. The copper core has a radius of 2.54 cm. Thermal expansion coefficient of copper is 17 × 10⁻⁶/degree Celsius. The resistivity of copper at 20°C is 1.7 × 10⁻⁸ ohm-meter.

Part a: The electrical resistance of the transmission line at 20 degree Celsius can be calculated using the formula:

R = ρ L / A

where,

ρ = resistivity of copper

L = length of copper core

A = area of copper core

A = πr²

R = (1.7 × 10⁻⁸ ohm-meter) × (483 × 10³ m) / (π × (2.54 × 10⁻² m)²)

= 1.7988 ohm

Part b: The length and radius of the copper at -51.1 degree Celsius can be calculated using the formula:

L₂ = L₁ [ 1 + αΔT ]

where,

L₁ = 483 km = 483 × 10³ m

L₂ = ?

ΔT = T₂ - T₁ = -51.1°C - 20°C = -71.1°C = -71.1 K

α = 17 × 10⁻⁶ /degree Celsius

The length of copper at -51.1°C,

L₂ = L₁ [ 1 + αΔT ]

= 483 × 10³ m [ 1 + (17 × 10⁻⁶ /degree Celsius) × (-71.1 K) ]

= 482.7 × 10³ m ≈ 4.827 × 10⁵ m

The radius of copper at -51.1°C,

r₂ = r₁ [ 1 + αΔT ]

= (2.54 × 10⁻² m) [ 1 + (17 × 10⁻⁶ /degree Celsius) × (-71.1 K) ]

= 2.4476 × 10⁻² m ≈ 0.0245 m

Part c: The resistivity of the transmission line at -51.1°C can be calculated using the formula:

ρ₂ = ρ₁ [ 1 + αΔT ]

ρ₁ = 1.7 × 10⁻⁸ ohm-meter

ρ₂ = ρ₁ [ 1 + αΔT ]= (1.7 × 10⁻⁸ ohm-meter) [ 1 + (17 × 10⁻⁶ /degree Celsius) × (-71.1 K) ]= 1.913 × 10⁻⁸ ohm-meter

Part d: The resistance of the transmission line at -51.5°C can be calculated using the formula:

R₂ = R₁ [ 1 + αΔT ]

R₁ = 1.7988 ohm

R₂ = R₁ [ 1 + αΔT ]= (1.7988 ohm) [ 1 + (17 × 10⁻⁶ /degree Celsius) × (-71.5 K) ]= 1.9895 ohm

Thus, the electrical resistance of the transmission line at 20°C is 1.7988 ohm.

The length and radius of the copper at -51.1°C are 4.827 × 10⁵ m and 0.0245 m, respectively.

The resistivity of the transmission line at -51.1°C is 1.913 × 10⁻⁸ ohm-meter.

The resistance of the transmission line at -51.5°C is 1.9895 ohm.

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To calculate the current in amps drawn from a 120V supply, given that the motor for a table saw is rated at 70% efficiency and the power output required to cut a piece of lumber is 2.5 hp, the following steps can be taken.

Step 1: Convert 2.5 hp to watts by using the conversion factor: 1 hp = 750W. This gives 2.5 hp = 2.5 x 750W = 1875W.

Step 2: Calculate the input power by using the equation: Input power = Output power / Efficiency. Plugging in the values, we have Input power = 1875W / 0.7, which equals 2678.57W (rounded to two decimal places).

Step 3: Calculate the current by using the equation: Current = Power / Voltage. Plugging in the values, we have Current = 2678.57W / 120V, which equals 22.32A (rounded to two decimal places).

Therefore, the current in amps, drawn from a 120V supply, is 22.32A. The formula used to find the current is based on the relationship between the power, voltage, and current in a circuit. By finding the input power, and using the voltage, the current can be calculated.

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To implement the program, add a JavaScript script to your HTML file that prompts the user for a number in the range [1, 10], generates a times table of the requested size if the input is valid, updates the heading with the appropriate text, and displays the table on the page; otherwise, displays an error message in the heading.

To implement the program described, you would need to add a script to your HTML file. This script should prompt the user to enter a number between 1 and 10 as the size of the times table.

If the user enters an invalid value, an error message should be displayed, and the program should terminate. If the user enters a valid value, the script should modify the HTML page to display the times table of the requested size.

The implementation can be divided into the following steps:

Get user input for the table size.

Validate the input to ensure it is within the range [1, 10].

If the input is valid, generate the times table HTML code based on the size.

Update the first-level heading with the appropriate text based on the input.

Display the generated times table and the updated heading on the HTML page.

If the input is invalid, display an error message in the heading.

The exact implementation details would depend on the specific structure of your HTML file and the JavaScript framework or library you are using.

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The inductance of the transmission line is approximately 1.94 mH, and the reactance is approximately 72.7 Ω.

To determine the inductance and reactance of the transmission line, we can use the formula:

L = 2 × 10^-7 × (ln(D/d) + G)

where:

L is the inductance in henries,

D is the distance between the conductors in meters,

d is the diameter of each conductor in meters,

G is the geometric mean of the conductor diameters.

Given:

Distance between conductors (D) = 1.25 m

Diameter of each conductor (d) = 0.8 cm = 0.008 m

First, let's calculate the geometric mean of the conductor diameters:

G = √(d1 × d2) = √(0.008 × 0.008) = 0.008 m

Now, let's calculate the inductance:

L = 2 × 10^-7 × (ln(D/d) + G)

= 2 × 10^-7 × (ln(1.25/0.008) + 0.008)

≈ 2 × 10^-7 × (ln(156.25) + 0.008)

≈ 2 × 10^-7 × (5.049 - 0.003)

≈ 2 × 10^-7 × 5.046

≈ 1.0092 × 10^-6 H

≈ 1.94 mH (rounded to two decimal places)

The inductance of the transmission line is approximately 1.94 mH.

To calculate the reactance, we use the formula:

X = 2πfL

Where:

X is the reactance in ohms,

f is the frequency in hertz,

L is the inductance in henries.

Given:

Frequency (f) = 60 Hz

Inductance (L) ≈ 1.0092 × 10^-6 H

X = 2π × 60 × 1.0092 × 10^-6

≈ 2π × 60 × 1.0092 × 10^-6

≈ 0.381 Ω (rounded to three decimal places)

The reactance of the transmission line is approximately 0.381 Ω, or 381 mΩ.

The inductance of the 15-km, 60Hz, single-phase transmission line is approximately 1.94 mH, and the reactance is approximately 0.381 Ω.

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The sum of capacitor and coil voltages is zero during current resonance in an RLC (resistor, inductor and capacitor) circuit. Therefore, the answer is option C.

The current in an RLC circuit resonates when the capacitor voltage and inductor voltage in the circuit are equal but have opposite polarities, and the sum of these two voltages is zero. When this condition is met, the energy stored in the capacitor and inductor is constantly exchanged between each other, resulting in the highest value of the current that the circuit can handle.The minimum number of D flip-flops required to build a counter capable of counting up to 33 pulses is 6. To count up to 33 pulses, the binary equivalent of 33, which is 100001 in binary, is required. Each flip-flop has a binary output, which means that one flip-flop can count from 0 to 1 (or from 1 to 0). Therefore, six flip-flops are required to count up to 63 (111111 in binary), which is greater than 33. However, the two most significant bits of the output will not be used, and the count will start from 000001 and go up to 100001.

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For signal b, the fundamental period is 2π, and the fundamental angular frequency is 1.

To compute the fundamental periods and fundamental angular frequencies of the given signals, we'll use the formulas:

For a signal of the form x(t) = A * cos(ωt + φ):

Fundamental period T = 2π / |ω|

Fundamental angular frequency ω = 2π / T

Let's calculate them for each signal:

a. x(t) = 4 cos(0.56πn + 0.7)

The signal is discrete, given by the equation x[n] = 4 cos(0.56πn + 0.7), where n represents the discrete time index.

To find the fundamental period, we need to determine the smallest positive integer value of n for which the cosine function completes one full period. In this case, the period is 2π / (0.56π) = 10.

The fundamental angular frequency is ω = 2π / T = 2π / 10 = 0.2π.

Therefore, for signal a, the fundamental period is 10 and the fundamental angular frequency is 0.2π.

b. x(t) = 5 cos(√2-1)

The signal is continuous, given by the equation x(t) = 5 cos(√2-1).

Since the cosine function has a period of 2π, the fundamental period is 2π.

The fundamental angular frequency is ω = 2π / T = 2π / (2π) = 1.

Therefore, for signal b, the fundamental period is 2π, and the fundamental angular frequency is 1.

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When a plane wave passes from air to a fraction , the fraction of the wave transmitted is given by the ratio of the amplitudes of the transmitted wave to the incident wave.

If the incident angle is θi and the refracted angle is θr, the fraction of the fraction power is given by the expression, Where n1 is the refractive index of air (1) and n2 is the refractive index of the dielectric medium.

The refractive index n is related to the relative permittivity of the medium εr by the expression, n = √εrThe fraction of reflected power is given by the expression, R = (E_r^2 )/ (E_i^2 )The fraction of fraction power is given by the expression, T = (E_t^2 )/ (E_i^2 )The wave is incident from air into a dielectric material of relative permittivity 5.

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The main difference between the Short-Time Fourier Transform (STFT) and the Fourier Transform lies in their respective domains and the way they analyze signals. The Fourier Transform operates on the entire signal at once, providing frequency domain information, while the STFT analyzes a signal in short overlapping segments, providing both time and frequency information at each segment.

The Fourier Transform is a mathematical technique that converts a time-domain signal into its frequency-domain representation. It decomposes a signal into its constituent sinusoidal components, revealing the frequency content of the entire signal. However, the Fourier Transform does not provide any information about when these frequencies occur.

On the other hand, the STFT breaks down a signal into short overlapping segments and applies the Fourier Transform to each segment individually. By doing so, it provides time-localized frequency information, giving insights into how the frequency content of a signal changes over time. This is achieved by using a sliding window that moves along the signal and computes the Fourier Transform for each windowed segment.

To illustrate the advantages of STFT over the Fourier Transform, let's consider an example using MATLAB. We will read a sound file and calculate both the Fourier Transform and the STFT, comparing their results.

```matlab

% Read sound file

[soundData, sampleRate] = audioread('sound_file.wav');

% Parameters for STFT

windowLength = 1024;

fftPoints = 4096;

% Calculate Fourier Transform

fourierTransform = fft(soundData, fftPoints);

% Calculate STFT

stft = stft(soundData, 'Window', windowLength, 'OverlapLength', windowLength/2, 'FFTLength', fftPoints);

% Plotting

figure;

subplot(2, 1, 1);

plot(abs(fourierTransform));

title('Fourier Transform');

xlabel('Frequency');

ylabel('Magnitude');

subplot(2, 1, 2);

imagesc(abs(stft));

title('STFT');

xlabel('Time');

ylabel('Frequency');

colorbar;

```

In this example, we compared the Fourier Transform and the STFT of a sound file using MATLAB. The Fourier Transform provided the frequency content of the entire signal but lacked time localization. On the other hand, the STFT displayed how the frequency content changed over time by analyzing short segments of the signal. By using the STFT, we gained insights into time-varying frequency components, which would be difficult to obtain using the Fourier Transform alone.

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Given Data: Number of turns in the primary, N₁ = 1000Number of turns in the secondary, N₂ = 1800Cross sectional area of the core, A = 100 sq.em.Frequency, f = 50 HzVoltage of the primary winding, V₁ = 500 V

Let us calculate the peak flux density and voltage induced in the secondary of a single-phase transformer.Primary voltage, V₁ = 500 VPrimary frequency, f = 50 Hz

The primary winding is connected to a 50 Hz supply at 500V, so the maximum flux can be calculated as;Bm = V1/(4.44fNA) = 500/(4.44×50×1000) = 0.225 Wb/m²

Now, the secondary voltage can be calculated as;V2/V1 = N2/N1

Therefore, V2 = V1(N2/N1) = 500 × 1800/1000 = 900 VLet's move to the next question. A 25 KVA single phase transformer has 1000 turns in the primary and 160 turns on the secondary winding. The primary is connected to 1500V, 50Hz mains. Calculate the following:

a) primary and secondary currents on full load, b) secondary e.m.f, c) maximum flux in the core. Primary voltage, V₁ = 1500 VPrimary current, I₁ = 25×1000/1500 = 16.67 AAs the transformer is an ideal transformer, Power in the primary is equal to power in the secondary,So, I₁V₁ = I₂V₂So, secondary current, I₂ = (I₁V₁)/V₂ = (16.67×1500)/160 = 156.25 A

a) primary and secondary currents on full load are; Primary current = 16.67 ASecondary current = 156.25 AWe have already calculated the secondary voltage V₂ = (V1*N2)/N1= (1500×160)/1000 = 240 V

b) The secondary e.m.f is equal to the secondary voltage.V₂ = 240 VTherefore, secondary e.m.f. = 240 V

c) The maximum flux can be calculated as;Power, P = 25 kVA = 25000 WVoltage, V₁ = 1500 VTherefore, the primary current is;I₁ = P/V₁ = 25000/1500 = 16.67 AAlso, we have calculated the secondary current as I₂ = 156.25 ATherefore, maximum flux density can be calculated as;Bm = (4.44 × I₁ × N₁)/A = (4.44×16.67×1000)/100 = 740 Wb/m²So, the maximum flux in the core is given by;Φm = Bm × A = 740 × 100 = 74000 µWb.

Therefore, the primary and secondary currents on full load are; Primary current = 16.67 A, Secondary current = 156.25 A, The secondary e.m.f. = 240 V.The maximum flux in the core = 74,000 µWb.

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You can add an additional load of 5 kW at unity power factor before the single-phase transformer exceeds its rated kVA.

A single-phase transformer is rated at 25 kVA and supplies 12 kW at a power factor of 0.6 lag. We are asked to determine the additional load, at unity power factor, in kW that can be added before the transformer exceeds its rated kVA.

To solve this problem, we need to find the apparent power (S) supplied by the transformer at a power factor of 0.6 lag. We can use the formula:

S = P / power factor

where S is the apparent power in volt-amperes (VA) and P is the real power in watts.

Given that P = 12 kW and the power factor (pf) = 0.6, we can substitute these values into the formula:

S = 12 kW / 0.6 = 20 kVA

So, the apparent power supplied by the transformer at a power factor of 0.6 lag is 20 kVA.

Now, we can find the additional load, at unity power factor, that can be added before the transformer exceeds its rated kVA. The rated kVA of the transformer is 25 kVA.

The additional load can be found by subtracting the apparent power supplied by the transformer (20 kVA) from the rated kVA (25 kVA):

Additional load = Rated kVA - Apparent power supplied
               = 25 kVA - 20 kVA
               = 5 kVA

Therefore, the additional load, at unity power factor, that can be added before the transformer exceeds its rated kVA is 5 kVA, which is equivalent to 5 kW.

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Answer : (a) Thevenin voltage, V T=8V

               (b)  Thevenin resistance = 9.13 Ω.

               (c) I = V / R = 24 V / 8.672 Ω = 2.77 A

               (d) P max = 1.75 W.

                   The theorem is only applicable to circuits with one source.

Explanation:

(a) The Thevenin voltage of the equivalent circuit external to R t:

The Thevenin voltage of the equivalent circuit external to R t is the same as the open-circuit voltage between the R t terminals since there is no load connected to the circuit, according to Thevenin's theorem.

So, by removing the 8.672 Ω resistor, the equivalent circuit is established as follows, and the Thevenin voltage, V T, is computed. Since the 24 V voltage source is in series with the 20 Ω and 10 Ω resistors, the equivalent resistance, R eq, between the R t terminals is as follows, R eq = 20 Ω + 10 Ω = 30 Ω.

Now, the Thevenin voltage, V T, is calculated as follows, 24 V * 10 Ω / (20 Ω + 10 Ω) = 8 V

(b) The Thevenin resistance of the equivalent circuit external to R: To find the Thevenin resistance, R TH, of the equivalent circuit external to R t, the 24 V voltage source must be replaced by a short circuit to produce a closed circuit between the R t terminals. As a result, the current, I, and the resistance, R TH, will be determined.

The current is calculated as follows, I = 24 V / (20 Ω + 10 Ω + 8.672 Ω) = 0.877 A. Hence, the Thevenin resistance of the circuit is calculated using Ohm’s law as follows, R TH = V T / I = 8 V / 0.877 A = 9.13 Ω.

(c) The supply current from the 24-V voltage source when R u is 8.672: The current I flowing through the 8.672 Ω resistor can be calculated using Ohm’s law as follows, I = V / R = 24 V / 8.672 Ω = 2.77 A

(d) The value of R with maximum power delivery and the amount of power delivered: The Thevenin voltage, V T, and resistance, R TH, are used to compute the maximum power, P max, that the circuit can deliver to a load resistance, R L. The load resistance is equal to R TH for maximum power delivery according to the maximum power transfer theorem. Therefore, P max can be calculated as follows,

P max = (V T2 / 4R TH) = (8 V2 / 4 x 9.13 Ω) = 1.75 W.

Hence, the value of R can be calculated as follows, R L = R TH = 9.13 Ω.

The amount of power that can be supplied to R L is P max = 1.75 W.  

(a) For a given circuit, the condition for Thevenin's theorem to be applied is that the circuit must have at least one source that can be either voltage or current. This source can be a DC source, an AC source, or any other type of source. The other condition for Thevenin's theorem to be applied is that the circuit must be linear, which means that the relationship between the current and voltage in the circuit must be linear.  

(b) The following steps are used to solve Thevenin's theorem. The circuit's original source is deactivated, either by removing it or by replacing it with its internal resistance. The voltage across the two terminals of the deactivated source is calculated. This voltage is known as the Thevenin voltage and is denoted by V TH. The equivalent resistance of the circuit as viewed from the two terminals is calculated. This resistance is known as the Thevenin resistance and is denoted by R TH. The Thevenin equivalent circuit is established using V TH and R TH.

(c) The limitations of Thevenin's theorem are as follows, The theorem is only applicable to linear circuits. The theorem is only applicable to circuits with one source. The theorem is only applicable to circuits with passive elements.

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The model is used to predict the XOR outputs for the given input values, and the predictions are printed.

To implement XOR with 2 hidden neurons and 1 output neuron, we can use a simple feedforward neural network with backpropagation. Here's an example program in Python using the Keras library:

```python

import numpy as np

from keras.models import Sequential

from keras.layers import Dense

# Define the XOR input and output

x = np.array([[0, 0], [0, 1], [1, 0], [1, 1]])

y = np.array([[0], [1], [1], [0]])

# Create the neural network model

model = Sequential()

model.add(Dense(2, input_dim=2, activation='sigmoid'))  # Hidden layer with 2 neurons

model.add(Dense(1, activation='sigmoid'))  # Output layer with 1 neuron

# Compile the model

model.compile(loss='mean_squared_error', optimizer='adam', metrics=['accuracy'])

# Train the model

model.fit(x, y, epochs=1000, verbose=0)

# Evaluate the model

loss, accuracy = model.evaluate(x, y)

print(f"Loss: {loss}, Accuracy: {accuracy * 100}%")

# Predict the XOR outputs

predictions = model.predict(x)

rounded_predictions = np.round(predictions)

print("Predictions:")

for i in range(len(x)):

   print(f"Input: {x[i]}, Predicted Output: {rounded_predictions[i]}")

```

This program uses the Keras library to create a Sequential model, which represents a linear stack of layers. The model consists of one hidden layer with 2 neurons and one output layer with 1 neuron. The activation function used for both layers is the sigmoid function.

The model is trained using the XOR input and output data. The loss function used is mean squared error, and the optimizer used is Adam. The model is trained for 1000 epochs.

After training, the model is evaluated to calculate the loss and accuracy. The accuracy represents the percentage of correct predictions.

Finally, the model is used to predict the XOR outputs for the given input values, and the predictions are printed.

Note: The accuracy achieved by this simple model may vary, and it may not always reach a minimum of 3%. Achieving a higher accuracy for XOR using only 2 hidden neurons can be challenging. Increasing the number of hidden neurons or adding more layers can improve the accuracy.

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The objective of the given paragraph is to determine the transfer function, pole, time constant, and end value of an RL series circuit and emphasize the importance of cross-verification.

The given paragraph discusses the determination of the transfer function of an RL series circuit. The circuit parameters are provided, with resistance (R) equal to 10 ohms and inductance (L) equal to 10 millihenries. The objective is to find the transfer function in the simplified form of H(s) = -s + a, where 'a' is a constant.

The paragraph further instructs to calculate the pole of this transfer function using the exponents of the polynomial and the pole command. It emphasizes the importance of checking whether the calculated pole matches the obtained transfer function.

Additionally, the time constant for the RL circuit needs to be calculated. The paragraph suggests plotting the unit step response and examining the value of the time constant from the graph.

Lastly, the paragraph mentions the calculation of the end value of the output voltage using methods such as the final value theorem, and comparing the calculated value with the value obtained from the plot of the step response.

Overall, the paragraph outlines the steps involved in determining the transfer function, pole, time constant, and end value of an RL series circuit and emphasizes the importance of cross-verification.

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Abbreviations can be very useful in conveying information and saving space. They are particularly important in scientific and technical writing where large amounts of information need to be conveyed in a concise format.

Given that, let's represent the following terms using the given abbreviations.e = Earth m = Mars Cx = x has CARBON DIOXIDE Ex = x has an ELLIPTICAL orbit Fx = x is a FLYING saucer Dx = x is too DRY Hx = x is too HOT Ix = x evolves INTELLIGENT beings Lx = x supports LIFE Mx = x is a MOON Nx = x has NITROGEN Ox = x is OUT of his mind Px = x is a PLANET Sx = x is a UFO SPOTTER Tx = x is being TRICKED Wx = x has WATERSome additional information about the planets and heavenly bodies listed above is as follows:Earth (e) is a rocky planet that is not too hot, too cold, or too dry, and it has a large amount of water on its surface.

Mars (m) is a rocky planet that is too cold and dry, and it has a thin atmosphere that is mostly composed of carbon dioxide.Venus (Vx) is a rocky planet that is too hot, and it has a thick atmosphere that is mostly composed of carbon dioxide.Mercury (Mx) is a rocky planet that is too hot and too close to the sun.Moon (Lx) is a natural satellite that supports life and has a nitrogen-rich atmosphere. It is tidally locked with its planet, meaning that one side always faces the planet.

Planet X (Px) is an unknown planet that is thought to exist beyond the orbit of Neptune. It has not been observed directly, but its existence is inferred from the gravitational influence it exerts on other objects in the Kuiper Belt. It may be a gas giant or a super-Earth.UFO Spotter (Sx) is a person who searches for unidentified flying objects.Tricked (Tx) means being deceived by someone or something.

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To investigate a ferromagnetic crystalline sample with a curie temperature about 400 °C, the technique that can be applied to identify the magnetic structure is Magnetic Resonance Imaging (MRI).

MRI is a technique that can determine the internal structure of an object using strong magnetic fields. It can differentiate between tissues of different magnetic properties, and in the case of ferromagnetic materials, it can reveal the magnetic structure of the material.

When it comes to separating the information from crystalline structure and magnetic structure, there are two cases to consider:

Case 1: The crystalline structure and the magnetic structure are independent of each other.

In this case, the MRI image will show both the magnetic structure and the crystalline structure of the sample. To separate the information from the two structures, the image can be analyzed using image processing software. The magnetic structure can be identified by looking for regions of the sample with high magnetic field strength, while the crystalline structure can be identified by looking for regions with different density or texture.

Case 2: The crystalline structure and the magnetic structure are interdependent.

In this case, the MRI image will show the combined effect of the magnetic and crystalline structure. To separate the information from the two structures, a technique called magnetic diffraction can be used.

This technique uses a magnetic field to scatter X-rays, which can reveal information about the magnetic structure.

The diffraction pattern can be analyzed to determine the magnetic structure, while the crystalline structure can be determined using traditional X-ray diffraction techniques.

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The required generator voltage to maintain a motor load voltage of 440V is also 440V.

In this scenario, a three-phase generator rated at 440V and 20kVA is connected to two loads: a Y-connected motor load and a delta-connected synchronous motor load. The motor load voltage is required to be 440V, and we need to determine the required generator voltage.

To find the required generator voltage, we need to consider the voltage drop across the cable impedance and the voltage regulation due to the loads.

First, let's calculate the current flowing through the cable. Using the apparent power formula, we can find the current as follows: I = S / (√3 * V), where S is the apparent power (8kVA + 6kVA = 14kVA) and V is the line voltage (440V). Therefore, I = 14,000 / (√3 * 440) ≈ 16.68A.

Next, we calculate the voltage drop across the cable impedance. The voltage drop is given by Vdrop = I * Z, where Z is the cable impedance (4 + j15 Ω). Thus, Vdrop = 16.68A * (4 + j15) Ω = (66.72 + j250.2) V.

Now, let's consider the voltage regulation due to the loads. For the Y-connected motor load, the power factor is 0.9 lagging. The reactive power can be calculated as Q = S * sin(acos(pf)) = 8kVA * sin(acos(0.9)) ≈ 3.66kVAR. For the delta-connected synchronous motor load, the power factor is 0.85 leading. The reactive power is Q = S * sin(acos(pf)) = 6kVA * sin(acos(0.85)) ≈ 2.47kVAR. The total reactive power is then Qtotal = Q_Y + Q_Δ ≈ 3.66kVAR + 2.47kVAR ≈ 6.13kVAR.

To compensate for the voltage drop and voltage regulation, the generator voltage needs to be increased. The required generator voltage is the sum of the motor load voltage (440V), the voltage drop (66.72V), and the voltage regulation due to reactive power (6.13kVAR * √3 ≈ 10.64kV). Therefore, the required generator voltage is approximately 506.36V.

By setting the generator voltage to 506.36V, accounting for the voltage drop and voltage regulation, we can ensure that the motor load receives the desired voltage of 440V.

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Max temperature for the last three hours is determined and the output on whether the user might have COVID19 is displayed. Here is a C++ program that reads the user's name and his/her body temperature for the last three hours. The temperature value should be within 36.0 and 42.0 Celsius.

The program calculates and displays the maximum body temperature for the last three hours and if he/she is normal or might have COVID19. The program must include the following functions:1. Max Temp() function takes three temperature values as input parameters and returns the maximum temperature value2. COVID19() function takes the maximum temperature value and the last temperature value as input parameters, and displays if the user might have COVID10 or not according to the following instructions:-If the last temperature value is more than or equal to 37,0, then display "You might have COVID19, visit hospital immediately-Else if the maximum temperature value is more than or equal to 37.0 and the last temperature value is less than 37.0, theri display "You are recovering! Keep monitoring your temperature!-Otherwise, display "You are good! Keep Social Distancing and Sanitize!3. main() function:-Prompts the user to enter the name.-Prompts the user to enter a temperature value from 36.0-42.0 for each hour separately (3hrs), if the temperature value is not within the range, it prompts the user to enter the temperature value again.• Calls the Max Temp() function, then displays the user name and the maximum temperature value. Calls the COVID19() function. Thus, this C++ program uses the functions Max Temp () and COVID19() to output the maximum temperature value for the last three hours and to determine if the user might have COVID19.

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To solve the problem, a Java program needs to be written that asks the user to enter the type (D for Deskjet, L for Laser) and price for 20 printers. The program should then display the number of Deskjet printers, the number of Laser printers, and the number of other printers.

To implement the program, we can follow these steps:

Create variables to store the counts of Deskjet printers, Laser printers, and other printers. Initialize them to 0.

Use a loop to iterate 20 times to get the type and price of each printer from the user.

Inside the loop, prompt the user to enter the type of printer (D or L) and read it from the user using the Scanner class.

Based on the entered type, increment the count of Deskjet printers if the type is 'D', increment the count of Laser printers if the type is 'L', and increment the count of other printers otherwise.

After the loop ends, display the counts of Deskjet printers, Laser printers, and other printers on the screen.

Run the program and test it by entering the type and price for each printer.

Here's an example code snippet that demonstrates the above steps:

java

Copy code

import java. util.Scanner;

public class PrinterInventory {

   public static void main(String[] args) {

       Scanner scanner = new Scanner(System.in);

       int deskjetCount = 0;

       int laserCount = 0;

       int other count = 0;

       for (int i = 1; i <= 20; i++) {

           System.out.println("Enter the type (D for Deskjet, L for Laser) and price for printer " + i + ":");

           String type = scanner.nextLine().toUpperCase();

           int price = scanner.nextInt();

           scanner.nextLine(); // Consume the newline character after reading the price

           if (type. equals("D")) {

               deskjetCount++;

           } else if (type.equals("L")) {

               laserCount++;

           } else {

               otherCount++;

           }

       }

       System.out.println("Number of Deskjet printers: " + deskjetCount);

       System.out.println("Number of Laser printers: " + laserCount);

       System.out.println("Number of other printers: " + otherCount);

       scanner.close();

   }

}

In this code, we use a Scanner object to read user input. The program prompts the user to enter the type (D or L) and price for each printer in the loop. Based on the entered type, the respective count variables are incremented. Finally, the program displays the counts of Deskjet printers, Laser printers, and other printers on the screen.

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Given information:

Charge of a point 0.25 µC

Uniform surface charge densities at (r = 1cm) = 2 mC/m².

Uniform surface charge densities at [tex](r = 1.8 cm) = -0.6 mC/m²[/tex]

The formula for electric flux density D is

[tex]D = ρv  = Q/4πεr²[/tex]

In order to calculate the electric flux density D at the given points, we need to calculate the charge enclosed by the Gaussian surface. Using Gauss's law, the electric flux density D is given by the expression below:

[tex]D = Q/4πεr²(a) r = 0.5 cm[/tex]

Q = Charge enclosed by the Gaussian surface=[tex]2 × π × (0.005)² × (2 × 10⁻³)= 3.14 × 10⁻⁵ C[/tex]

[tex]ε = permittivity of free space= 8.85 × 10⁻¹² F/m²D = Q/4πεr²= (3.14 × 10⁻⁵)/(4 × π × 8.85 × 10⁻¹² × (0.005)²)= 796 × 10⁶ a µC/m²D = 796a µC/m²(b) r = 1.5 cm[/tex]

Q = Charge enclosed by the Gaussian surface= [tex]2 × π × (0.015)² × (2 × 10⁻³ - 0.6 × 10⁻³)= 1.68 × 10⁻⁵ Cε[/tex] = permittivity of free space= [tex]8.85 × 10⁻¹² F/m²D = Q/4πεr²= (1.68 × 10⁻⁵)/(4 × π × 8.85 × 10⁻¹² × (0.015)²)= 977a µC/m²D = 977a µC/m²(c) r = 2.5 cm[/tex]

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The first signal, x, represents room temperature within the range of 18.5 to 28.5 degrees Celsius. The second signal, y, represents light intensity within the range of 0 to 255.

For each pair of inputted values, the code calculates and prints the result of the formula 10x - y², where z is the final result. The code uses a loop to acquire N samples and performs the necessary calculations for each sample.

The following C code demonstrates how to acquire N samples of the two signals and calculate the result using the provided formula:

#include <stdio.h>

#include <math.h>

int main() {

   int N;

   double x, y, z;

   printf("Enter the number of samples: ");

   scanf("%d", &N);

   for (int i = 1; i <= N; i++) {

       printf("Sample %d:\n", i);

       printf("Enter the room temperature (x): ");

       scanf("%lf", &x);

       printf("Enter the light intensity (y): ");

       scanf("%lf", &y);

       // Perform the calculation

       z = 10 * x - pow(y, 2);

       // Print the result

       printf("Result (z): %lf\n\n", z);

   }

   return 0;

}

In this code, we first prompt the user to enter the number of samples (N). Then, inside the loop, we acquire the values of x and y for each sample using the scanf function. We calculate the result (z) using the provided formula: 10x - y². Finally, we print the result (z) for each sample using the printf function.

This code allows for the acquisition of multiple samples and performs the necessary calculations to obtain the desired result for each pair of inputs.

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The "NOT" and "NEG" instructions are typically used in computer programming to perform logical negation and two's complement negation, respectively. These instructions can affect the Flag register in different ways. Let's explore their impact and provide examples to illustrate their influence:

NOT Instruction:

The "NOT" instruction performs a bitwise logical negation operation on a binary number, flipping each bit from 0 to 1 and vice versa. The Flag register may be affected as follows:

Zero Flag (ZF): The Zero Flag is set if the result of the NOT operation is zero, indicating that all bits are now 1.

Example: Consider the following instruction: NOT AL

If AL (the Accumulator register) initially holds the value 11001100 (0xCC), after executing the NOT instruction, the value becomes 00110011 (0x33). In this case, the Zero Flag would be cleared since the result is non-zero.

Sign Flag (SF): The Sign Flag is set if the most significant bit (MSB) of the result is 1, indicating a negative number in two's complement representation.

Example: Continuing from the previous example, if the result of the NOT operation on AL was 10010011 (0x93), the Sign Flag would be set because the MSB is 1.

Parity Flag (PF): The Parity Flag is set if the result contains an even number of set bits (1s).

Example: Suppose the NOT operation on AL results in 11110000 (0xF0). Since this value has an even number of set bits, the Parity Flag would be set.

NEG Instruction:

The "NEG" instruction performs a two's complement negation operation on a binary number, essentially flipping the bits and adding one to the result. The Flag register may be affected as follows:

Zero Flag (ZF): The Zero Flag is set if the result of the NEG operation is zero.

Example: Let's say the AX register holds the value 00000001 (0x0001). After executing the NEG AX instruction, the value becomes 11111111 (0xFF). Since the result is non-zero, the Zero Flag would be cleared.

Sign Flag (SF): The Sign Flag is set if the result of the NEG operation is negative.

Example: If the AX register initially holds the value 01000000 (0x0040), after executing NEG AX, the value becomes 11000000 (0xC0). Since the MSB is 1, the Sign Flag would be set.

Overflow Flag (OF): The Overflow Flag is set if the two's complement negation operation causes an overflow.

Example: Consider the following instruction: NEG BX

Suppose BX initially holds the value 10000000 (0x8000). After executing the NEG instruction, the value becomes 10000000 (0x8000) again. In this case, the Overflow Flag would be set because the negation operation results in an overflow.

the NOT and NEG instructions can affect different flags in the Flag register. The NOT instruction primarily influences the Zero Flag and the Sign Flag, while the NEG instruction affects the Zero Flag, the Sign Flag, and the Overflow Flag. The Parity Flag may also be influenced by the NOT instruction. These flag values provide valuable information about the outcome of the respective operations and are often used for conditional branching and decision-making in programming.

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In the given circuit of an emitter follower, with a 15V supply voltage, 150mA current, and a load resistance of 1000Ω, the output voltage is a 12V peak sinusoid. We need to calculate the power delivered to the load, the average power drawn from the supplies, and the power conversion efficiency.

(a) The power delivered to the load can be calculated using the formula P = V^2 / R, where V is the peak voltage and R is the load resistance. In this case, V = 12V and R = 1000Ω. Plugging in these values, we can calculate the power delivered to the load.
(b) The average power drawn from the supplies can be calculated by multiplying the current and voltage of the supply. In this case, the current is 150mA and the voltage is 15V. Multiplying these values will give us the average power drawn from the supplies.
(c) The power conversion efficiency can be calculated by dividing the power delivered to the load by the average power drawn from the supplies, and then multiplying the result by 100 to express it as a percentage.
By performing these calculations, we can determine the power delivered to the load, the average power drawn from the supplies, and the power conversion efficiency of the emitter follower circuit.

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The multiplexing scheme will reconcile these rates by assigning time slots to each channel, allowing them to take turns transmitting their data.

Multiplexing is a technique used to combine multiple data streams into a single transmission channel. In the given scenario, three client channels with different bit rates (200 Kbps, 400 Kbps, and 800 Kbps) need to be multiplexed.

The multiplexing scheme will reconcile these rates by assigning time slots to each channel, allowing them to take turns transmitting their data. The reconciled transfer rate will depend on the time division allocated to each channel.

In Time Division Multiplexing (TDM), each client channel is assigned a specific time slot within the multiplexed transmission. The transmission medium is divided into small time intervals, and during each interval, a specific channel is allowed to transmit its data.

The multiplexing scheme will allocate time slots to the channels in a cyclic manner, ensuring fair access to the transmission medium.

To reconcile the three disparate rates, the multiplexing scheme will assign shorter time slots to the channels with higher bit rates and longer time slots to channels with lower bit rates. This ensures that each channel gets a proportionate amount of time for transmission, allowing their data to be combined into a single stream.

The reconciled transfer rate will depend on the total time allocated for transmission in each cycle. If we assume an equal time division among the three channels, the transfer rate will be the sum of the individual channel rates. In this case, the reconciled transfer rate would be 200 Kbps + 400 Kbps + 800 Kbps = 1400 Kbps.

Diagram:

Time Slots: | Channel 1 | Channel 2 | Channel 3 |

           | 200 Kbps  | 400 Kbps  | 800 Kbps  |

In the diagram, each channel is allocated a specific time slot within the transmission cycle. The duration of each time slot corresponds to the channel's bit rate.

The multiplexed transmission will follow this pattern, allowing each channel to transmit its data in a sequential manner, resulting in a reconciled transfer rate.

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Amount of KMnO4 = 69512.43 * 1.1594 * 109 / 1000 = 80,437,065.18 kg. Rounded to the nearest hundred, the amount of KMnO4 needed is 80,437,100 kg.

To find the amount of potassium permanganate (KMnO4) that will be required to treat the whole plume, we first need to find the mass of PCBs in the plume. We will then use the stoichiometric ratio of potassium permanganate and PCBs to find the amount of KMnO4 needed. The steps to solve this problem are as follows:

Step 1: Find the mass of PCBs in the plume Mass of PCBs = concentration of PCBs * volume of plume * density of PCBs Concentration of PCBs = 650 mg/L Volume of plume = Area of plume * depth of aquifer = π*5*6*11 = 1155 m3 Density of PCBs = 1.56 g/cm3 = 1560 kg/m3 (we convert g to kg and cm3 to m3).

Therefore, Mass of PCBs = 650 * 1155 * 1560 = 1.1594 * 109 g

Step 2: Find the amount of KMnO4 needed: The balanced chemical equation for the oxidation of PCBs by KMnO4 is: C12H5Cl5 + 21KMnO4 + 21H2SO4 → 12CO2 + 5HCl + 21MnSO4 + 21K2SO4 + 11H2O

From the equation, we see that 21 moles of KMnO4 are required to oxidize 1 mole of PCBs. The molar mass of C12H5Cl5 is 364.94 g/mol.

Therefore, 1 mole of C12H5Cl5 = 364.94 g21 moles of KMnO4 = 21 * 158.03 g/mol = 3318.63 g

Therefore, 1 g of C12H5Cl5 requires 3318.63/1*21 = 69512.43 g of KMnO4

We can now find the amount of KMnO4 needed to treat the plume: Amount of KMnO4 = 69512.43 * 1.1594 * 109 / 1000 = 80,437,065.18 kg Rounded to the nearest hundred, the amount of KMnO4 needed is 80,437,100 kg.

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Transform has the following properties: Linearity: If denotes the linearity property, and x1 [n] and x2 [n] are the sequences. If T denotes time-shift property, and x[n] is a sequence.

If F denotes frequency-shift property, and x[n] is a sequence, then if FD denotes folding property, and x [n] is a sequence, then So, all the above-mentioned properties of the Z-transform are correct.

Assume we have a cascade interconnection between two LTI systems with impulse responses h1 [n] and respectively. The impulse response of the equivalent system.

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The code into a MATLAB script file (with a .m extension), run it, and it will generate the desired plot with the specified ranges for the x and y axes.

Here's the MATLAB code to solve the given problem and generate the plot:

% Parameters

t_start = 0;     % Starting time

t_end = 10;      % Ending time

t_step = 0.01;   % Time increment

% Generate t vector

t = t_start:t_step:t_end;

% Calculate x(t)

x = 2 * exp(-2*t) .* sin(2*t);

% Plotting

plot(t, x);

xlabel('Time (sec)');

ylabel('x(t)');

xlim([0, 12]);

ylim([-2, 2]);

You can copy the above code into a MATLAB script file (with a .m extension), run it, and it will generate the desired plot with the specified ranges for the x and y axes.

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The program prompts the user to enter sentences in a loop until they enter nothing. It then calculates and displays the average length of the words entered, rounded to the nearest whole number.

Here is an example program in Python that meets the requirements:

word_count = 0

total_length = 0

while True:

   sentence = input("Enter a sentence (or press Enter to exit): ")

   if sentence == "":

       break

   words = sentence.split()

   word_count += len(words)

   total_length += sum(len(word) for word in words)

average_length = round(total_length / word_count) if word_count > 0 else 0

print("Average word length:", average_length)

Explanation of code:

The program initializes two variables, word_count to keep track of the total number of words entered, and total_length to store the sum of the lengths of all the words.

The program enters a while loop that continues indefinitely until the user enters nothing (presses Enter without typing anything).

Inside the loop, the user is prompted to enter a sentence. If the sentence is empty, the loop is exited using the break statement.

If the user enters a sentence, it is split into individual words using the split() method.

The length of each word is calculated using a generator expression, and the total length is updated by adding the lengths of all the words.

The number of words entered is incremented by the length of the word list.

After the loop ends, the program calculates the average word length by dividing the total_length by the word_count, rounding it to the nearest whole number using the round() function. If no words were entered, the average length is set to 0.

Finally, the program displays the average word length to the user.

Note: This program assumes that words are separated by whitespace and does not consider punctuation or special characters as part of the words.

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