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Definition of Economic Utility

Economic Utility is the total satisfaction a consumer derives from consuming a product. In other words, it is the satisfying power of any good or commodity. For example, Mr. Vivek can go to his workplace by cycling or by car. He prefers cycling as he derives greater utility (both health-wise and cost-saving) from it.

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In the above example, the utility is not measured in numbers. When numbers come in to measure utility, we mostly use them to compare products.

Therefore economic utility is totally psychology. The utility of a given product may be different for every person based on the demands of the person.

A consumer/buyer usually purchases a particular product when he will derive some benefit/benefit by using the product. He believes that the use or consumption of the purchased goodwill fulfills his want. Utility depends on consumer demand. A consumer’s demand/want will be fulfilled on the basis of the amount of utility fulfilled by the product.

Types of Economic Utility

An economic utility can be broadly divided into four main types:

Form

Time

Place

Possession

We will now discuss each form of utility in detail:-

1. Form

A utility is created by changing its form. Form utility is the value that the customer sees in the finished product. Every company tries to increase its form utility as the finished product is more useful to the consumer than the raw materials used to make it.

Companies always try to understand and analyze the target market segment. This will help the company to figure out what kind of product they should make.

For example

A company may use wood to make finished products like cabinets which will add significant value for the customers and thus increase the form utility.

Wood logs converted to furniture.

Wood pulp is used to make finished products like paper which add significant value to the customer in everyday life.

2. Place

The physical location for the availability of the product increases the attractiveness of the good to the consumers. So the place utility has more to do with the physical location of the product’s availability and the distribution channels.

For examples

If goods are sold in stores close to the buyer’s home or office, it will be convenient and efficient for the buyer.

Goods in store increase the utility of place.

3. Time

The availability of products and services when the customer needs them. The customer wants a good or service depending on the season and the weather conditions.

For examples

During the rainy seasons, umbrellas are very important, and their demand also increases. During the winter, the demand for warm clothes increases. Time utility increases when the product is easily available when the customer needs it.

Companies are increasing the time utility even more with e-commerce’s coming up with one-day or same-day delivery services. In this way, time utility increases as the customer gets a product when he needs it the most.

4. Possession

If a product is useful for multiple purposes, the possession utility of the product increases. Like when we buy a product for one use but use it for multiple purposes.

For example

we can use a vase for keeping flowers, as an item for decoration, or to keep cutleries.

Vase is used to keep cutleries or flowers.

Can we measure Economic Utility?

Consumers buy a product for different kinds of reasons. The price a buyer is ready to pay is the worth of the product. No buyer will be ready to pay more than the derived utility from the product.

For example

If I buy a television for ₹ 25,000, I derive a utility equivalent to the value of ₹ 25,000. Similarly, if I buy furniture for ₹ 5,000, I will derive utility equivalent to the amount I pay.

But many economists have not agreed with the above statement by Prof Marshall because the utility is different for different people, and it is completely personal and psychological.

A brand of a television set might fulfill my demand, but the same brand X might not satisfy the need of another person.

Conclusion

Therefore economic utility is the total satisfaction or usefulness a consumer derives by consuming the good. In other words, economic utility is how the consumer perceives a given product to fulfill its demand. As discussed, there are four different types of utility: Form, Place, Time, and Possession.

Form utility is the value a consumer sees in the final product. Place utility makes a good or service more easily available to the target customers. Time utility provides easy availability of a good or service when customers need or want it. And lastly, possession utility describes the benefits available to the customers from owning the product.

5 Different Types Of Raster

Introduction to Raster Data

Raster Data is the type of geospatial data that is used to geocode maps and fill in the information related to surface features. It can be a pixel, matrix or even collection of cell forming a picture in general term. The Satellite imagery and the layers are classified into Raster Data. Unlike Vector Data, this form of data represents the interior part of the feature. Vector Data forms the boundary of any geo feature, and Raster Data fills the feature with specific pixelation. Raster Data are more into storing temperature, elevation, depth and soil pH value related data. The colour contrast varies from. Location to location and also depends on various geographical features covering the area. Two types of Raster data are Discrete Raster Data and Continuous Raster Data.

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How does Raster Data Work?

As given in the above definition, each cell or the matrix act as a data container. They can be called the variables that store colour-specific information depending on the classification and nature of the geographic feature. In the Raster form of data, the map area is divided into several cells and a matrix. The area is equally distributed with the help of Rows and Columns. Each cell of the row and the column has some unique attributes that define the value.

Most of the raster data pixels are in a square or rectangular format, but other shapes like triangular or hexagonal are also possible. The whole imagery or datasheet contains all these uniquely filled cells and forms the Raster data. Raster spatial data structures are two-dimensional arrays; this means that the area that each cell grid represents can both be used to define map resolution and the number of cell grids to describe the spatial distribution. Single-pixel or a cell in the layer can only have one attribute being mapped to it. To handle more than one attribute, more data layers need to be created. These layers can be visualized as stacked, one on top of the other.

While working on any project, GIS Analysts and Technicians load the Raster data models from the serving source and then work on the geocoding and referencing part. Based on the Raster data’s reference, they further create the vector map objects that consist of point, line, and polygon. The data is stored in various file formats like Images (.IMG, .JPG, and . PNG file extensions), ESRI uses bit maps (.BMP, .BPW) and many more customized formats.

The Raster Data is the imagery form of the surface area where each pixel in the data describes the surface area.Camera Sensors are used to capture the features with the help of electromagnetic waves generated through the sensors. The data collected from these sensors are the measurements that are reflected using electromagnetic waves.

There are primarily two types of sensors, Active Sensors and Passive Sensors.Passive Sensorsin the satellite sensors that detect only the data emitted from the landscape or reflected from any other light source. Active Sensors emits their signal, and the sensors in the satellite measures what is reflected. SONAR and RADAR are perfect examples of this type of sensor.

Passive Sensor Active Sensor

Types of Raster Data

Raster Data is further classified into various types; they are:

Satellite Imagery

Digital Elevation Model(DEM)

Digital Orthophotos

Binary Scanned Files

Graphic Files

Let us study the above-mentioned types in details:

1. Satellite Imagery

The imagery is remotely sensed and collected data in the raster format. The image value in the pixel represents the light or energy that is emitted and reflected from the earth back to the satellite sensors, which collects the data. Various types of land use and hydrography features can be classified during image processing. The imagery generated through this method can be either in RGB format or in traditional black & white format.

2. Digital Elevation Model (DEM)

DEM of Snow covered mountains

3. Digital Orthophotos

Digital Orthophoto is a type of aerial imagery or satellite imagery that is extracted using remote sensing techniques. It is said to the corrected and processed imagery where the camera tilts and terrain relief is removed. This imagery form is geometrically correct and used for the digitization of 2D models. The collection of these Orthophotos form a large sheet of imagery, also known as Google Earth imagery is the perfect example of this orthophoto.

4. Binary Scanned Files

Binary Images Showing the presence in black, grey and white

5. Graphic Files

In this format, the Maps, Photographs and Images can be stored as digital graphic files. The popular graphic files that we come across in our daily life are GIF (Graphic Interchange Format), TIFF (Tagged Image File Format), JPEG (Joint Photographic Experts Group) and PNG (Portable Network Graphics)

Advantages of Raster Data

Raster Datais the simplest form of data structures, and hence they are easy to use and understand by the Geographic Information Systems Workforce.

This data form can be used to do various spatial analysis.

The model maintains uniformity when it comes to size and shape due to matrix and multi-array like structure.

Comparatively to its vector counterpart, the technology is far cheaper and affordable.

This makes the data livelier and presentable due to the involvement of colour codes, and hence when pairing with vector models, it gives proper relatable information.

Conclusion

With the help of Raster data form, spatial data becomes valuable. Most of the organization that is into GIS domain refer to external raster data forms. Raster data is simple yet heavy to handle due to toa large amount of imagery related files. Unlike earlier days, RDMS and Systems have become robust to handle these large and heavy data models. Both the data types are crucial in the world of GIS, but Raster data is the most preferred one.

Different Types Of Sql Functions

SQL, or Structured Query Language, is a programming language used for managing and manipulating relational databases. One of the most powerful features of SQL is the ability to use functions to perform various operations on the data in a database. In this article, we’ll discuss the different categories of SQL functions and provide code examples to help illustrate their use.

Aggregate Functions

Aggregate functions are used to perform calculations on a set of values and return a single result. Some of the most commonly used aggregate functions in SQL include −

COUNT() – Returns the number of rows in a table or the number of non-NULL values in a column

SUM() – Returns the sum of all non-NULL values in a column

AVG() – Returns the average of all non-NULL values in a column

MIN() – Returns the minimum value in a column

MAX() – Returns the maximum value in a column

Here’s an example of using the COUNT() function to find the number of rows in a table called “orders” −

SELECT

COUNT

(

)

FROM

orders

;

And here’s an example of using the SUM() function to find the total cost of all orders in the table −

SELECT

SUM

(

total_cost

)

FROM

orders

;

Scalar Functions

Scalar functions are used to perform calculations on a single value and return a single result. Some examples of scalar functions in SQL include −

LENGTH() – Returns the number of characters in a string

UPPER() – Converts a string to uppercase

LOWER() – Converts a string to lowercase

CONCAT() – Concatenates two or more strings together

ROUND() – Rounds a number to a specified number of decimal places

Here’s an example of using the UPPER() function to display the names of all customers in uppercase −

SELECT

UPPER

(

customer_name

)

FROM

customers

;

And here’s an example of using the ROUND() function to round the total cost of an order to two decimal places −

SELECT

ROUND

(

total_cost

)

FROM

orders

;

Date and Time Functions

SQL also provides a number of functions for working with date and time values. Some examples of date and time functions in SQL include −

NOW() – Returns the current date and time

CURRENT_DATE() – Returns the current date

CURRENT_TIME() – Returns the current time

YEAR() – Returns the year of a date

MONTH() – Returns the month of a date

DAY() – Returns the day of a date

Here’s an example of using the NOW() function to find the current date and time −

SELECT

NOW

(

)

;

And here’s an example of using the MONTH() function to find the month of an order’s date −

SELECT

MONTH

(

order_date

)

FROM

orders

;

String Functions

SQL also provides a number of string manipulation function. Some examples of string functions in SQL include −

LTRIM() – Removes the leading whitespace of the string

RTRIM() – Removes the trailing whitespace of the string

TRIM() – Removes both leading and trailing whitespace of the string

SUBSTRING() – Extracts a specific portion of a string

REPLACE() – Replaces all occurrences of a specified string with another string

Conditional Functions

SQL also provides a number of functions that perform different actions based on certain conditions. Some examples of conditional functions in SQL include −

CASE – evaluates a list of conditions and returns a result for the first condition that is met

IF – return a specified value if the condition is met, otherwise return another specified value

COALESCE – return the first non-null expression among multiple expressions.

Here’s an example of using the CASE function to assign a label to each order based on the total cost −

SELECT

order_id

total_cost

CASE

ELSE

'inexpensive'

END

"price range"

FROM

orders

;

Here’s an example of using the IF function to check the availability of stock of a product

SELECT

product_name

"Availability"

FROM

products

;

Here’s an example of using the COALESCE function to display the primary phone number and the secondary phone number of a customer −

SELECT

customer_name

COALESCE

(

primary_phone

secondary_phone

)

"Phone Number"

FROM

customers

;

Logical Functions

SQL provides a set of logical functions that return a Boolean value, which can be either true or false. Some examples of logical functions in SQL include −

AND – Returns true if both the conditions are true

OR – Returns true if at least one of the conditions is true

NOT – Negates a boolean value

Here’s an example of using the AND function to find all customers who live in a specific city and have an account balance greater than a certain amount −

SELECT

customer_name

city

account_balance

FROM

customers

Conversion Functions

SQL provides a number of functions that can be used to convert data from one type to another. Some examples of conversion functions in SQL include −

CAST() – Converts a value from one data type to another

CONVERT() – Converts a value from one data type to another (This function is specific for some database vendors like SQL Server)

TO_DATE() – Converts a string to a date value

TO_TIME() – Converts a string to a time value

TO_TIMESTAMP() – Converts a string to a timestamp value

Here’s an example of using the CAST() function to convert a float value to an int −

SELECT

CAST

(

price

INT

)

"Integer Price"

FROM

products

;

Here’s an example of using the TO_DATE() function to convert a string to a date value −

SELECT

TO_DATE

(

order_date

'yyyy-mm-dd'

)

"Formatted Order Date"

FROM

orders

;

Window Functions

SQL provides a set of functions that can be used to perform calculations across a set of rows that are related to the current row. These functions are known as window functions. Some examples of window functions in SQL include −

RANK() – Assigns a unique rank to each row within a result set, based on the values in one or more columns

DENSE_RANK() – Assigns a unique rank to each row within a result set, based on the values in one or more columns, but does not leave gaps in the ranking sequence when there are ties

ROW_NUMBER() – Assigns a unique number to each row within a result set, based on the order specified in the ORDER BY clause of the function

Here’s an example of using the RANK() function to find the rank of each customer based on their account balance −

SELECT

customer_name

account_balance

RANK

(

)

OVER

(

ORDER

account_balance

DESC

)

"Rank"

FROM

customers

;

Here’s an example of using the ROW_NUMBER() function to find the row number of each customer in the table −

SELECT

customer_name

ROW_NUMBER

(

)

OVER

(

ORDER

customer_id

)

"Row Number"

FROM

customers

;

These are just a few examples of the many functions that SQL provides for working with and manipulating data in a relational database. Each category of functions serves its own unique purpose, and understanding when and how to use them can help to make working with SQL and relational databases more efficient and effective.

Conclusion

SQL functions are an incredibly powerful tool for working with and manipulating data in a relational database. In this article, we’ve discussed the different categories of SQL functions, including aggregate functions, scalar functions, date and time functions, string functions, and conditional functions, and provided examples of how they can be used. Understanding and being proficient in the use of these functions is an essential part of working with SQL and relational databases.

Different Types Of Operators In Postgresql

Introduction to PostgreSQL Operators

PostgreSQL Operators is a database management system and open-source software that enables easy access for the public to use for relational database purposes. Relational Database purposes are data manageability to explain it in a nutshell.

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PostgreSQL Operators

Below are the different PostgreSQL Operators, which are as follows:

1. Logical Operators

In PostgreSQL, the logical operators consist of the general operators, namely, logical operators are used to perform the logical operations described below.

AND

NOT

a. OR Operator

OR The operator returns TRUE if either value of an operand is TRUE.

Values passed as logic can be applied in different combinations to gain desired results.

So let us look at the truth table below.

We can assume 0 is FALSE and 1 as TRUE. Hence 0 or 1 is 1, which is essentially TRUE.

We can see that the OR operator returns FALSE (0) only when both X and Y are FALSE.

X OR Y

0 0

1 1

b. AND Operator

AND The operator returns TRUE only if the values of all operands are TRUE.

Unlike the OR operator, AND operator returns TRUE (1) only when both X and Y are TRUE.

X AND Y

1 1

c. NOT Operator

NOT This operator negates the initial value of an operand. If the operand value is TRUE, then FALSE is returned.

Regarding the NOT operator, the logic is that the operator returns FALSE if the operand is TRUE and vice versa.

NOT(X)

2. Arithmetic Operators/Mathematical Operators

Arithmetic operators perform specific mathematical operations like addition, subtraction, etc. In PostgreSQL, Arithmetic operators are used to perform the Arithmetic operations as described below.

Operator Name

Operators

Functionality

Example

Result

Addition

Adds values of operands 10 +11 21

Subtraction

–

Subtracts values of operands 10 -11 -1

Multiplication

Performs multiplication on operands 10 * 11 110

Division

Performs Division on operands 10/5 2

Modulo

Performs Division but returns the remainder as output 11%10 1

Exponentiation

This provides the power value of the desired operand 10^2 100

Square Root

Performs Square Root of an operand |/ 16 4

Cube Root

Performs Cube root of an operand ||/64 4

Factorial

Returns factorial of a given number (Postfix form) 4! 24

Factorial ( with prefix operator)

Returns factorial of a given number (Prefix form) !! 4 24

3. Bitwise Operators

To understand Bitwise operators’ functionality, we need to know that these operators will work only on integrals and that the operator’s functionality takes place in the operand’s binary form (representation in 0s and 1s). In PostgreSQL, Bitwise operators are used to perform the Bitwise operators as described below.

Operators Example

Result

Bitwise AND

10 & 12 8

Bitwise OR

Bitwise NOT

~10 5

Bitwise XOR

10 # 12 6

Bitwise shift left

10 << 2 40

Bitwise shift right

Let us take two operands, for example:

10 – Binary Representation is 1010.

12 – Binary Representation is 1100.

Refer below to how operands 10 and 12 get interpreted into their equivalent Binary form.

10 – Binary Representation is 1010

12 – Binary Representation is 1100

a. Bitwise AND Operator

This operator interprets the operands in their binary representation and performs the AND function on every digit of the operands.

b. Bitwise OR Operator

This operator interprets the operands in their binary representation and performs the OR function on every digit of the operands.

c. Bitwise Not Operator

This operator performs the negation operation on each digit of the operand. It can take only one operand at a time; hence it is known as a unary operator.

In the above example, all 0S are converted to 1S and vice versa.

d. Bitwise XOR Operator

This operator interprets the operands in their binary representation and performs the XOR function on every digit of the operands.

XOR function returns TRUE or 1 if either one of the operands is TRUE or 1

XOR function returns FALSE or 0 if all the operands are TRUE or all the operands are FALSE.

e. Bitwise Shift Left Operator

This operator shifts the given number’s bits in its binary representation to the left side by a specified number of bits. Let us say the specified number of bits is x, then shift each bit of 10 to the left by x bits is denoted as 10 <<x. If x is 2, then 10 << 2 is 40.

f. Bitwise Shift Right Operator 4. Comparison Operators

Comparison Operators interpret an expression and provide output in Boolean values. (TRUE or FALSE). In PostgreSQL, Comparison Operators perform the Comparison Operators described below.

Some of the common Comparison operators are shown below.

Operator

Operator Name

Less than an operator

Greater than operator

Equals

not equals

Less than or equal to the operator

Greater than or equal to the operator

a. Operator ‘<.’

This operator compares the given expression and returns TRUE if the first operand is less than the second operand in the expression, or else it returns FALSE.

This operator compares the given expression and returns TRUE if the first operand is greater than the second operand in the expression, or else it returns FALSE.

c. Operator ‘=.’

This operator compares the operands in the expression and returns TRUE if both operands are of the same value, or else it returns FALSE.

This operator compares the operands in the expression and returns TRUE if both operands are not of the same value or return FALSE.

e. Operator ‘<=.’

This operator returns TRUE if the first operand’s value is lesser or equal to the value of the second operand.

This operator returns TRUE if the first operand’s value is greater or equal to the value of the second operand.

Different Types Of Ram (Random Access Memory) Explained

What is RAM?

The full form of RAM is Random Access Memory. The information stored in this type of memory is lost when the power supply to the PC or laptop is switched off. The information stored in RAM can be checked with the help of BIOS. It is generally known as the main memory or temporary memory or cache memory or volatile memory of the computer system.

In this Operating system tutorial, you will learn:

History of RAM

Here, are important landmarks from the history of RAM:

Type of RAM Year Invented

FPM-(Fast page mode RAM)- 1990

EDO RAM (Extended data out random access memory) 1994

SDRAM (Single dynamic RAM) 1996

RDRAM (Rambus RAM) 1998

DDR (Double Data Rate) 2000

DDR2 2003

DDR3 2007

DDR4 2012

Types of RAM

Two main types of RAM are:

Static RAM

Dynamic RAM

Static RAM

Static RAM is the full form of SRAM. In this type of RAM, data is stored using the state of a six transistor memory cell. Static RAM is mostly used as a cache memory for the processor (CPU).

Dynamic RAM

DRAM stands for Dynamic Random Access Memory. It is a type of RAM which allows you to stores each bit of data in a separate capacitor within a specific integrated circuit. Dynamic RAM is a standard computer memory of the many modern desktop computers.

This type of RAM is a volatile memory that needs to be refreshed with voltage regularly. Else it loses the information stored on it.

SRAM VS DRAM

SRAM DRAM

SRAM has lower access time, so it is faster compared to DRAM. DRAM has higher access time, so it is slower than SRAM.

SRAM is costlier than DRAM. DRAM costs less compared to SRAM.

SRAM requires a constant power supply, which means this type of memory which consumes more power. DRAM offers reduced power consumption because the information is stored in the capacitor.

It is a complex internal circuitry, and it offers less storage capacity is available compared to the same physical size of a DRAM memory chip. It is the small internal circuitry in the one-bit memory cell of DRAM. The large storage capacity is available.

SRAM has a low packaging density. DRAM has a high packaging density.

Other Important Types of RAM FPM DRAM

FPM DRAM

Fast Page Mode Dynamic Random Access Memory is a type of RAM that waits through the entire process of locating a bit of data by column and row and then reading the bit before it begins on the next bit. Max transfer rate is around 176 Mbps.

SDR RAM

SDR RAM is a full form of synchronous dynamic access memory. It has access times between 25 and 10 ns(nanosecond), and they are in DIMM (dual in-line memory module) modules of 168 contacts.

They store data using capacitors using IC’s (Integrated Circuits). On one of its sides, they have terminations, which can be inserted inside of the individual slots for the Motherboard’s memory.

RD RAM

Rambus Dynamic Random Access Memory is a full form of RDRAM. This type of RAM chips works in parallel, which allows you to achieve a data rate of 800 MHz or 1,600 Mbps. It generates much more heat as they operate at such high speeds.

VRAM (Video):

VRAM

EDO RAM

EDO DRAM is an abbreviation of Extended Data Output Random Access Memory. It doesn’t wait for the completion of the processing of the first bit before continuing to the next one. As soon as the address of the first bit is located, EDO DRAM begins looking for the next bit.

Flash Memory :

Flash Memory

Flash memory is an electrically erasable and programmable permanent type of memory. It uses a one-transistor memory to store a bit. It offers low power consumption and helps to reduce the cost. It is mainly used in digital cameras, MP3 players, etc.

DDR SDRAM

DDR RAM

The full form of DDR SDRAM is Double Data Rate Synchronous Dynamic Random-Access Memory. It is just like SDRAM. The only difference between the two is that it has a higher bandwidth, which offers greater speed. It’s maximum transfer rate to L2 cache which is approximately 1,064 Mbps.

Uses of RAM

Here, are important uses of RAM:

RAM is utilized in the computer as a scratchpad, buffer, and main memory.

It offers a fast operating speed.

It is also popular for its compatibility

It offers low power dissipation

Performance Comparison of RAM Types

Standard Time in Market Internal Rate Bus Clock(MHZ) Perfectch Data rate(MT/s) Tranfer rate(GB/s) Voltage

SDRAM 1993 100-166 100-166 1n 100-166 0.8-1.3 3.3

DDR 2000 133-200 133-200 2n 266-400 2.1-3.2 2.5/2.6

DDR2 SDRAM 2003 133-200 266-400 4n 533-800 4.2-6.4 1.8

DDR3 2007 133-200 533-800 8n 1066-1600 8.5-14.9 1.35/1.5

DDR 4 2014 133-200 1066-1600 8n 2133-3200 17-21.3 1.2

Summary:

The full form of RAM is Random Access Memory.

Two main types of RAM are 1)Static RAM and 2) Dynamic RAM

Static RAM is the full form of SRAM. In this type of RAM, data is stored using the state of a six transistor memory cell.

DRAM stands for Dynamic Random Access Memory. It is a type of RAM which allows you to stores each bit of data in a separate capacitor

FPM DRAM is a full form of Fast Page Mode Dynamic Random Access Memory

Rambus Dynamic Random Access Memory is an extended form of an RDRAM

RAM optimized for video adapters is called VRAM.

EDO DRAM is an abbreviation of Extended Data Output Random Access Memory.

Flash memory is an electrically erasable and programmable permanent type of memory

The full form of DDR RAM is Double Data Rate.

SRAM has lower access time, so it is faster compared to DRAM.

RAM is utilized in the computer as a scratchpad, buffer, and main memory.

Types Of Seam With Fullness

The additional fabric used to cover the drape’s width and occasionally its height is known as “fullness.” A drape with more fullness has a richer appearance. It offers additional light and sound absorption as well as an increase in the depth of field that may be seen. How much fullness to add to a drape depends on its usage, style, and price range. If seams need to be “hidden” within the pleat, there is another thing to think about. The meaning of “fullness” is that it helps achieve proper fit and comfort and is done to create variation. Fullness is released by pleats, tucks, and gathers; darts are used to create flat patterns; and fullness gives clothing more adornment.

Types of Seam with Fullness

Following are the major terminologies used as types

Pleats

Pleats are folds in clothing made at equal intervals on the yoke, sleeves, and waistband of skirts to release fullness. Pleats are made at the top and smoothly flow down the bottom of the fabric. A final pleat’s size is three times as large as the material needed to create it. They usually range in size from 2.5 to 5 cm. They can be employed as a style detail and cause eye movement.

Depending on the fabric chosen, a pleat has a different effect. The depth of the pleat is determined by the fabric’s weight and the desired look. Knife, Box, Inverted, Accordion, Sun Ray, Pinch, and Kick pleats are a few examples of the various pleat styles.

Ruffles and Frills

A ruffle is a fabric strip that has been trimmed or handled in a way that creates fullness. These are employed in order to embellish clothing. They can occasionally be used to lengthen the hems of skirts and dresses.

To create flare and add ornamentation, frills can be gathered or pleated and cut on a straight, bias, or circular axis. It is crucial to leave enough fullness for gathering, but how much should be left depends on the fabric type. They can be used to trim the neckline, wrists, and hem of a garment either individually or in tiers. Ruffles and frills are best made from light-weight, sheer fabrics.

Darts

A dart is a triangular fold that is crucial when manufacturing clothes. It contours a flat piece of cloth to fit the natural curves of the body’s bust, armholes, neckline, and waist. They are primarily used in clothing for women. They are essential when designing clothing and cannot be disregarded. In the process of making darts, the stitching should begin at the broad edge and travel toward the tip. Normally, darts are made before a garment is sewn. It aids in improving the fit of the clothing. Single-pointed darts and double-pointed darts are the two different varieties of darts.

Tucks

A tuck is a fold in the cloth that is sewn down to give the garment more fullness. They should have an even width and aid in shaping a garment. Depending on whether the garment is used for ornamental or functional purposes, tucks can be done on either the right or wrong side of the garment. They produce a decorative accent that gives clothing more fullness. They appear more alluring when wearing exquisite and delicate fabrics. They ought to be separated equally. The various tuck styles include the pin, cross, piped, and shell tucks.

Gathers

Gathers are used to distribute fullness evenly in a specific area. Depending on the desired impact, the material requirement can be adjusted to be twice as wide. Cotton that is stiff has a crisp look, whereas silk or any man-made fibre has a graceful one. Elastic, a machine, or a hand can be used to gather material. Using the sewing technique of “gathering,” a fabric strip can be made shorter so that it can be joined to a shorter piece. It is frequently used to manage fullness in clothes, such as when a full sleeve is attached to a shirt’s armscye or cuff or when a skirt is fastened to a body.

Godet

A godet is an additional piece of cloth sewn onto a garment, typically a dress or skirt, in the shape of a circular sector. When a godet is added, the item of clothing in question flares, adding width and volume. A godet gives a piece of clothing added range of motion for the wearer.

Flares

According to current fashion trends, flares can be added to skirts, sleeves, trouser legs, and other garments. To add diversity, you can change the degree of flare. For instance, an A-line skirt has the least amount of flare at the hem, while a circle skirt has the most. Bell sleeves have a modest flair, whereas circular sleeves have the most flare.

Shirring Gores

To create a fitted bodice or hip and a flared-out hem, gores can be added to a skirt, kameez, or top. The type and availability of the fabric, the grain, and the desired level of fullness for the hemline all affect how many gores are inserted. It can be anywhere from 4 and 12; either 6 in the front and 6 in the rear, or 2 in the front and 2 in the back. In order for gored skirts or dresses to drape properly, the grain line is crucial. In order to achieve a decent, uniformly distributed flare and an appropriate slant on the seams, the centre of the gore should be on the straight grain.

Conclusion

To sum up, fullness makes a cloth look appealing and helps it accommodate the body’s natural curves. The contour is shaped by darts. Any area of the garment can be made fuller by pleating, gathering, or tucking. The type of material determines the choice of fullness.

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