Hello readers! Welcome to the next episode of the Deep Learning Algorithm. We are studying modern neural networks and today we will see the details of a reinforcement learning algorithm named Deep Q networks or, in short, DQN. This is one of the popular modern neural networks that combines deep learning and the principles of Q learning and provides complex control policies.
Today, we are studying the basic introduction of deep Q Networks. For this, we have to understand the basic concepts that are reinforcement learning and Q learning. After that, we’ll understand how these two collectively are used in an effective neural network. In the end, we’ll discuss how DQN is extensively used in different fields of daily life. Let’s start with the basic concepts.
Unlike this learning, supervised learning is done with the help of labeled data. Here are some important components of the reinforcement learning method that will help you understand the workings of deep Q networks:
Fundamental Components of Reinforcement Learning |
|
Name of Component |
Detail |
Agent |
An agent is a software program, robot, human, or any other entity that learns and makes decisions within the environment. |
Environment |
In reinforcement, the environment is the closed world where the agent operates with other things within the environment through which the agent interacts and perceives. |
Action |
The decision or the movement the agent takes within the environment at the given state. |
State |
At any specific time, the complete set of all the information the agent has is called the state of the system. |
Reward |
|
Policy |
A policy is a strategy or mapping based on the states. The main purpose of reinforcement learning is to design policies that maximize the long-term reward of the agent. |
Value Function |
It is the expectation of future rewards for the agent from the given set of states. |
Q learning is a type of reinforcement learning algorithm that is denoted by Q(s,a). Here, here,
Q= Q learning function
s= state of the learning
a= action of the learning
This is called the action value function of the learning algorithm. The main purpose of Q learning is to find the optimal policy to maximize the expected cumulative reward. Here are the basic concepts of Q learning:
In Q learning, the agent and environment interaction is done through the state action pair. We defined the state and action in the previous section. The interaction between these two is important in the learning process in different ways.
The core update rule for Q learning is the Bellman equation. This updates the Q values iteratively on the basis of rewards received during the process. Moreover, future values are also estimated through this equation. The Bellman equation is given next:
Q(s,a)←(1−α)⋅Q(s,a)+α⋅[R(s,a)+γ⋅maxa′Q(s′,a′)]
Here,
γ = discount factor of the function which is used to balance between immediate and future rewards.
R(s, a) = immediate reward of taking the action “a” within the state “s”.
α= The learning rate that controls the step size of the update. It is always between 0 and maxa′Q(s′,a′) = The prediction of the maximum Q values over the next state s′ and action value a′
The deep Q networks are the type of neural networks that provide different models such as the simulation of video games by using the Q learning we have just discussed. These networks use reinforcement learning specifically for solving the problem through the mechanism in which the agent sequentially makes a decision and provides the maximum cumulative reward. This is a perfect combination of learning with the deep neural network that makes it efficient enough to deal with the high dimensional input space.
This is considered the off-policy temporal difference method because it considers the future rewards and updates the value function of the present state-action pair. It is considered a successful neural network because it can solve complex reinforcement problems efficiently.
The Deep Q network finds applications in different domains of life where the optimization of the results and decision-making is the basic step. Usually, the optimized outputs are obtained in this network therefore, it is used in different ways. Here are some highlighted applications of the Deep Q Networks:
The Atari 2600 games are also known as the Atari Video Computer System (VCS). It was released in 1977 and is a home video controller system. The Atari 2600 and Deep Q Network are two different types of fields and when connected together, they sparked a revolution in artificial intelligence.
The Deep Q network makes the Atari games and learns in different ways. Here are some of the ways in which DQN makes the Atari 2600 train ground:
Learning from pixels
Q learning with deep learning
Overcoming Sparse Rewards
Just like reinforcement learning, DQN is used in the field of robotics for the robotic control and manipulation of different processes.
It is used for learning specific processes in the robots such as:
Grasping the objects
Navigate to environments
Tool manipulation
The feature of DQN to handle the high dimensional sensory inputs makes it a good option in robotic training where these robots have to perceive and create interaction with their complex surrounding.
The DQN is used in autonomous vehicles through which the vehicles can make complex decisions even in a heavy traffic flow.
Different techniques used with the deep Q network in these vehicles allow them to perform basic tasks efficiently such as:
Navigation of the road
Decision-making in heavy traffic
Avoid the obstacles on the road
DQN can learn the policies from adaptive learning and consider various factors for better performance. In this way. It helps to provide a safe and intelligent vehicular system.
Just like other neural networks, the DQN is revolutionizing the medical health field. It assists the experts in different tasks and makes sure they get the perfect results. Some of such tasks where DQN is used are:
Medical diagnosis
Treatment optimization
Drug discovery
DQN can analyze the medical record history and help the doctors to have a more informed background of the patient and diseases.
It is used for the personalized treatment plans for the individual patients.
Deep Q learning helps with resource management with the help of policies learned through optimal resource management.
It is used in fields like energy management systems usually for renewable energy sources.
In video streaming, deep Q networks are used for a better experience. The agents of the Q network learn to adjust the video quality on the basis of different scenarios such as the network speed, type of network, user’s preference, etc.
Moreover, it can be applied in different fields of life where complex learning is required based on current and past situations to predict future outcomes. Some other examples are the implementation of deep Q learning in the educational system, supply chain management, finance, and related fields.
Hence in this way, we have learned the basic concepts of Deep Q learning. We started with some basic concepts that are helpful in understanding the introduction of the DQN. These included reinforcement learning and Q learning. After that, when we saw the introduction of the Deep Q network it was easy for us to understand the working. In the end, we saw the application of DQN in detail to understand its working. Now, I hope you know the basic introduction of DQN and if you want to know details of any point mentioned above, you can ask in the comment section.
Hello students! I hope you are doing great. Today, we are talking about the decoders in the proteus. We know that decoders are the building blocks of any digital electronic device. These electronic circuits are used for different purposes, such as memory addressing, signal demultiplexing, and control signal generation. These decoders have different types and we are discussing the 3 to 8 line decoders.
In this tutorial, we will start learning the basic concept of decoders. We’ll also understand what the 3-to-8line decoders are and how we connect this concept with the 74LS138 IC in proteus. We’ll discuss this IC in detail and use it in the project to present the detailed work.
| Where To Buy? | ||||
|---|---|---|---|---|
| No. | Components | Distributor | Link To Buy | |
| 1 | 74LS138 | Amazon | Buy Now | |
A three to eight line decoder is an electronic device that takes three inputs and based on their combination, provides one of its eight outputs. In simple words, the 3 to 8 line decoder gets three inputs and reads the binary combination of its input. As a result, the single output is obtained at the output of the decoder. Here are the basic concepts to understand its working:
A 3 to 8 line decoder has three input pins which are usually denoted as A, B and C. These correspond to the three bits of the binary code. The term binary means these can only be 0 or 1 and no other digits are allowed. This can be the raw bits from the user or can be the output signal from the circuits’ device that becomes the input of the decoder.
The 3 to 8 decoder has eight possible output pins. These are usually denoted as Y0, Y1, Y2,..., Y7 and the output is obtained only at one of these pins. The output depends on the binary combination of the input provided to it. In large circuits, its output is fed into any other component and the circuit works.
As mentioned before, the combination of the binary input decides the output. Only one of the eight output pins of the decoder gets high which means, only one output has the value of one and all others are zero. The high pin is considered active and all other pins are said to be inactive.
The truth talbe of all the inputs and possible output of 3 to 8 decoders are given here:
Input MSB (A) |
Input B |
Input LSB (C) |
Active Output |
Y0 |
Y1 |
Y2 |
Y3 |
Y4 |
Y5 |
Y6 |
Y7 |
0 |
0 |
0 |
Y0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
Y1 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
Y2 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
1 |
Y3 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
Y4 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
1 |
0 |
1 |
Y5 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
1 |
1 |
0 |
Y6 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
1 |
1 |
1 |
Y7 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
Here,
MSB= Most significant bit
LSB= Least significant bit
I hope the above concepts are now clear with the help of this truth table.
The 74LS138 is a popular integrated circuit IC that is commonly used 3 to 8 line decoder. It is one of the members of 74LS therefore, it is named so. The 74LS is a group of transistor transistor logic (TTL) chips. The basic feature of this IC is to get three inputs and provide the signal on only one pin of the output automatically based on the binary inputs. In addition to the input, output, and functionality of the 74LS138, there are some additional features listed below:
The 74LS138 has the cascading feature which means, two or more 74LS138 can be connected together to enhance the number of output lines. The circuit is arranged in such a way that the output of one 74LS138 IC becomes the input of the other and as a result, more than one ICs can work together.
The structure of this IC is designed in such a way that it provides high-speed operation. It is done because the decoders are supposed to decode the input so quickly that its output may stimulate other functions of the circuits.
The TTL compatibility of the 74LS138 makes it more accurate. The LS in its name indicate that these are part of low-power shotkey series therefore, these can be operated at the 5V power supply. This makes it ideal for multiple electronic circuits and these do not require any additional device to get accurate power.
These ICs are versatile because they come in different packages and the users can have the right set of ICs depending on the circuit he is using. Two common packages of this IC are given next:
DIP (Dual Inline Package)
SOP (Small Outline Package)
It has multiple modes of operation therefore, it has versatile applications.
Before using any IC in the circuit, it is important to understand its pinouts. The 73LS138 has the 16 pins structure that which is shown here:
The detailed names and features of these pins can be matched with the table given below:
Pin Number |
Pin Name |
Pin Function |
1 |
A |
Address input pin |
2 |
B |
Address input pin |
3 |
C |
Address input pin |
4 |
G2A |
Active low enable pin |
5 |
G2B |
Active low enable pin |
6 |
G1 |
Active high enable pin |
7 |
Y7 |
Output pin |
8 |
GND |
Ground pin |
9 |
Y6 |
Output pin 6 |
10 |
Y5 |
Output pin 5 |
11 |
Y4 |
Output pin 4 |
12 |
Y3 |
Output pin 3 |
13 |
Y2 |
Output pin 2 |
14 |
Y1 |
Output pin 1 |
15 |
Y0 |
Output pin 0 |
16 |
VCC |
Power supply pin |
The structure and working of this IC can be understood by creating a project with it and for this, we have chosen the Porteus to show the detailed working. Here are the steps to create the project of a 3 to 8 line decoder in Proteus:
Open your Proteus software.
Create a new project.
Go to the pick library by clicking the “P” button at the left side of the screen. It will show you a search box with details of the components.
Here, type 74LS138 and you will see the following search:
Double click on the IC to collect it on your devices.
Selecting this IC, click on the working sheet to place it there.
You can see the pins and labels of this IC.
The 74LS138 requires some additional components to be used as a decoder. Here is the project where we are using it as 3 to 8 line decoder:
74LS138 IC
8 LEDs of different colors
Switch SPDT
Switch SPST
Switch Mom
Switch (simple)
Connecting wires
Go to the pick library and get all the components of the circuits one after the other.
Set the 74LS138 IC in the working area.
On the left side of the IC, arrange the switches to be used as the input devices.
On the left side of the IC, arrange the LEDs that will indicate the output.
Go toto the terminal mode from the left side of the screen and arrange the ground and power terminals with the required devices.
The circuit at this point must look like the following image:
Connect all of these with the help of connecting wires. For convenience, I am using the labels to have better work:
Once you have connected all the components, the circuit is ready to use. In the left bottom corner, search for the play button and run the project.
Change the input with the help of switches and check for the output LEDs. You will see the circuit works exactly according to the truth table.
The 74LS138 is designed to be used as a 3 to 8 line so there is no need to connect different ICs and components to design the working of this decoder.
The input and output pins are present with this IC therefore, the user simply connects the switches as an input device. A switch has only two possible states that are either on or off therefore, it is an ideal way to present the binary input.
Usually, LEDs are used as the output devices so that when they get the signal, they are turned on and vice versa.
The ground and power terminals are used to complete the circuit.
Pins 4, 5, and 6 are called the enabled pins. These are labeled as E1, E2, and E3 pins. Out of these, E1 and E2 are considered as the active low pins which means, these are active only when they are pulled down. On the other hand, the E3 is considered an active high; hence it activates the output only when it is pulled high.
Once the circuit is complete, the user can change the binary inputs through the switches and check for the output LEDs.
The combination of inputs results in the required output hence the user can easily design the circuit without making any technical changes.
Today, we have seen the details of 74LS138 decoder IC in Proteus. We started with the basic introduction of a decoder and saw what is the 3 to 8 line decoder isdecoder. After that, we saw the truth table and the features of a 3 to 8 line decoder. We saw how 74LS128 works and in the end, we designed the circuit of a 3 to 8 line decoder using 74LS138. The circuit was easy and we saw it working in detail. If you have any questions, you can ask in the comment section.
Step into the world of precision engineering—where custom CNC machined parts transform raw materials into the sinews and bones of your next big project. Like a tailor crafting a bespoke suit, CNC machining offers an unparalleled fit for your specific requirements.
The prospect of holding your idea in your hands, not just on paper, is the realm where imagination meets implementation. But what options lie at your fingertips? Let's explore the paths to turning those digital blueprints into tangible assets.
Before the whirring of machines begins, your quest starts with choosing the right material—a decision as critical as selecting the foundation for a skyscraper. Each material whispers its own strengths and secrets, waiting to align with your project's demands.
For starters, aluminum stands out as a front-runner in popularity due to its lightweight yet robust nature —an ally for components in aerospace or portable devices. Imagine the sleek body of a drone or the frame of a prototype sports car; they likely share an aluminum heartbeat.
Stainless steel steps forward for projects where endurance and rust resistance are paramount. Think of medical devices that can withstand repetitive sterilization or marine parts whispering secrets to ocean waves without fear of corrosion.
Image Source: Pixabay
Delving deeper into specialties, titanium emerges when the strength-to-weight ratio is not just a preference but a necessity—ideal for high-performance sectors such as motorsports or prosthetics.
Brass occupies a niche where electrical conductivity must dance elegantly with malleability—perhaps in custom electronic connectors or intricate musical instruments.
Each material imparts its essence to your project, shaping not just function but also future possibilities. Which one will be the bedrock for your engineering aspirations?
The next step on our journey approaches like the unveiling of a trail in dense fog—selecting the appropriate CNC machining process that will breathe life into your vision. Each method manifests its prowess through sparks and shavings, ready to tackle complexity with finesse.
Better yet, since there are a variety of machines from Revelation Machinery on offer, with second-hand units representing better value than new equivalents, you can pick one of the following without breaking the bank or limiting yourself in terms of functionality and features.
3-axis milling is like the steadfast hiker; it's reliable and perfect for parts with fairly simple geometries. If your project involves creating a prototype bracket or a basic gear, this could be your marching tune. But when contours call for more intricate choreography, 5-axis milling pirouettes onto the stage. It invites you to envision turbine blades sculpted with aerodynamic grace or an ergonomic joystick that fits into hands as naturally as pebbles on a beach.
Image Source: Pixabay
Turning—the spinning dance between material and tool—offers cylindrical mastery manifested in objects rotating around their own axis. This is where items such as shafts for motors or precision rollers for conveyor systems are born from rotation's embrace.
But what if your piece hides complex internal features, akin to secret passages within a castle? Enter EDM—Electrical Discharge Machining —a process where electrical sparks rather than physical cutting tools unlock hidden gems. Ideal perhaps for making intricate molds used in injection molding machines that will churn out hundreds of thousands of perfectly replicated plastic knights.
As if wielding a magic wand, wire EDM carves with finesse where traditional tools cannot tread, slicing through hardened steel as easily as a hot knife through butter. Consider the labyrinthine path of a lightweight gear or the delicate framework of an instrument sensor—wire EDM is your guide through these intricate landscapes.
Then there’s the level-headed sibling in this family, plunge/sinker EDM—an ace up your sleeve when three-dimensional complexity calls. It's perfect for forming punch and die combinations used in manufacturing presses that shape sheet metal into automotive body panels or appliance housings with clockwork precision.
The truth nestled within these processes promises tailored solutions to even the most enigmatic engineering puzzles. Your custom CNC machined part will emerge from its fiery birthright not just created, but crafted with intent. In this emporium of efficiency and accuracy, which CNC sorcery will you enlist to transform your concept into creation?
Now that the form has been forged, it's time for the maestro—finishing—to step up and conduct a symphony of surfaces. This is where rough edges soften and exteriors gleam, ready for their grand debut.
Anodizing tiptoes onto stage left, offering its protective embrace to aluminum parts. It’s a finish that doesn't just add a splash of color but also bolsters resistance to wear and corrosion. Picture an aerospace fitting beaming with radiant blue or a fire engine red bicycle frame standing resilient against scratches and weathering.
Powder coating strides in with its own brand of rugged beauty—a finish that cloaks objects in a uniform, durable skin impervious to the elements. Outdoor machinery basks in its shielding layer, flaunting colors that withstand sun, rain, and the passage of seasons.
Image Source: Pixabay
For components that need to glide together as smoothly as ballroom dancers, you’ll want to consider precision grinding. Imagine automotive pistons or mechanical bearing races—their surfaces milled down to microscopic levels for tolerances tighter than a drum skin.
Perhaps your masterpiece calls for an understated elegance; then bead blasting might brush across the scene. It leaves behind a matte texture that diffuses light and speaks to sophistication. Its application speaks volumes on products where glare is the enemy and understated aesthetics are paramount—like the dashboard of a luxury car or the casing of high-end audio equipment, where touch and sight merge into user experience.
Let's not forget electroplating—the alchemist's choice that transmutes base metals into gold, well, in appearance at least. Here we witness components such as plumbing fixtures or electronic connectors being vested in extra layers for improved conductivity and aesthetic appeal, shimmering with purpose and resilience.
If subtlety is your aim, then passivation is your unassuming guardian. Stainless steel medical instruments or food processing parts bask in this chemical bath, emerging more stoic against rust and degradation—an invisible shield for an unspoken duty.
As the encore approaches with laser etching taking center stage, customization reaches another level. It allows you to adorn surfaces with serial numbers, logos, or intricate patterns—turning each part into a storyteller of its own journey from concept to finality.
All this info should set you up to make smart decisions ahead of creating custom CNC machined parts for any engineering project you have in the pipeline. And it’s worth restating that as well as choosing carefully, buying used machinery is another way to get great results that will make your budget manageable.
In today's digital age, remote workers are on the frontlines of an invisible war, battling unseen cyber threats. As they maneuver through the complex terrain of remote work environments, they're confronted with potential hazards at every turn.
From a compromised network and data breach to phishing attacks, remote workers are tasked with safeguarding the organization's digital fort.
The remote workforce is instrumental in building a cybersecurity culture where everyone becomes their own expert, advocating for security measures and promptly reporting suspicious activities. This culture is particularly significant in virtual office environments, where workers are the custodians of sensitive data.
As remote employees constantly face cybersecurity challenges, from unsecured Wi-Fi networks to malware attacks, their actions shape the security landscape of their organization.
This environment isn't built overnight but through continuous education and reinforcement of secured virtual office tools from trusted providers like iPostal1 .
While remote workers are integral to building a cybersecurity culture, it's equally essential to have secure network access, especially when working virtually. Remote work security risks are abundant. Hence, implementing cybersecurity solutions for remote working is critical.
Secure network access can be achieved through virtual private networks (VPNs), providing a safe conduit for data transmission.
However, a virtual private network alone isn't enough. Multi-factor authentication (MFA) adds an extra layer of security, reducing the possibility of unauthorized system access. With MFA, even if a cybercriminal cracks your password, they're still one step away from breaching your account.
Even though you've secured your network access, don't overlook the importance of password protection and router security in maintaining robust online network security.
Remote workers must change default passwords on home routers and ensure the creation of strong, unique ones. Regular reminders to change these passwords can also help strengthen the router's security.
Moreover, using a mix of characters, numbers, and symbols and avoiding easily guessable phrases can fortify password protection. Remember, the stronger the password, the more challenging it is for cybercriminals to breach it.
Staying ahead in the cybersecurity game requires continuously reviewing and enhancing these protection measures.
Building on the importance of password protection and router security, remote working involves instituting cybersecurity policies and best practices to further safeguard the virtual office environment.
While remote workers assess the cybersecurity challenges in virtual office environments, they must learn the vital role these policies play in protecting sensitive company data.
Cybersecurity policies cover all aspects of data handling, from remote access procedures to transfer and storage. It includes guidelines on secure network use, encryption protocols, and device security.
Businesses must ensure their policies are comprehensive to address all areas where sensitive company information might be at risk. Regularly reviewing and updating these policies will help organizations avoid emerging threats.
To ramp up the company's cybersecurity defenses, remote work leaders should prioritize installing robust anti-malware software and educating their team on how to avoid phishing scams.
Anti-malware software is the first line of defense against cybersecurity threats, capable of detecting and neutralizing malicious programs before they infiltrate the system.
But software alone isn't enough. Phishing prevention is equally important, as phishing attacks are increasingly sophisticated, often involving social engineering attacks. These scams trick remote workers into revealing sensitive information, compromising security.
The combination of both robust software and thorough education is vital to a secure virtual office environment.
As remote workers fortify their virtual office's cybersecurity, focusing on security infrastructure and strengthening authentication methods is critical.
Robust authentication methods help to ensure that only authorized individuals have access to sensitive data. Remote work leaders must consider biometrics as an additional layer of security for personal devices.
Whether fingerprint scanning, facial recognition, or voice patterns, these technologies can add a more secure, personal touch to remote work authentication methods.
To enhance cybersecurity, remote work leaders must implement a zero-trust strategy for cloud security. A zero-trust approach assumes no user or device is trustworthy, be it inside or outside the network.
This strategy demands verification for every access request, thus reducing the cybersecurity risks of data breaches.
As virtual office environments become more prevalent, the cybersecurity risks and challenges they present require advanced strategies.
Before implementing a zero-trust strategy, assessing your data's sensitivity and storage locations is critical. Remember, zero trust should only be applied where it aligns with your organization's needs and capabilities.
This approach is particularly beneficial for protecting data stored in the cloud . By assessing cybersecurity challenges and adopting a zero-trust strategy, you bolster your defenses against potential threats.
Just like implementing a zero-trust strategy, adapting to new technologies is crucial to fortifying your virtual office's cybersecurity. However, ensuring your employees are well-versed in these changes is equally vital.
Before introducing new systems or software, verifying compatibility with the existing tech stack is crucial. This step will help avoid potential conflicts or vulnerabilities arising from integrating new technology.
The next step is educating remote work staff. This part goes beyond simply training employees on how to use new software. It's about making them understand why these changes are necessary for security.
Educating remote work employees on the importance of cybersecurity can encourage a culture of vigilance and active participation in your defense strategy.
Regular training sessions, updates on emerging threats, and clear communication lines for reporting suspicions are essential. These measures will empower your workforce to contribute effectively to your cybersecurity efforts.
By keeping them informed and providing them with the remote working tools they need, employees can be an asset in protecting virtual office data from potential threats.
Balancing cost and robust security measures is no small feat. Yet, with diligent attention to network access, secure passwords, and comprehensive policies, remote workers can successfully navigate these murky waters. Embrace a zero-trust strategy and wield new technologies to be steadfast guardians. Remember, every vigilant eye is a lighthouse against potential threats in cybersecurity.
By using CNC-machined parts for your next engineering project, you can ensure precision, quality, and speed. So, let us take a look at three options for creating custom parts.
Before we look at the three options available to you, it is worth briefly explaining what CNC machining is. CNC machining is short for Computer Numerical Control. It is a modern manufacturing method that involves the use of computer-controlled machinery to make custom parts.
The process begins with creating a CAD design of the part you want to make. The design is then translated into g-code and fed into the item of CNC machinery.
The machine then simply gets to work at creating your design with the utmost precision and consistency. The types of CNC machines
range widely – from milling machines and lathes to routers and grinders. Each type has its unique advantages depending on your specific production needs.
CNC machining comes with numerous benefits. These include improved efficiency, enhanced safety, consistent quality, and significant time savings.
Additionally, this manufacturing method allows for a wide range of materials to be used. Metals like steel and aluminum are common. But plastics like nylon or ABS as well as wood can be processed.
Now, here are your three options for creating the custom CNC machined parts you need for your next engineering project .
Firstly, you have the option to purchase new CNC machinery. If the scale of your project is substantial or if you foresee continuous use, investing in new machinery could well be the best economical choice in the long run.
New CNC machines represent the crux of modern manufacturing technology. They usually have more current features and capabilities compared to older models – including newer software, which offers advanced programming and control options that result in more accuracy and speed.
Remember, when it comes to large-scale repetitive tasks or projects demanding high precision and consistency, nothing beats the efficiency of these machines, so it could definitely be worth investing in the purchase of one or more CNC machines.
Furthermore, owning CNC machinery means you have unrestricted access anytime according to your production schedule’s needs.
Additionally, most new models come complete with warranties that offer maintenance services and part replacement plans from manufacturers. However, a critical factor here is the cost consideration, as top-tier CNC machinery can carry hefty price tags up front.
That being said, many businesses find that prices eventually pay off through improvements in production efficiency, product uniformity, and reductions in material waste.
Overall, acquiring new CNC machinery is not just an asset purchase but an investment towards improved operational efficiency and product quality for your upcoming projects.
A cheaper option is to buy used CNC machinery for your engineering project. This alternative can be particularly attractive if you are working with a limited budget or if the project is not continuous or large-scale.
Used CNC machines often come at a much lower price point in comparison to new ones. Depending on factors such as age, condition, and functional capacity, you might discover good deals that cater perfectly to your needs without straining your budget.
While they may lack some of the advanced functions found in the newest models, well-maintained used machines can still provide commendable performance in precision and repetitive tasks.
However, take note that maintenance consideration is key. Since warranties may not be available for older models, setting aside a budget for potential repairs is prudent.
Lastly, you may want to consider using an online CNC machining service for manufacturing the custom machined parts
you need for your next engineering project. This option can be the most suitable if you do not have the needed expertise in-house or you lack sufficient workspace. You can also avoid the hefty upfront costs of purchasing machinery.
Online CNC services open up a world of opportunities. They allow access to professional and experienced machinists who operate state-of-the-art machines that cater to virtually any custom specifications. This ensures high-quality parts with excellent precision.
Plus, using such services lifts off the time and effort normally needed for maintaining machines and training personnel. All you need is your digital design file. The service provider will take care of turning your design into a physical part or component.
For your upcoming engineering project, the possibilities of CNC machined parts you could produce are vast. Whether your project demands small individual components or larger assemblies, CNC machining can cater to them all with unyielding precision.
You can easily manufacture custom components that are specifically tailored to your project’s needs. Here are just some of the common types of CNC machined parts used in engineering projects.
One common part that you can create using CNC machining is gears. Various types such as helical, bevel, or worm gears can be accurately machined. Gears are fundamental in various machinery configurations where power transmission is required.
CNC machines are also perfect for creating flanges, which are flat rims that enhance strength or provide a method for attachment. As standard components in piping systems, flanges serve to connect pipes or aid in maintenance access points.
You can fabricate enclosures too – they serve as protective cases for delicate electrical or mechanical devices. Accurate machining ensures that interior elements fit perfectly while external dimensions comply with assembly requirements.
Machined plates are another type of part you could manufacture with CNC machinery. They are used in numerous applications, ranging from mounting brackets to structural support elements.
CNC machining is quite useful when making shafts from materials of your choice. Shafts serve as a mechanical component used in power transmission. The exact sizing and surface finish are critical for these elements, which CNC machining can accurately achieve.
The above list is far from exhaustive. The versatility of CNC machining allows you to create almost any part that your specific engineering project might necessitate.
So, explore the options of buying new CNC machines or used CNC machines in comparison to outsourcing the manufacturing to determine which method to use for creating custom parts for your next project. You may also be interested in learning how industrial robots are revolutionizing engineering projects.
Hello readers! I hope you are doing great. Today, we are discussing the latest library for proteus. In the tutorial, we will look at the Arduino Mega 2560 library for Porteus V 3.0, which is one of the most versatile and useful microcontrollers from the Arduino family. We have shared the previous versions with you before this; these were the Arduino Mega 2560 library for Proteus and the Arduino Mega 2560 library for Proteus V2.0. The current version is better in structure and does not have a link to the website so you may use it in your projects easily.
Here, I will discuss the detailed specifications of this microcontroller. After that, I will show you the procedure to download and install this library in the Proteus and in the end, we’ll create a mini project using this microcontroller. Here is the introduction to the Arduino Mega 2560:
| Where To Buy? | ||||
|---|---|---|---|---|
| No. | Components | Distributor | Link To Buy | |
| 1 | Buzzer | Amazon | Buy Now | |
| 2 | Arduino Mega 2560 | Amazon | Buy Now | |
The Arduino Mega 2560 belongs to the family of Arduino microcontrollers and is one of the most important devices in embedded systems. Here are some of its specifications:
Specification |
Value |
Microcontroller |
ATmega2560 |
Operating Voltage |
5V |
Input Voltage (recommended) |
7-12V |
Input Voltage (limit) |
6-20V |
Digital I/O Pins |
54 (of which 15 provide PWM output) |
Analog Input Pins |
16 |
DC Current per I/O Pin |
20 mA |
DC Current for 3.3V Pin |
50 mA |
Flash Memory |
256 KB (8 KB used by bootloader) |
SRAM |
8 KB |
EEPROM |
4 KB |
Clock Speed |
16 MHz |
LED_BUILTIN |
Pin 13 |
Length |
101.52 mm |
Width |
53.3 mm |
Weight |
37 g |
Now that we know the basic features of this device, we can understand how it works in Proteus.
This library is not present by default in Porteus. The users have to download and install it in the Porteus library folder. Click on the following link to start the downloading process:
Arduino Mega 2560 V3.0 for Proteus
If the downloading process is complete, you can see a zip file in the downloading folder of your system. Click on it.
Extract the zip folder at the desired location.
Along with some other files, you can see there are two files with the following names in the zip folder:
ArduinoMega3TEP.IDX
ArduinoMega3TEP.LIB
You have to copy these two files only and go to the folder of the given path:
C>Program files>Lab centre electronics>Proteus 7 Professional>Library
If you want more details on this process, you must see How to Add a New Library File in Proteus .
Note: The procedure to install the same package in Proteus Professional 8 is the same.
Now, the Arduino Mega 2560 V3.0 can be run on your Proteus software. Open your Proteus software or if it was already opened, restart it so the libraries may load successfully.
Click on the “P” button on the left side of the screen and it will open a search box for devices in front of you.
Here, type “Arduino Mega 2560 V3.0,” and it will show you the following device:
Double-click on it to pick it up.
Close the search box and click on the name of this microcontroller from the pick library section present on the left side.
Place it in the working area to see the structure of the Arduino Mega 2560 V3.0.
If you have seen the previous versions of this microcontroller in Proteus, you can see that the latest version has some changes in it. The design and colour are closer to the real Arduino Mega 2560. Moreover, it does not have a link to the website and the pins are more realistic.
The workings of the Arduino Mega 2560 V3.0 library can be understood with the help of a simple project. Let’s create one. For this, follow the steps given here:
Now, connect all the components through the connecting wires. Here is the final circuit:
Now, it's time to add code to the simulation.
const int buttonPin = 2; // Pin connected to the button
const int speakerPin = 3; // Pin connected to the speaker
int buttonState = 0; // Variable to store the button state
boolean isPlaying = false; // Variable to track whether the speaker is playing
void setup() {
pinMode(buttonPin, INPUT);
pinMode(speakerPin, OUTPUT);
}
void loop() {
// Read the state of the button
buttonState = digitalRead(buttonPin);
// Check if the button is pressed
if (buttonState == HIGH) {
// Toggle the playing state
isPlaying = !isPlaying;
// If playing, start the speaker
if (isPlaying) {
digitalWrite(speakerPin, HIGH);
} else {
// If not playing, stop the speaker
digitalWrite(speakerPin, LOW);
}
// Add a small delay to debounce the button
delay(200);
}
}
You can get the same code from the zip file you have downloaded from this tutorial.
Click on the "verify" button present on the above side of the code.
Once the loading is complete, click on the “upload” button present just at the side of the verify button. It will create a hex file in your system.
From the console of loading, search for the address of the file where the code is saved.
In my case, it looks like this:
Copy this path to the clipboard.
Once again, go to your Proteus software.
Click on the Arduino Mega 2560 to open its control panel.
Paste the path of the hex file in the place of the program file:
Hit the “OK” button to close the window.
Once you have loaded the code into the microcontroller, you can now run the project.
At the bottom left side of the project, you can see different buttons, click on the play button to run the project.
Before clicking on the button of the project, the project looks like the following:
Once the button is pressed, you will hear the sound from the speaker. Hence, the speaker works with the button.
If all the above steps are completed successfully, you will hear the sound of the speaker. I hope all the steps are covered in the tutorial and you have installed and run the Arduino Mega 2560 v3.0 in Proteus, but if you want to know more about this microcontroller, you can ask in the comment section.
Hello friends! I hope you are doing great. Today, we are discussing the latest version of the Arduino Mega 1280 library for Proteus. This can be used in both versions (Proteus 7 and Proteus. We have shared the previous versions, which are the Arduino Mega 1280 library for Proteus and the Arduino Mega 1280 library for Proteus V2.0 with you. With the advancement in the version, these microcontrollers have a better structure and the design is closer to the real microcontrollers.
In this article, I will discuss the introduction of the Arduino Mega 1280 in detail. Here, you will learn the features and functions of this microcontroller. Then, we’ll see how to download and install this library in Proteus. In the end, we’ll see a mini project using the Arduino Mega 1280 V3.0. Let’s move towards our first topic:
| Where To Buy? | ||||
|---|---|---|---|---|
| No. | Components | Distributor | Link To Buy | |
| 1 | Battery 12V | Amazon | Buy Now | |
| 2 | Resistor | Amazon | Buy Now | |
| 3 | LCD 20x4 | Amazon | Buy Now | |
Now, let’s see the Arduino Mega 1280 library V3.0 in Porteus.
The download and installation process for Arduino Mega 1280 is easy. The Proteus software does not have this library by default. To use it, the first step is to download it from the link given below:
Arduino Mega 1280 V3.0 for Proteus
The downloading does not take much time. Once it is complete, it can be seen in the download folder on your system.
You will see a zip file when it is extracted to a particular path of your choice.
There are two files in the folder named:
ArduinoMega3TEP.IDX
ArduinoMega3TEP.LIB
Copy these files and paste them into the folder with the following path:
C>Program files>Lab centre electronics>Proteus 7 Professional>Library
If you want more details on this process, you must see How to Add a New Library File in Proteus .
Note: The same process is applicable to Proteus 8 professional if you are using that.
You can see it has many pins and the structure and design are closer to the real Arduino Mega. There is no link to the website on this microcontroller and it has more details about the pins on it. These points are different from the previous versions.
The Arduino Mega 1280 has many features and it is used in a great number of projects. But, as a beginner, we’ll check the work with the help of a simple project. In this project, we’ll use the LED with Arduino Mega 1280 V3.0 and print the message of our own choice. Follow the steps to perform this example:
Go to the terminal mode from the left side of the screen, and then choose the default pins for the clean circuit.
Set and label the pins according to the image given here:
The circuit is fine but it can’t be run without coding.
Fire up your Arduino IDE.
Create a new sketch for this project.
The upper side has a drop-down menu, choose Arduino from there.
Delete the default code.
Paste the following code into it:
#include
//Setting the LCD pins
LiquidCrystal lcd(13, 12, 11, 10, 9, 8);
const int buttonPin = 0;
boolean lastButtonState = LOW;
boolean displayMessage = false;
void setup() {
pinMode(buttonPin, INPUT);
//Printing the first message
lcd.begin(20, 4);
lcd.setCursor(1, 0);
lcd.print("Press the button to see the message");
}
void loop() {
int buttonState = digitalRead(buttonPin);
// Using if loop to create the condition
if (buttonState != lastButtonState) {
lastButtonState = buttonState;
if (buttonState == LOW) {
displayMessage = true;
lcd.clear();
lcd.setCursor(1, 0);
//Printing the message on screen when buttin is pressed
lcd.print("www.TheEngineering");
lcd.setCursor(4, 1);
lcd.print("Projects.com");
} else {
displayMessage = false;
lcd.clear();
lcd.setCursor(1, 0);
lcd.print("Press the button to see the message");
}
}
}
The same code is also present in the zip file of the Arduino Mega 1280 V3.0 library folder you have downloaded.
Click on the tick mark to run the code. It will take some moments to be loaded.
Once the loading is complete, click on the upload button to get the hex file address.
In the loading process, you have to search for the path to the hex file. In my case, it looks like the following image:
Go to the proteus where we have created our project.
Double-click on the Arduino Mega 1280 V3.0 module. It will open its properties panel in front of you.
Paste the address of the hex file into the section named “Program File.".
Hit the “OK” button and close the window.
There are some buttons at the bottom left corner of the screen. Out of these, you have to click the play button to run the project.
If all the above procedures are completed successfully, you will see the output on the screen.
When the button is opened, the LCD shows the message that you have to push the button to see the message.
Click on the button, and now you can see the message on the LCD.
If all the above steps are completed successfully, you will see that you have used the Arduino Mega 1280 V3.0 to show the required message on the LCD. This microcontroller can be used in different complex projects and can provide the basic working according to the code. Now, you can try different projects on your Proteus. I hope you have installed the microcontroller successfully. Yet, if you are stuck at any point, you can ask in the comment section.
Hello friends! I hope you are doing great. Today, we are presenting another version of the Arduino Pro mini library. We have seen the Arduino Pro Mini library for Proteus and the Arduino Pro Mini library for Proteus V2.0 with you. As expected, the Arduino Mini Library for Proteus V3.0 has a better structure and size that make it even better than the previous ones. We will go through the details of the features to understand the library.
In this article, I will briefly discuss the introduction of Arduino Pro Mini V3.0. You will learn the features of this board and see how to download and install this library in Proteus. In the end, I will create and elaborate on a simple project with this library to make things clear. Let’s move towards our first topic:
| Where To Buy? | ||||
|---|---|---|---|---|
| No. | Components | Distributor | Link To Buy | |
| 1 | Battery 12V | Amazon | Buy Now | |
| 2 | LEDs | Amazon | Buy Now | |
| 3 | Resistor | Amazon | Buy Now | |
| 4 | Arduino Pro Mini | Amazon | Buy Now | |
In the vast range of microcontrollers, the Arduino Pro mini stands as the most powerful and compact member of the Arduino family. With the advancement in the version, the better functionalities and easy working of this microcontroller have been seen. Here are some important features of this microcontroller:
Now, let’s see the Arduino Pro Mini library V3.0 in Porteus.
By default, the Proteus does not have any Arduino Pro mini library. This can be used in Proteus by installing it manually. For this, download the library through the link given next:
Arduino Pro Mini Library for Proteus V3.0
Once the downloading process is complete, you can see a zip folder with the same name in your download folder. Double-click on it or extract the file to the current folder with any other method. Remember the path to this extracted file.
Now, go to the required path and open the folder named “Proteus Library Files.”.
Here, you will find the following files:
ArduinoProMini3TEP.IDX
ArduinoProMini3TEP.LIB
These folders have to be placed in the library folder of Proteus so that we can have them in Proteus.
For this, follow the path C>Program files>Lab centre electronics>Proteus 7 Professional>Library. Simply paste both of these into the folders of other libraries.
If you want the details of this process, you must see How to Add a New Library File in Proteus .
Note: The procedure to add the same library to Proteus 8 is the same.
If you have followed the above procedure successfully, the Arduino Pro mini V3.0 will work in your Proteus. If the software was already open, restart it. Otherwise, open your Proteus software.
Click on the P button on the left side of the screen. This will prompt you to enter the search box.
Here, search for “Arduino Pro Mini V.30,” and if you have installed it successfully, you will see it in the options:
Click on the name “Arduino Pro Mini V3.0.”. It will be shown in the Pick Library of your Porteus.
Click on the name of this microcontroller and double-click on the working area to fix it there.
Look at the structure and pinouts of this Arduino board.
You can see this version has a better structure of pins and is similar to the real Arduino Pro Mini. We have removed the link to the website from this library and created an even smaller Arduino Pro Mini so the users can have a better experience with it.
It’s time to test the workings of this microcontroller in Porteus.
This will not work until we program the Arduino pro Mini in Arduino IDE.
int LED = 2; // the PWM pin the LED is attached to
int brightness = 2; // how bright the LED is
int fadeAmount = 5; // how many points to fade the LED by
void setup() {
// declaring pin 9 to be an output:
pinMode(LED, OUTPUT);
}
void loop() {
// setting the brightness of pin 9:
analogWrite(led, brightness);
// changing the brightness for next time through the loop:
brightness = brightness + fadeAmount;
// reversing the direction of the fading at the ends of the fade:
if (brightness <= 0 || brightness >= 255) {
fadeAmount = -fadeAmount;
}
// waiting for 30 milliseconds to see the dimming effect
delay(50);
}
}
You can have the same code in the zip file you downloaded before through this article. Click on the tick mark at the above side of the screen.
Wait for the loading to complete.
Click on the “Upload” button next to the tick mark. The loading will start at the bottom and you will see the hex file in the console.
Search for the whole address of the hex file to copy it.
Now, the project is ready to be played. Hit the play button to start the simulation.
If all the components are set up well and the project does not have any errors, the simulation will be started.
If all the steps are accomplished completely, your project will run successfully. I hope you have installed and worked with the Arduino Pro mini V3.0 without any errors and you can now create complex projects with this. Still, if you are stuck at any point, you can ask in the comment section.
Hello! I hope you are doing great. Today, we will talk about another modern neural network named gated recurrent units. It is a type of recurrent neural network (RNN) architecture but is designed to deal with some limitations of the architecture so it is a better version of these. We know that modern neural networks are designed to deal with the current applications of real life; therefore, understanding these networks has a great scope. There is a relationship between gated recurrent units and Long Short-Term Memory (LSTM) networks, which has also been discussed before in this series. Hence, I highly recommend you read these two articles so you may have a quick understanding of the concepts.
In this article, we will discuss the basic introduction of gated recurrent units. It is better to define it by making the relations between LSTM and RNN. After that, we will show you the sigmoid function and its example because it is used in the calculations of the architecture of the GRU. We will discuss the components of GRU and the working of these components. In the end, we will have a glance at the practical applications of GRU. Let’s move towards the first section.
The gated recurrent unit is also known as the GRU and these are the types of RNN that are designed for processes that involve sequential data. One example of such tasks is natural language processing (NLP). These are variations of long short-term memory (LSTM) networks, but they have an upgraded mechanism and are therefore designed to provide easy implementation and working features.
The GRU was introduced in 2014 by Kyunghyun Cho, Bart van Merriënboer, Dzmitry Bahdanau, and Yoshua Bengio. They have written the paper with the title "Learning Phrase Representations using Gated Recurrent Units." This paper gained fame because it was published at the 31st International Conference on Machine Learning (ICML 2014). This mechanism was successful because it was lightweight and easy to handle. Soon, it became the most popular neural network for complex tasks.
The sigmoid function in neural networks is the non-linear activation function that deals with values between 0 and 1 as input. It is commonly used in recurrent networks and in the case of GRU, it is used in both components. There are different sigmoid functions and among these, the most common is the sigmoid curve or logistic curve.
Mathematically, it is denoted as: f(x) = 1 / (1 + e^(-x))
Here,
f(x)= Output of the function
x = Input value
When the x increases from -∞ to +∞, the range increases from 0 to 1.
The basic mechanism for the GRU is simple and approaches the data in a better way. This gating mechanism selectively updates the hidden state of the network and this happens at every step. In this way, the information coming into the network and going out of it is easily controlled. There are two basic mechanisms of gating in the GRU:
The following is a detailed description of each of them:
The update gate controls the flow of the precious state. It shows how much information from the previous state has to be retained. Moreover, it also provides information about the update and the new information required for the best output. In this way, it has the details of the previous and current steps in the working of the GRU. It is denoted by the letter z and mathematically, the update gate is denoted as:
Here,
W(z) = weight matrix for the update gate
ℎ(t−1)= Previous hidden state
x(t)= Input at time step t
σ = Sigmoid activation function
The resent gate determines the part of the previous hidden state that must be reset or forgotten. Moreover, it also provides information about the part of the information that must be passed to the new candidate state. It is denoted by "r,” and mathematically,
Here,
r(t) = Reset gate at the time step
W(r) = Weight matrix for the reset gate
h(t−1) = Previous hidden state
x(t)= Input at time step
σ = Sigmoid activation function.
Once both of these are calculated, the GRU then apply the calculations for the candidate state h(t). The “h” in the symbol has a tilde at it. Mathematically, the candidate state is denoted as:
ht=tanh(Wh⋅[rt⋅ht−1,xt]+bh)
When these calculations are done, the results obtained are shown with the help of this equation:
ht=(1−zt)⋅ht−1+zth~t
These calculations are used in different ways to provide the required information to minimize the complexity of the gated recurrent unit.
The gated recurrent unit works by processing the sequential data, then capturing dependencies over time and in the end, making predictions. In some cases, it also generates the sequences. The basic purpose of this process is to address the vanishing gradient and, as a result, improve the overall modelling of long-range dependencies. The following is the basic introduction to each step performed through the gated recurrent unit functionalities:
In the first step, the hidden state h0 is initialized with a fixed value. Usually, this initial value is zero. This step does not involve any proper processing.
This is the main step and here, the calculations of the update gate and reset gate are carried out. This step requires a lot of time, and if everything goes well, the flow of information results in a better output than the previous one. The step-by-step calculations are important here and every output becomes the input of the next iteration. The reason behind the importance of some steps in processing is that they are used to minimize the problem of vanishing gradients. Therefore, GRU is considered better than traditional recurrent networks.
Once the processing is done, the initial results are updated based on the results of these processes. This step involves the combination of the previous hidden state and the processed output.
Since the beginning of this lecture, we have mentioned that GRU is better than LSTM. Recall that long short-term memory is a type of recurrent network that possesses a cell state to maintain information across time. This neural network is effective because it can handle long-term dependencies. Here are the key differences between LSTM and GRU:
The GRU has a relatively simpler architecture than the LSTM. The GRU has two gates and involves the candidate state. It is computationally less intensive than the LSTM.
On the other hand, the LSTM has three states named:
In addition to this, it has a cell state to complete the process of calculations. This requires a complex computational mechanism.
The gate structures of both of these are different. In GRU, the update gate is responsible for the information flow from the current candidate state to the previous hidden state. In this network, the reset gate specifies the data to be forgotten from the previous hidden state.
On the other hand, the LSTM requires the involvement of the forget gate to control the data to be retained in the cell state. The input gates are responsible for the flow of new information into the cell state. The hidden state also requires the help of an output gate to get information from the cell state.
The simple structure of GRU is responsible for the shorter training time of the data. It requires fewer parameters for working and processing as compared to LSTM. A high processing mechanism and more parameters are required for the LSTM to provide the expected results.
The performance of these neural networks depends on different parameters and the type of task required by the users. In some cases, the GRU performs better and sometimes the LSTM is more efficient. If we compare by keeping computation time and complexity in mind, GRU has a better output than LSTM.
The GRU does not have any separate cell state; therefore, it does not explicitly maintain the memory for long sequences. Therefore, it is a better choice for the short-term dependencies.
On the other hand, LSTM has a separate cell state and can maintain the long-term dependencies in a better way. This is the reason that LSTM is more suitable for such types of tasks. Hence, the memory management of these two networks is different and they are used in different types of processes for calculations.
The gated recurrent unit is a relatively newer neural network in modern networks. But, because of the easy working principle and better results, this is used extensively in different fields. Here are some simple and popular examples of the applications of GRU:
The basic and most important example of an application is NLP. It can be used to generate, understand, and create human-like language. Here are some examples to understand this:
The GRU can effectively capture and understand the meaning of words in a sentence and is a useful tool for machine translation that can work between different languages.
The GRU is used as a tool for text summarization. It understands the meaning of words in the text and can summarize large paragraphs and other pieces of text effectively.
The understanding of the text makes it suitable for the question-answering sessions. It can reply like a human and produce accurate replies to queries.
The GRU does not only understand the text but is also a useful tool for understanding and working on the patterns and words of the speech. They can handle the complexities of spoken languages and are used in different fields for real-time speech recognition. The GRU is the interface between humans and machines. These can convert the voice into text that a machine can understand and work according to the instructions.
With the advancement of technology, different types of fraud and crimes are becoming more common than at any other time. The GRU is a useful technique to deal with such issues. Some practical examples in this regard are given below:
Today, we have learned about gated recurrent units. These are modern neural networks that have a relatively simple structure and provide better performance. These are the types of recurrent neural networks that are considered a better version of long short-term neural networks. Therefore, we have discussed the structure and processing steps in detail and in the end, we compared the GRU with the LSTM to understand the purpose of using it and to get an idea about the advantages of these neural networks. In the end, we saw practical examples where the GRU is used for better performance. I hope you like the content and if you have any questions regarding the topic, you can ask them in the comment section.
Hey readers! Welcome to the next lecture on neural networks. We are learning about modern neural networks, and today we will see the details of residual networks. Deep learning has provided us with remarkable achievements in recent years, and residual learning is one such output. This neural network has revolutionized the design and training process of the deep neural network for image recognition. This is the reason why we will discuss the introduction and all the content regarding the changes these network has made in the field of computer vision.
In this article, we will discuss the basic introduction of residual networks. We will see the concept of residual function and understand the need for this network with the help of its background. After that, we will see the types of skip connection methods for the residual networks. Moreover, we will have a glance at the architecture of this network and in the end, we will see some points that will highlight the importance of ResNets in the field of image recognition. This is going to be a basic but important study about this network so let’s start with the first point.
Residual networks (ResNets) were introduced by Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun in 2015. They introduced the ResNets, for the first time, in the paper with the title “Deep Residual Learning for Image Recognition”. The title was chosen because it was the IEEE Conference for Computer Vision and Pattern Recognition (CVPR) and this was the best time to introduce this type of neural network.
These networks have made their name in the field of computer vision because of their remarkable performance. Since their introduction into the market, these networks have been extensively used for processes like image classification, object detection, semantic segmentation, etc.
ResNets are a powerful tool that is extensively used to build high-performance deep learning models and is one of the best choices for fields related to images and graphs.
The residual functions are used in neural networks like ResNets to perform multiple functions, such as image classification and object detection. These are easier to learn than traditional neural networks because these functions don’t have to learn features from scratch all the time, but only the residual function. This is the main reason why residual features are smaller and simpler than the other networks.
Another advantage of using residual functions for learning is that the networks become more robust to overfitting and noise. This is because the network learns to cancel out these features by using the predicted residual functions.
These networks are popular because they are trained deeply without the vanishing gradient problem (you will learn it in just a bit). The residual networks allow smooth working because they have the ability to flow through the networks easily. Mathematically, the residual function is represented as:
Residual(x) = H(x) - x
Here,
The background of the residual neural networks will help to understand the need for this network, so let’s discuss it.
In 2012, the CNN-based architecture called AlexNet won the ImageNet competition, and this led to the interest of many researchers to work on the network with more layers in the deep learning neural network and reduce the error rate. Soon, the scientists find that this method is suitable for a particular number of layers, and after that limit, the gradient becomes 0 or too large. This problem is called the vanishing or exploding of the gradient. As a result of this process, the training and testing errors increase with the increased number of layers. This problem can be solved with residual networks; therefore, this network is extensively used in computer vision.
ResNets are popular because they use a specialized mechanism to deal with problems like vanishing/exploding. This is called the skip connection method (or shortcut connections), and it is defined as:
"The skip connection is the type of connection in a neural network in which the network skips one or more layers to learn residual functions, that is, the difference between the input and output of the block."
This has made ResNets popular for complex tasks with a large number of layers.
There are two types of skip connections listed below:
Both of these types are responsible for the accurate performance of the residual neural networks. Out of both of these, short skip connections are more common because they are easy to implement and provide better performance.
The architecture of these networks is inspired by the VGG-19 and then the shortcut connection is added to the architecture to get the 34-layer plain network. These short connections make the architecture a “residual network” and it results in a better output with a great processing speed.
There are some other uses of residual learning, but mostly these are used for image recognition and related tasks. In addition to the skip connection, there are multiple other ways in which this network provides the best functionality in image recognition. Here are these:
It is the fundamental building block of ResNets and plays a vital role in the functionality of a network. These blocks consist of two parts:
Here, the identity path does not involve any major processing, and it only passes the input data directly through the block. Whereas, the network learns to capture the difference between the input data and the desired output of the network.
The residual neural network learns by comparing the residuals. It compares the output of the residual with the desired output and focuses on the additional information required to get the final output. This is one of the best ways to learn because, with every iteration, the results become more likely to be the targeted output.
The ResNets are easy to train, and the users can have the desired output in less time. The skip connection feature allows it to go directly through the network. This is applicable even in deep architecture, and the gradient can flow easily through the network. This feature helps to solve the vanishing gradient problem and allows the network to train hundreds of layers efficiently. This feature of training the deep architecture makes it popular among complex tasks such as image recognition.
The residual network can adjust the parameters of the residual and identity paths. In this way, it learns to update the weights to minimize the difference between the output of the network and the desired outputs. The network is able to learn the residuals that must be added to the input to get the desired output.
In addition to all these, features like performance gain and best architecture depth allow the residual network to provide significantly better output, even for image recognition.
Hence, today we learned about a modern neural network named residual networks. We saw how these are important networks in deep learning. We saw the basic workings and terms used in the residual network and tried to understand how these provide accurate output for complex tasks such as image recognition.
The ResNets were introduced in 2015 at a conference of the IEE on computer vision and pattern recognition (CVPR), and they had great success and people started working on them because of the efficient results. It uses the feature of skip connections, which helps with the deep processing of every layer. Moreover, features like residual block, learning residuals, easy training methods, frequent updates of weights, and deep architecture of this network allow it to have significantly better results as compared to traditional neural networks. I hope you got the basic information about the topic. If you want to know more, you can ask in the comment section.