Sunday, 17 February 2019

What are Ultrasonic Sensors ? How do they work ? || techtalksgroup ||

theprogrammer.harshit  February 17, 2019    No comments


When you need input from the real world to your robot or data collection system, there are several options to choose from:

• Light detection (infrared sensors, light-dependent resistors, and computer vision setups)

• Sensors based on magnetic fields

• Ultrasonic sensors

How do Ultrasonic Sensors Work?


Ultrasonic sensors work by emitting sound waves at a frequency too high for humans to hear. They then wait for the sound to be reflected back, calculating distance based on the time required. This is similar to how radar measures the time it takes a radio wave to return after hitting an object.

While some sensors use a separate sound emitter and receiver, it’s also possible to combine these into one package device, having an ultrasonic element alternate between emitting and receiving signals. This type of sensor can be manufactured in a smaller package than with separate elements, which is convenient for applications where size is at a premium.

While radar and ultrasonic sensors can be used for some of the same purposes, sound-based sensors are readily available—they can be had for just a couple dollars in some cases—and in certain situations, they may detect objects more effectively than radar.

For instance, while radar, or even light-based sensors, have a difficult time correctly processing clear plastic, ultrasonic sensors have no problem with this. In fact, they’re unaffected by the color of the material they are sensing.

On the other hand, if an object is made out of a material that absorbs sound or is shaped in such a way that it reflects the sound waves away from the receiver, readings will be unreliable.

If you need to measure the specific distance from your sensor, this can be calculated based on this formula:

Distance = ½ T x C

(T = Time and C = the speed of sound)

At 20°C (68°F), the speed of sound is 343 meters/second (1125 feet/second), but this varies depending on temperature and humidity.

Specially adapted ultrasonic sensors can also be used underwater. The speed of sound, however, is 4.3 times as fast in water as in air, so this calculation must be adjusted significantly.

Applications for Ultrasonic Sensors

So where can we use these sensors? Robot navigation comes to mind, as well as factory automation. Water-level sensing is another good use, and can be accomplished by positioning one sensor above a water surface. Another aquatic application is to use these sensors to “see” the bottom of a body of water, traveling through the water, but reflecting off the bottom surface below.

Though it might not be immediately obvious, if configured correctly ultrasonic sensors can even measure fluid flow rates. In the simplest case, an emitter and a receiver (separate in this configuration) are aligned with the flow of a fluid. Since sound is traveling through a moving medium, the speed of sound relative to these elements will be increased or decreased by the velocity of the fluid. This can be applied to flow inside pipes by aligning these two elements at an angle to each other, calculating the effective velocity increase based on the trigonometric relations between the two. Flowrate accuracy can be increased by using data from multiple ultrasonic elements, giving results accurate to within a fraction of a percent.

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Friday, 1 February 2019

What are the 5 ways you can use #hastags effectively of your Facebook Page . || techtalksgroup ||

theprogrammer.harshit  February 01, 2019    No comments


Do you include Facebook hashtags in your Facebook Page posts?
With 1.15 billion users, Facebook is an attractive place for businesses to market to customers.
Today I’m going to cover Facebook hashtag usage and how your brand can benefit from using Facebook hashtags.

The role of Facebook hashtags in marketing

While Facebook hashtags don’t seem as popular as on Twitter or Instagram, they can still help your brand.
With 1.15 billion users, Facebook is a great place to put your marketing efforts for your business.
When compared to other social networks, no other network comes close when in terms of active user.

Facebook hashtag usage

Don’t overdo Facebook hashtags

While users are encouraged to use on average 11 Instagram hashtags, Facebook hashtag usage is much lower.
For example, you don’t want to use them in every post.
You also don’t want to use too many. 2-3 hashtags typically work best for Facebook hashtag usage.

Hashtags must be one word

I often get asked what is a hashtag.

Capitalization isn’t important

When looking at Facebook hashtag usage, remember, capitalization isn’t important.
For example, using #Facebookmarketing instead of #FacebookMarketing will take users to the same hashtag.
Personally, I like to capitalize the second word. This way it is a little easier to read the hashtag.

Don’t blindly pick a hashtag – research it first

When choosing a hashtag, be sure you’ve done some research.
Not only can they save you a lot of time, but you can also see how popular a hashtag is before beginning your Facebook marketing campaign.


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Monday, 7 January 2019

Have you ever noticed, Why does your Flash Plugins get crashed time to time..?? || techtalksgroup ||

theprogrammer.harshit  January 07, 2019    No comments

The Flash plugin is a small program that works within your browser, allowing you to view and interact with animated files created in Flash format. The reasons for a crash can vary from browser to browser. Here, we'll look at the most likely causes of Flash plugin crashes in Chrome, Firefox and Internet Explorer.

Google Chrome has its own internal Flash installation, unlike Firefox and Internet Explorer, which rely on your computer system's Flash installation to handle Flash content. In some cases, Chrome tries to simultaneously use both its internal version and the installation on your machine, and everything freezes up. To find out if this is the cause of your Flash crash, type "about://plugins" (without quotes) in the address bar of your Chrome window. If you find two Flash files in use, disable one of them and give the site another try.

If duplicate Flash files aren't the source of your problem, you may have software or malware on your system that's causing the crash. To check this, type "chrome://conflicts" into your address bar, and Chrome will display a list of any third-party applications known to conflict with Chrome. You can also check to see if a browser extension such as ad-blocking software may be causing a conflict. Type (you guessed it) "chrome://extensions" into your browser address bar and go down the list one by one to see if disabling one of the extensions resolves the issue.

In Firefox, the most common reason for a Flash plugin crash is an outdated version of the Flash player. To check, go to Mozilla's Plugin Check page and see if Flash needs to be updated. If so, you will need to manually install the latest version of Flash from the Adobe website. If Flash is up to date, try disabling hardware acceleration, first in Flash (you can find this setting in your Adobe Flash Player Settings), then in the Firefox browser itself [source: Mozilla Support]. (Hardware acceleration uses the video or graphics card on your computer for extra processing power when displaying animations or videos.)

Flash plugin crashes seem to be slightly less common in Internet Explorer, but if you do experience a crash, the most likely culprit is an outdated version of Flash. If installing the latest version of Flash Player from the Adobe website doesn't solve the problem, another browser add-on may be causing a conflict. To remove or disable add-ons, click on Manage Add-ons, under the Tools button in Internet Explorer.

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Thursday, 27 December 2018

Problems that may come while implementing IOT || techtalksgroup ||

theprogrammer.harshit  December 27, 2018    No comments

In the coming century, the biggest threat to us will not be the wars between the countries or states. The biggest threat or the war that we should be concerned about is the cyber war. It is a direct threat to our privacy, our private conversations, moments, pictures-everything that sums up our life.
Technology has always been a double-edged sword. With all the benefits and advantages, follows unknown and unprecedented threats. For us to succeed and work in harmony with technology, we need to address and confront the threats that it carries. Simply ignoring or putting them aside is not the solution.
In fact, it is the last thing we can do bring the house of cards crashing down. Ignoring a problem is the same as inviting the problem. And similar is the case with IoT, Internet of Things.
A very less number of people genuinely address the threats and challenges IoT could or will face as part of its journey.

Here Are the 5 Biggest Security Threats and Challenges for IoT

Anything which is connected to the Internet is open to threat. Like the saying goes, ‘There are two types of companies. One which has been hacked and one which does not not know it has been hacked.’ This rightly sheds some light on the fact that, we are always vulnerable. It all depends upon how less vulnerable you are.
Until and unless we do not address and come face to face with the evil of Internet, we would not be able to create counter measures that protect us from these threats.
Any threat, be it on IoT or on a website, is backed by a purpose. In 100% of the cases, these threats or attacks are human generated. The purpose may vary depending upon the intruder’s target:
i) Since IoT devices are used and operated by humans, an intruder may want to gain unsolicited access to the human.
ii) By eavesdropping on the wireless IoT devices the intruder may want to catch hold of confidential information.
iii) IoT devices run on low power and less computing resource capability, due to this they cannot afford to have complex security protocols. Hence, it becomes an easy target for intruders.

Vulnerability

The most basic and easy to pick threat to IoT devices is its vulnerability. Companies providing IoT solutions start with addressing this issue first before commemorating on the underlying software.
We also need to understand, vulnerability can be of two types: Hardware and Software. Hardware vulnerability is often tough to detect or penetrate. However, it is even tougher to repair or overhaul the damage.
Software vulnerability points towards a poorly written algorithm or a line of code with a backdoor. This backdoor can easily provide access to intruders prying for such moments.

Easy Exposure

This is one of the most fundamental issues faced by IoT industry. Any device, if unattended or exposed to troublemakers, is an open invitation to discomfort. In most of the cases IoT devices are not resilient to third-party exposure-they either lay open, easily accessible to anyone.
This means that an intruder can either, easily steal the device, connect the device to another device containing harmful data, or try to extract cryptographic secrets, modify the programming or even replace those devices with malicious ones of which the intruder has complete control.

Threats

Threats can be of two types: Human threat and Natural threat. Any threat arising from natural occurrences such as Earthquakes, Hurricanes, Floods or Fires can cause severe to very severe damage to IoT devices. In such cases, we often take a backup or create contingency plans to safeguard the data. But, any damage caused to the devices physically cannot be restored.
Today, IoT solutions have matured over time. Devices today have evolved to be waterproof. It is a long journey before IoT solution providers come up with something which is fireproof or earthquake proof.
On contrary, we do everything in power to curb any human threats to IoT devices. These threats are usually malicious attacks.

Human Attacks Can Be Further Identified As:

Cyber reconnaissance: Where an intruder uses cracking techniques and malicious softwares to conduct espionage on the targeted user; to either gain access to secret information or sabotage the existing systems.

Brute Force attacks on passwords: Intruders make an attempt to guess the user’s passwords with the help of an automated software which makes innumerable attempts until the right password grants the access.

Stalking or Tracking: User’s each and every move can be tracked or traced by the UID of the IoT device. Tracking a user gives out away their precise location in time where they wish to remain anonymous.

Controlled Attacks: Using Denial of Services (DoS), Trojans or Viruses are some examples of controlled attacks. In such cases, intruders develop a particular Virus which is programmed to function in a certain manner in order to destroy the host device. Programmers and developers have to be vigilant while working on current IoT solutions since hackers today have strong artillery to launch cyber attacks around the globe.

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Monday, 10 December 2018

Alibaba's Voice Asistant is smarter than Google's Voice Asistant. Check it out !! || techtalksgroup ||

theprogrammer.harshit  December 10, 2018    No comments


In May, Google made quite the splash when it unveiled Duplex, its eerily humanlike voice assistant capable of making restaurant reservations and salon appointments. It seemed to mark a new milestone in speech generation and natural-language understanding, and it pulled back the curtain on what the future of human-AI interaction might look like.
                But while Google slowly rolls out the feature in a limited public launch, Alibaba’s own voice assistant has already been clocking overtime. On December 2 at the 2018 Neural Information Processing Systems conference, one of the largest annual gatherings for AI research, Alibaba demoed the AI customer service agent for its logistics company Cainiao. Jin Rong, the dean of Alibaba’s Machine Intelligence and Technology Lab, said the agent is already servicing millions of customer requests a day.

The pre-recorded demo call involved the agent asking a customer where he wanted his package delivered. In the back-and-forth exchange, the agent successfully navigated several conversational elements that demonstrated the breadth of its natural-language capabilities.

Take this exchange at the beginning of the call, translated from Mandarin:

Agent: Hello, I am Cainiao’s voice assistant. I am—
Customer: Hello.
A: Yes, hi, you have package scheduled for morning delivery to 588 Culture West Road. Is it convenient for you to receive?
C: Who are you?
A: I am Cainiao’s voice assistant. I’d like to confirm your morning delivery to 588 Culture West Road. Does that work for you?
C: I’m not home in the morning.
A: Then do you have another address that you’d like to use?

Within 30 seconds, the agent has smoothly handled three common, and tricky, conversational ingredients: interruption, nonlinear conversation, and implicit intent. Interruption is self-explanatory: the agent can respond to the customer’s interruption and continue relaying relevant information without starting over or skipping a beat.

The nonlinear conversation occurs when the customer asks, “Who are you?” This requires the agent to register that the customer is not answering the preceding question but rather starting a new line of inquiry. In response, the agent reintroduces itself before returning to the original question.

The implicit intent occurs when the customer responds, “I’m not home in the morning.” He never explicitly says what he actually means—that home delivery won’t work—but the agent is able to read between the lines and follow up sensibly.
These elements may be boringly commonplace in human conversations, but machines often struggle to handle them. That Alibaba’s voice assistant can do so suggests it’s more sophisticated than Google Duplex, judging from similar sample calls demoed by Google. It’s worth noting, however, that Alibaba’s demo call is designed for onstage presentation; the experience could differ in reality.
Currently, the agent is used only to coordinate package deliveries, but Jin said it could be expanded to handle other topics. He wouldn’t fully reveal how the assistant was trained. But he alluded to using the massive number of customer recordings at the company’s disposal, in addition to other resources. On a typical day the company averages 50,000 customer service calls, according to the presentation slides—a number that quintuples for Singles’ Day (November 11), its highest revenue-generating holiday of the year.
Alibaba is also developing digital assistants for other aspects of its business, including a food-ordering agent that can take your order in noisy restaurants and stores; a humanlike virtual avatar that can field questions about Alibaba products; and a price-haggling chatbot that is already used by 20% of sellers on Alibaba’s resale platform Xianyu.
At their core, each of these assistants is powered by the speech-recognition and natural-language-processing engine called AliMe, developed by the company’s Machine Intelligence and Technology Lab. They are then packaged and adapted to different parts of the business.
Alibaba’s biggest advantage in this field is the overwhelming wealth of data it has to train its AI. The assistants learn and improve faster because of the amount of practice they get in handling all kinds of situations. A huge business incentive to deploy these technologies quickly also helps. In addition to handling a high volume of customer support calls, Alibaba delivers one billion packages per day. Offloading certain tasks to AI helps alleviate the burden on humans and keep the business running smoothly.

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Face Detection V/S Facial Recognition. Check it out !! || techtalksgroup ||

theprogrammer.harshit  December 10, 2018    No comments


What is Face Detection?

The definition of face detection refers to computer technology that is able to identify the presence of people’s faces within digital images. In order to work, face detection applications use machine learning and formulas known as algorithms to detecting human faces within larger images. These larger images might contain numerous objects that aren’t faces such as landscapes, buildings and other parts of humans (e.g. legs, shoulders and arms).

Face detection is a broader term than face recognition. Face detection just means that a system is able to identify that there is a human face present in an image or video. Face detection has several applications, only one of which is facial recognition. Face detection can also be used to auto focus cameras. And it can be used to count how many people have entered a particular area. It can even be used for marketing purposes. For example, advertisements can be displayed the moment a face is recognized.


Face recognition can confirm identity. It is therefore used to control access to sensitive areas.

How Face Detection Works

While the process is somewhat complex, face detection algorithms often begin by searching for human eyes. Eyes constitute what is known as a valley region and are one of the easiest features to detect. Once eyes are detected, the algorithm might then attempt to detect facial regions including eyebrows, the mouth, nose, nostrils and the iris. Once the algorithm surmises that it has detected a facial region, it can then apply additional tests to validate whether it has, in fact, detected a face.

Face Detection vs. Face Recognition

One of the most important applications of face detection, however, is facial recognition. Face recognition describes a biometric technology that goes way beyond recognizing when a human face is present. It actually attempts to establish whose face it is. The process works using a computer application that captures a digital image of an individual’s face (sometimes taken from a video frame) and compares it to images in a database of stored records. While facial recognition isn’t 100% accurate, it can very accurately determine when there is a strong chance that an person’s face matches someone in the database.

There are lots of applications of face recognition. Face recognition is already being used to unlock phones and specific applications. Face recognition is also used for biometric surveillance. Banks, retail stores, stadiums, airports and other facilities use facial recognition to reduce crime and prevent violence.

So in short, while all facial recognition systems use face detection, not all face detection systems have a facial recognition component.

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Saturday, 24 November 2018

What are Chatbots and how does a chatbots work..?? || techtalksgroup ||

theprogrammer.harshit  November 24, 2018    1 comment

A chatbot is an artificial intelligence (AI) software that can simulate a conversation (or a chat) with a user in natural language through messaging applications, websites, mobile apps or through the telephone.

 A chatbot is often described as one of the most advanced and promising expressions of interaction between humans and machines. However, from a technological point of view, a chatbot only represents the natural evolution of a Question Answering system leveraging Natural Language Processing (NLP).



The ability to identify the user’s intent and extract data and relevant entities contained in the user’s request is the first condition and the most relevant step at the core of a chatbot: If you are not able to correctly understand the user’s request, you won’t be able to provide the correct answer.
Returning the response: once the user’s intent has been identified, the chatbot must provide the most appropriate response for the user’s request. The answer may be:

• a generic and predefined text
• a text retrieved from a knowledge base that contains different answers
• a contextualized piece of information based on data the user has provided
• data stored in enterprise systems
• the result of an action that the chatbot performed by interacting with one or more backend application
• a disambiguating question that helps the chatbot to correctly understand the user’s request

Why chatbots are important

Chatbot applications streamline interactions between people and services, enhancing customer experience. At the same time, they offer companies new opportunities to improve the customers engagement process and operational efficiency by reducing the typical cost of customer service.

To be successful, a chatbot solution should be able to effectively perform both of these tasks. Human support plays a key role here: Regardless of the kind of approach and the platform, human intervention is crucial in configuring, training and optimizing the chatbot system.
Which chatbot application is right for you?
There are different approaches and tools that you can use to develop a chatbot. Depending on the use case you want to address, some chatbot technologies are more appropriate than others. In order to achieve the desired results, the combination of different AI forms such as natural language processing, machine learning and semantic understanding may be the best option.
In upcoming posts, we will give you an overview of the main chatbot applications so you can evaluate them based on your specific needs and desired goals.

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