Carroll proposed traditional cognitive approach in 1964. It arose when audio-lingual approach was attacked and challenged. The audio-lingual habit theory "emphasized the primacy of auditory discrimination and oral production habits over other aspects of language use, the importance of the auto-mitigation of habits over other aspects of language use, the importance of the auto-mitigation of habits and the role of repetition in such auto-mitigation," while cognitive code learning theory is "a modified up-to-date grammar-translation theory", according to which "foreign language learning is a second language largely through the study and analysis of these patterns as a body of knowledge". ™ The information-processing cognitive approach (as represented in, for example, Schifrin and domains 1981; Schneider, domains, and Schifrin 1984; Anderson 1980, 1982 ( see hulstijn, 1990s with the publication of "A cognitive approach to language learning" by Skehan in 1998. during the last few decades, sociolinguistics has grown in influence on second language learning, which focuses on the importance of the social contexts in which languages are learned, and the way they influence the meanings which are expressed. however, the recent achievements in psycholinguistics and their influences on SLA have been neglected. the aim of information-processing cognitive approach is to investigate second language learning through the cognitive abilities of the learner and the processing problems that the learner has to confront, and redress the balance of viewpoints in second language acquisition research and language teaching pedagogy, which the author feels has leaned too far towards linguistics and sociolinguistics in recent years and has not, until recently, drawn effectively on contemporary cognitive psychology. The cognitive code framework offers a structurist view of learning. It focuses on knowledge components (representation) at any point of development, giving it a static nature. The information- processing framework, on the other hand, provides us with a developmental view of acquisition of skills in terms of both knowledge (mental representation) and executive control (the processing of mental representations). To be sure, both frameworks are intended to cover both static and dynamic (developmental) aspects of skills, but there is a difference in emphasis. Do you have a fetish for attractive lactating women? If the answer is yes then I am sure that at one time or another you have wanted to date such a beautiful woman. Years ago this would have been difficult to say the least. Now, however, with new niche dating sites appearing almost every day and advanced dating technology, it has become easy to find a date with this special category of woman. In the paragraphs to follow you will learn a simple way to easily meet the kind of women you desire. If you choose your favorite search engine and enter a search with your fetish words followed by either personals or dating, this will uncover a smattering of fetish dating sites. The problem with these sites is they require a credit card for membership and charge a massive fee. If you join one you are also likely to be disappointed. More often than not you will fail to find lactating women in your town or city; this is made more upsetting after having paid a large fee. Is there a good, free solution to finding lactating females on the internet? Yes. It is free and can be accomplished in minutes. Find a popular paid dating site with a few million members; between 5 and 10 million members should be sufficient. Do not choose a totally free dating site. Why? These sites are free for a reason. They steal identities and spam you with live cams, among other things. Choose a dating site you can trust; something popular with millions of members. Get AI 개발 a free account and make a quick profile. Your free account entitles you to send and receive messages, add friends, and search profiles; all you need from a dating site. You do not need a credit card for this and you only upgrade if you want extra features. How do you find attractive lactating women? Simple. In your profile you should state the kind of women you desire. This will do two things. The internet search engine of the site will deliver these type of women to your profile when they put in searches. Not only that but the advanced match-making software will tell you which women are suitable in your town or city; you can then contact them or add them as friends. Now the last part requires some work but is more than worth it. Go to advanced search and enter your criteria. You want women who lactate in your town or city. You can actually enter this into a search and it will bring up hundreds, maybe even thousands of results. What you do then is begin adding these women as friends. Add as many as you like and then wait for replies. You should get replies almost instantly. You can then reply to these women and see which ones you would like to meet most. So this is how you can easily meet attractive lactating women in your neighborhood. It is free, simple and, best of all, a very effective method to meet this difficult to find category of woman.
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Video Digital Marketing ™ Video digital marketing for SEO is very big in 2020 in the realm of search engine optimization (SEO). First off don't forget to create videos and submit them to YouTube,Vimeo, Daily Motion, Blip, Wistia, Meta cafe, Veoh, and Mega video. Be sure to make each video at least slightly different. The major search engines such as Google, Yahoo, Bing, and Duckduckgo.com really don't want you to post duplicate content. It's either highly frowned upon or even Penalized. Check out Google console to see any penalties enforced by Google. You'll also see keywords that don't show their origin in Google Analytics in Google console. Make the video descriptions relevant with keywords that you've researched on Google Ad planner for traffic volume, and keyword competition. The Web 3.0 The internet or web 3.0 is still huge albeit the term was coined a while ago. This is that the internet will be semantically or big data driven from now on. Google even uses latent semantic indexing to cross reference web pages and semantically rank them. That's why it's crucial to canonize your website pages especially the home page. Make sure your main URL is the same URL throughout the website information architecture. Web 3.0 was termed by John Markoff of the New York Times in 2006. It refers to the third generation of internet-based services that all in all aggregate the smart or intelligent internet. It's web based services that compose of the intelligent web. Those using big data are an example, using intelligent analytics reports, Google trends, Advanced advertising mathematics, Google Ad planner, Ubersuggest, and more. Google introduced Rank Brain which we're still only even beginning to understand in 2020. It came out five years ago. Rank Brain is Google's AI that uses machine learning to rank web pages with latent semantic indexing mathematical models, then latent diriclay, and after that dirrivitive allocation. This can be derived from a list of things that we can't assume. It could be co occurrence in web documents. This refers to distance between the keywords on the page itself. Google Ranks the importance of keywords in a search phrase. So if you search for "Super Mario Brothers" it will rank the keywords that should come up and give them a score based on abstractions and meanings that Google generates rather than the exact phrase which could return the wrong results without the semantic Rank Brain modeling (connectivity modeling). Citations and links on the web. This would be if there are a lot of pages about Mario, Luigi, Bowser, Princess, Toad, that link to the web page. It looks at linking in text, Bias to corpuses. This means that Google only cares about trusted sites linking in as opposed to all of the internet. Searcher click data corpi may be used. So this means that if you can brainstorm keywords that are semantically on topic and use them in the web page, then semantically you have a better chance of showing up first as opposed to just sprinkling in the exact keywords into the article and making the article even sound bad or robotic/un human readable or even keyword stuffed (a big white hat SEO no no). Where the website is pointing is important. If the site links to a Nintendo website often then this is factored into the semantic connectivity. Also, be sure to look at competitors pages or other sites that are ranking for this phrase and get keyword ideas for semantic connectivity or even keyword suggest tools. Bidirectional Transformers for Language Understanding (BERT) is the latest addition to Google's AI. It touches one out of ten searches. It gives Google a better understanding of how language is utilized to help learn the context of single words inside of searches. It's important to follow these algorithm changes in case they can be optimized for in the future, which will most likely be so. Google's John Mueller finally gave SEO's hints for optimizing websites and web pages for BERT. BERT focuses on the relevance of the text on the website pages. SEO's need to make sure that the pages aren't random at all. Being relevant also means original content. BERT is trying to catch keyword spinning tools. Don't just post the same old same old, which an auto spinner can spin and pass SEO copy scape tools. Your content won't be as relevant as more thought out content, more detailed content, and more relevant content that has more depth, content research, on hands journalism, and SEO content correspondence to it. Everyone is excited about artificial intelligence. Great strides have been made in the technology and in the technique of machine learning. However, at this early stage in its development, we may need to curb our enthusiasm somewhat. Already the value of AI can be seen in a wide range of trades including marketing and sales, business operation, insurance, banking and finance, and more. In short, it is an ideal way to perform a wide range of business activities from managing human capital and analyzing people's performance through recruitment and more. Its potential runs through the thread of the entire business Eco structure. It is more than apparent already that the value of AI to the entire economy can be worth trillions of dollars. Sometimes we may forget that AI is still an act in progress. Due to its infancy, there are still limitations to the technology that must be overcome before we are indeed in the 소프트웨어개발 brave new world of AI. In a recent podcast published by the McKinsey Global Institute, a firm that analyzes the global economy, Michael Chui, chairman of the company and James Manyika, director, discussed what the limitations are on AI and what is being done to alleviate them. Factors That Limit The Potential Of AI Manyika noted that the limitations of AI are "purely technical." He identified them as how to explain what the algorithm is doing? Why is it making the choices, outcomes and forecasts that it does? Then there are practical limitations involving the data as well as its use. He explained that in the process of learning, we are giving computers data to not only program them, but also train them. "We're teaching them," he said. They are trained by providing them labeled data. Teaching a machine to identify objects in a photograph or to acknowledge a variance in a data stream that may indicate that a machine is going to breakdown is performed by feeding them a lot of labeled data that indicates that in this batch of data the machine is about to break and in that collection of data the machine is not about to break and the computer figures out if a machine is about to break. Chui identified five limitations to AI that must be overcome. He explained that now humans are labeling the data. For example, people are going through photos of traffic and tracing out the cars and the lane markers to create labeled data that self-driving cars can use to create the algorithm needed to drive the cars. Manyika noted that he knows of students who go to a public library to label art so that algorithms can be created that the computer uses to make forecasts. For example, in the United Kingdom, groups of people are identifying photos of different breeds of dogs, using labeled data that is used to create algorithms so that the computer can identify the data and know what it is. This process is being used for medical purposes, he pointed out. People are labeling photographs of different types of tumors so that when a computer scans them, it can understand what a tumor is and what kind of tumor it is. The problem is that an excessive amount of data is needed to teach the computer. The challenge is to create a way for the computer to go through the labeled data quicker. Tools that are now being used to do that include generative adversarial networks (GAN). The tools use two networks -- one generates the right things and the other distinguishes whether the computer is generating the right thing. The two networks compete against each other to permit the computer to do the right thing. This technique allows a computer to generate art in the style of a particular artist or generate architecture in the style of other things that have been observed. Manyika pointed out people are currently experimenting with other techniques of machine learning. For example, he said that researchers at Microsoft Research Lab are developing in stream labeling, a process that labels the data through use. In other words, the computer is trying to interpret the data based on how it is being used. Although in stream labeling has been around for a while, it has recently made major strides. Still, according to Manyika, labeling data is a limitation that needs more development. Another limitation to AI is not enough data. To combat the problem, companies that develop AI are acquiring data over multiple years. To try and cut down in the amount of time to gather data, companies are turning to simulated environments. Creating a simulated environment within a computer allows you to run more trials so that the computer can learn a lot more things quicker. Then there is the problem of explaining why the computer decided what it did. Known as explainability, the issue deals with regulations and regulators who may investigate an algorithm's decision. For example, if someone has been let out of jail on bond and someone else wasn't, someone is going to want to know why. One could try to explain the decision, but it certainly will be difficult. Chui explained that there is a technique being developed that can provide the explanation. Called LIME, which stands for locally interpretable model-agnostic explanation, it involves looking at parts of a model and inputs and seeing whether that alters the outcome. For example, if you are looking at a photo and trying to determine if the item in the photograph is a pickup truck or a car, then if the windscreen of the truck or the back of the car is changed, then does either one of those changes make a difference. That shows that the model is focusing on the back of the car or the windscreen of the truck to make a decision. What's happening is that there are experiments being done on the model to determine what makes a difference. Finally, biased data is also a limitation on AI. If the data going into the computer is biased, then the outcome is also biased. For example, we know that some communities are subject to more police presence than other communities. If the computer is to determine whether a high number of police in a community limits crime and the data comes from the neighborhood with heavy police presence and a neighborhood with little if any police presence, then the computer's decision is based on more data from the neighborhood with police and no if any data from the neighborhood that do not have police. The oversampled neighborhood can cause a skewed conclusion. So reliance on AI may result in a reliance on inherent bias in the data. The challenge, therefore, is to figure out a way to "de-bias" the data. So, as we can see the potential of AI, we also have to recognize its limitations. Don't fret; AI researchers are working feverishly on the problems. Some things that were considered limitations on AI a few years ago are not today because of its quick development. That is why you need to constantly check with AI researchers what is possible today. So you decided that you wanted to build a catapult. Now it's finished and ready to fire. Your excitement builds as you pull the release mechanism then, plop. Your ammo sails a few feet and drops to the ground with a disappointing thud. So much for your plans to hurl water balloons at your neighbor on the other side of the fence. You feel the sting of defeat. What went wrong? Why didn't it work? Do not despair my friend, for I may have a solution to your problem. The next couple of paragraphs will explain a few things that you can do to increase the firing distance of your siege engine. ™ Check your construction. Make sure your catapult has been properly built. Improperly fitted parts or loose parts can affect the efficiency of your machine. One of the biggest areas of energy loss in a catapult is the pivot points. Anywhere something pivots there will be friction. Make sure the parts move freely, without binding. Depending on your construction lubrication may be needed. If your pivot point is a wooden axle through a hole drilled in another piece of wood make sure it's not too tight. If the fit is too tight, lightly sand until a proper fit is achieved. If there is too much play replace the piece of wood with the hole in it with a new piece that has a smaller hole. Too much play can also cause energy loss. More tension! Many catapults are built using springs, bungee cords, or surgical tubing as the source for tension to the firing arm. Beef them up! Replace your existing springs with stronger springs. The same applies to bungee cords rubber bands. Replace the existing ones with something a little stronger. You can also add more springs or cords to the existing ones (double them up). If you have an onager, try winding the cord that is 데이터바우처 attached to the throwing arm a little tighter. This will increase the tension and force of the throwing arm when it is released. One thing to keep in mind if you are going to increase your spring tension: make sure the framework and firing arm are sturdy enough to handle the increased tension. You don't want your siege engine to blow apart when you fire it. You may need to reinforce the frame and throwing arm to accomplish this. All hail the trebuchet! Ah, the mighty trebuchet. It is by far my favorite of all the siege engines. It is far more sophisticated in design than other types of catapults. When properly tuned the distance and accuracy are incredible. Getting to this point can be a real pain in the rear end if you're not sure what to do. You can build a trebuchet that works, or build one that works really well. I have a small table top model that can hurl a small wooden cannonball about 20 feet across my basement. If I place a 9" paper plate on the floor as my target I can land every shot in the plate. I achieved this accuracy by simply making adjustments to the sling (length is critical!). Read on to find out how to tune your trebuchet. As I mentioned above, pivot points are areas of friction. Excess friction means energy loss. Make sure the pivot point of the throwing arm moves freely without binding. Adjust as necessary. If your trebuchet has a hinged counterweight make sure this pivot point moves freely as well. While we're on the subject of counterweights, keep in mind that the further the distance the counterweight falls, the greater the energy is to the throwing arm. Raising the height of the main axle (pivot point for throwing arm) and lengthening the throwing arm will allow the counterweight to travel further when released. Increasing the weight of the counterweight will help as well. Note that changing the length and height of the throwing arm will require adjustments to the sling. Slings are a very critical piece of a well tuned trebuchet. Incorrect lengths can cause the sling to release at the wrong time. This can result in a high arc with very short distance or a low arc with a short distance. Experiment with the sling length for greatest distance. Make sure the pouch isn't too large for the ammo. This can result in excess wind drag. Use as small a pouch as possible for the size ammo you are using. I hope this information is helpful to those who may need it. As a final note I want to mention that while catapults are fun, they can be dangerous as well. When making modifications to your catapult make sure the overall structure can handle the changes. Reinforce as necessary. Always use proper safety measures when firing a catapult. Eyewear is always recommended. Maintain a safe distance from the machine when you are firing it. With safety in mind operating a catapult can be a fun experience for people of all ages. Happy Hurling! With the increasing population, economic crisis and loose values some people practice, incidences of crime has really persisted to exist in every society. The bigger the population, the more crimes are committed. It is not only in businesses that crimes really occur but also in schools, buses, other public places, and even in our homes. Even the availability or visibility of a security guard or police officer cannot deter some criminals to do their acts. Ordinary tenants cannot also afford to hire a private security guard. Nonetheless, these sentinels are not enough to monitor a place. The trend nowadays is to install security surveillance equipment in strategic areas of a building, house and other security-risk locales. Surveillance technology uses equipment that would detect and record what is actually happening in a particular area where the equipment focuses. Most equipment are not ''secret'' and is visible to the public. One such equipment is the CCTV. It is a closed circuit television. Its disadvantages are the following: 1. It invades privacy - People are very much against this because it steps on their privacy and that they are viewed by others without their consent. 2. it is stationary - This equipment is steady in its place so there is no possibility for an offender to be caught if he knows there is a CCTV around. The offender can simply avoid passing in front of the camera. The CCTV has become very popular this 2010. 3. Interference in signal - When there is an object between the camera and its subject, recording it becomes a failure. 4. It becomes useless once it has a scratch- Sometimes, this results to a waste of capital or money. Surveillance technology equipment is the wire tap. Wire taps are secretly used and not seen by the public. Some of its disadvantages are the following: 1. It also invades privacy - Just like other security surveillance equipment, wire tapping is a threat to a person's privacy. 2. Audibility is a problem sometimes - This happens when the subject moves out of range of the equipment. Voices become inaudible. Aside from the equipment's disadvantages, a general disadvantage for this on the part of the owner is that they become too dependent on the security surveillance equipment. In effect, they become lax in their security maintenance. Nevertheless, with a security surveillance technology, it is the closest route to one's safety and security. |
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