Question

1. What are some challenges faced by businesses when trying to use a 3D virtual environment? What are some unique benefits?
2. What is Affective Computing? What are some of the main goals of this research domain? Give an example of a related technology
3. What are methods that can be used to capture Affective Data
4. Describe the limitations or problems of Affective Computing. Do you believe that the limitations can be overcome? (support your answer)

Answer 1

Answer:-

What are some challenges faced by businesses when trying to use a 3D virtual environment?

As every coin has two face, similarly AR/VR do have disadvantages besides having numerous advantages. With passing of each day now no field or industry is untouched by the application of AR/VR, so it depends how the technology is applied in each sector or field. As the question has not specified disadvantages in which respect , I would be mentioning few of the adverse effect of AR/VR on our health.

1. Virtual Reality Sickness- VR headsets contain 2 small LCD monitors, each projected at one eye, creating a stereoscopic effect which gives users the illusion of an artificial environment created all around you. And longer time of screen focus increase feeling of nausea and distortion , a phenomenon called Virtual Reality Sickness.
2. Eye Strain- While using AR/VR headsets we are confined in a limited area from our environment. And we see and focus on particular details for long due to which we may tend to blink less compared to normal frequency of blinking. This results in drying of the front surface of our eyes and strain on eyes.
3. Diziness- Individuals having amblyopia( an imbalance in visual strength beween the 2 eyes) or other conditions inhibits focusing, depth perception or normal 3D vision may not experience 3D effects of VR headsets. Individuals with these disorders may be ore likely to experience headaches and eye fatigue when using VR gear.
4. Distortion- VR lenses often suffer from strong distortion especially in the peripheral area. The distortion is still severe after many software curation, human eyes will try very hard to correct these distortion, which puts eyes in tension and sometimes leads to nausea.
5. VR games may be a very interesting for children or adults but prolong use of VR headsets may not only result in headaches and eye strain it may increase the chances of early myopia for children.

6. Some additional disadvantages:-

7. Breach of security:- AR game PokemonGo is the best example how any stranger can just barge into your garden just to chase any augmented character and breach your personal security.
8. No control over personal details- With the application of AR in web browsing and browsing in realtime, it would be possible in near future to just get any person’s details like Facebook profile details or other details just by pointing your camera on the person. So imagine, how dangerous it could be!
9. Addictive and laziness- Well, this is from my personal opinion, with application of AR in all fields, all the works would be automated with just one tap on your smartphone, most of your works would be done. So you become more lazy, and more addicted to this technology.

What are some unique benefits?

Helps with Impressive Visualization

Creating Interest

Improves Educational Value

Helps to Overcome Language Barriers

What is Affective Computing? What are some of the main goals of this research domain? Give an example of a related technology

Affective computing is the study and development of systems and devices that can recognize, interpret, process, and simulate human affects. It is an interdisciplinary field spanning computer science, psychology, and cognitive science. While the origins of the field may be traced as far back as to early philosophical inquiries into emotion (“affect” is, basically, a synonym for “emotion.”), the more modern branch of computer science originated with Rosalind Picard’s 1995 paper on affective computing. A motivation for the research is the ability to simulate empathy. The machine should interpret the emotional state of humans and adapt its behavior to them, giving an appropriate response for those emotions.

Affective computing technologies sense the emotional state of a user (via sensors, microphone, cameras and/or software logic) and respond by performing specific, predefined product/service features, such as changing a quiz or recommending a set of videos to fit the mood of the learner.

The more computers we have in our lives the more we’re going to want them to behave politely, and be socially smart. We don’t want it to bother us with unimportant information. That kind of common-sense reasoning requires an understanding of the person’s emotional state.

Affective computing aims at providing effective and natural interaction between human and computers. One important goal is to enable computers to understand the emotional states expressed by the human subjects, so that personalized responses can be delivered accordingly.

A major area in affective computing is the design of computational devices proposed to exhibit either innate emotional capabilities or that are capable of convincingly simulating emotions. A more practical approach, based on current technological capabilities, is the simulation of emotions in conversational agents in order to enrich and facilitate interactivity between human and machine. While human emotions are often associated with surges in hormones and other neuropeptides, emotions in machines might be associated with abstract states associated with progress (or lack of progress) in autonomous learning systemsIn this view, affective emotional states correspond to time-derivatives in the learning curve of an arbitrary learning system.Two major categories describing emotions in machines: Emotional speech and Facial affect detection.

What are methods that can be used to capture Affective Data

Manual keying

Manual keying of metadata from unstructured data is appropriate for data that is received in low volumes and results in low levels of recognition by intelligent data capture products (IDR, ICR). ProcessFlows has a Manual Keying service as part of our Outsourcing Solutions, please click here for more information.

Nearshore keying

Have you considered outsourcing data entry?

ProcessFlows Managed Services is here to help. We provide manual data entry and data management services from our office in Bulgaria. To find out more, please click here.

Nearshore keying of Metadata is most appropriate for the following reasons:

• High volumes of individual documents where the level of recognition achieved using intelligent data capture products is low (can include documents with a high level of handwritten data).
• Potentially capturing the data that has not been successfully captured using an Intelligent data capture product.
• High volume of individual documents where the data to be extracted is not consistent from page to page.
• Can be very cost efficient based on the lower labour costs that can be achieved.

ProcessFlows has a Nearshore Keying service as part of our Outsourcing Solutions, please click here for more information.

SingleClick

SingleClick is an Optical Character Recognition (OCR) tool that can be used to capture machine produced characters in low volume ad-hoc capture applications and populating a line of business application. For more on SingleClick, please click here.

OCR (Optical Character Recognition)

OCR as a technology provides the ability to successfully capture machine produced characters in preset zones or, full page. OCR systems can recognise many different OCR fonts, as well as typewriter and computer-printed characters. Dependent upon the capabilities of the particular OCR product, this can be used to capture low to high volumes of data, where the information is in consistent location(s) on the documents. Please click here to learn more about OCR.

ICR (Intelligent Character Recognition)

ICR is the computer translation of hand printed and written characters. Data is entered from hand-printed forms through a scanner, and the image of the captured data is then analysed and translated by sophisticated ICR software. ICR is similar to optical character recognition (OCR) but is a more difficult process since OCR is from printed text, as opposed to handwritten characters. Please click here to learn more about ICR.

Bar code recognition

Dependent upon the type of barcode that is used, the amount of metadata that can be included is high, as is the level of recognition. The application of single or multiple bar codes to particular document types such as Proof of Delivery notes, membership forms, application forms, gift aid etc, can dramatically increase the effectiveness of a business process. For more about Barcodes, please click here.

Template based intelligent capture

The level of capability is dependent upon the individual template based intelligent capture product! More advanced products are able to identify machine produced and to a lesser degree handwritten characters that are contained in particular area(s) of a document. These applications are used where the number of document types being received are relatively low (typically up to 30 different document types) but consistent. Used in applications such as census, inter-bank transfers and application forms. For more information on this technology, please see our ReadSoft Forms page.

Intelligent Document Recognition (IDR)

The level of capability is dependent upon the individual product. These applications are used to capture metadata from documents that is rules based. For example, the product will identify post codes, logos, key words, VAT registration numbers and, through an ongoing learning process, capture information from multiple document types.

This type of capture is used for high volume invoice processing and digital mailroom applications, where the classification and indexing of incoming documents is key. IDR software applications use rules to identify and capture information from semi-structured documents. Rules, specified by end users, look for specific text on a document to identify the document type and additional rules can then be applied to each different type from then on, extracting different metadata fields from each type.

These applications are commonly used for digital mailroom environments, with the idea that documents are taken out of their envelopes and fed straight into a scanner with very little manual processing.

Specialised applications exist for departmental projects such as invoice processing. IDR applications can hold information about suppliers generated from other line-of-business systems and match invoices to that information, using recognised text such as VAT number, telephone number, post code etc. The application then looks for keyword identifiers on the invoice and extrapolates the value nearby. Validation rules are then applied, for example the NET amount plus the VAT amount must equal the gross amount, minimising the chance for errors.

For more information regarding IDR Solutions, please see our Automated Document Processing and Automated Invoice Processing pages in the ReadSoft section.

Describe the limitations or problems of Affective Computing. Do you believe that the limitations can be overcome?

deep fakes,
- manipulation,
- surveillance,
- hyper-targeting etc.

In case you have any thoughts on this topic please feel free to contact me. Since I'm launching a publicly available Affective Computing API (Neurodata Lab API ) it's important for me to know what people think about these technologies.

sollution

Supporting positive interactions: AI’s need to detect, comprehend, and respond appropriately to human emotions in order to support human decision making, bonding with humans as a team…etc. that have implications on fields such as education, policy making, healthcare, and day to day living.

Avoiding negative implications: Machines need to detect, comprehend, and respond appropriately to human emotions in order to not accidentally destroy human property, relationships, and lives.