Human Computer Interface

Human–computer Interaction (HCI) involves the study, planning, and design of the interaction between people (users) and computers. It is often regarded as the intersection of computer science, behavioral sciences, design and several other fields of studyInteraction between users and computers occurs at the user

Interface (or simply interface), which includes both software and hardware; for example, characters or objects displayed by software on a personal computer's monitor, input received from users via hardware peripherals such as keyboards and mouses, and other user interactions with large-scale computerized systems such as aircraft and power plants. The Association for Computing Machinery defines human-computer interaction as "a discipline concerned with the design, evaluation and implementation of interactive computing systems for human use and with the study of major phenomena surrounding them."An often-sought facet of HCI is the securing of user satisfaction (see Computer user satisfaction), although user satisfaction is not the same thing as user performance by most meaningful metrics.

Because human–computer interaction studies a human and a machine in conjunction, it draws from supporting knowledge on both the machine and the human side. On the machine side, techniques in computer graphics, operating systems, programming languages, and development environments are relevant. On the human side, communication theory, graphic and industrial design disciplines, linguistics, social sciences, cognitive psychology, and human factors such as computer user satisfaction are relevant. Engineering and design methods are also relevant. Due to the multidisciplinary nature of HCI, people with different backgrounds contribute to its success. HCI is also sometimes referred to as man–machine interaction (MMI) or computer–human interaction (CHI).

What is Human–computer interface?

The human–computer interface can be described as the point of communication between the human user and the computer. The flow of information between the human and computer is defined as the loop of interaction. The loop of interaction has several aspects to it including:

· Task environment: The conditions and goals set upon the user.

· Machine environment: The environment that the computer is connected to, e.g. a laptop in a college student's dorm room.

· Areas of the interface: Non-overlapping areas involve processes of the human and computer not pertaining to their interaction. Meanwhile, the overlapping areas only concern themselves with the processes pertaining to their interaction.

· Input flow: The flow of information that begins in the task environment, when the user has some task that requires using their computer.

· Output: The flow of information that originates in the machine environment.

· Feedback: Loops through the interface that evaluate, moderate, and confirm processes as they pass from the human through the interface to the computer and back

     Goals of HCI

·       A basic goal of HCI is to improve the interactions between users and computers by making computers more usable and receptive to the user's needs. Specifically, HCI is concerned with:

·          methodologies and processes for designing interfaces (i.e., given a task and a class of users, design the best possible interface within given constraints, optimizing for a desired property such as learnability or efficiency of use)

·          methods for implementing interfaces (e.g. software toolkits and libraries; efficient algorithms)

·          techniques for evaluating and comparing interfaces

·          developing new interfaces and interaction techniques

·         developing descriptive and predictive models and theories of interaction

      A long term goal of HCI is to design systems that minimize the barrier between the human's cognitive model of what they want to accomplish and the computer's understanding of the user's task.

 

Future of HCI

The future for HCI, based on current promising research, is expected to include the following characteristics:

· Ubiquitous communication. Computers are expected to communicate through high speed local networks, nationally over wide-area networks, and portably via infrared, ultrasonic, cellular, and other technologies. Data and computational services will be portably accessible from many if not most locations to which a user travels.

· High-functionality systems. Systems can have large numbers of functions associated with them. There are so many systems that most users, technical or non-technical, do not have time to learn them in the traditional way (e.g., through thick manuals).

· Mass availability of computer graphics. Computer graphics capabilities such as image processing, graphics transformations, rendering, and interactive animation are becoming widespread as inexpensive chips become available for inclusion in general workstations and mobile devices.

· Mixed media. Commercial systems can handle images, voice, sounds, video, text, formatted data. These are exchangeable over communication links among users. The separate worlds of consumer electronics (e.g., stereo sets, VCRs, televisions) and computers are partially merging. Computer and print worlds are expected to cross-assimilate each other.

· High-bandwidth interaction. The rate at which humans and machines interact is expected to increase substantially due to the changes in speed, computer graphics, new media, and new input/output devices. This can lead to some qualitatively different interfaces, such as virtual reality or computational video.

· Large and thin displays. New display technologies are finally maturing, enabling very large displays and displays that are thin, lightweight, and low in power consumption. This is having large effects on portability and will likely enable the development of paper-like, pen-based computer interaction systems very different in feel from desktop workstations of the present.

· Information utilities. Public information utilities (such as home banking and shopping) and specialized industry services (e.g., weather for pilots) are expected to proliferate. The rate of proliferation can accelerate with the introduction of high-bandwidth interaction and the improvement in quality of interfaces.

 Factors of change

Human–computer interaction is affected by the forces shaping the nature of future computing. These forces include:

· Decreasing hardware costs leading to larger memory and faster systems

· Miniaturization of hardware leading to portability

· Reduction in power requirements leading to portability

· New display technologies leading to the packaging of computational devices in new forms

· Specialized hardware leading to new functions

· Increased development of network communication and distributed computing

· Increasingly widespread use of computers, especially by people who are outside of the computing profession

· Increasing innovation in input techniques (e.g., voice, gesture, pen), combined with lowering cost, leading to rapid computerization by people previously left out of the "computer revolution."

· Wider social concerns leading to improved access to computers by currently disadvantaged groups

BIOINFORMATICS

Bioinformatics  is a branch of biological science which deals with the study of methods for storing, retrieving and analyzing biological data, such as nucleic acid (DNA/RNA) and protein sequence, structure, function, pathways and genetic interactions. It generates new knowledge that is useful in such fields as drug design and development of new software tools to create that knowledge. Bioinformatics also deals with algorithms, databases and information systems, web technologies, artificial intelligence and soft computing, information and computation theory, structural biology, software engineering, data mining, image processing, modeling and simulation, discrete mathematics, control and system theory, circuit theory, and statistics.
Commonly used software tools and technologies in this field include Java, XML, Perl, C, C++, Python, R, MySQL, SQL, CUDA, MATLAB, and Microsoft Excel.

Building on the recognition of the importance of information transmission, accumulation and processing in biological systems, in 1978 Paulien Hogeweg, coined the termed "Bioinformatics" to refer to the study of information processes in biotic systems . This definition placed bioinformatics as field parallel to biophysics and biochemistry. Examples of relevant biological information processes studied in the early days of bioinformatics are the formation of complex social interaction structures by simple behavioral rules, and the information accumulation and maintenance in models of prebiotic evolution.

At the beginning of the "genomic revolution", the term bioinformatics was re-discovered to refer to the creation and maintenance of a database to store biological information such as nucleotide sequences and amino acid sequences. Development of this type of database involved not only design issues but the development of complex interfaces whereby researchers could access existing data as well as submit new or revised data.

In order to study how normal cellular activities are altered in different disease states, the biological data must be combined to form a comprehensive picture of these activities. Therefore, the field of bioinformatics has evolved such that the most pressing task now involves the analysis and interpretation of various types of data. This includes nucleotide and amino acid sequences, protein domains, and protein structures. The actual process of analyzing and interpreting data is referred to as computational biology. Important sub-disciplines within bioinformatics and computational biology include:

• the development and implementation of tools that enable efficient access to, and use and management of, various types of information.
• the development of new algorithms (mathematical formulas) and statistics with which to assess relationships among members of large data sets. For example, methods to locate a gene within a sequence, predict protein structure and/or function, and cluster protein sequences into families of related sequences.

The primary goal of bioinformatics is to increase the understanding of biological processes. What sets it apart from other approaches, however, is its focus on developing and applying computationally intensive techniques to achieve this goal. Examples include: pattern recognition, data mining, machine learning algorithms, and visualization. Major research efforts in the field include sequence alignment, gene finding, genome assembly, drug design, drug discovery, protein structure alignment, protein structure prediction, prediction of gene expression and protein–protein interactions, genome-wide association studies and the modeling of evolution.

Interestingly, the term bioinformatics was coined before the "genomic revolution". Paulien Hogeweg and Ben Hesper defined the term in 1978 to refer to "the study of information processes in biotic systems". This definition placed bioinformatics as a field parallel to biophysics or biochemistry (biochemistry is the study of chemical processes in biological systems). However, its primary use since at least the late 1980s has been to describe the application of computer science and information sciences to the analysis of biological data, particularly in those areas of genomics involving large-scale DNA sequencing.

Bioinformatics now entails the creation and advancement of databases, algorithms, computational and statistical techniques and theory to solve formal and practical problems arising from the management and analysis of biological data.

Over the past few decades rapid developments in genomic and other molecular research technologies and developments in information technologies have combined to produce a tremendous amount of information related to molecular biology. Bioinformatics is the name given to these mathematical and computing approaches used to glean understanding of biological processes.
Common activities in bioinformatics include mapping and analyzing DNA and protein sequences, aligning different DNA and protein sequences to compare them, and creating and viewing 3-D models of protein structures.

There are two fundamental ways of modelling a Biological system (e.g., living cell) both coming under Bioinformatic approaches.

• Static
  • Sequences – Proteins, Nucleic acids and Peptides
  • Structures – Proteins, Nucleic acids, Ligands (including metabolites and drugs) and Peptides
  • Interaction data among the above entities including microarray data and Networks of proteins, metabolites
• Dynamic
  • Systems Biology comes under this category including reaction fluxes and variable concentrations of metabolites
  • Multi-Agent Based modelling approaches capturing cellular events such as signalling, transcription and reaction dynamics

A broad sub-category under bioinformatics is structural bioinformatics.

Brainwaves into Speech

Attempt To Convert Prof Hawking’s Brainwaves Into Speech

An American scientist is to unveil details of work on the brain patterns of Prof Stephen Hawking which he says could help safeguard the physicist’s ability to communicate.

Prof Philip Low said he eventually hoped to allow Prof Hawking to “write” words with his brain as an alternative to his current speech system which interprets cheek muscle movements.

Prof Low said the innovation would avert the risk of locked-in syndrome.

Intel is working on an alternative.

Prof Hawking was diagnosed with motor neurone disease in 1963. In the 1980s he was able to use slight thumb movements to move a computer cursor to write sentences.
His condition later worsened and he had to switch to a system which detects movements in his right cheek through an infrared sensor attached to his glasses which measures changes in light.

Because the nerves in his face continue to deteriorate his rate of speech has slowed to about one word a minute prompting him to look for an alternative.

The fear is that Prof Hawking could ultimately lose the ability to communicate by body movement, leaving his brain effectively “locked in” his body.

In 2011, he allowed Prof Low to scan his brain using the iBrain device developed by the Silicon Valley-based start-up Neurovigil.

Prof Hawking will not attend the consciousness conference in his home town of Cambridge where Prof Low intends to discuss his findings, but a spokesman told the BBC: “Professor Hawking is always interested in supporting research into new technologies to help him communicate.”

Decoding brainwaves

The iBrain is a headset that records brain waves through EEG (electroencephalograph) readings – electrical activity recorded from the user’s scalp.

Prof Low said he had designed computer software which could analyse the data and detect high frequency signals that had previously been thought lost because of the skull.”

An analogy would be that as you walk away from a concert hall where there’s music from a range of instruments,” he told the BBC.”As you go further away you will stop hearing high frequency elements like the violin and viola, but still hear the trombone and the cello. Well, the further you are away from the brain the more you lose the high frequency patterns.

The iBrain device collects EEG data which it transfers to a computer

“What we have done is found them and teased them back using the algorithm so they can be used.”
Prof Low said that when Prof Hawking had thought about moving his limbs this had produced a signal which could be detected once his algorithm had been applied to the EEG data.
He said this could act as an “on-off switch” and produce speech if a bridge was built to a similar system already used by the cheek detection system.

Prof Low said further work needed to be done to see if his equipment could distinguish different types of thoughts – such as imagining moving a left hand and a right leg.
If it turns out that this is the case he said Prof Hawking could use different combinations to create different types of virtual gestures, speeding up the rate he could select words at.
To establish whether this is the case, Prof Low plans trials with other patients in the US.

Intel’s effort

The US chipmaker Intel announced, in January, that it had also started work to create a new communication system for Prof Hawking after he had asked the firm’s co-founder, Gordon Moore, if it could help him.

It is attempting to develop new 3D facial gesture recognition software to speed up the rate at which Prof Hawking can write.

“These gestures will control a new user interface that takes advantage of the multi-gesture vocabulary and advances in word prediction technologies,” a spokeswoman told the BBC.

“We are working closely with Professor Hawking to understand his needs and design the system accordingly.”

Intel began working with Prof Hawking after he wrote a letter to its co-founder Gordon Moore in 2011

Source : techpark.net