This document provides an overview of Human Information Processing (HIP) models in human-computer interaction (HCI). It discusses 1) what HIP is as a cognitive model that uses the computer as a metaphor for human cognitive functioning, 2) how HIP models are used in HCI to predict human-computer interaction, focusing on the GOMS model, 3) predictive versus descriptive HIP models and examples of each, 4) alternatives to cognitive models like Activity Theory, and 5) conclusions about increasing complexity in models and the need for multidisciplinary approaches.
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Presented by:
Lars Strong, P.E., Senior Engineer, Upsite Technologies
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The specifications for the environmental operating conditions of IT equipment used in data centres have recently been revised, opening the way to evaporative cooling in such buildings. Evaporative cooling can provide a highly effective solution, with low installation and running costs, minimal maintenance requirements and quiet operation.
This seminar covers:
• Revisions to the specifications for the environmental operating conditions of IT equipment in data centres
• Options for cooling in a data centre
• Implementing evaporative cooling in a data centre.
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Presentation covers fundamental of CPU architecture and memory model used for Parallel Processing in easy to understand language.
Apart from theory, small example C code has also been provided.
Topics covered are
1. Introduction
2. Michael Flynn Classification (SISD, SIMD, MISD, MIMD)
3. Memory Model ( Shared vs Distributed)
4. SIMD
5. MIMD on Shared Memory
6. MIMD on Distributed Memory
Data Center Cooling Efficiency: Understanding the Science of the 4 Delta T'sUpsite Technologies
While the term Delta T may be commonly used in the industry, there is much misunderstanding about where and why temperatures are changing in computer rooms. While two ΔT’s are commonly known, there are actually four different ΔT’s which contribute to the health of the data center. Understanding the sources of these differences and measuring them in your site provides insight about how to further improve the efficiency and capacity of computer room cooling.
Presented by:
Lars Strong, P.E., Senior Engineer, Upsite Technologies
CPD Presentation Evaporative cooling in data centresColt UK
Data centres that use evaporative cooling can cut their energy bills by up to 80% compared to conventional cooling methods!
The specifications for the environmental operating conditions of IT equipment used in data centres have recently been revised, opening the way to evaporative cooling in such buildings. Evaporative cooling can provide a highly effective solution, with low installation and running costs, minimal maintenance requirements and quiet operation.
This seminar covers:
• Revisions to the specifications for the environmental operating conditions of IT equipment in data centres
• Options for cooling in a data centre
• Implementing evaporative cooling in a data centre.
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Containment solutions can eliminate hot spots and provide energy savings over traditional uncontained data center designs. The best containment solution for an existing facility will depend on the constraints of the facility. While ducted hot aisle containment is preferred for highest efficiency, cold aisle containment tends to be easier and more cost effective for facilities with existing raised floor air distribution. This presentation investigates the constraints, reviews all available containment methods, and provides recommendations for determining the best containment approach.
Clarifying ASHRAE's Recommended Vs. Allowable Temperature Envelopes and How t...Upsite Technologies
The topic of raising temperatures in data centers used to be met with much criticism in the industry, but in recent years has become more accepted. A big driver for this acceptance has been ASHRAE’s expanded envelope for recommended and allowable server inlet temperatures. However, while this has eased the discussion, there are still some questions that have been left unanswered. What’s the difference between recommended and allowable? Which one is best to use? What steps must be taken to safely raise set points? How do you ensure servers are still adequately cooled? What if you have different server types (A1, A2, A3, A4)? This presentation will examine these questions to give a clearer understanding of ASHRAE’s recommended and allowable guidelines. Also covered will be an explanation on how, in some cases, it is possible to raise cooling control set points without raising server inlet temperatures.
Presentation covers fundamental of CPU architecture and memory model used for Parallel Processing in easy to understand language.
Apart from theory, small example C code has also been provided.
Topics covered are
1. Introduction
2. Michael Flynn Classification (SISD, SIMD, MISD, MIMD)
3. Memory Model ( Shared vs Distributed)
4. SIMD
5. MIMD on Shared Memory
6. MIMD on Distributed Memory
The segmentation of data centers into alternating hot and cold aisles is an established best practice. A number of manufacturers are taking this premise of airflow separation a step further by marketing "containment" solutions. By containing the hot or cold aisle, the air paths have little chance to mix, presenting data center operators with both reliability and efficiency gains.
To view the recording of the webinar presentation, please visit http://www.42u.com/webinars/Aisle-Containment-Webinar/playback.htm
This code deals with the work satges required to commission automatic control systems in HVAC constuction industry. Represents standards for good practice in the form of recomantations and guidance. Is applicable for stand alone, BMS, DDC networked DDC and Integrated BMS systems.
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Dekon one of the professional manufacture and supplier for DC inverter VRF system in China. Here is the Dc inverter vrf installation instructions and tips.
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When developing data center energy-use estimations, engineers must account for all sources of energy use in the facility. Most energy consumption is obvious: computers, cooling plant and related equipment, lighting, and other miscellaneous electrical loads. Designing efficient and effective data centers is a top priority for consulting engineers. Cooling is a large portion of data center energy use, second only to the IT load. Although there are several options to help maximize HVAC efficiency and minimize energy consumption, data centers come in many shapes, sizes, and configurations. By developing a deep understanding of their client’s data center HVAC requirements, consulting engineers can help maintain the necessary availability level of mission critical applications while reducing energy consumption.
https://www.cedengineering.com/courses/description-of-useful-hvac-terms
This course contains a compilation of almost 1000 bits and pieces of HVAC terminology, definitions and/or descriptions that will help resolve ambiguities in common usage of terms in normal interactions of people, infrastructure and environment. The compilation is arranged in an alphabetical order for easy referencing. The detailed description can be traced in handbooks and the web sites. This course document is a constant work in progress and your feedback is always welcome in an effort to continually update it.
This online PDH course is aimed at mechanical, electrical, controls and HVAC engineers, architects, building designers, contractors, estimators, energy auditors and facility managers and other professionals who plan, design, construct, manage and use the building services infrastructure.
Distributed Control Systems (DCS) are dedicated systems used to control manufacturing processes that are continuous or batch-oriented, such as oil refining, petrochemicals, central station power generation, fertilizers, pharmaceuticals, food and beverage manufacturing, cement production, steelmaking, and papermaking. DCSs are connected to sensors and actuators and use set point control to control the flow of material through the plant.
The most common example is a set point control loop consisting of a pressure sensor, controller, and control valve. Pressure or flow measurements are transmitted to the controller, usually through the aid of a signal conditioning input/output (I/O) device. When the measured variable reaches a certain point, the controller instructs a valve or actuation device to open or close until the fluidic flow process reaches the desired set point.
Large oil refineries have many thousands of I/O points and employ very large DCSs. Processes are not limited to fluidic flow through pipes, however, and can also include things like paper machines and their associated quality controls (see quality control system QCS), variable speed drives and motor control centers, cement kilns, mining operations, ore processing facilities, and many others.
Innovic India Private Limited provides industrial Training on DCS as well as other automationtechnologies like PLC, SCADA, HMI, VFD and many more.
For Core Engineering jobs and 100% Job Oriented Industrial Training
Feel free to contact us on: +91-9555405045/+91-9811253572
Email: group.innovic2gmail.com
Web: www.innovicindia.com
At the very heart of cognitive psychology is the idea of information processing. Cognitive psychology sees the individual as a processor of information, in much the same way that a computer takes in information and follows a program to produce an output.Cognitive psychology compares the human mind to a computer, suggesting that we too are information processors and that it is possible and desirable to study the internal mental / mediational processes that lie between the stimuli (in our environment) and the response we make.
The information processing paradigm of cognitive psychology views that minds in terms of a computer when processing information.
However, there are important difference between humans and computers. The mind does not process information like a computer as computers don’t have emotions or get tired like humans
Comprehensive Guide to Taxonomy of Future KnowledgeMd Santo
(Cited from http://mobeeknowledge.ning.com/forum/topics/comprehensive-guide-to-... )
Our “Comprehensive Guide to Taxonomy of Future Knowledge” covering two variables continuum :
Data – Information – Knowledge – Wisdom or DIKW continuum origin (considered as Modern Knowledge) and
Nature Knowledge continuum origin (considered as Post Modern Knowledge)
The sub-variables being discussed consecutively are the followings :
Source of Consciousness as Knowledge attribute, Knowledge considered as....., Format of Knowledge, Terms given and the features of the domain, Knowledge Assessment, Methodology of Science, Definition of Knowledge, Eclectic definition of Knowledge Management
The segmentation of data centers into alternating hot and cold aisles is an established best practice. A number of manufacturers are taking this premise of airflow separation a step further by marketing "containment" solutions. By containing the hot or cold aisle, the air paths have little chance to mix, presenting data center operators with both reliability and efficiency gains.
To view the recording of the webinar presentation, please visit http://www.42u.com/webinars/Aisle-Containment-Webinar/playback.htm
This code deals with the work satges required to commission automatic control systems in HVAC constuction industry. Represents standards for good practice in the form of recomantations and guidance. Is applicable for stand alone, BMS, DDC networked DDC and Integrated BMS systems.
Gaining Data Center Cooling Efficiency Through Airflow ManagementUpsite Technologies
This presentation highlights research from Upsite Technologies regarding the latest best in data center airflow management and cooling, including steps to improvement. Originally delivered by Upsite President John Thornell at the AFCOM Boston-New England Chapter meeting.
Dekon one of the professional manufacture and supplier for DC inverter VRF system in China. Here is the Dc inverter vrf installation instructions and tips.
Darwin Logerot of ProSys presented an Alarm Rationalization Workshop - Tips, Tricks and Tracks at ISA Automation Week 2012 Contact us at prosys.com or 225-291-9591 x225 if you have any questions.
When developing data center energy-use estimations, engineers must account for all sources of energy use in the facility. Most energy consumption is obvious: computers, cooling plant and related equipment, lighting, and other miscellaneous electrical loads. Designing efficient and effective data centers is a top priority for consulting engineers. Cooling is a large portion of data center energy use, second only to the IT load. Although there are several options to help maximize HVAC efficiency and minimize energy consumption, data centers come in many shapes, sizes, and configurations. By developing a deep understanding of their client’s data center HVAC requirements, consulting engineers can help maintain the necessary availability level of mission critical applications while reducing energy consumption.
https://www.cedengineering.com/courses/description-of-useful-hvac-terms
This course contains a compilation of almost 1000 bits and pieces of HVAC terminology, definitions and/or descriptions that will help resolve ambiguities in common usage of terms in normal interactions of people, infrastructure and environment. The compilation is arranged in an alphabetical order for easy referencing. The detailed description can be traced in handbooks and the web sites. This course document is a constant work in progress and your feedback is always welcome in an effort to continually update it.
This online PDH course is aimed at mechanical, electrical, controls and HVAC engineers, architects, building designers, contractors, estimators, energy auditors and facility managers and other professionals who plan, design, construct, manage and use the building services infrastructure.
Distributed Control Systems (DCS) are dedicated systems used to control manufacturing processes that are continuous or batch-oriented, such as oil refining, petrochemicals, central station power generation, fertilizers, pharmaceuticals, food and beverage manufacturing, cement production, steelmaking, and papermaking. DCSs are connected to sensors and actuators and use set point control to control the flow of material through the plant.
The most common example is a set point control loop consisting of a pressure sensor, controller, and control valve. Pressure or flow measurements are transmitted to the controller, usually through the aid of a signal conditioning input/output (I/O) device. When the measured variable reaches a certain point, the controller instructs a valve or actuation device to open or close until the fluidic flow process reaches the desired set point.
Large oil refineries have many thousands of I/O points and employ very large DCSs. Processes are not limited to fluidic flow through pipes, however, and can also include things like paper machines and their associated quality controls (see quality control system QCS), variable speed drives and motor control centers, cement kilns, mining operations, ore processing facilities, and many others.
Innovic India Private Limited provides industrial Training on DCS as well as other automationtechnologies like PLC, SCADA, HMI, VFD and many more.
For Core Engineering jobs and 100% Job Oriented Industrial Training
Feel free to contact us on: +91-9555405045/+91-9811253572
Email: group.innovic2gmail.com
Web: www.innovicindia.com
At the very heart of cognitive psychology is the idea of information processing. Cognitive psychology sees the individual as a processor of information, in much the same way that a computer takes in information and follows a program to produce an output.Cognitive psychology compares the human mind to a computer, suggesting that we too are information processors and that it is possible and desirable to study the internal mental / mediational processes that lie between the stimuli (in our environment) and the response we make.
The information processing paradigm of cognitive psychology views that minds in terms of a computer when processing information.
However, there are important difference between humans and computers. The mind does not process information like a computer as computers don’t have emotions or get tired like humans
Comprehensive Guide to Taxonomy of Future KnowledgeMd Santo
(Cited from http://mobeeknowledge.ning.com/forum/topics/comprehensive-guide-to-... )
Our “Comprehensive Guide to Taxonomy of Future Knowledge” covering two variables continuum :
Data – Information – Knowledge – Wisdom or DIKW continuum origin (considered as Modern Knowledge) and
Nature Knowledge continuum origin (considered as Post Modern Knowledge)
The sub-variables being discussed consecutively are the followings :
Source of Consciousness as Knowledge attribute, Knowledge considered as....., Format of Knowledge, Terms given and the features of the domain, Knowledge Assessment, Methodology of Science, Definition of Knowledge, Eclectic definition of Knowledge Management
1. HCI notes
HIP Human
Information
Processing
1. What is HIP
2. HIP in HCI
3. Predictive and Descriptive models
4. An alternative to the Cognitive Model
5. Conclusion
6. References
HCI notes: Human Information Processing
2. 1. What is HIP
HUMAN + INFORMATION PROCESSING
≅
The computer is adopted as a
metaphor of human cognitive functioning.
how? people receive, store, integrate, retrieve
and use information
3. 1.
primarily developed a theory of memory.
HIP
theory
focused on the way people pay attention to the environment events,
encodes information and related with already stored knowledge for
learning, and how information is retrieval when needed.
sensory working long term
memory memory memory motor
stimulus processor
(sensory
input)
■ Are responsible for
■ the memory buffer that holds ■ The mental storage
transforming environmental input
currently and recently system responsible for
into neural impulses which the
processed information, and the storing information on a
Short Term Memory system can
can manipulate that information relatively permanent
process.
as well. basis Motor
Subsystem
Perceptual Subsystem Cognitive Subsystem
Analogous to Input
Analogous to ROM
device. Analogous to CPU memory where software is
(keyboard or scanner, or stored
voice recognition system)
4. 1.
sensory working
memory memory
PROCESSES
■ Pattern recognition. Process of granting meaning to the
stimulus by comparing the entry with the known information.
PERCEPTION ■ Bottom-up (data-driven). Physical characteristics of stimulus
drive perception. The interpretation emerges from the data.
ATTENTION ■ Top-down (schema-driven). Knowledge, expectations, or
thoughts influence perception. Constructivism: we structure the
world. A higher-level concept influences your interpretation of
lower level sensory data.
“We go "beyond the information given" constantly
in our mental processes. We learn to add
assumptions and supplemental information
derived from past experience to the evidence of
our senses, and that is how we make sense of
our world.”(Jerome Bruner, Beyond the
The "Rat-Man" of
Bugelski
Information Given, 1972) and Alampay (1961).
5. 1.
■ Bottleneck models. Broadbent's -and other attention models likeTreisman's
and Deutsch and Deutsch - are all bottleneck models because they predict we cannot
consciously attend to all of our sensory input at the same time.
ATTENTION This limited capacity for paying attention is therefore a bottleneck and the models each try
to explain how the material that passes through the bottleneck is selected.
Broadbentʼs (1958) Filter Model of Selective Attention
Factors related with the filter:
The number of input of information | The similarity of the input | The complexity of the
input.
■ Controlled and Automatic
processing. Controlled processes must be
executed in series because they need attention.
Autonomous processes do not need much attention so
they can run in parallel with other processes.
As a controlled task becomes habitual,
eventually becomes automatic.
Example: The stroop effect, It is very hard to
disconnect an automatic process. The stroop effect
6. 2. HIP in HCI
HUMAN INFORMATION PROCESSOR MODEL
“is a cognitive modeling method used to calculate
how long it takes to perform a certain task”
■ Cognitive models come from cognitive science. Unlike behavioral models
COGNITIVE (theories based on the analysis of stimuli and responses) cognitivism is based
MODEL? on internal mental processes.
E R
INPUT OUTPUT
?
■ The origin of the cognitive sciences coincides with the emergence and development of computers.
The operation of these machines serves as a metaphor for the researcher to explore the workings of
internal cognitive processes.
7. 2.
why?
■ HIP models are used in HCI to predict how an interactive
HCI
HIP
GOMS
system can be used.
■ Inside the HIP the dominant model - and most used- is the
GOMS, developed for Card, Moran & Newell in the 80s. GOMS is
a theory of the cognitive skills involved in human-computer tasks.
■ HIP approach is broader than GOMS. HIP can be used to
model more complex human behaviors like: Problem solving,
Learning or group interaction.
GOMS According to the GOMS, cognitive structure consist of 4 components:
■ Is a predictive model (related mainly to
routine skills). Reduces user-computer
interaction to its elementary actions (physical,
cognitive or perceptual)
G a set of goals
■ The method uses experimental time to
O a set of operators
calculate cognitive motor processing time.
M a set of methods for achieving the goals
■ Allows a system designer to predict the
PERFORMANCE with respect to time it takes S a set of selection rules for chosing
a person to complete a task without among competing methods.
performing experiments.
9. 3.
PREDICTIVE AND DESCRIPTIVE MODELS
Predictive Descriptive
models models
[quantitative] [qualitative]
Key-action
Hick-Hyman Law Model
Fitt’s law GOMS Buxton’s 3-states model
Keystroke-level Guiard’s model
model of bimanual control
*PM. Refers to a mathematical model that can *DM. Refers to a mathematical model that
accurately predict future outcomes. describes historical events, and the presumed
or real relationship between elements that
created
10. 3.
Predictive Descriptive
models models
■ Also engineering models or performance models. ■ Provide a framework or context for thinking about
or describing a problem or situation.
■ In HCI, allow metrics of human performance to be
determined analytically without experiments. Often the framework is little more than a verbal or
graphic articulation of categories or identifiable
■ Predictions are a priori: allow a design scenario to features in an interface. Nevertheless, the simple
be explored hypothetically. possession of such a framework arms the
designer with a tool for studying and thinking
about the user-interaction EXPERIENCE.
Example: Keystroke-level model Example: Key-action Model
TEXECTUTE= tK + tP + tH + tD + tM + tR
(motor-control operators)
K= key stroking | P= pointing | H= homing | D= drawing. Symbol keys: deliver graphic symbols ( letters, numbers, or punctuation)
Executive keys: invoke actions in the application or at the system level or meta
M= metal operator level. (examples include ENTER, F1 or ESC)
R= System-response operator
Modifier keys: Set up a condition necessary to modify the effect of a subsequently
pressed key. (example SHIFT or ALT)
11. 4. Alternatives to Cognitive Models. Activity Theory
ALTERNATIVES TO COGNITIVE MODELS
Why alternatives are necessary?
There is some evidence that the cognitive approach may be limited for HCI.
The limitation of modelling methods to support the design
process, may be due to their lack of taking 'context' into account.
■ It does not provide an appropriate conceptual basis for ■ Humans are not processing the information input from
studies of computer use in its social, organizational and the environment - they are actively picking up the
cultural contexts. information that is relevant in the context of their
current needs and goals.' It is control of this
■ The method has a number of 'defects' such as information pickup where the focus of HCI should be
reducing problem solving and judgement to mere rule Gibson, 1966.
following, ignoring informal communication,
underestimating of errors, giving no help to analysing ■ Difference in the information processes of computers
work organisation, etc and human mental decision processes.(Rasmussen)
In some contexts, HIP model is not completely satisfactory.
Activity Theory (AT) has been a recognized conceptual framework in HCI and related
disciplines.
12. 4.
Cognitive Science represent two different approaches Activity theory
to the study of cognitive processes
Activity Theory
■ Develop by Vygotsky (1920-30) Is an alternate
psychological approach (Russian). A more broad based
and durable framework for understanding ‘humans
His basic idea was that human activity is
interacting with computers’.
mediated by cultural signs: words and tools,
which causes changes in a person's activity,
■ The subject and the object are viewed as poles of a
and thus its mental reflection.
system of activity, which emphasises the active nature
of humans.
■ Takes a broader view of the 'technisation' of human
operations and places HCI within this wider framework.
■ Emphasises the contextuality of computer use. The contextual model of Activity.
■ (Respect to Cognitive Models) Activity Theory attacks
its theoretical basis: the principle of cognitive identity
between human thinking and computer simulation
13. 4.
Cognitive Activity
Science theory theory
Information Processing Loop Tool-mediation
The main difference between the two theories (applied to HCI) is
the point of view of the problem, or “clipping” (constraints) that
makes the reality.
The Tool Mediation perspective suggest a different structure
from the Information Processing Loop.
■ In HPI model the components of the ■ The computer is just another tool that
mediates the interaction of human beings
structure is limited to two entities: with the environment.
■ There are 2 interfaces: The human-
computer a n d t h e c o m p u t e r-
USER COMPUTER environment.
Information Processing Loop: USER TOOL OBJECT
The output from the human being,
enters the computer's input, and visa versa.
14. 5.
CONCLUSION
@
computer internet social software
(social information systems)
Thanks to the internet and social software boom (and many others), it seems that we have taken a
step higher in the scale of complexity described by Modridge.
anthropometrics physiology psychology sociology anthropology ecology
simplest level most complex
The sizes of people, for the The way the body works, The way the mind works, The way people relate to The human need to understand the
design of physical objects for the design of physical for the design of human- one another, for the design condition, for global issues that will affect the
man-machine systems computer interactions of connected systems design. environmental
(cultural variations ) condition of our planet
as well as the
interconnected social and
economic systems that
we need to sustain.
15. ■ Increasing complexity.
■ Need to incorporate more complex and wider models to help us predict
behavior in dynamic contexts (as in social networks).
■ Need to work with multidisciplinary teams (Psychologists. Sociologists... )
■ Need to incorporate frameworks beyond usability (Funology, emotional design, etc...)
thanks!
persuability design affective
emotional
funology interactions
human centered design
16. 6.
REFERENCES
Aboulafia, Annette; Gould, Edward; Spyrou, Thomas. Activity Theory vs Cognitive Science in the Study of Human-Computer Interaction.
Carroll, John M. (2003) HCI models, theories, and frameworks: toward a multidisciplinary science.
http://books.google.com/books?id=gR3Imgvr5dYC&pg=PA30&lpg=PA30&dq=map+of+HCI
+models&source=bl&ots=C86ciZWVKk&sig=v7YhY8JEdclkNY4goyb5Nc0u0h4&hl=en&ei=LMb2S-
zzNabWmgOS48zHAg&sa=X&oi=book_result&ct=result&resnum=1&ved=0CBYQ6AEwAA#v=onepage&q=map%20of%20HCI%20models&f=false.
Gibson J. J. (1966) The Senses Considered as Perseptual Systems, Boston, Houghton Mifflin.
Kaptelini, Victor. Activity Theory: Implications for Human-Computer Interaction.
Moggridge, Bill (2007) Designing Interactions. Boston, MIT Press.
Mwanza,Daisy; Bertelsen, Olav W. (2003) Methods for applying Activity Theory to HCI Design.
Norman, Donald (1998) The Invisible Computer. Boston, MIT Press.