Human Interface and the Management of Information. Information in Applications and Services

In UX research, people with idiosyncratic or stigmatized conditions may go unrecognized, be dismissed as outliers, or be lumped within the larger normative group. This most directly affects persons with disabilities, medical conditions, or differing lifestyle or belief systems. This tendency may over represent the homogenous group while under representing other idiosyncratic groups based on complex factors such as stigma or perceived risk associated with revealing more accurate aspects of conditions, beliefs or lifestyle. This research bias negatively impacts the outcomes of the UX data and impacts the quality of designed products or services. Therefore, there is a critical need to identify the roles of ethnographic research, cultural programming, and cultural relativism with regard to stigmatized and idiosyncratic populations. The Divergency Model is a UX research and design methodology to identify and measure proximal distances in stigma/conformity and apathy/motivation between individual or target groups.

[1]  Tom Stonier,et al.  Information and Meaning , 1997, Springer London.

[2]  R. Ackoff.  From Data to Wisdom , 2014 .

[3]  Takatoshi Ishii,et al.  Development and evaluation of a self-learning support system for Patent Act suited to the current state of intellectual property education in engineering departments , 2016, 2016 IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE).

[4]  Rolf Landauer,et al.  Dissipation and noise immunity in computation and communication , 1988, Nature.

[5]  L. Brillouin,et al.  Physical Entropy and Information. II , 1951 .

[6]  Stephen Wolfram,et al.  Universality and complexity in cellular automata , 1983 .

[7]  N. Margolus,et al.  The maximum speed of dynamical evolution , 1997, quant-ph/9710043.

[8]  E. Schrödinger,et al.  What is life? : the physical aspect of the living cell , 1946 .

[9]  L. Szilard.  On the decrease of entropy in a thermodynamic system by the intervention of intelligent beings. , 1964, Behavioral science.

[10]  Tom Stonier,et al.  Information and the Internal Structure of the Universe , 1990, Springer London.

[12]  E. T. Jaynes.  Gibbs vs Boltzmann Entropies , 1965 .

[13]  Gregory J. Chaitin,et al.  Algorithmic Information Theory , 1987, IBM J. Res. Dev..

[14]  A. Kolmogorov.  Three approaches to the quantitative definition of information , 1968 .

[15]  L. Goddard.  Information Theory , 1962, Nature.

[16]  Ray J. Solomonoff,et al.  A Formal Theory of Inductive Inference. Part I , 1964, Inf. Control..

[17]  Sven Schmerwitz,et al.  A concept for a virtual flight deck shown on an HMD , 2016, SPIE Defense + Security.

[18]  S. Lloyd.  Ultimate physical limits to computation , 1999, Nature.

[19]  Yoshikazu Nakamura,et al.  Online Writer Verification Using Feature Parameters Basedonthe Document Examiners' Knowledge , 2009 .

[20]  Tieniu Tan,et al.  Online Text-Independent Writer Identification Based on Stroke's Probability Distribution Function , 2007, ICB.

[21]  Claude E. Shannon,et al.  Recent Contributions to The Mathematical Theory of Communication , 2009 .

[22]  E. Bass,et al.  Using Relative Position and Temporal Judgments to Assess the Effects of Texture and Field of View on Spatial Awareness for Synthetic Vision Systems Displays , 2006 .

[23]  T. Stonier.  Beyond Information: The Natural History Of Intelligence , 1992 .

[24]  Takashi Matsumoto,et al.  Online Signature Verification Based on User-Generic Fusion Model with Markov Chain Monte Carlo, Taking into Account User Individuality , 2009, J. Adv. Comput. Intell. Intell. Informatics.

[25]  Ronaldo Vigo,et al.  Complexity over Uncertainty in Generalized Representational Information Theory (GRIT): A Structure-Sensitive General Theory of Information , 2012, Inf..

[26]  Ron Fulbright,et al.  Cognitive Augmentation Metrics Using Representational Information Theory , 2017, HCI.

[27]  Gregory J. Chaitin,et al.  On the Length of Programs for Computing Finite Binary Sequences , 1966, JACM.

[28]  Christopher G. Langton,et al.  Computation at the edge of chaos: Phase transitions and emergent computation , 1990 .

[29]  Kikuo Tanaka,et al.  Standard Structure of Legal Provisions -For The Legal Knowledge Processing by Natural Language- , 1993 .

[30]  Ronaldo Vigo.  Mathematical Principles of Human Conceptual Behavior: The Structural Nature of Conceptual Representation and Processing , 2014 .

[31]  William Turin,et al.  Statistical Methods for On-Line Signature Verification , 1994, Int. J. Pattern Recognit. Artif. Intell..

[32]  R. Hartley.  Transmission of information , 1928 .

[33]  Stephen Wolfram,et al.  A New Kind of Science , 2003, Artificial Life.

[34]  H.-U. Doehler,et al.  Virtual aircraft-fixed cockpit instruments , 2015, Defense + Security Symposium.