Attentional capture by meaning: A multi-level modelling study

We present a computational study of attentional capture by meaning, based on Barnard et al's key-distractor attentional blink task. We highlight a sequence of models, from an abstract black-box to a structurally detailed white-box model. Each of these models reproduces the major findings from the key-distractor blink task. We argue that such multi-level modelling gives greater confidence in the theoretical position encapsulated by these models

MINING OF WEB LOG FILES USING RELEVANT COMPUTING TECHNIQUES FOR IMPROVING FUTURE ANTICIPATION USAGE OF WEB NAVIGATION

The Internet has evolved extensively over the past few decades. Web navigation refers to the process of navigating a network of information resources in the World Wide Web, which is organized as hypertext or hypermedia. The navigation related to web navigation usability gets solved by comparing the actual and anticipated usage patterns. The actual usage pattern removed from web server logs are sporadically recorded in operational websites for handling the log data. This process is used to identify the users, user session and user task oriented transactions. The pattern can be discovered among the actual usage path by using the algorithms of data mining generally the ideal user’s interactive path models are framed by cognitive experts based on the cognition of user behavior, which is utilized to pull out the anticipated usage, that includes information about both the time required for user-oriented tasks and the mechanism to identify the user navigation problems here the usability issues get detected from the deviation of the data. It is observed that Genetic algorithms can be used as optimization methods and for corrective action to improve the web navigation usability

Modeling of Stimulus-Response Secondary Tasks with Different Modalities while Driving in a Computational Cognitive Architecture

This paper introduces a computational human performance model based upon the queueing network cognitive architecture to predict driver’s eye glances and workload for four stimulus-response secondary tasks (i.e., auditorymanual, auditory-speech, visual-manual, and visual-speech types) while driving. The model was evaluated with the empirical data from 24 subjects, and the percentage of eyes-off-road time and driver workload generated by the model were similar to the human subject data. Future studies aim to extend the types of voice announcements/commands to enable Human-Machine-Interface (HMI) evaluations with a wider range of usability test for in-vehicle infotainment system developments

An Overview of Personalized Recommendation System to Improve Web Navigation

We present a new personalized recommendation system, which means the searches of each user is done according to their interest which is based on ranking or preference method. It also maintains the logs which records the sessions of each user and brings out the exact data required by the user. This is done by fetching the data that is already stored in the database. Web server logs maintains history of page results and consists of a log file which automatically creates and maintains the list of activities performed by the users. For extracting the data according to the user’s previous searches, we are using Stemming Algorithm. The Stemming Algorithm is a process where the exact, meaningful words are extracted from the URL. Because of this process the user’s search time will be reduced. It also improves the quality of web navigation and overcomes the limitation of existing system. In the proposed system we extract user’s behaviour from web server logs in the actual process whereas, in the anticipated system, the user’s behaviour is done with the help of cognitive user model and we perform the comparison between the two usage processes. The data produced from this comparison can help the users to discover usability issues and take actions to improve usability. In the anticipated usage the cognitive user model is done that can be used to simulate or predict human behaviour or by performance and task. Finally, the system is executed by using the top-k ranking algorithm. The advantage of this system are accuracy and better processing speed. The user’s convenience deals with the ease of navigation which helps the users to interact with their interface

Method and engineering tools for in-vehicle information systems (In-Vehicle Information Systems), focusing on the risk of driver distraction

Thousands of deaths a year are attributed to driver distractions while driving. The automotive industry has worked for decades maturing development guidelines and complex evaluation scenarios for the acceptance of infotainment centers as an integral part of the vehicle. The massification of smart wearable devices with a gigantic ecosystem of mobile applications not designed for the particularities of the automotive environment, easily bypasses the precautions of safe driving schemes. There is then, a niche of developers without the formal knowledge and economic support to adequately enter the automotive applications development. Cost-benefit methods and tools accessible in the context of software engineering are proposed to support the development of in-vehicle information systems in accordance with the requirements of current regulations and standards.Facultad de Informátic

Assessing the Human Factor in Truck Driving

Human factors assessment techniques are commonly applied to a variety of workplaces to examine the nature of operations and how key functions are controlled operationally; however, these tools appear to overlook key aspects of truck driving, particularly the driver’s relationship to the driving experience. The fundamental issue is with the ability to completely decompose truck driving and accurately document the truck drivers working environment will be problematic. Therefore, to demonstrate how a truck driver moves between each series of sub-tasks will require a purpose-built assessment tool that that is both practical and relevant to truck driving