No abstract

In the field of Human Computer Interaction and Psychology, it is accepted that spatial visualization (VZ) is one ability that can indicate individual’s performance on computer applications. Since users with different levels of VZ seem to prefer different types of user interfaces (UI), knowing a user’s level of VZ provides a great opportunity for application developers to design software with higher satisfaction and usability. In this paper, we proposed three models to predict a participant’s level of VZ based on the participant’s actions (taps) on the tablet screen while doing an address verification task in the neighbor- hood using the tablet. After applying the proposed prediction models with data of thirty participants, they yielded an optimal accuracy of 93.33%.

An adaptive software system is known as an application that can adapt itself based on different conditions of users. There are multiple conditions/criteria that can be used to direct how an application would adapt. Spatial visualization (VZ) is one of several human spatial abilities that is used to predict human’s performance when using a computer application. Therefore, a difference in VZ level is a suitable choice as an adapting indicator, i.e., high VZ and low VZ users should get different features on a user interface (UI) to complete the same task. In this paper, we look at three studies where we asked participants to verify a set of housing addresses using a location-based application on an Android tablet with different versions of the application, especially, an adaptive version of the application was involved in the last study. We found that, for high VZ participants, the number of UI errors that participants created was significantly smaller when they were equipped with the adaptive software. We refer to a UI error (User Interface Error) as an error where a user tapped on a non-sensitive region of the screen. The results of the three studies and hypothesis tests for significance are reported.

Many users use a location-based application on a portable device to be a navigator when driving. However, there exists an incident that two roads are located on the same geolocation, i.e., same values of latitude and longitude but different altitude, for very long distance where one road is located on the ground level and another one is elevated. This incident mostly confuses a location-based application to precisely retrieve the actual road that a vehicle is currently on and, consequently, causes the application to either navigate incorrectly or suggest a route that is a detour. Calling an altitude from a GPS sensor might be a possible solution but it came with problems of accuracy, especially for mid-grade GPS sensors that equipped with most smartphone in today’s market. We proposed a concept of implementing a classification model that can classify whether a vehicle is on a ground road or an elevated road regardless of geolocation data. We trained and validated two models using a dataset that we had collected from actual driving on two roads in Thailand that fell under this condition. A data instance that we collected contained measurements related to driving or driving environment such as a real-time speed at any certain interval of time. We reported validation results of both models as well as other important statistics.

Deadlock between processes and resources is a serious problem in development of operating system. Multiple methods were invented to deal with deadlock issue. Deadlock detection is one method that allows a deadlock to take place then detects thereafter which processes and resources have caused it. In traditional process-resource graph, we propose an approach to detect a deadlock by implementing model checking technique and Computation Tree Logic (CTL) specification. In this paper, we modified traditional process-resource graph such that the outcome graph satisfied valid model of Kripke structure, which over- came limitations of traditional representation of process-resource graph and still preserved every proposition, correctness, and property of the system. With the modified graph, we designed a CTL specification that verified whether or not there existed a deadlock caused by one or more pairs of process and resource. A Java application was developed to implement the proposed approach such that it was capable of dynamically generating a valid model for any process-resource graph input, dynamically generating CTL formula for specification, and verifying the model with corresponding CTL formula.