Designing effective user interfaces (UIs) is a complex decisionmaking process that often relies on usability testing and understanding users' preferences.However, user preferences can vary widely based on contextual information (such as age, nationality, or use-case of the software system), posing a significant challenge in creating universally effective studies.To address this, we propose a novel framework of contextual discrete choice experimentation (DCE) to learn the relationship between contextual information and user preferences, enabling the creation of more statistically efficient studies for new cohorts of participants.In this framework, users are presented with a sequence of questions where they choose their preferred option between two or more design alternatives.This preference data, combined with contextual information, is used to develop a statistical model that recommends UI designs to new or existing users.We detail the methodology for designing contextual DCEs and demonstrate its application with a real-world example involving users of a statistical software system.Our results indicate that the contextual DCE framework effectively captures user preferences and provides personalized UI recommendations.

An automated biological fluid dispensing system for microarray fabrication using inkjet technology is presented in this paper. The hardware of the system consists of a high-precision motion system, a robotic material handling system, computer control systems, and extensive vision systems. The system software includes algorithms to handle control, communication, and manufacturing process information. This fluid dispensing system has been successfully used to produce cDNA microarrays and in the investigation of protein microarray manufacturing.

This paper presents an automated DNA and protein microarray fabrication system using inkjet technology. The hardware of the system consists of a high-precision motion system, a robotic material handling system, computer control systems, and extensive vision systems. The software of the system includes sophisticated algorithms to handle control, communication, and manufacturing process information. The system has been successfully used to produce cDNA microarrays and in the investigation of protein microarray manufacturing. Ground-breaking results have been attributed to the use of cDNA and protein microarrays in genomics and proteomics research

This paper presents a functional model based object-oriented framework for mechatronic system development. The approach has been applied to conceptual design of a new generation plate making system for DNA micro-array manufacturing automation. The contributions of this paper include the functional model and object-oriented development framework for mechatronic systems, and concepts of cost and design optimization at the system functional model level.

This paper first reviews the DNA microarray deposition technology. Different aspects of factory automation for DNA microarray manufacturing are then discussed. Problems, challenges and suggestions for investing factory automation, design, implementation as well as managing automated fab for DNA microarray manufacturing are presented from an industrial automation viewpoint. The purpose is to propose an idea of systematic investment, development and management of factory automation for DNA microarray manufacturing.

Proposes a sensor-based planar object mapping and handling robot system for DNA micro-array deposition equipment. The contributions of the paper include a sensor-based mapping algorithm for planar objects, and the idea of an efficient planar object handling system for DNA micro-array deposition process. The mapping algorithm gives a robust way for mapping a planar object's physical situation based on simple sensor inputs. The success of the algorithm benefits from its unique mathematical modelling of a physical system by simply changing the viewpoint. The new planar object handling system is obtained by integrating the mapping algorithm, and a revised end-effector for current widely used 3-degree-of-freedom robot manipulator.