Specification Of Temporal Constraints Research Articles

Not all phenotypes are created equal: covariates of success in e-phenotype specification.

Electronic (e)-phenotype specification by noninformaticist investigators remains a challenge. Although validation of each patient returned by e-phenotype could ensure accuracy of cohort representation, this approach is not practical. Understanding the factors leading to successful e-phenotype specification may reveal generalizable strategies leading to better results. Noninformaticist experts (n = 21) were recruited to produce expert-mediated e-phenotypes using i2b2 assisted by a honest data-broker and a project coordinator. Patient- and visit-sets were reidentified and a random sample of 20 charts matching each e-phenotype was returned to experts for chart-validation. Attributes of the queries and expert characteristics were captured and related to chart-validation rates using generalized linear regression models. E-phenotype validation rates varied according to experts' domains and query characteristics (mean = 61%, range 20-100%). Clinical domains that performed better included infectious, rheumatic, neonatal, and cancers, whereas other domains performed worse (psychiatric, GI, skin, and pulmonary). Match-rate was negatively impacted when specification of temporal constraints was required. In general, the increase in e-phenotype specificity contributed positively to match-rate. Clinical experts and informaticists experience a variety of challenges when building e-phenotypes, including the inability to differentiate clinical events from patient characteristics or appropriately configure temporal constraints; a lack of access to available and quality data; and difficulty in specifying routes of medication administration. Biomedical query mediation by informaticists and honest data-brokers in designing e-phenotypes cannot be overstated. Although tools such as i2b2 may be widely available to noninformaticists, successful utilization depends not on users' confidence, but rather on creating highly specific e-phenotypes.

Formal Synthesis of Real-Time Embedded Software by Time-Memory Scheduling of Colored Time Petri Nets

With the computerization of most daily-life human amenities such as home appliances, the software in a real-time embedded system now accounts for as much as 70% of a system design. On one hand, this increase in software has made embedded systems more accessible and easy to use, while on the other hand, it has also necessitated further research on how a complex, real-time, embedded software can be designed automatically and correctly. Enhancing recent advances in this research, we propose a Time-Memory Scheduling (TMS) method for formally synthesizing and automatically generating code for real-time embedded software, using the Colored Time Petri Nets model. Our method extends previous work in three ways: (1) by allowing the specification of temporal constraints in the system description to model real-time behaviors of software, (2) by allowing the specification of colored tokens in the system description to model different memory usages by data-types, and (3) by proposing an extended algorithm to schedule the enhanced system model and generate static code. A real-time embedded software, which is specified by a set of CTPN, is scheduled using TMS such that the schedules satisfy limited embedded memory requirements and all real-time and task precedence constraints. Finally, a portable embedded software program is generated in the C programming language using the valid TMS schedules. The proposed method was implemented in Java so that it can be installed in design prototypes for on-line code change in order to satisfy the dynamic needs of users. Through a real-world example on the ATM Virtual Private Network server, we illustrate the feasibility and advantages of the proposed TMS method for synthesizing embedded real-time software.