Automated detection of naming conflicts in schema integration: Experiments with quiddities*

This paper discusses experiments involving a method for the automatic detection, prior to the integration of data base schemas, of conflicts in the naming of data elements within these schemas. The method relies on the representation of semantic information (called quiddity) about the data elements present in the various schemas. We develop several inference procedures which, utilizing this information, determine whether to distinctly named elements in fact represent the same object, or if elements with the same name actually represent different objects. The experiments are concerned with (a) examining the accuracy and consistency with which quiddities of data elements might be declared by different database designers, and (b) evaluating the accuracy and errors of these automated procedures. Our results indicate that the method has promise for use in detection of naming conflicts, and that certain inference procedures are superior to others in terms of their accuracy and error ratesNaval Postgraduate School, Monterey, CAhttp://archive.org/details/automateddetecti00bharO&MN Direct FundingNAApproved for public release; distribution is unlimited

On the integration of data and mathematical modeling languages

This paper examines ways in which the addition of data modeling features can enhance the capabilities of mathematical modeling languages, and demonstrates how such integration might be achieved as an application of the embedded languages technique proposed by Bhargava and Kimbrough. Decision making, and decision support systems, require the representation and manipulation of both data and mathematical models. Several data modeling languages as well as several mathematical modeling languages exist, but they have differences sets of capabilities. We motivate with a detailed example the need for the integration of these languages. We describe the benefits that might result, and claim that this could lead to a significant improvement in the functionality of model management systems. Then we present our approach for the integration of these languages, and specify how the claimed benefits are realized.This paper examines ways in which the addition of data modeling features can enhance the capabilities of mathematical modeling languages, and demonstrates how such integration might be achieved as an application of the embedded languages technique proposed by Bhargava and Kimbrough, [4]Decision-making, and decision support systems, require the representation and manipulation of both data and mathematical models. Several data modeling languages as well as several mathematical mod- eling languages exist, but they have differences sets of capabilities. We motivate with a detailed example the need for the integration of these languages. We describe the benefits that might result, and claim that this could lead to a significant improvement in the functionality of model management systems. Then we present our approach for the integration of these languages, and specify how the claimed benefits are realized.Naval Postgraduate School, Monterey, California.Approved for public release; distribution is unlimited

Unique Names Violations, a Problem for Model Integration, You Say Tomato, I Say Tomahto

The article of record as published may be found at https://doi.org/10.1287/ijoc.3.2.107The tomato-tomahto problem (known as the synonymy problem in the database literature) arises in the context of model management when different names are used in different models for what should be identical variables, and these different models are to be integrated or combined into a larger model. When this problem occurs, it is said that the unique names assumption has been violated. We propose a method by which violations of the unique names assumption can be automatically detected. The method relies on declaring four kinds of information and modeling variables: dimensional information, laws relating dimensional expressions, information (called the quiddity) about the intended interpretation of the variables, and laws relating quiddity expressions. We present and discuss the method and the principles and theory behind it, and we describe our (prototype) implementation of the method, as an additional function of an existing model management system

Competence in Endoscopic Ultrasound and Endoscopic Retrograde Cholangiopancreatography, From Training Through Independent Practice.

BACKGROUND & AIMS: It is unclear whether participation in competency-based fellowship programs for endoscopic ultrasound (EUS) and endoscopic retrograde cholangiopancreatography (ERCP) results in high-quality care in independent practice. We measured quality indicator (QI) adherence during the first year of independent practice among physicians who completed endoscopic training with a systematic assessment of competence. METHODS: We performed a prospective multicenter cohort study of invited participants from 62 training programs. In phase 1, 24 advanced endoscopy trainees (AETs), from 20 programs, were assessed using a validated competence assessment tool. We used a comprehensive data collection and reporting system to create learning curves using cumulative sum analysis that were shared with AETs and trainers quarterly. In phase 2, participating AETs entered data into a database pertaining to every EUS and ERCP examination during their first year of independent practice, anchored by key QIs. RESULTS: By the end of training, most AETs had achieved overall technical competence (EUS 91.7%, ERCP 73.9%) and cognitive competence (EUS 91.7%, ERCP 94.1%). In phase 2 of the study, 22 AETs (91.6%) participated and completed a median of 136 EUS examinations per AET and 116 ERCP examinations per AET. Most AETs met the performance thresholds for QIs in EUS (including 94.4% diagnostic rate of adequate samples and 83.8% diagnostic yield of malignancy in pancreatic masses) and ERCP (94.9% overall cannulation rate). CONCLUSIONS: In this prospective multicenter study, we found that although competence cannot be confirmed for all AETs at the end of training, most meet QI thresholds for EUS and ERCP at the end of their first year of independent practice. This finding affirms the effectiveness of training programs. Clinicaltrials.gov ID NCT02509416

Competence in Endoscopic Ultrasound and Endoscopic Retrograde Cholangiopancreatography, From Training Through Independent Practice.

BACKGROUND & AIMS: It is unclear whether participation in competency-based fellowship programs for endoscopic ultrasound (EUS) and endoscopic retrograde cholangiopancreatography (ERCP) results in high-quality care in independent practice. We measured quality indicator (QI) adherence during the first year of independent practice among physicians who completed endoscopic training with a systematic assessment of competence. METHODS: We performed a prospective multicenter cohort study of invited participants from 62 training programs. In phase 1, 24 advanced endoscopy trainees (AETs), from 20 programs, were assessed using a validated competence assessment tool. We used a comprehensive data collection and reporting system to create learning curves using cumulative sum analysis that were shared with AETs and trainers quarterly. In phase 2, participating AETs entered data into a database pertaining to every EUS and ERCP examination during their first year of independent practice, anchored by key QIs. RESULTS: By the end of training, most AETs had achieved overall technical competence (EUS 91.7%, ERCP 73.9%) and cognitive competence (EUS 91.7%, ERCP 94.1%). In phase 2 of the study, 22 AETs (91.6%) participated and completed a median of 136 EUS examinations per AET and 116 ERCP examinations per AET. Most AETs met the performance thresholds for QIs in EUS (including 94.4% diagnostic rate of adequate samples and 83.8% diagnostic yield of malignancy in pancreatic masses) and ERCP (94.9% overall cannulation rate). CONCLUSIONS: In this prospective multicenter study, we found that although competence cannot be confirmed for all AETs at the end of training, most meet QI thresholds for EUS and ERCP at the end of their first year of independent practice. This finding affirms the effectiveness of training programs. Clinicaltrials.gov ID NCT02509416

Dimensional Analysis in Mathematical Modeling Systems a Simple Numerical Method

This paper discusses dimensional manipulation, essentially a problem requiring symbolic techniques, using a numerical method obeys the laws of dimensional arithmetic. This is achieved by specifying an encoding of units of measurement as prime numbers, and manipulating the resulting expressions numerically. The unique factorization theorem is applied to show that this method makes trivial the problems of dimensional simplification and verification of dimensional equivalency, which are central issues in dimensional arithmetic. The solution has immediate application in mathematical modeling system, chiefly in the model validation and model solution phasesNaval Postgraduate School, Monterey, California.http://archive.org/details/dimensionalanaly00bharO&MN Direct FundingNAApproved for public release; distribution is unlimited

Fleet Mix Planning in the U.S. Coast Guard: Issues and Challenges for DSS*

Fleet mix planning in the U.S. Coast Guard involves determining a combination of naval assets best suited to meet the Coast Guard's future mission requirements while satisfying various resource constraints. In this paper, I describe the problem, and present and discuss certain challenges it raises in the field of decision support systems (DSS). The fleet mix planning problem is fairly unstructured, has a long-term planning horizon and impact, and there is uncertainty about future mission objectives and demand for the fleet's services. As such, I believe, it is a classical application suited to the use of DSS technology, according to accepted definitions of a DSS. However, an examination of DSS theory and technology reveals that current DSS theories and implementations do not adequately address this problem. Thus, the fleet mix planning problem raises several research challenges in the design and implementation of decision support systems. In this paper, I discuss the problem and these challenges in detail, and propose that fleet mix planning could be a useful benchmark problem for DSSNaval Postgraduate School, Monterey, CAhttp://archive.org/details/fleetmixplanning00bharO&MN, Direct FundingNAApproved for public release; distribution is unlimited

Reasoning with assumptions, defeasibly, in model formulation

Working papers of the Naval Postgraduate School Department of Administrative Sciences are preliminary materials circulated to stimulate discussion and critical comment. The views stated herein are the author's and not necessarily those of the Department of the Navy or the Naval Postgraduate School.This paper examines the relevance of reasoning with assumptions in two processes that are desired to be supported in model management systems, namely model formulation and model version management. We submit, and illustrate with an example, that the ability to represent and reason with assumptions in modeling languages could lead to significant improvement in the functionality of model management systems. We also argue that the process of reasoning with assumptions is non-monotonic and propose that defeasible reasoning is a useful candidate for modeling this processhttp://archive.org/details/reasoningwithass00bharNaval Postgraduate School, Monterey, California