Implementation of Software Process Improvement Through TSPi in Very Small Enterprises

This article shows an experience in a very small enterprise related to improving software quality in terms of test and process productivity. A customized process from the current organizational process based on TSPi was defined and the team was trained on it. The pilot project had schedule and budget constraints. The process began by gathering historical data from previous projects in order to get a measurement repository. Then the project was launched and some metrics were collected. Finally, results were analyzed and the improvements verified

The Skills to Pay the Bills: An Evaluation of an Effort to Help Nonprofits Manage Their Finances

This study examines a Wallace Foundation-sponsored initiative aimed at improving the financial management skills and practices of 25 Chicago afterschool providers through training and coaching. Two models for this professional development were provided and each produced long-lasting improvements. Moreover, organizations receiving the less-expensive group training and coaching improved almost as much as those receiving more intensive customized coaching

Quality Improvement for Well Child Care

Presented to the Faculty of University of Alaska Anchorage in Partial Fulfillment of Requirements for the Degree of MASTER OF SCIENCEThe American Academy of Pediatrics (AAP) Bright Futures (BF) guidelines for well child care were designed to provide quality pediatric care. Adherence to AAP-BF guidelines improves: screenings, identification of developmental delay, immunization rates, and early identification of children with special healthcare needs. The current guideline set is comprehensive and includes thirty one well child exams, thirty three universal screening exams and one hundred seventeen selective screening exams. Many providers have difficulty meeting all guideline requirements and are at risk of committing Medicaid fraud if a well exam is coded and requirements are not met. The goal of this quality improvement project was to design open source and adaptable templates for each pediatric age group to improve provider adherence to the BF guidelines. A Plan-Do-Study-Act (PDSA) quality improvement model was used to implement the project. Templates were created for ages twelve months to eighteen years and disseminated to a pilot clinic in Anchorage, Alaska. The providers were given pre-implementation and postimplementation surveys to determine the efficacy and usefulness of the templates. Templates were determined to be useful and efficient means in providing Bright Futures focused well child care. The templates are in the process of being disseminated on a large scale to assist other providers in meeting BF guideline requirements.Title Page / Table of Contents / List of Tables / List of Appendices / Abstract / Introduction / Background / Clinical Significance / Current Clinical Practice / Research Question / Literature Review / Framework: Evidence Based Practice Model/ Ethical Considerations and Institutional Review Board / Methods / Implementation Barriers / Findings / Discussion / Disseminatio

Attribute Identification and Predictive Customisation Using Fuzzy Clustering and Genetic Search for Industry 4.0 Environments

Today´s factory involves more services and customisation. A paradigm shift is towards “Industry 4.0” (i4) aiming at realising mass customisation at a mass production cost. However, there is a lack of tools for customer informatics. This paper addresses this issue and develops a predictive analytics framework integrating big data analysis and business informatics, using Computational Intelligence (CI). In particular, a fuzzy c-means is used for pattern recognition, as well as managing relevant big data for feeding potential customer needs and wants for improved productivity at the design stage for customised mass production. The selection of patterns from big data is performed using a genetic algorithm with fuzzy c-means, which helps with clustering and selection of optimal attributes. The case study shows that fuzzy c-means are able to assign new clusters with growing knowledge of customer needs and wants. The dataset has three types of entities: specification of various characteristics, assigned insurance risk rating, and normalised losses in use compared with other cars. The fuzzy c-means tool offers a number of features suitable for smart designs for an i4 environment

Constructing a Toolkit to Evaluate Quality of State and Local Administrative Data

State and local agencies administering programs have in their administrative data a powerful resource for policy analysis to inform evaluation and guide improvement of their programs. Understanding different aspects of their administrative data quality is critical for agencies to conduct such analyses and to improve their data for future use. However, state and local agencies often lack the resources and training for staff to conduct rigorous evaluations of data quality. We describe our efforts developing tools that can be used to assess data quality as well as the challenges encountered in constructing these tools. The toolkit focuses on critical dimensions of quality for analyzing an administrative dataset, including checks on data accuracy, the completeness of the records, and the comparability of the data over time and among subgroups of interest. State and local administrative databases often include a longitudinal component which our toolkit also aims to exploit to help evaluate data quality. While we seek to develop general tools for common data quality analyses, most administrative datasets have particularities that can benefit from a customized analysis building on our toolkit. In addition, we incorporate data visualization to draw attention to sets of records or variables that contain outliers or for which quality may be a concern

Real time trajectory matching and outlier detection for assembly operator trajectories

Flexible, reactive and adaptive manufacturing systems are a prerequisite to cope with the demand for low volumes of highly customized products of today’s market. For years, manufacturing companies have been using real-time data capturing systems, such as RFID, to gather the necessary data to obtain insights in their production processes, mainly in the domain of quality control and inventory management. However, very few work has been done on monitoring an assembly operator during his work cycle in real-time. This paper presents a method to match operator trajectories, obtained through a multi-camera vision system, in real-time to predefined models. This way, the performance of the operator can be assessed online and problematic or anomalous work cycles can be detected. This information can then be used to support the operator in his pursuit for continuous improvement by pointing out improvement potential