9,033 research outputs found
UMSL Bulletin 2023-2024
The 2023-2024 Bulletin and Course Catalog for the University of Missouri St. Louis.https://irl.umsl.edu/bulletin/1088/thumbnail.jp
Towards A Practical High-Assurance Systems Programming Language
Writing correct and performant low-level systems code is a notoriously demanding job, even for experienced developers. To make the matter worse, formally reasoning about their correctness properties introduces yet another level of complexity to the task. It requires considerable expertise in both systems programming and formal verification. The development can be extremely costly due to the sheer complexity of the systems and the nuances in them, if not assisted with appropriate tools that provide abstraction and automation.
Cogent is designed to alleviate the burden on developers when writing and verifying systems code. It is a high-level functional language with a certifying compiler, which automatically proves the correctness of the compiled code and also provides a purely functional abstraction of the low-level program to the developer. Equational reasoning techniques can then be used to prove functional correctness properties of the program on top of this abstract semantics, which is notably less laborious than directly verifying the C code.
To make Cogent a more approachable and effective tool for developing real-world systems, we further strengthen the framework by extending the core language and its ecosystem. Specifically, we enrich the language to allow users to control the memory representation of algebraic data types, while retaining the automatic proof with a data layout refinement calculus. We repurpose existing tools in a novel way and develop an intuitive foreign function interface, which provides users a seamless experience when using Cogent in conjunction with native C. We augment the Cogent ecosystem with a property-based testing framework, which helps developers better understand the impact formal verification has on their programs and enables a progressive approach to producing high-assurance systems. Finally we explore refinement type systems, which we plan to incorporate into Cogent for more expressiveness and better integration of systems programmers with the verification process
TeamSTEPPS and Organizational Culture
Patient safety issues remain despite several strategies developed for their deterrence. While many safety initiatives bring about improvement, they are repeatedly unsustainable and short-lived. The index hospital’s goal was to build an organizational culture within a groundwork that improves teamwork and continuing healthcare team engagement. Teamwork influences the efficiency of patient care, patient safety, and clinical outcomes, as it has been identified as an approach for enhancing collaboration, decreasing medical errors, and building a culture of safety in healthcare. The facility implemented Team Strategies and Tools to Enhance Performance and Patient Safety (TeamSTEPPS), an evidence-based framework which was used for team training to produce valuable and needed changes, facilitating modification of organizational culture, increasing patient safety compliance, or solving particular issues. This study aimed to identify the correlation between TeamSTEPPS enactment and improved organizational culture in the ambulatory care nursing department of a New York City public hospital
A review on detecting brain tumors using deep learning and magnetic resonance images
Early detection and treatment in the medical field offer a critical opportunity to survive people. However, the brain has a significant role in human life as it handles most human body activities. Accurate diagnosis of brain tumors dramatically helps speed up the patient's recovery and the cost of treatment. Magnetic resonance imaging (MRI) is a commonly used technique due to the massive progress of artificial intelligence in medicine, machine learning, and recently, deep learning has shown significant results in detecting brain tumors. This review paper is a comprehensive article suitable as a starting point for researchers to demonstrate essential aspects of using deep learning in diagnosing brain tumors. More specifically, it has been restricted to only detecting brain tumors (binary classification as normal or tumor) using MRI datasets in 2020 and 2021. In addition, the paper presents the frequently used datasets, convolutional neural network architectures (standard and designed), and transfer learning techniques. The crucial limitations of applying the deep learning approach, including a lack of datasets, overfitting, and vanishing gradient problems, are also discussed. Finally, alternative solutions for these limitations are obtained
Standardized Handoffs For Anesthesia Students
Communication between healthcare providers is an essential aspect of caring for patients. Effective communication is vital during the patient handoff process. The patient handoff process involves exchanging patient’s medical information between a provider currently caring for the patient and the provider assuming care of the patient. If the information exchanged during the handoff process is inaccurate or essential information is omitted, that could potentially lead to harmful consequences for the patient. Currently, no standardized handoff tool exists for student registered nurse anesthesia students (SRNAs) in clinical practicum at the local level one trauma center. The lack of a standardized handoff tool at this facility suggests an increased likelihood of communication errors during the handoff process. The purpose of this quality improvement project is to implement a standardized handoff tool called the AneSBAR tool that SRNA students can utilize in their practice to ensure proper and effective handoffs in the post-anesthesia care unit (PACU) and the intensive care unit (ICU). The inclusion criteria for the project are 2nd or 3rd-year SRNA students currently enrolled full-time in the local Certified Registered Nurse Anesthetist (CRNA) program. The quality improvement project will follow a Plan-Do-Study-Act (PDSA) model. Both qualitative and quantitative data will be collected to determine the impact of the standardized handoff tool. Data collected from surveys and simulations will determine if the PDSA cycle needs repeated or if the QI measure is ready for implementation
Assimilating sense into disaster recovery databases and judgement framing proceedings for the fastest recovery
The replication between the primary and secondary (standby) databases can be configured in either synchronous or asynchronous mode. It is referred to as out-of-sync in either mode if there is any lag between the primary and standby databases. In the previous research, the advantages of the asynchronous method were demonstrated over the synchronous method on highly transactional databases. The asynchronous method requires human intervention and a great deal of manual effort to configure disaster recovery database setups. Moreover, in existing setups there was no accurate calculation process for estimating the lag between the primary and standby databases in terms of sequences and time factors with intelligence. To address these research gaps, the current work has implemented a self-image looping database link process and provided decision-making capabilities at standby databases. Those decisions from standby are always in favor of selecting the most efficient data retrieval method and being in sync with the primary database. The purpose of this paper is to add intelligence and automation to the standby database to begin taking decisions based on the rate of concurrency in transactions at primary and out-of-sync status at standby
Improvement of construction process by adopting lean construction principles: a construction model development
Lessons learned from the construction industry have shown that adopting lean principles within construction processes can significantly enhance the overall success of a construction project. However, currently the potential benefits of such an approach are still not being fully realised in a uniform way. The application of lean principles in construction projects has an underlying aim to increase the value of projects and to eliminate construction waste, in order to achieve project targets of time, cost, and quality while reducing damage to the environment consistent with the underlying principles of sustainable development. This research project presents a newly developed framework that contains a set of lean methods and techniques to support the application of lean principles to construction project practice. In so doing the method helps those within the construction industry to more consistently achieve the full benefits that lean construction approaches can offer.
The aim of this research project is to investigate the lean construction techniques currently used in the industry and the principles of lean construction applications, particularly, the problems and challenges, and develop a new construction process model in which lean methods/tools can be integrated. This will provide an effective and efficient way for managing construction projects in the construction industry. A parallel aim is to improve the construction process to better manage construction waste, time and cost and to improve the levels of quality and sustainability achieved. The adaptation of lean principles with identified enablers has been assessed where a combination of different lean principles and techniques were considered as the main enablers to develop a framework for the construction process. The RIBA Plan of Work was used to integrate and incorporate several lean construction principles and techniques to develop a standardised model where both the construction stages and the associated activities of the construction process in projects can be described.
The underlying philosophy of the developed framework is to increase the efficiency of transformation activities (known as value-adding activities – processing). The innovative construction process models presented in this research are developed based on the core enablers that can be used to identify and eliminate waste in the construction process. These include set-based concurrent engineering (SBCE) integrated with the Last Planner® System (LPS) and lean thinking (LT) within traditional construction process activities. A number of measurement and control methods and guidelines for implementation of the framework are presented. In addition, case study materials have been collected from the industry in order to test and validate the framework. The results provide useful information and guidance to the construction industry as a whole.
The novelty and contribution to knowledge of the research includes: improvement of construction process and performance through the development and implementation of an integrated lean-enabled pull flow construction process framework (i.e. pull flow control embedded within lean construction management) integrated with measurement and control methods within the RIBA Plan of Works. The research concludes by suggesting that the most effective way to implement lean methods and techniques in construction activities is to use the framework proposed and developed in this research which is integrated with the RIBA Plan of Work
A Bigraphical Vending Machine as a Webservice: From Specification and Analysis to Implementation using the Bigraph Toolkit Suite
A bigraph-driven vending machine is implemented. The application is realized as a Spring-based webservice. Actions can be initiated by REST endpoints.
The system follows a rule-based architecture, where possible operations are grounded on a rule set. Bigraphical Reactive Systems are used for the specification and execution. The actual state of the application is a bigraph stored in a database, which can be viewed and altered directly in the database. A history of states is kept - the application can be transferred to any prior state. The application can be updated or extended by merely changing the bigraphical database model.:First Part:
A system of a vending machine is specified and analyzed using BDSL.
This concerns the static and dynamic aspects of the system.
Second Part:
The analysis results are re-used for the implementation using Bigraph Framework.
The application is realized as a webservice that is built using the Spring framework.Ein bigraph-gesteuerter Verkaufsautomat wird implementiert. Die Anwendung ist als Spring-basierter Webservice realisiert. Aktionen können über REST-Endpunkte initiiert werden.
Das System folgt einer regelbasierten Architektur, bei der die möglichen Operationen auf einem Regelsatz beruhen. Für die Spezifikation und Ausführung werden Bigraphical Reactive Systems verwendet. Der aktuelle Zustand der Anwendung ist ein in einer Datenbank gespeicherter Bigraph, der direkt in der Datenbank eingesehen und verändert werden kann. Es wird eine Historie der Zustände geführt - die Anwendung kann in einen beliebigen früheren Zustand überführt werden. Die Anwendung kann aktualisiert oder erweitert werden, indem lediglich das bigraphische Datenbankmodell geändert wird.:First Part:
A system of a vending machine is specified and analyzed using BDSL.
This concerns the static and dynamic aspects of the system.
Second Part:
The analysis results are re-used for the implementation using Bigraph Framework.
The application is realized as a webservice that is built using the Spring framework
Building performance simulation in the brave new world of Artificial Intelligence and Digital Twins : a systematic review
In an increasingly digital world, there are fast-paced developments in fields such as Artificial Intelligence, Machine Learning, Data Mining, Digital Twins, Cyber-Physical Systems and the Internet of Things. This paper reviews and discusses how these new emerging areas relate to the traditional domain of building performance simulation. It explores the boundaries between building simulation and these other fields in order to identify conceptual differences and similarities, strengths and limitations of each of these areas. The paper critiques common notions about these new domains and how they relate to building simulation, reviewing how the field of building performance may evolve and benefit from the new developments
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