In this workshop National Science Foundation (NSF) program directors from two different directorates will share information about programs and funding opportunities focused on institutional and PI research capacity building. As is well known, NSF offers a wide variety of funding opportunities to promote discovery in science and engineering, accelerate technology and innovation, and advance diversity in science and engineering. This workshop aims to improve participants' knowledge about 1) capacity building programs in NSF, specifically in Computer and Information Science and Engineering (CISE) and Directorate for STEM Education (EDU) directorates, 2) writing competitive NSF proposals, and 3) designing effective project evaluation plans and budgets. The workshop will include a panel of successful principal investigators (PIs) who will share their insights on successful grant-writing and implementation. This workshop will provide an opportunity for the participants to engage with NSF program directors, an NSF evaluator, and successful PIs that could potentially help them identify appropriate funding opportunities and develop a strong NSF proposal. The workshop will include a mix of presentations, panel discussion, hands-on activities, and question and answer session.

The National Science Foundation (NSF) supports engineering and computing education research that generates new knowledge about evidence-based practices and broadens participation in the engineering and computing workforce. Multiple NSF programs provide funding for projects that address current challenges in engineering and computing education at all levels of education including K-12, technical, undergraduate, and graduate education at different institutions (including HSIs). The goal of this workshop is for Program Director to provide prospective Principal Investigators with guidance on engineering and computing education funding opportunities at NSF and provide insights on preparing competitive proposals.

Software for electronic prescriptions offers healthcare providers numerous benefits including increased patient safety, prescribing effectiveness, workflow efficiencies, and financial savings. Particularly due to recent legislation, an increasing number of organizations are adopting this software. Yet, there are many concerns and risks associated with e-prescription technologies. Despite increased prescribing effectiveness, there is still the potential for human error. Many software concerns including integration and the implementation of specific transactions like CancelRx still need to be addressed. Additionally, some patients have negative perceptions of e-Rx that must be overcome. To this effect, this research conducts risk assessment of two real world cases (the CVS Pharmacy (retail setting) and the Ascension Seton (inpatient setting)) using the NIST risk model. The study concludes that the top three challenges in the pharmacy domain are comprised of a lack in the implementation of essential software functionalities, the loss and theft of portable devices, and errors due to email phishing attacks.

The purpose of this project was the development of a web application, that allow users to find the Emergency Department that provides the best timely and effective care in a defined area. The inputs that the user must provide are a location ZIP code and a maximum radius in miles. The output is a list of ED in the defined area and each one is associated to a "timely and effective care index" that can be used as an indicator of quality care and estimate travel time to the corresponding ED.

Studies have shown that triage nurses often have difficulty correctly predicting triage level when using the Emergency Severity Index (ESI), even after having been previously trained on the algorithm. This paper examines nurses' difficulties with applying the ESI and previous attempts at electronic triage support systems. United States emergency department data obtained from the National Center for Health Statistics website is analyzed using the random forest algorithm and C5.0 decision tree algorithm to determine if refinements can be made to the current ESI algorithm so that it can be more easily implemented by nurses. A model electronic triage application is produced based on the current ESI algorithm and the results of the decision tree analysis.

OpenEMR is a free medical practice management, electronic medical records, prescription writing, and medical billing application used by Healthcare Professionals. This project focuses on research and analysis surrounding security vulnerabilities within the OpenEMR application. OpenEMR offers a wide range of features and can run on various operating systems, including Windows, Linux and MacOS [3]. It is the most widely used medical record application on the internet. Recent analysis has identified several vulnerabilities within OpenEMR's source code that could potentially expose medical records and other PHI information.

Information technology is increasingly being used in healthcare paramedic sector with the goal to improve management of resources and enhance medical services to save lives. In this paper, we introduce EMTriage, a distributed Android application with the ability to access patients EHR's, and depending on the data and inputs, assess and distribute an acuity level to patients in need of resources. We use the Emergency Severe Index, a proven triage tool to set acuity level so paramedics know who to attend to first. We also introduce functionality such as, patients emailing their primary care doctors, directions to their closet hospital, access to information about diagnosing yourself, and an emergency warning system to inform people that you need help. Our solution provides client platform security and appropriately combines this with network security concepts. Moreover, we discuss further open problems and research challenges on security, privacy and usability of e-health cloud systems.

The increasing adoption of health information technologies in the United States accelerates their potential to facilitate beneficial studies that combine large, complex data sets from multiple sources. The process of de-identification, by which identifiers are removed from the health information, mitigates privacy risks to individuals and thereby supports the secondary use of data for comparative effectiveness studies, policy assessment, life sciences research, and other endeavors. The de-identification process also comes with the limitation that all the data cannot be de-identified for an object as it might affect future research. Also, if the exact data which is needed for the research are kept original then it may re-identify the person. To this effect, this research presents the design of a comprehensive data de-identification solution and evaluates the strengths of the application.

The purpose of this research is to explore and identify the vulnerabilities in OpenEMR 5.0.0, which is a free and open source medical practice management application. We are to provide recommendations/suggestions to OpenEMR developers on identifying the vulnerabilities. We chose to use vulnerabilities scanning tools to manually explore the demo site of OpenEMR 5.0.0. The targeted vulnerabilities belong to the following three types, namely, SQL Injection, Cross-Site Scripting (XSS) including persistent XSS and reflected XSS and Arbitrary File Upload. We have inducted a qualitative based risk assessment to determine the risk levels for the vulnerabilities identified. The results of risk assessment include two kinds of risk levels, which are high risk and medium risk, and two kinds of priorities, which are priority 1 (high) and priority 2 (medium). In addition, we provided recommendations and best practices about how to prevent the identified vulnerabilities. Furthermore, the research also presents an exploit automation program written in Python to test and exploit the vulnerabilities including SQL Injection and reflected XSS on the demo server of OpenEMR.

Drug traffickers are active and always looking for new ways to mix drugs to avoid their detection and identification. One example is black cocaine, which is a mixture of cocaine base and cocaine hydrochloride and other additional substances. It is challenging for investigators to accurately identify the test for investigative purposes without conducting an on-site evaluation. Presumptive drug test is the preliminary on-site test, conducted by a crime scene investigative officer to detect the presence of a substance by changing color with a chemical reagent. The current approach is manual and relies heavily on the expertise of the officer conducting the test and is limited by their physical ability and other environmental factors. This research aims at developing a novel web-based solution to perform automated presumptive drug tests. The reporting and attestation and reporting are also fully automated. The solution includes real-time interactions between the on-site and the off-site investigative teams. The practical application of this approach is in the field of crime scene investigation both on-site and in the off-site laboratories. The application has been evaluated successfully with two nationally recognized forensic laboratories. Furthermore, a stand-alone hardware/software co-design approach (for security and privacy reasons) is being incorporated as am automated tool in the mobile vehicles of the investigative team.

As mobile users continue to trust their devices with sensitive data, it is important to assess the applications that are responsible for securing it. Healthcare related applications are particularly unique because of their involvement with the storage of healthcare information. The healthcare data within an application is used for treatment, payment, operations (TPO). Securing mobile healthcare applications is important because in some cases if a critical application is compromised then it could cause loss of life. This kind of worst case scenario can happen because of incorrect treatment to a patient. With the Open Web Application Security Project (OWASP) as a reference, we will present a methodology based on a checklist implementation and test it against applications that store healthcare data. This methodology is meant for developers to follow when attempting to secure their mobile applications.

This research seeks to examine the use of Google Rapid Response (GRR) in the healthcare setting and the general necessity for a more in-depth approach to malware incident response in healthcare organizations in general. GRR is a scalable framework that allows for data to be gathered from many machines at once, through multiple clients, single server architecture, in order to detect incidents of malware or malicious activity. With the increase in malware incidents and the sensitivity of healthcare data, it is important to make sure this information is secure. GRR is examined for its uses in the detection of malware, along with its meeting of HIPAA requirements such as privacy and the detection and notification of breaches (security being handled through the detection of this malware). It was determined that GRR has some great potential within this field, albeit it has some flaws and limitations that should be accounted for before implementing it within a healthcare organization. The biggest issue is making sure that the access control and privacy settings are correctly implemented to prevent a breach of information from GRR itself, due to the power of this tool to allow great access to any of the client computers connected to it.

Patient portal is a secure online application which allows patients to have access to their personal health information via Internet around the clock. Patients can view their recent visit information, medications, labs and exams, doctor appointments and communicate with their healthcare providers securely. There have been numerous efforts to build effective patient portals but have not been able to address the cost, security and compliance issues to the fullest. To this effect, the goal of this research is to create a secure patient portal which provides access to patient data, implement all security measures ideal for a healthcare system and to implement OWASP top 10 security measures and industry standard encryption techniques to secure patient data.

In recent years there has been an increased growth in the use of smart applications to better care and manage various medical conditions. Recent studies have concluded that the daily management via an application improves Asthma control compared to manual or paper based monitoring [1]. To this effect, this research aims to study existing Asthma applications and propose a holistic approach to Asthma care and management by developing a novel Android application that provides a real-time, multi-way communication between patients and providers (healthcare, insurance, food, drug, etc.) The current state-of-art smart applications are able to aid users send information to their physicians typically via email, but, healthcare providers still need to contact patients through traditional methods (phone, email or face-to-face appointments). Our proposed multi-way communication can eliminate phone calls, emails and appointment scheduling to save time and provide real time feedback to the patients. Furthermore, providers can monitor the health status of patients remotely by checking their patient specific journal entry and set new and/or modified action plans and also uploads those to the patient's smart devices. Providers can also send notifications to patients even if the device is in sleep mode. In case of emergency patients are able to call 911 or find the nearest hospital and pharmacy via a pre-programmed one-click method. Our pilot evaluation at a nationally recognized HIMSS Stage 6 regional trauma center (> 500 beds) and its affiliated 20 partner clinical practices has confirmed that the proposed application has the potential to significantly improve the quality of care while reducing the overall cost of care delivery for the target population.

The mounting pressure to enable widespread access to electronic health record systems is being felt by healthcare providers. The federal government's Meaningful Use incentives are reason alone for providers to address this significant usability issue. As the healthcare industry considers solutions, attention should be given to the Cloud and the considerable investment that has been made related to the establishment of digital identities and making them interoperable across heterogeneous systems. This research considered how the Cloud could be leveraged by healthcare providers to not only provide patients with a familiar way of accessing electronic resources but also creating a significant cost savings for providers. An examination was performed of similar work being done in other industries as well as the standards laid out by the federal government for EHRs and digital identities. This research lays out a comprehensive framework for healthcare providers to easily follow to integrate with the Cloud for identity validation, while meeting compliance guidelines for security and privacy. To demonstrate the viability of this research, a number of pilots and proof of concept projects have already been implemented at a large regional hospital and have produced immediate and tangible improvements.

This work presents a novel slack management technique, the Service Rate Proportionate(SRP) Slack Distribution, for real-time distributed embedded systems to reduce energy consumption. The proposed SRP based Slack Distribution Technique has been considered with EDF and Rate Based scheduling schemes that are most commonly used with embedded systems. A fault tolerance mechanism has also been incorporated into the proposed technique inorder to utilize the available dynamic slack to maintain checkpoints and provide for rollbacks on faults. Results show that in comparion to contemporary techniques, the proposed SRP Slack Distribution Technique provides for about 29% more performance/overhead improvement benefits when validated with real world and random benchmarks.

The overall performance of a firewall is crucial in enforcing and administrating security, especially when the network is under attack. The continuous growth of the Internet, coupled with the increasing sophistication of the attacks, is placing stringent demands on firewall performance. In this paper, we describe a traffic-aware optimization framework to improve the operational cost of firewalls. Based on this framework, we design a set of tools that inspect and analyze both multidimensional firewall rules and traffic logs and construct the optimal equivalent firewall rules based on the observed traffic characteristics. To the best of our knowledge, this work is the first to use traffic characteristics in firewall optimization. Furthermore, we develop a novel adaptation mechanism that dynamically detects anomalous traffic behavior and adaptively alters the firewall rules to avoid serious performance degradation due to the traffic anomaly. To evaluate the performance of our approaches, we collected a large set of firewall rules and traffic logs at tens of enterprise networks managed by a Tier-1 service provider. Our evaluation results find these approaches very effective. In particular, we achieve more than 10 fold performance improvement by using the proposed traffic-aware firewall optimization.