Embedded System Verification Using Formal Model an Approach Based on the Combined Use of UML and Maude Language

The approach proposed in this article presents a formal verification of embedded systems. The method relies on an automated modeling and code generation based on the systems' behavior. The key concept is the combined use of a subset of UML behavior diagrams extended with timing annotations (Real-Time Statechart and Real-Time Collaboration diagrams) for system modeling and the Maude language for verification. First, UML modeling tools are developed. Then, an automatic generation of equivalent Maude specification is performed. The approach is based on code generation. This is why it is possible to use an available model checking tool to verify certain timed properties represented in Linear Temporal Logic (LTL). The meta-modeling tool ATOM3 is used. A case study is presented to illustrate the feasibility of the approach.

Using Business Ontology to Integrate Business Architecture and Business Process Management for Healthcare Modeling

Patient safety and quality of health care services continue to be an issue within healthcare organizations. Quality improvement of healthcare processes at a systems level requires a shared language so the system is well understood across and between business areas. Business ontology provides the ability to create a shared language which can be used to integrate business process management (BPM) and business architecture (BA) concepts to identify, prioritize, and plan system wide improvement. The effective application of this comprehensive management approach has been demonstrated using medication management services within a publicly funded Canadian healthcare organization. This article illustrates how the foundational ontology developed by the Global University Alliance and the related Business Process Management Ontology (BPMO) can be used to facilitate the integration of BA and BPM concepts to improve quality of medication management. The development of business artefacts resulted in a prioritized list of improvement initiatives and an action plan to implement and monitor the initiatives. The integration of BPM and BA using an ontology in a healthcare setting yields improved services at the systems level.

On Because and Why

Because, as an act of verbal reasoning, is described in terms of its transitivity, composite assertions and reasoning. The latter includes induction through X because Y and the deduction subsequently afforded by why X. Once the component assertions X and Y are disavowed, it illustrates the third level of Peircean reasoning, abduction. The language engine, Enguage, is introduced and positioned as a novel approach to language processing. Three utterance repertoires of the Enguage test suite, which support because and why, are described. These are then applied using Enguage, and the resultant output is presented. A user can thus demonstrate reasoning interactively, via text-to-speech software, with a machine that can be said to understand why.

Virtual/Mixed Reality

Use of classroom and online learning and administrative technologies in schools and higher education institutions has grown at an exponential pace. With growth comes expectations by students of using new and emerging technologies to support their learning. Such expectations are due in part to the generational shift from digital immigrant to more students being digital natives, and is particularly true for Gen z/iGen/Centennials (born in 1996 or later). The purpose of the critical review and exploratory case study was to gain insights from 18 instructional designers, information systems professionals, and content/subject matter experts pertaining to the current and future use of virtual/mixed reality technologies for both public and higher education.

Improving Learning Outcomes for Higher Education Through Smart Technology

The ever-decreasing time between the doubling of knowledge creates a problem for education concerning how to handle information overload. To address this issue, educators must learn to make learning more effective and more efficient. Currently, there is more to learn and less time in which to learn. Therefore, Smart technology offers a solution: It helps manage cognitive load through the formation of a schema, which helps humans learn more with greater efficiency and greater effectiveness. This can be accomplished by instructional design that makes use of Gagné's conditions of learning and the nine instructional events based on them. These can be brought together through the ADDIE instructional design model. This process is amplified by using Smart instructional technology to create the learning material and to deliver it to the learner. The educational venues for learning include face to face, online, or mobile communication devices. Examples are provided about the conditions of learning, nine instructional events, and the ADDIE Model, which are applied to classical guitar instruction. Further, the elements of Smart technology are presented as a resource for teaching and learning.

Using Facebook's Open Source Capture the Flag Platform as a Hands-on Learning and Assessment Tool for Cybersecurity Education

There is a high demand for skilled cybersecurity professionals, however, entry-level employees and college graduates often lack the hands-on and real-world experience they need to be successful in the cybersecurity industry. This high demand has led educators to pursue innovative and smart application technologies as a way for students to gain hands-on skills and to practice those skills in a safe and fun environment. Cybergames are now being used by educational institutions and in private and public industry sectors. One popular game in the cybersecurity space is called Capture the Flag (CTF). This study investigates Facebook's CTF platform as a cost-effective learning and assessment tool for undergraduate and graduate cybersecurity adult students for an online university.

The Educational Contribution of Interactive Whiteboards

Interactive whiteboards (IWBs) are a key element of smart technology being used in classrooms. The principal concern when using interactive whiteboards in an educational setting is how effectively IWB's serve the student and the instructor. A key question is whether the high cost of interactive whiteboards is providing enough value to justify the cost. The purpose of this article is to provide a preliminary exploration of the perceptions of students and teachers regarding their use of IWBs. The study also discusses the factor of bias that might influence these perceptions. This study reported preliminary results of what will be a larger report on the full content analysis. However, preliminary results showed wide variance between teacher and student perceptions of interactive whiteboard use that suggests a need for further research.

Effectiveness of a Student Response System Supported Curriculum and a Middle School Leadership Program

A student response system (SRS) with an engaging and interactive curriculum to support 21st -century skills could increase student performance in U.S. schools. This article will include student and teacher feedback to provide educators with possible solutions to poor student performance. Students respond positively to engagement opportunities related to their peers and classroom content. Through data collection and analysis, students learn, become involved, construct individual understanding, and experience real-time digital feedback. Why do many classrooms exclude technology and active learning strategies (ALS) although usage has resulted in great enthusiasm and consistent results? Could student success be facilitated by embedding an SRS and ALS in a standardized curriculum in a Title I middle school leadership classroom? To explore these questions, it is necessary to understand SRS technology and its capabilities, as well as its use in conjunction with an ALS embedded curriculum used in leadership programs.

Case Studies in Applying Data Mining for Churn Analysis

The advent of price and product comparison sites now makes it even more important to retain customers and identify those that might be at risk of leaving. The use of data mining methods has been widely advocated for predicting customer churn. This paper presents two case studies that utilize decision tree learning methods to develop models for predicting churn for a software company. The first case study aims to predict churn for organizations which currently have an ongoing project, to determine if organizations are likely to continue with other projects. While the second case study presents a more traditional example, where the aim is to predict organizations likely to cease being a subscriber to a service. The case studies include presentation of the accuracy of the models using a standard methodology as well as comparing the results with what happened in practice. Both case studies show the significant savings that can be made, plus potential increase in revenue by using decision tree learning for churn analysis.

Specifying Constraints for Detecting Inconsistencies in A Conceptual Graph Knowledge Base

This paper proposes a strategy for representing constraints in a conceptual graph knowledge base. We describe a set of techniques for using these constraints to detect inconsistencies in a knowledge base by finding sets of nodes that are inconsistent with these constraints. The detection method is designed to be efficient. An algorithm was developed and analyzed and its computational complexity was found to be polynomial with respect to knowledge base size and number of child nodes for each constraint node.