Mission-critical Processes Research Articles

Uncertainty Detection in Supervisor–Operator Audio Records of Real Electrical Network Operations

The quality of verbal communication, understood as the absence of uncertainty in the message transmitted, is a key factor in mission-critical processes. Several processes are handled by direct voice communication between these endpoints and any miscommunication could have an impact in success of the task. For that reason, the quality control of verbal communication is required to ensure that the instructions issued are effectively understood and adequately executed. In this context, it is expected that instructions from the command center are issued once, and that the acknowledgment from the field are minimal. In the present work, the communication between an electrical company control center and factory workers in the field was chosen for analysis. We developed two complementary approaches by using machine learning and deep learning algorithms to assess, in an automatic way, the quality of information transmission in the voice communications. Preliminary results demonstrate that the automatic uncertainty detection is feasible, despite the small number of samples available at the present time. To support further studies, a repository was created in GitHub with the spectrogram and the tokenized words of all audios.

Earliest Deadline First Scheduling for Real-Time Computing in Sustainable Sensors

Energy harvesting is a green technology that authorizes small electronic devices to be supplied for perpetual operation. It enables wireless sensors to be integrated in applications that previously were not feasible with conventional battery-powered designs. Intermittent computing and scheduling are the two central aspects of designing a Real-Time Energy Harvesting (RTEH) sensor, generally used to monitor a mission critical process. Traditional scheduling algorithms fail to timely execute the hard deadline tasks because they accommodate no fluctuations in power supply and therefore no intermittent computing. A suitable energy-harvesting-aware scheduling algorithm has been proposed so as to achieve a higher schedulability rate. Unlike the classical EDF (Earliest Deadline First) scheduler, the ED-H algorithm is idling and clairvoyant, with an improved performance in terms of the deadline missing ratio. This paper reviews the main advances in dynamic priority scheduling based on EDF for energy-neutral systems.

Applications of information channels to physics-informed neural networks for WiFi signal propagation simulation at the edge of the industrial internet of things

The ubiquitous presence of data driven technologies that move information from the edge of the Industrial Internet of Things (IIoT) to the cloud for advanced computation and back to the edge for action are pushing wireless connections to the limit. Under these conditions optimizing WIFI Received Signal Strength Intensity (RSSI) can improve data management, computational workflows, and geolocation accuracy while reducing energy consumption in order to minimize charging and computational resource requirements at the edge. Ensuring connectivity for these mission critical processes will require detailed knowledge (either measured or simulated) of the state of the electromagnetic fields in advanced manufacturing scenarios. Simulation has the advantage of developing more scalable solutions to this characterization problem but comes at a very high computational cost that may not be possible on edge devices with limited computational resources. In order to reduce the time and resource cost of achieving real time simulations with low computing specification edge devices, we propose creating a novel method that exploits the notion of information channels to create efficient Convolutional Neural Networks (CNNs) capable of determining the RSSI given a completely new geometry (never used in training) where objects or obstacles (walls, machines, tables, etc.) and their respective location, size and reflectivity indices, along with the antenna location are completely random.

A mindfulness toolkit to optimise incident management and business continuity exercises

Mindfulness is the daily practice of noticing our present moment experiences (thoughts, emotions and physical sensations) with curiosity, non-judgment and equanimity (accepting what is). Scientific research shows that the regular practice of mindfulness can help lower stress, boost the immune system and increase productivity. Recognising these benefits, companies such as Google, Nike and Goldman Sachs have incorporated mindfulness programmes into the workplace. Among the positive results reported, these companies have observed a reduction in sick leave, improved collaboration between employees, and projects being completed more effectively. But these are only some of the benefits that mindfulness can offer. Other advantages include improved emotional regulation and better decision-making during a crisis. This suggests that those C-level executives and recovery teams who play key roles in restoring mission-critical processes following business-disruptive events would benefit from mindfulness training. This paper will explore how and why mindfulness can help optimise incident management, the training tools required, and how to build mindfulness into a business continuity management training and exercise programme.

Modeling, analyzing and predicting security cascading attacks in smart buildings systems-of-systems

Software systems intelligence and complexity have been continuously increasing to deliver more and more features to support business critical and mission critical processes in numerous domains such as defense, health-care, and smart cities. Contemporary software-based solutions are composed of several software systems, that form System-of-Systems (SoS). SoS differentiating characteristics, such as emergent behavior, introduce specific issues that render their security modeling, simulation and analysis a critical challenge. The aim of this work is to investigate how Software Engineering (SE) approaches can be leveraged to model and analyze secure SoS solutions for predicting high impact (cascading) attacks at the architecture stage. In order to achieve this objective, we propose a Model Driven Engineering method, Systems-of-Systems Security (SoSSec), that comprises: (1) a modeling language (SoSSecML) for secure SoS modeling and (2) Multi-Agent Systems (MAS) for security analysis of SoS architectures. To illustrate our proposed approach in terms of modeling, simulating, and discovering attacks, we have conducted a case study on a real-life smart building SoS, the Adelaide University Health and Medical School (AHMS). The results from this case study demonstrate that our proposed method discovers cascading attacks comprising of a number of individual attacks, such as a Denial of Service, that arise from a succession of exploited vulnerabilities through interactions among the constituent systems of SoS. In future work, we intend to extend SoSSec to address diverse unknown emergent behaviors and non-functional properties such as safety and trust.

AMQP Communication Interface on RT Middleware for highly-reliable IoR System Construction

MQTT is a very simple messaging protocol. This causes messaging systems to get high performance and low power consumption, and therefore MQTT protocol is suitable to construct IoT/IoR systems. However, the messaging performance is not only objective for IoT/IoR systems. In some cases, the quality of messaging service is more important than the messaging performance for some systems including mission critical process. On the other hand, AMQP messaging protocol just fits to construct highly-reliable systems. In this study, we focused on the advantage of AMQP and developed a new communication interface using AMQP on data port communication of OpenRTM-aist. The proposed communication interface enables developers to easily construct highly-reliable robot systems on RT middleware.

Perioperative Medication Management: Reconciling Differences across Clinical Sites

Medication reconciliation (MedRec) is a mission-critical process which can serve to reduce adverse drug events (ADEs) in surgical settings. However, providing quality care is limited by current health information technology (IT), which is often inefficient and unintuitive due to poor usability, resulting in high cognitive burden. We have been characterizing EHR mediated workflow in the Mayo Clinic enterprise prior to a system-wide electronic health records (EHR) conversion in order to harmonize workflows. We compared and evaluated MedRec processes in pre-operative nursing assessments across two different EHRs in place in different locales at baseline. The interfaces differed both in their modes of interaction and cognitive support. Analyses surfaced interface elements that were unintuitive and inefficient, creating unnecessary complexities in clinicians’ interactive behavior. Keystroke level models (KLM), a modeling tool for predicting task completion time, showed that to access medication lists required a different series of operations across the two systems. Different designs can differentially mediate task performance, which can aid in the mitigation of errors for complex cognitive tasks. Identification of barriers in EHR-mediated workflow and barriers to interface usability could lead to system redesigns that minimize cognitive load while improving patient safety and efficiency.

Supplier Evaluation Model on SAP ERP Application using Machine Learning Algorithms

For business enterprises, supplier evaluation is a mission critical process. On ERP (Enterprise Resource Planning) applications such as SAP, the supplier evaluation process is performed by configuring a linear score model, however this approach has a limited success. Therefore, author in this paper has proposed a two-stage supplier evaluation model by integrating data from SAP application and ML algorithms. In the first stage, author has applied data extraction algorithm on SAP application to build a data model comprising of relevant features. In the second stage, each instance in the data model is classified, on a rank of 1 to 6, based on the supplier performance measurements such as on-time, on quality and as promised quantity features. Thereafter, author has applied various machine learning algorithms on training sample with multi-classification objective to allow algorithm to learn supplier ranking classification. Encouraging test results were observed when learning algorithms,(DT) and Support Vector Machine (SVM), were tested with more than 98 percent accuracy on test data sets. The application of supplier evaluation model proposed in the paper can therefore be generalised to any other other information management system, not only limited to SAP, that manages Procure to Pay process.

Computer and Information Security Handbook

This book presents information on how to analyze risks to your networks and the steps needed to select and deploy the appropriate countermeasures to reduce your exposure to physical and network threats. It also imparts the skills and knowledge needed to identify and counter some fundamental security risks and requirements, inlcuding Internet security threats and measures (audit trails IP sniffing/spoofing etc.) and how to implement security policies and procedures.In addition, this book also covers security and network design with respect to particular vulnerabilities and threats. It also covers risk assessment and mitigation and auditing and testing of security systems.From this book, the reader will also learn about applying the standards and technologies required to build secure VPNs, configure client software and server operating systems, IPsec-enabled routers, firewalls and SSL clients.Chapter coverage includes identifying vulnerabilities and implementing appropriate countermeasures to prevent and mitigate threats to mission-critical processes. Techniques are explored for creating a business continuity plan (BCP) and the methodology for building an infrastructure that supports its effective implementation.A public key infrastructure (PKI) is an increasingly critical component for ensuring confidentiality, integrity and authentication in an enterprise. This comprehensive book will provide essential knowledge and skills needed to select, design and deploy a PKI to secure existing and future applications. This book will include discussion of vulnerability scanners to detect security weaknesses and prevention techniques, as well as allowing access to key services while maintaining systems security. Chapters contributed by leaders in the field cover theory and practice of computer security technology, allowing the reader to develop a new level of technical expertise. This book's comprehensive and up-to-date coverage of security issues facilitates learning and allows the reader to remain current and fully informed from multiple viewpoints.Presents methods of analysis and problem-solving techniques, enhancing the readers grasp of the material and ability to implement practical solutions.

Introducing a Taxonomy for Classifying Qualitative Spreadsheet Errors

Most organizations use large and complex spreadsheets that are embedded in their mission-critical processes and are used for decision-making. Identification of the various types of errors that can be present in these spreadsheets is, therefore, an important first step to creating controls that organizations can use to govern their spreadsheets. While a considerable amount of research on quantitative error taxonomies exists, there is comparatively little research concerning qualitative error taxonomies. In this paper, we propose a taxonomy for categorizing qualitative errors in spreadsheet models that offers an exploratory framework for evaluating the quality of a spreadsheet model before it is released for use by others in the organization. The classification was developed based on types of qualitative errors identified in the literature and errors committed by end-users in developing a spreadsheet model for Panko's (1996) “Wall Problem.” A principal component analysis of the errors reveals four logical groupings thereby creating four categories of qualitative errors. The usability and limitations of the proposed taxonomy and areas for future research are discussed.

Effective Talent Management in R&D Organisation a Case Study

Talent is one of the most important resource of the research organisation which enables the organisation to achieve the best results and success. Talent management is a mission critical process which ensures organizations have the highly skilled man power in place to meet the organisation's current and future research goals. One of the key factor of talent management is identification of the key gaps between the talent in place and the talent required to drive research success. Organisations are made up of people. As an organisation strives to meet its organisational goals, it must make sure that it has a continuous and integrated process for recruiting, training, managing, supporting and compensating these people. Succession planning, a very important function, enables managers and individuals to identify the right candidates for a position. Talent identification, skills acquisition and development plan improves the research works. In this paper the concept of TM and its application in R&D is explored. Innovation continues to be the domain of R&D division. R&D typically refers to the Creative work undertaken on a systematic basis in order to increase the stock of knowledge and the use of this knowledge to devise new applications. In this research we scrutinize the way the notions of talent management relate in R&D settings and its correlation with process and design innovation that contributes to the competitive advantage of the organization. The outcome of the paper is to examine how to understand the concept of talent management applied in research and development and its effectiveness using the single case study design.

Guardians of the matrix

Guardians of the matrix

How technology will make or break banks integrating mission-critical processes as a result of a merger

This paper provides an in-depth look at the road ahead for the financial services technology challenges that are the result of both mergers and cross-business-line efficiency initiatives. It will look back at the information technology (IT) trends in banking over the past two years in order to build the context required to understand how reduced IT budgets will be spent in 2009. While the paper is primarily focused on the consolidation and optimisation of IT resources to integrate and transform business processes, these initiatives are also applicable to enterprises that are not merging with another bank, but instead are building tighter integration across their own internal business lines and/or with their partners and clients.

Quality of service management framework for dynamic chaining of geographic information services

Dynamic chaining of geographic information services (geo-services) is gaining popularity as a new paradigm for evolving flexible geo-information systems and for providing on-demand access to geo-information. In dynamic chaining, disparate geo-services are discovered and composed at run time to yield more elaborate functionality and create value-added geo-information. Common approaches to service chaining discover and compose disparate geo-services based on the functional capability of individual geo-services. The primary concern of common approaches is thus the emergent behavior of the resulting composite geo-service. However, as geo-services become mundane and take on a greater and more strategic role in mission critical processes, deliverable quality of service (QoS) becomes an important concern. QoS concerns operational characteristics of a service that determine its utility in an application context. To address pertinent QoS requirements, a new approach to service chaining becomes necessary. In this paper we propose a QoS-aware chaining approach in which geo-services are discovered, composed and executed considering both functional and QoS requirements. We prescribe a QoS management framework that defines fundamental principles, concepts and mechanisms which can be applied to evolve an effective distributed computing platform for QoS-aware chaining of geo-services – the so-called geo-service infrastructure. The paper also defines an extensible QoS model for services delivered by dynamic compositions of geo-services. The process of orthophoto generation is used to demonstrate the applicability of the prescribed framework to service-oriented geographic information processing.

Reliability Against the Odds: The Lessons of Open Source Communities for Developing Reliable Software

Open source software is increasingly used in mission-critical processes of organizations, signaling its acceptance as highly reliable software. That said, the development process in open source communities differs radically from conventional approaches to reliable software development. Stronger still, open source software seems to thrive under conditions of that are orthogonal to the conventional approach: extreme fragmentation, weak planning and coordination structures and lack of control over objectives, priorities and resource allocation. Therefore, we argue that open source communities provide us with valuable and innovative lessons for managing the production of reliable software - especially since the conditions for contemporary software development increasingly resemble those of open source communities rather than those of tightly controlled corporate environments. To draw out these lessons, this paper applies concepts from High Reliability Theory (HRT) on two recent case studies of open source communities, Linux and Apache. We identify a number of important reliability-enhancing mechanisms. Understanding these mechanisms is important to a) managers of corporate software developers participating in open source communities and b) managers who want to transfer mechanisms and lessons from open source communities to their organization.

CE2IT: continuous ethics enhancement for IT professionals

As IT moves into more mission-critical processes, the possibility for ethical dilemmas with far-reaching consequences increases. This article presents "Continuous Ethics Enhancement for IT Professionals" (CE2IT), a personal framework that responds to an IT professional's need for guidance in ethical decision-making. It is designed to "see to it" that IT professionals integrate ethics into their personal and professional lives.

Decentralized fault-tolerant control system design for unstable processes

Fault-tolerant control is an important issue in control of mission critical processes. In this paper, a new approach to fault-tolerant control of unstable processes is proposed based on the Passivity Theorem. The control system is designed in two sequential steps: A multi-loop proportional controller is used to stabilize the unstable process; a passivity-based decentralized unconditionally stabilizing (DUS) controller is then applied to the stabilized process. While the multi-loop stabilizing controllers need to be built with redundancy, the DUS controller is inherently fault tolerant and can maintain closed-loop stability when any of its loops fail. By using a stabilizing proportional controller with the fewest loops, control redundancy can be reduced to the minimum level.

Management control of complex, mission-critical processes

Because the failure of complex, mission-critical systems—such as certain process control and manufacturing operations—can be exceptionally costly to an organization, appropriate management control of these systems is imperative. This paper presents a theory of management control of complex systems that is the potential basis for an intelligent DSS, which would be capable of supporting human agents monitoring complex systems. The theory is derived from field studies of agent decision making under procedural guidance, and it focuses on the most crucial—and interesting—aspect of agent behavior, i.e. the decision to deviate from a procedure when the procedure is considered detrimental to the achievement of organizational goals. The theory is instantiated in a computer model of the agents' decision processes. The computer model in turn embeds a simulation of the agents' situation and goal assessment processes that produce procedural non-compliance. © 2000 John Wiley & Sons, Ltd.

From contemporary workflow process automation to adaptive and dynamic work activity coordination and collaboration

This position paper outlines a research agenda for researchers in the area of workflow. We believe that today’s workflow systems should evolve to what is termed as work coordination and collaboration systems (WCCSs). A WCCS will (a) adapt to various changes in the organization (including its interactions with external organizations) and the organizational processes by being able to change the processes definitions as well as change the processes and component activities while they are being enacted or executed, and (b) support a unified framework for managing coordination, collaboration, and information- based decision making activities that naturally occur as part of organizational processes. A WCCS can then not only support automation of the routine and well defined processes, but also support better human involvement and manage more complex, dynamic, and higher value mission critical processes. This can lead to significantly improved productivity and quality of results . It is further suggested that a multidisciplinary approach is an essential element of the part toward developing WCCSs.