Development of a total system simulation modelling approach for management decision support

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Case-based Reasoning Method for Real-time Expert Diagnostics Systems

The method of case-based reasoning for a solution of problems of real-time diagnostics and forecasting in intelligent decision support systems (IDSS) is considered. Special attention is drawn to case library structure for real-time IDSS (RT IDSS) and algorithm of k-nearest neighbors type. This work was supported by RFBR.

All-analogue real-time broadband filter bank multicarrier optical communications system

This paper studies the key aspects of an optical link which transmits a broadband microwave filter bank multicarrier (FBMC) signal. The study is presented in the context of creating an all-analogue real-time multigigabit orthogonal frequency division multiplexing electro-optical transceiver for short range and high-capacity data center networks. Passive microwave filters are used to perform the pulse shaping of the bit streams, allowing an orthogonal transmission without the necessity of digital signal processing (DSP). Accordingly, a cyclic prefix that would cause a reduction in the net data rate is not required. An experiment consisting of three orthogonally spaced 2.7 Gbaud quadrature phase shift keyed subchannels demonstrates that the spectral efficiency of traditional DSP-less subcarrier multiplexed links can be potentially doubled. A sensitivity of -29.5 dBm is achieved in a 1-km link.

Westminster Serious Games Platform (wmin-SGP) a tool for real-time authoring of roleplay simulations for learning

The use of serious games in education and their pedagogical benefit is being widely recognized. However, effective integration of serious games in education depends on addressing two big challenges: the successful incorporation of motivation and engagement that can lead to learning; and the highly specialised skills associated with customised development to meet the required pedagogical objectives. This paper presents the Westminster Serious Games Platform (wmin-SGP) an authoring tool that allows educators/domain experts without games design and development technical skills to create bespoke roleplay simulations in three dimensional scenes featuring fully embodied virtual humans capable of verbal and non-verbal interaction with users fit for specific educational objectives. The paper presents the wmin-SGP system architecture and it evaluates its effectiveness in fulfilling its purpose via the implementation of two roleplay simulations, one for Politics and one for Law. In addition, it presents the results of two types of evaluation that address how successfully the wmin-SGP combines usability principles and game core drives based on the Octalysis gamification framework that lead to motivating games experiences. The evaluation results shows that the wmin-SGP: provides an intuitive environment and tools that support users without advanced technical skills to create in real-time bespoke roleplay simulations in advanced graphical interfaces; satisfies most of the usability principles; and provides balanced simulations based on the Octalysis framework core drives. The paper concludes with a discussion of future extension of this real time authoring tool and directions for further development of the Octalysis framework to address learning.

Video anomaly detection in real-time on a Power-Aware Heterogeneous Platform

FPGAs and GPUs are often used when real-time performance in video processing is required. An accelerated processor is chosen based on task-specific priorities (power consumption, processing time and detection accuracy), and this decision is normally made once at design time. All three characteristics are important, particularly in battery-powered systems. Here we propose a method for moving selection of processing platform from a single design-time choice to a continuous run time one.We implement Histogram of Oriented Gradients (HOG) detectors for cars and people and Mixture of Gaussians (MoG) motion detectors running across FPGA, GPU and CPU in a heterogeneous system. We use this to detect illegally parked vehicles in urban scenes. Power, time and accuracy information for each detector is characterised. An anomaly measure is assigned to each detected object based on its trajectory and location, when compared to learned contextual movement patterns. This drives processor and implementation selection, so that scenes with high behavioural anomalies are processed with faster but more power hungry implementations, but routine or static time periods are processed with power-optimised, less accurate, slower versions. Real-time performance is evaluated on video datasets including i-LIDS. Compared to power-optimised static selection, automatic dynamic implementation mapping is 10% more accurate but draws 12W extra power in our testbed desktop system.

Real-time tracking system using C80 DSPs and a binocular robotic head

[EN]An active vision system to perform tracking of moving objects in real time is described. The main goal is to obtain a system integrating off-the-self components. These components includes a stereoscopic robotic-head, as active perception hardware; a DSP based board SDB C80, as massive data processor and image acquisition board; and finally, a Pentium PC running Windows NT that interconnects and manages the whole system. Real-time is achieved taking advantage of the special architecture of DSP. An evaluation of the performance is included.

A C80 DSP-based active vision system for real-time tracking

[EN]Active Vision Systems can be considered as dynamical systems which close the loop around artificial visual perception, controlling camera parameters, motion and also controlling processing to simplify, accelerate and do more robust visual perception. Research and Development in Active Vision Systems [Aloi87], [Bajc88] is a main area of interest in Computer Vision, mainly by its potential application in different scenarios where real-time performance is needed such as robot navigation, surveillance, visual inspection, among many others. Several systems have been developed during last years using robotic-heads for this purpose...

A Valuation Analysis of the Physical Oceanographic Real Time System (PORTS)

This analysis estimates several economic benefits derived from national implementation of the National Oceanic and Atmospheric Administration’s Physical Oceanographic Real-Time System (PORTS®) at the 175 largest ports in the United States. Significant benefits were observed owing to: (1) lower commercial marine accident rates and resultant reductions in morbidity, mortality and property damage; (2) reduced pollution remediation costs; and, (3) increased productivity associated with operation of more fully loaded commercial vessels. Evidence also suggested additional benefits from heightened commercial and recreational fish catch and diminished recreational boating accidents. Annual gross benefits from 58 current PORTS® locations exceeded $217 million with an addition $83 million possible if installed at the largest remaining 117 ports in the United States. Over the ten-year economic life of PORTS® instruments, the present value for installation at all 175 ports could approach $2.5 billion.

Real-time analytics on large dynamic graphs

In today's fast-paced and interconnected digital world, the data generated by an increasing number of applications is being modeled as dynamic graphs. The graph structure encodes relationships among data items, while the structural changes to the graphs as well as the continuous stream of information produced by the entities in these graphs make them dynamic in nature. Examples include social networks where users post status updates, images, videos, etc.; phone call networks where nodes may send text messages or place phone calls; road traffic networks where the traffic behavior of the road segments changes constantly, and so on. There is a tremendous value in storing, managing, and analyzing such dynamic graphs and deriving meaningful insights in real-time. However, a majority of the work in graph analytics assumes a static setting, and there is a lack of systematic study of the various dynamic scenarios, the complexity they impose on the analysis tasks, and the challenges in building efficient systems that can support such tasks at a large scale. In this dissertation, I design a unified streaming graph data management framework, and develop prototype systems to support increasingly complex tasks on dynamic graphs. In the first part, I focus on the management and querying of distributed graph data. I develop a hybrid replication policy that monitors the read-write frequencies of the nodes to decide dynamically what data to replicate, and whether to do eager or lazy replication in order to minimize network communication and support low-latency querying. In the second part, I study parallel execution of continuous neighborhood-driven aggregates, where each node aggregates the information generated in its neighborhoods. I build my system around the notion of an aggregation overlay graph, a pre-compiled data structure that enables sharing of partial aggregates across different queries, and also allows partial pre-computation of the aggregates to minimize the query latencies and increase throughput. Finally, I extend the framework to support continuous detection and analysis of activity-based subgraphs, where subgraphs could be specified using both graph structure as well as activity conditions on the nodes. The query specification tasks in my system are expressed using a set of active structural primitives, which allows the query evaluator to use a set of novel optimization techniques, thereby achieving high throughput. Overall, in this dissertation, I define and investigate a set of novel tasks on dynamic graphs, design scalable optimization techniques, build prototype systems, and show the effectiveness of the proposed techniques through extensive evaluation using large-scale real and synthetic datasets.

Development of a Real Time System in Algol 68.

For various reasons, many Algol 68 compilers do not directly implement the parallel processing operations defined in the Revised Algol 68 Report. It is still possible however, to perform parallel processing, multitasking and simulation provided that the implementation permits the creation of a master routine for the coordination and initiation of processes under its control. The package described here is intended for real time applications and runs in conjunction with the Algol 68R system; it extends and develops the original Algol 68RT package, which was designed for use with multiplexers at the Royal Radar Establishment, Malvern. The facilities provided, in addition to the synchronising operations, include an interface to an ICL Communications Processor enabling the abstract processes to be realised as the interaction of several teletypes or visual display units with a real time program providing a useful service.

A real time electromagnetic analysis of electric machines for educational purposes and laboratory implementation

This thesis presents a system for visually analyzing the electromagnetic fields of the electrical machines in the energy conversion laboratory. The system basically utilizes the finite element method to achieve a real-time effect in the analysis of electrical machines during hands-on experimentation. The system developed is a tool to support the student's understanding of the electromagnetic field by calculating performance measures and operational concepts pertaining to the practical study of electrical machines. Energy conversion courses are fundamental in electrical engineering. The laboratory is conducted oriented to facilitate the practical application of the theory presented in class, enabling the student to use electromagnetic field solutions obtained numerically to calculate performance measures and operating characteristics. Laboratory experiments are utilized to help the students understand the electromagnetic concepts by the use of this visual and interactive analysis system. In this system, this understanding is accomplished while hands-on experimentation takes place in real-time.

Introducing a pilot data collection model for real-time evaluation of data redundancy

In order to reduce serious health incidents, individuals with high risks need to be identified as early as possible so that effective intervention and preventive care can be provided. This requires regular and efficient assessments of risk within communities that are the first point of contacts for individuals. Clinical Decision Support Systems CDSSs have been developed to help with the task of risk assessment, however such systems and their underpinning classification models are tailored towards those with clinical expertise. Communities where regular risk assessments are required lack such expertise. This paper presents the continuation of GRiST research team efforts to disseminate clinical expertise to communities. Based on our earlier published findings, this paper introduces the framework and skeleton for a data collection and risk classification model that evaluates data redundancy in real-time, detects the risk-informative data and guides the risk assessors towards collecting those data. By doing so, it enables non-experts within the communities to conduct reliable Mental Health risk triage.

Advanced decision-support methods for the design, control, and optimization of perishable products life cycle

In the last decades, global food supply chains had to deal with the increasing awareness of the stakeholders and consumers about safety, quality, and sustainability. In order to address these new challenges for food supply chain systems, an integrated approach to design, control, and optimize product life cycle is required. Therefore, it is essential to introduce new models, methods, and decision-support platforms tailored to perishable products. This thesis aims to provide novel practice-ready decision-support models and methods to optimize the logistics of food items with an integrated and interdisciplinary approach. It proposes a comprehensive review of the main peculiarities of perishable products and the environmental stresses accelerating their quality decay. Then, it focuses on top-down strategies to optimize the supply chain system from the strategical to the operational decision level. Based on the criticality of the environmental conditions, the dissertation evaluates the main long-term logistics investment strategies to preserve products quality. Several models and methods are proposed to optimize the logistics decisions to enhance the sustainability of the supply chain system while guaranteeing adequate food preservation. The models and methods proposed in this dissertation promote a climate-driven approach integrating climate conditions and their consequences on the quality decay of products in innovative models supporting the logistics decisions. Given the uncertain nature of the environmental stresses affecting the product life cycle, an original stochastic model and solving method are proposed to support practitioners in controlling and optimizing the supply chain systems when facing uncertain scenarios. The application of the proposed decision-support methods to real case studies proved their effectiveness in increasing the sustainability of the perishable product life cycle. The dissertation also presents an industry application of a global food supply chain system, further demonstrating how the proposed models and tools can be integrated to provide significant savings and sustainability improvements.

Real-time PMU monitoring of an IEEE 5-Bus Network implemented on OPAL system

This thesis studies the state-of-the-art of phasor measurement units (PMUs) as well as their metrological requirements stated in the IEEE C37.118.1 and C37.118.2 Standards for guaranteeing correct measurement performances. Communication systems among PMUs and their possible applicability in the field of power quality (PQ) assessment are also investigated. This preliminary study is followed by an analysis of the working principle of real-time (RT) simulators and the importance of hardware-in-the-loop (HIL) implementation, examining the possible case studies specific for PMUs, including compliance tests which are one of the most important parts. The core of the thesis is focused on the implementation of a PMU model in the IEEE 5-bus network in Simulink and in the validation of the results using OPAL RT-4510 as a real-time simulator. An initial check allows one to get an idea about the goodness of the results in Simulink, comparing the PMU data with respect to the load-flow steady-state information. In this part, accuracy indices are also calculated for both voltage and current synchrophasors. The following part consists in the implementation of the same code in OPAL-RT 4510 simulator, after which an initial analysis is carried out in a qualitative way in order to get a sense of the goodness of the outcomes. Finally, the confirmation of the results is based on an examination of the attained voltage and current synchrophasors and accuracy indices coming from Simulink models and from OPAL system, using a Matlab script. This work also proposes suggestions for an upcoming operation of PMUs in a more complex system as the Digital Twin (DT) in order to improve the performances of the already-existing protection devices of the distribution system operator (DSO) for a future enhancement of power systems reliability.