A simulation study of the shift system at a UK police communications centre

The UK Police Force is required to operate communications centres under increased funding constraints. Staff represent the main cost in operating the facility and the key issue for the efficient deployment of staff, in this case call handler staff, is to try to ensure sufficient staff are available to make a timely response to customer calls when the timing of individual calls is difficult to predict. A discrete-event simulation study is presented of an investigation of a new shift pattern for call handler staff that aims to improve operational efficiency. The communications centre can be considered a specialised case of a call centre but an important issue for Police Force management is the particularly stressful nature of the work staff are involved with when responding to emergency calls. Thus decisions regarding changes to the shift system were made in the context of both attempting to improve efficiency by matching staff supply with customer demand, but also ensuring a reasonable workload pattern for staff over time.

An efficient knowledge transfer solution to a novel SMDP formalization of a broker's decision problem

This paper introduces a new technique for optimizing the trading strategy of brokers that autonomously trade in re- tail and wholesale markets. Simultaneous optimization of re- tail and wholesale strategies has been considered by existing studies as intractable. Therefore, each of these strategies is optimized separately and their interdependence is generally ignored, with resulting broker agents not aiming for a glob- ally optimal retail and wholesale strategy. In this paper, we propose a novel formalization, based on a semi-Markov deci- sion process (SMDP), which globally and simultaneously op- timizes retail and wholesale strategies. The SMDP is solved using hierarchical reinforcement learning (HRL) in multi- agent environments. To address the curse of dimensionality, which arises when applying SMDP and HRL to complex de- cision problems, we propose an ecient knowledge transfer approach. This enables the reuse of learned trading skills in order to speed up the learning in new markets, at the same time as making the broker transportable across market envi- ronments. The proposed SMDP-broker has been thoroughly evaluated in two well-established multi-agent simulation en- vironments within the Trading Agent Competition (TAC) community. Analysis of controlled experiments shows that this broker can outperform the top TAC-brokers. More- over, our broker is able to perform well in a wide range of environments by re-using knowledge acquired in previously experienced settings.

Energy-efficient multihop cooperative MISO transmission with optimal hop distance in wireless ad hoc networks

In this paper, we investigate the hop distance optimization problem in ad hoc networks where cooperative multiinput- single-output (MISO) is adopted to improve the energy efficiency of the network. We first establish the energy model of multihop cooperative MISO transmission. Based on the model, the energy consumption per bit of the network with high node density is minimized numerically by finding an optimal hop distance, and, to get the global minimum energy consumption, both hop distance and the number of cooperating nodes around each relay node for multihop transmission are jointly optimized. We also compare the performance between multihop cooperative MISO transmission and single-input-single-output (SISO) transmission, under the same network condition (high node density). We show that cooperative MISO transmission could be energyinefficient compared with SISO transmission when the path-loss exponent becomes high. We then extend our investigation to the networks with varied node densities and show the effectiveness of the joint optimization method in this scenario using simulation results. It is shown that the optimal results depend on network conditions such as node density and path-loss exponent, and the simulation results are closely matched to those obtained using the numerical models for high node density cases.

3D simulation of the effects of sphericity on char entrainment in fluidised beds

The paper presents a 3-dimensional simulation of the effect of particle shape on char entrainment in a bubbling fluidised bed reactor. Three char particles of 350 μm side length but of different shapes (cube, sphere, and tetrahedron) are injected into the fluidised bed and the momentum transport from the fluidising gas and fluidised sand is modelled. Due to the fluidising conditions, reactor design and particle shape the char particles will either be entrained from the reactor or remain inside the bubbling bed. The sphericity of the particles is the factor that differentiates the particle motion inside the reactor and their efficient entrainment out of it. The simulation has been performed with a completely revised momentum transport model for bubble three-phase flow, taking into account the sphericity factors, and has been applied as an extension to the commercial finite volume code FLUENT 6.3. © 2010 Elsevier B.V.All rights reserved.

Algorithms for efficient transaction management and consistent queries in client -server semantic object-oriented parallel databases

Large read-only or read-write transactions with a large read set and a small write set constitute an important class of transactions used in such applications as data mining, data warehousing, statistical applications, and report generators. Such transactions are best supported with optimistic concurrency, because locking of large amounts of data for extended periods of time is not an acceptable solution. The abort rate in regular optimistic concurrency algorithms increases exponentially with the size of the transaction. The algorithm proposed in this dissertation solves this problem by using a new transaction scheduling technique that allows a large transaction to commit safely with significantly greater probability that can exceed several orders of magnitude versus regular optimistic concurrency algorithms. A performance simulation study and a formal proof of serializability and external consistency of the proposed algorithm are also presented.^ This dissertation also proposes a new query optimization technique (lazy queries). Lazy Queries is an adaptive query execution scheme which optimizes itself as the query runs. Lazy queries can be used to find an intersection of sub-queries in a very efficient way, which does not require full execution of large sub-queries nor does it require any statistical knowledge about the data.^ An efficient optimistic concurrency control algorithm used in a massively parallel B-tree with variable-length keys is introduced. B-trees with variable-length keys can be effectively used in a variety of database types. In particular, we show how such a B-tree was used in our implementation of a semantic object-oriented DBMS. The concurrency control algorithm uses semantically safe optimistic virtual "locks" that achieve very fine granularity in conflict detection. This algorithm ensures serializability and external consistency by using logical clocks and backward validation of transactional queries. A formal proof of correctness of the proposed algorithm is also presented. ^

Energy-efficient self -organization of wireless acoustic sensor networks for ground target tracking

With the developments in computing and communication technologies, wireless sensor networks have become popular in wide range of application areas such as health, military, environment and habitant monitoring. Moreover, wireless acoustic sensor networks have been widely used for target tracking applications due to their passive nature, reliability and low cost. Traditionally, acoustic sensor arrays built in linear, circular or other regular shapes are used for tracking acoustic sources. The maintaining of relative geometry of the acoustic sensors in the array is vital for accurate target tracking, which greatly reduces the flexibility of the sensor network. To overcome this limitation, we propose using only a single acoustic sensor at each sensor node. This design greatly improves the flexibility of the sensor network and makes it possible to deploy the sensor network in remote or hostile regions through air-drop or other stealth approaches. Acoustic arrays are capable of performing the target localization or generating the bearing estimations on their own. However, with only a single acoustic sensor, the sensor nodes will not be able to generate such measurements. Thus, self-organization of sensor nodes into virtual arrays to perform the target localization is essential. We developed an energy-efficient and distributed self-organization algorithm for target tracking using wireless acoustic sensor networks. The major error sources of the localization process were studied, and an energy-aware node selection criterion was developed to minimize the target localization errors. Using this node selection criterion, the self-organization algorithm selects a near-optimal localization sensor group to minimize the target tracking errors. In addition, a message passing protocol was developed to implement the self-organization algorithm in a distributed manner. In order to achieve extended sensor network lifetime, energy conservation was incorporated into the self-organization algorithm by incorporating a sleep-wakeup management mechanism with a novel cross layer adaptive wakeup probability adjustment scheme. The simulation results confirm that the developed self-organization algorithm provides satisfactory target tracking performance. Moreover, the energy saving analysis confirms the effectiveness of the cross layer power management scheme in achieving extended sensor network lifetime without degrading the target tracking performance.

Developing an enhanced model for combined heat and air infiltration energy simulation

The need for efficient, sustainable, and planned utilization of resources is ever more critical. In the U.S. alone, buildings consume 34.8 Quadrillion (1015) BTU of energy annually at a cost of $1.4 Trillion. Of this energy 58% is utilized for heating and air conditioning. ^ Several building energy analysis tools have been developed to assess energy demands and lifecycle energy costs in buildings. Such analyses are also essential for an efficient HVAC design that overcomes the pitfalls of an under/over-designed system. DOE-2 is among the most widely known full building energy analysis models. It also constitutes the simulation engine of other prominent software such as eQUEST, EnergyPro, PowerDOE. Therefore, it is essential that DOE-2 energy simulations be characterized by high accuracy. ^ Infiltration is an uncontrolled process through which outside air leaks into a building. Studies have estimated infiltration to account for up to 50% of a building's energy demand. This, considered alongside the annual cost of buildings energy consumption, reveals the costs of air infiltration. It also stresses the need that prominent building energy simulation engines accurately account for its impact. ^ In this research the relative accuracy of current air infiltration calculation methods is evaluated against an intricate Multiphysics Hygrothermal CFD building envelope analysis. The full-scale CFD analysis is based on a meticulous representation of cracking in building envelopes and on real-life conditions. The research found that even the most advanced current infiltration methods, including in DOE-2, are at up to 96.13% relative error versus CFD analysis. ^ An Enhanced Model for Combined Heat and Air Infiltration Simulation was developed. The model resulted in 91.6% improvement in relative accuracy over current models. It reduces error versus CFD analysis to less than 4.5% while requiring less than 1% of the time required for such a complex hygrothermal analysis. The algorithm used in our model was demonstrated to be easy to integrate into DOE-2 and other engines as a standalone method for evaluating infiltration heat loads. This will vastly increase the accuracy of such simulation engines while maintaining their speed and ease of use characteristics that make them very widely used in building design.^

Energy-Efficient Self-Organization of Wireless Acoustic Sensor Networks for Ground Target Tracking

With the developments in computing and communication technologies, wireless sensor networks have become popular in wide range of application areas such as health, military, environment and habitant monitoring. Moreover, wireless acoustic sensor networks have been widely used for target tracking applications due to their passive nature, reliability and low cost. Traditionally, acoustic sensor arrays built in linear, circular or other regular shapes are used for tracking acoustic sources. The maintaining of relative geometry of the acoustic sensors in the array is vital for accurate target tracking, which greatly reduces the flexibility of the sensor network. To overcome this limitation, we propose using only a single acoustic sensor at each sensor node. This design greatly improves the flexibility of the sensor network and makes it possible to deploy the sensor network in remote or hostile regions through air-drop or other stealth approaches. Acoustic arrays are capable of performing the target localization or generating the bearing estimations on their own. However, with only a single acoustic sensor, the sensor nodes will not be able to generate such measurements. Thus, self-organization of sensor nodes into virtual arrays to perform the target localization is essential. We developed an energy-efficient and distributed self-organization algorithm for target tracking using wireless acoustic sensor networks. The major error sources of the localization process were studied, and an energy-aware node selection criterion was developed to minimize the target localization errors. Using this node selection criterion, the self-organization algorithm selects a near-optimal localization sensor group to minimize the target tracking errors. In addition, a message passing protocol was developed to implement the self-organization algorithm in a distributed manner. In order to achieve extended sensor network lifetime, energy conservation was incorporated into the self-organization algorithm by incorporating a sleep-wakeup management mechanism with a novel cross layer adaptive wakeup probability adjustment scheme. The simulation results confirm that the developed self-organization algorithm provides satisfactory target tracking performance. Moreover, the energy saving analysis confirms the effectiveness of the cross layer power management scheme in achieving extended sensor network lifetime without degrading the target tracking performance.

Docking and simulation study of the enantiospecificity of chiral epoxidation reactions catalyzed by chloroperoxidase

Chloroperoxidase (CPO), a 298-residue glycosylated protein from the fungus Caldariomyces fumago, is probably the most versatile heme enzyme yet discovered. Interest in CPO as a catalyst is based on its power to produce enantiomerically enriched products. Recent research has focused its attention on the ability of CPO to epoxidize alkenes in high regioselectivity and enantioselectivity as an efficient and environmentally benign alternative to traditional synthetic routes. There has been little work on the nature of ligand binding, which probably controls the regio- and enantiospecifity of CPO. Consequently it is here that we focus our work. We report docking calculations and computer simulations aimed at predicting the enantiospecificity of CPO-catalyzed epoxidation of three model substrates. On the basis of this work candidate mutations to improve the efficiency of CPO are predicted. In order to accomplish these aims, a simulated annealing and molecular dynamics protocol is developed to sample potentially reactive substrate/CPO complexes.

Evaluating the effectiveness of signal timing optimization based on microscopic simulation evaluation

The optimization of the timing parameters of traffic signals provides for efficient operation of traffic along a signalized transportation system. Optimization tools with macroscopic simulation models have been used to determine optimal timing plans. These plans have been, in some cases, evaluated and fine tuned using microscopic simulation tools. A number of studies show inconsistencies between optimization tool results based on macroscopic simulation and the results obtained from microscopic simulation. No attempts have been made to determine the reason behind these inconsistencies. This research investigates whether adjusting the parameters of macroscopic simulation models to correspond to the calibrated microscopic simulation model parameters can reduce said inconsistencies. The adjusted parameters include platoon dispersion model parameters, saturation flow rates, and cruise speeds. The results from this work show that adjusting cruise speeds and saturation flow rates can have significant impacts on improving the optimization/macroscopic simulation results as assessed by microscopic simulation models.

The (Un)Folding of Multidomain Proteins Through the Lens of Single-molecule Force-spectroscopy and Computer Simulation

Proteins are specialized molecules that catalyze most of the reactions that can sustain life, and they become functional by folding into a specific 3D structure. Despite their importance, the question, "how do proteins fold?" - first pondered in in the 1930's - is still listed as one of the top unanswered scientific questions as of 2005, according to the journal Science. Answering this question would provide a foundation for understanding protein function and would enable improved drug targeting, efficient biofuel production, and stronger biomaterials. Much of what we currently know about protein folding comes from studies on small, single-domain proteins, which may be quite different from the folding of large, multidomain proteins that predominate the proteomes of all organisms.

In this thesis I will discuss my work to fill this gap in understanding by studying the unfolding and refolding of large, multidomain proteins using the powerful combination of single-molecule force-spectroscopy experiments and molecular dynamic simulations.

The three model proteins studied - Luciferase, Protein S, and Streptavidin - lend insight into the inter-domain dependence for unfolding and the subdomain stabilization of binding ligands, and ultimately provide new insight into atomistic details of the intermediate states along the folding pathway.

Detecting stealthy attacks: Efficient monitoring of suspicious activities on computer networks

Stealthy attackers move patiently through computer networks - taking days, weeks or months to accomplish their objectives in order to avoid detection. As networks scale up in size and speed, monitoring for such attack attempts is increasingly a challenge. This paper presents an efficient monitoring technique for stealthy attacks. It investigates the feasibility of proposed method under number of different test cases and examines how design of the network affects the detection. A methodological way for tracing anonymous stealthy activities to their approximate sources is also presented. The Bayesian fusion along with traffic sampling is employed as a data reduction method. The proposed method has the ability to monitor stealthy activities using 10-20% size sampling rates without degrading the quality of detection.

An Efficient Precoder Design for Multiuser MIMO Cognitive Radio Networks with Interference Constraints

We consider a linear precoder design for an underlay cognitive radio multiple-input multiple-output broadcast channel, where the secondary system consisting of a secondary base-station (BS) and a group of secondary users (SUs) is allowed to share the same spectrum with the primary system. All the transceivers are equipped with multiple antennas, each of which has its own maximum power constraint. Assuming zero-forcing method to eliminate the multiuser interference, we study the sum rate maximization problem for the secondary system subject to both per-antenna power constraints at the secondary BS and the interference power constraints at the primary users. The problem of interest differs from the ones studied previously that often assumed a sum power constraint and/or single antenna employed at either both the primary and secondary receivers or the primary receivers. To develop an efficient numerical algorithm, we first invoke the rank relaxation method to transform the considered problem into a convex-concave problem based on a downlink-uplink result. We then propose a barrier interior-point method to solve the resulting saddle point problem. In particular, in each iteration of the proposed method we find the Newton step by solving a system of discrete-time Sylvester equations, which help reduce the complexity significantly, compared to the conventional method. Simulation results are provided to demonstrate fast convergence and effectiveness of the proposed algorithm. 

Assessment of turbulence model predictions for a centrifugal compressor simulation

Steady-state computational fluid dynamics (CFD) simulations are an essential tool in the design process of centrifugal compressors. Whilst global parameters, such as pressure ratio and efficiency, can be predicted with reasonable accuracy, the accurate prediction of detailed compressor flow fields is a much more significant challenge. Much of the inaccuracy is associated with the incorrect selection of turbulence model. The need for a quick turnaround in simulations during the design optimisation process, also demands that the turbulence model selected be robust and numerically stable with short simulation times.
In order to assess the accuracy of a number of turbulence model predictions, the current study used an exemplar open CFD test case, the centrifugal compressor ‘Radiver’, to compare the results of three eddy viscosity models and two Reynolds stress type models. The turbulence models investigated in this study were (i) Spalart-Allmaras (SA) model, (ii) the Shear Stress Transport (SST) model, (iii) a modification to the SST model denoted the SST-curvature correction (SST-CC), (iv) Reynolds stress model of Speziale, Sarkar and Gatski (RSM-SSG), and (v) the turbulence frequency formulated Reynolds stress model (RSM-ω). Each was found to be in good agreement with the experiments (below 2% discrepancy), with respect to total-to-total parameters at three different operating conditions. However, for the off-design conditions, local flow field differences were observed between the models, with the SA model showing particularly poor prediction of local flow structures. The SST-CC showed better prediction of curved rotating flows in the impeller. The RSM-ω was better for the wake and separated flow in the diffuser. The SST model showed reasonably stable, robust and time efficient capability to predict global and local flow features.

Discrete-event Simulation and Optimization to Improve the Performance of a Healthcare System

Thesis (Ph.D.)--University of Washington, 2016-08