Subspace estimation and prediction methods for hidden Markov models

Hidden Markov models (HMMs) are probabilistic functions of finite Markov chains, or, put in other words, state space models with finite state space. In this paper, we examine subspace estimation methods for HMMs whose output lies a finite set as well. In particular, we study the geometric structure arising from the nonminimality of the linear state space representation of HMMs, and consistency of a subspace algorithm arising from a certain factorization of the singular value decomposition of the estimated linear prediction matrix. For this algorithm, we show that the estimates of the transition and emission probability matrices are consistent up to a similarity transformation, and that the $m$-step linear predictor computed from the estimated system matrices is consistent, i.e., converges to the true optimal linear $m$-step predictor.Comment: Published in at http://dx.doi.org/10.1214/09-AOS711 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Publicity for Lawyers

Antalet förstainsatsaktörer i Sverige idag utanför de traditionella (räddningstjänst, polis och ambulans) är få, och lite forskning har förts på området. Det finns dock exempel där räddningstjänsten har anlitat väktarbolag eller utrustat hemtjänstpersonal med pulversläckare. Flertalet av dessa samarbeten är relativt nystartade och få utvärderingar har gjorts som visar de faktiska effekterna av dem. Syftet med denna rapport är att beskriva och kartlägga samhällekonomiska nyttor och kostnader av icke-traditionella förstainsatsaktörer som samarbetar med räddningstjänsten. Studien har genomförts genom fallstudier av två samarbeten; Söderköping räddningstjänst som har ett avtal med LA Jour & Säkerhet AB samt Södertörns brandförsvarsförbund (SBBF) som samarbetar med väktarbolag i Södertälje och Botkyrka. Sju semistrukturerade intervjuer har genomförts med representanter från väktarbolag, räddningstjänst och kommun. Den metod som används vid analysen är nationalekonomisk kostnadsnyttoanalys. De nyttor som har identifierats är att väktarna sparar tid, bidrar med lägesrapporter, stöttar insatserna genom att vara behjälpliga på plats, upptäcker incidenter eller bränder vid rondering. De har god lokalkännedom och kan hjälpa till att låsa upp brandbommar och dörrar, vilket indirekt sparar tid åt räddningstjänsten. Samarbetet bidrar också till att de arbetar preventivt; de pratar med ungdomar och andra grupper i samhället och skapar relationer som på sikt har möjlighet att gagna säkerheten och tryggheten i kommunen. Kostnaderna för att utbilda och utrusta väktarna är idag låga. Däremot har det framkommit att väktarna gärna skulle vilja ha mer utbildning så att de kan rycka ut vid fler typer av larm. Det har även framkommit att bättre kommunikationskanaler skulle kunna bidra till ökade möjligheter att åka på fler larm och att vara bättre förberedda på vad de kan bidra med vid olika typer av larm. Den kvantitativa analysen utförs för samarbetet i Söderköping och visar att detta har en hög utdelning. Varje investerad krona i Söderköping har gett en avkastning på åtta kronor, när värdet av den minskade insatstid som väktarna bidrar med beräknas. Nyttan är dock undervärderad då många nyttor (beskrivna ovan) inte kan värdesättas monetärt. Det som har begränsat den kvantitativa analysen är det faktum att väktarnas rapportering i Botkyrka och Södertälje inte särskiljer räddningstjänstsuppdrag från övriga uppdrag. Detta hade möjliggjort en kvantitativ analys även för samarbetet med Södertörn, vilket hade kunnat bidra till att resultaten blivit applicerbara på fler kommuner. Emellertid finns inget som indikerar att andra kommuner inte kommer att erfara samma effekter eller kostnader som de undersökta samarbetena har lett till. Däremot bör kommuner analysera behov och förutsättningar i sin kommun för samarbeten av det här slaget innan de inför dem med tanke på att det uppstår kostnader, om än låga

Из опыта проведения итоговых занятий по разделу "Гигиена детей и подростков" на лечебном факультете медицинского вуза

ГИГИЕНАучебный процессСТУДЕНТЫ ЛЕЧЕБНЫХ ФАКУЛЬТЕТОВметодика преподавани

The Enabling of School Participants' Access to Negotiation of Meaning: A Way of Improving Intercultural Understanding

RoboCup 2D Soccer Simulation League is an international artificial intelligence (AI) competition in which computer programs compete in soccer. This report will present the work of analyzing the successful teamWrightEagle, and the isolation of the key strategic and behavioral aspects that make them successful. It will also present the work of creating a new team in which the aspects exctracted from WrightEagle has been implemented, but in a much simpler way. It was found that good passing play, good stamina preservation and the ability to stay spread out wereWrightEagle’s key strategic and behavioral aspects. While these aspects has been implemented in the created team, the lack of good core functionality proved to be a moreRoboCup 2D Soccer Simulation League är en internationell tävling i artificiell intelligens (AI), där datorprogram tävlar i fotboll. Den här rapporten kommer presentera arbetet i att analysera det framgångsrika laget WrightEagle, och att hitta de aspekter vad gäller strategi och betéende som gör dem så framgångsrika. Den kommer också att presentera skapandet av ett nytt lag som implementerar de funna aspekterna från WrightEagle, men på ett mycket enklare sätt. Bra passningsspel, bra uthållighetsbevarande, och deras förmåga att hålla sig utspridda var de funna aspekterna från WrightEagle vad gäller strategi och betéende. De här aspekterna har blivit implementerade i det skapade laget, men bristen av bra basfunktionalitet visade sig väga mycket tyngre och det resulterande laget preseterar dåligt

Mapping and analysis of a distribution process in a make-to-order supply chain

Background: Supply chains become more and more complex. Mapping can be a good way to understand a company’s supply chain and its processes. IKEA’s Direct Delivery Customer (DDC) process has a rather unique characteristic at IKEA. By using a make-to-order strategy are sofas, sofa covers and custom made worktops delivered to customers’ home from the supplier. The material flow goes through IKEA’s Customer Distribution Center (CDC). The DDC material flow has historically been very small and has therefore not received much attention. The volume of this material flow is continuously increasing. Problem description: The CDC terminal in Torsvik perceives problems as lack of space and much manual administrative work due to the growing DDC material flow. The trend indicates that the impact of the perceived problems becomes more and more serious as the flow continues to grow. To fully understand the process and enable process improvements, it is requested to thoroughly map the process. Purpose: The purpose of this study is to map the DDC process and investigate how it is managed. Another purpose is to identify problems in the process and suggest improvements. Objectives: 1. Explain why a product is classified as DDC and why transshipment is made at the CDC terminal in Torsvik. 2. Create understanding of the DDC process by mapping from customer order to the point when the products are delivered at customer’s home. 3. Identify and describe problems that occur in the part of the DDC process managed by the CDC terminal in Torsvik. 4. Suggest short-term and long-term improvements in the DDC process for the CDC terminal in Torsvik. Method: The study is based on a system approach since synergy effects are expected between the different parts in the studied process. Improvement efforts require a system view to avoid sub optimization. The study was performed as a case study with single case design. Primary qualitative methods were used, as semi-structured, unstructured interviews and participating observations. Quantitative methods for collecting data also occurred, but to a minor extent. The authors developed their own research procedure. After the literature review the research procedure was refined, in order to explain how the literature review would be used to answer the objectives. The refined research procedure contains the 6 steps; exploration, current state, identify and describe problems, analysis of problems and recommendations. Conclusion: The mapping resulted in a description of the DDC process current state. Nine problems were identified through the mapping and analysis. Seven of these problems; lack of gate area, long lead time, no one responsible for the entire process, low efficiency in administrative work, missing goods, large amount of handovers, and custom related problems were further analyzed in terms of source, consequences and customer impact and potential solutions. From these seven problems it became clear that five depends upon low IT-support, one way or another. In this case study it became clear that a growing material flow creates a more complex information flow. This information flow often requires to be managed with IT-support, which was missing in this case. The analysis resulted in five short-term and two long-term recommendations. The short-term recommendations are; reduce lead time, share process maps, conduct a workshop with intention to increase efficiency in administrative work, inspection of loaded goods and modify the limit of orders in the IT-system. The long-term recommendations are; investigate possibility to implement IT-support and centralize process responsibility

Can the forecast of the cotton price be improved using a model based upon economic variables?

The purpose of this thesis is to find a model, which is based on economic variables that can forecast the cotton price better than commonly used benchmark models. A vector error correction model is used because of the existence of non-stationary variables and one cointegration relation in the data. Two types of forecasting methods are used for out-of sample predictions. The dynamic forecasting in this thesis is used to predict the cotton price six days ahead and the static forecast only predicts one day ahead. Three different types of estimation windows are used to see which gives the best forecasting results. The residuals are then used to calculate the root mean squared error, RMSE, enabling the comparison with random walks and autoregressive processes. The static forecasts did result in significant better forecasts than the benchmark models while the dynamic forecasts did not produce significantly better nor worse results than the benchmark models. Including economic variables when predicting the cotton price only significantly improves static forecasts of one-day ahead predictions. A sign prediction test was conducted in order to test the static method for one-day speculative purposes, and significant results were found

Statistical mechanics for metabolic networks during steady-state growth

Which properties of metabolic networks can be derived solely from stoichiometric information about the network's constituent reactions? Predictive results have been obtained by Flux Balance Analysis (FBA), by postulating that cells set metabolic fluxes within the allowed stoichiometry so as to maximize their growth. Here, we generalize this framework to single cell level using maximum entropy models from statistical physics. We define and compute, for the core metabolism of Escherichia coli, a joint distribution over all fluxes that yields the experimentally observed growth rate. This solution, containing FBA as a limiting case, provides a better match to the measured fluxes in the wild type and several mutants. We find that E. coli metabolism is close to, but not at, the optimality assumed by FBA. Moreover, our model makes a wide range of predictions: (i) on flux variability, its regulation, and flux correlations across individual cells; (ii) on the relative importance of stoichiometric constraints vs. growth rate optimization; (iii) on quantitative scaling relations for singe-cell growth rate distributions. We validate these scaling predictions using data from individual bacterial cells grown in a microfluidic device at different sub-inhibitory antibiotic concentrations. Under mild dynamical assumptions, fluctuation-response relations further predict the autocorrelation timescale in growth data and growth rate adaptation times following an environmental perturbation.Comment: 12 pages, 4 figure

Antitrust, the Gig Economy, and Labor Market Power

The purpose of the current study was to develop and validate an automatic algorithm for classification of cross-country (XC) ski-skating gears (G) using Smartphone accelerometer data. Eleven XC skiers (seven men, four women) with regional-to-international levels of performance carried out roller skiing trials on a treadmill using fixed gears (G2left, G2right, G3, G4left, G4right) and a 950-m trial using different speeds and inclines, applying gears and sides as they normally would. Gear classification by the Smartphone (on the chest) and based on video recordings were compared. Formachine-learning, a collective database was compared to individual data. The Smartphone application identified the trials with fixed gears correctly in all cases. In the 950-m trial, participants executed 140 ± 22 cycles as assessed by video analysis, with the automatic Smartphone application giving a similar value. Based on collective data, gears were identified correctly 86.0% ± 8.9% of the time, a value that rose to 90.3% ± 4.1% (P < 0.01) with machine learning from individual data. Classification was most often incorrect during transition between gears, especially to or from G3. Identification was most often correct for skiers who made relatively few transitions between gears. The accuracy of the automatic procedure for identifying G2left, G2right, G3, G4left and G4right was 96%, 90%, 81%, 88% and 94%, respectively. The algorithm identified gears correctly 100% of the time when a single gear was used and 90% of the time when different gears were employed during a variable protocol. This algorithm could be improved with respect to identification of transitions between gears or the side employed within a given gear

TOMO link mounted lorry chipper

Tomo Hugglink (TOMO Skog) is an innovation for harvest and transport of biofuels. The system consists of a truck, a chipping unit and crane mounted on a link and a wood chip trailer. The system works in such a way that the chipping unit is disconnected and placed on the site and wood chips are loaded directly into the wood chip trailer. The aim of this study was: - To examine the performance of the TOMO Hugglink system under different conditions such as the size, placement and quality of the pile. - To calculate the cost per raw ton for two vehicle combinations at different transport distances and to examine the effect of a reduction in set-up time and an increase in load weight. - To identify possible improvements with the TOMO Hugglink system. A time study was conducted within the thesis work to make it possible to determine production and time consumption. In the subsequent economic analysis the cost per tone at different transport distances was calculated for two different lorry concepts. Furthermore the effect of a reduction in set-up time and an increase in load weight was calculated. Under current conditions the utilization of the chipper is low and only 29 % of the total system time is occupied by chipping. This problem can be remedied by adding another truck and chip trailer to the system. According to estimates the cost per tone can be reduced for objects with transport distances longer than 34 km by adding another truck and trailer. An increase in load weight can reduce the cost for the system and the impact is greatest on long transport distances. An increase in load weight from 25, 6 tons to 28 tons results in the configuration with one truck and trailer having lowest cost up to a transport distance of 37 km. By reducing the set-up time by 20 % the cost can be lowered and the configuration with two trucks and two trailer are cost efficient up to a transport distance of 31 km

Startup Methodology for Production Flow Simulation Projects Assessing Environmental Sustainability

Environmental impact assessments for companies and products are important to increase sales and reduce environmental impact. To support improvements and detailed analyses, researchers have extended the use of simulation of production flows to include sustainability performance indicators. The research cases performed until recently lack standardized methodology and thus have comparability issues and an increase number of common faults. By using a common methodology and gathering best practice, future cases can gain a lot. Especially noted by the authors is that the project startup phase is critical for success. This paper proposes a methodology to support the startup phases of simulation projects with sustainability aspects in production flows. The methodology is developed and applied in an automotive industry study presented in this paper. Using a rigid project startup, such as the proposed methodology, reduces iterations during modeling and data collection and decreases time spent on modeling