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Timetable evaluation with focus on quality for travellersWarg, Jennifer January 2016 (has links)
Punctuality and reliability are important for travellers. Railway lines with heterogeneous and dense traffic have proved to be prone to generate delays. Faster services and increased traffic have to be counterbalanced with measures for increased reliability. Efficient timetable planning can improve the use of such lines. Usually, that aim is treated from either a capacity or a socio-economic point of view. Because both are important, this thesis aims to combine the fields. A new method to evaluate timetable alternatives is developed. Commonly used methods are combined in a novel way to reveal values for different variables as input for evaluation of alternatives. That enables the comparison of timetable strategies using relevant input data. The idea is to estimate the benefits of a timetable for a traveller by expressing them as a timetable performance index (TTPI). For this purpose, quality indicators and methods to reveal them are identified. In the next step, traditional valuations for relationships between the indicators are used to test different model configurations for evaluation of alternatives, for example alternative departures on the same line or different timetables. To treat this multidisciplinary task, several case studies were performed on the Swedish Southern and Western Main lines. As part of a study focussing on methods to measure and evaluate capacity based on travellers’ valuations, the importance of delays was analysed in a questionnaire study and relationships between several variables describing the timetable were found. The other case studies aimed to identify relevant variables and use them to evaluate alternatives. Static and dynamic variables are distinguished. The static ones describe the timetable before operation, the dynamic ones the result of operation or estimated outcome revealed by means of, for example, simulation. Empirical delay data is used in one study, simulation with the microscopic tool RailSys in the others. In one of the studies, analysis is combined with the macroscopic timetabling tool TVEM (Lindfeldt, 2010). The case studies showed the characteristics of the analysed lines described by the chosen variables and which methods and variables are relevant to use for a comparison of timetable slots or evaluation of effects of changes in the timetable. An evaluation method was developed where simulation and timetable analysis reveal the variables. The idea is to construct an analytical function using traditional weights for relationships between the variables to convert the values of the variables into a performance index (PI). Based on a PI for each train slot (TSPI), the TTPI for the whole timetable is estimated. It describes the quality of a timetable in terms of timetable time, i.e. the resulting value is a time that is comparable to the scheduled travel time of one train departure, but includes additional information. With this method, complex timetables can be evaluated regarding their robustness to perturbations, which is valuable for socio-economic analysis of effects of measures applied on the railway system. As shown in a one of the case studies, quality in terms of punctuality and reliability is important for travellers, at the same time as the design of the timetable has significant impact on these aspects. Timetable analysis and simulation are relevant methods to reveal variables that describe these characteristics and evaluation with the presented method is recommended. The configuration of the TTPI is essential for the outcome whereas it is important to choose variables and parameters adequately. If this is taken into account, the approach can be an efficient way to adjust timetables and choose the best alternative, for instance if a train path or timetable change is to be chosen among several. / Punktlighet och tillförlitlighet är viktiga för resenärer. Järnvägar med heterogen och tät trafik har visat sig vara benägna att generera förseningar. Snabbare tåg och utökat trafikutbud måste uppvägas mot punktlighetsåtgärder. Effektiv tidtabellsplanering kan förbättra utnyttjandet av sådana linjer. Detta ändamål behandlas oftast utifrån antingen kapacitets eller samhällsekonomisk synvinkel. Eftersom bägge är viktiga syftar den här avhandlingen på att kombinera dessa områden. En metod för utvärdering av tidtabellsalternativ utvecklas. Befintliga metoder kombineras på ett nytt sätt för att ta fram värden för olika variabler som indata för en utvärdering av alternativen. Detta möjliggör en jämförelse av tidtabellsstrategier med relevant indata. Idén bygger på att bedöma en tidtabells nytta för resenären genom att uttrycka denna som ett prestationsindex (TTPI). För detta syfte identifieras kvalitetsindikatorer och metoder för att ta fram dessa. Traditionella valideringar för relationerna mellan indikatorerna används sedan för att testa olika konfigurationer av modellen för att utvärdera alternativ, till exempel alternativa avgångar på samma linje eller olika tidtabeller. För denna multidisciplinära uppgift har flera fallstudier på svenska Södra och Västra stambanan genomförts. Som del av en studie med fokus på metoder för att mäta och utvärdera kapacitet baserad på resenärers värderingar har förseningens värde analyserats med hjälp av en enkätundersökning och relationer mellan några variabler som beskriver tidtabellen hittats. De övriga fallstudierna syftade på att ta fram relevanta variabler och att använda dem för att utvärdera alternativ. Variablerna delades upp i statiska och dynamiska. De statiska beskriver tidtabellen innan den körs, de dynamiska det verkliga utfallet eller det estimerade resultatet framtaget med hjälp av exempelvis simulering. Empiriska förseningsdata används i en studie, simulering med det mikroskopiska programmet RailSys i de andra. I en av studierna kombineras analysen med det makroskopiska tidtabellsverktyget TVEM (Lindfeldt, 2010). Fallstudierna visade de analyserade linjernas egenskaper beskrivna av de valda variablerna och vilka metoder och variabler som är relevanta för en jämförelse av olika tåglägen eller en utvärdering hur en ändring i tidtabellen påverkar. En utvärderingsmetod där simulering och tidtabellsanalys används för att ta fram variablerna utvecklades. Idén är att skapa en analytisk funktion med hjälp av traditionella vikter som beskriver sambanden mellan variablerna för att räkna om variablernas värden till en prestationsindex (PI). Baserad på en PI för varje tågläge (TSPI) estimeras värdet för hela tidtabellen (TTPI). Detta index beskriver tidtabellens kvalitet som tidtabellstid, dvs. värdet är en tid som är jämförbar med den tidtabellslagda restiden för en avgång, men med ytterligare information inkluderat. Med hjälp av denna metod kan komplexa tidtabeller utvärderas med avseende på robusthet mot störningar vilket är värdefullt för samhällsekonomiska bedömningar av åtgärder i järnvägssystemet. Som en av fallstudierna visade är kvalitet i form av punktlighet och tillförlitlighet viktig för resenärer samtidigt som tidtabellens utformning har en signifikant påverkan på samma aspekter. Tidtabellsanalys och simulering är relevanta metoder för att ta fram variabler som beskriver dessa egenskaper och utvärdering med de visade metoderna rekommenderades. Modellens konfiguration är betydelsefull för resultatet vilket gör det viktigt att välja variabler och parametrar som är lämpliga. Om detta respekteras kan metoden vara effektiv för att anpassa tidtabeller och välja det bästa alternativet, till exempel när det gäller att välja mellan olika tåglägen eller justeringar i tidtabellen. / Pünktlichkeit und Zuverlässigkeit sind wichtig für Reisende. Stark belastete Eisenbahnlinien mit heterogenem Verkehr sind störungsanfällig. Zugleich besteht oft ein Bedarf an schnelleren und häufigeren Verbindungen, was jedoch mit potentiellen negativen Effekten auf die Kapazität aufgewogen werden muss. Effiziente Fahrplankonstruktion kann die Nutzung solcher Linien verbessern. Dieses Ziel wird meist entweder aus der Sicht der Kapazitätsanalyse oder wirtschaftlichen Aspekten betrachtet. Da beide Betrachtungsweisen wichtig sind, strebt diese Arbeit die Kombination beider Felder an. Eine Methode für die Auswertung verschiedener Fahrpläne wird entwickelt. Bewährte Methoden werden in neuer Weise kombiniert um Werte für verschiedene Variablen als Input für die Auswertung von Alternativen zu erhalten. Das ermöglicht es potentielle Änderungen im Fahrplan mithilfe relevanter Werte zu vergleichen. Die Idee basiert auf einem Leistungsindex (TTPI), der den Nutzen eines Fahrplans für die Reisenden ausdrücken soll. Zu diesem Zweck werden Qualitätsindikatoren gewählt und Methoden zur Berechnung und Bearbeitung der Indikatoren entwickelt. Traditionelle Werte für die Abhängigkeiten zwischen den Indikatoren dienen dann dem Test verschiedener Modelkonfigurationen sowie der Auswertung von Alternativen, z. B unterschiedlicher Trassen oder Fahrpläne. Für diese multidisziplinäre Aufgabe wurden mehrere Fallstudien für die südliche und westliche Hauptstrecke in Schweden durchgeführt. In einer Fragenbogenstudie mit den Schwerpunkten Mess- und Auswertungsmethoden wurde der Wert von Verspätungen für Reisende untersucht und Verhältnisse zwischen mehreren Indikatoren ermittelt. Die weiteren Fallstudien strebten das Finden relevanter Variablen und deren Anwendung zur Auswertung von Alternativen an. Statische und dynamische Variablen wurden unterschieden. Die statischen beschreiben den geplanten Fahrplan vor dem Betrieb, die dynamischen den wirklichen Ausfall oder das beispielsweise durch Simulation berechnete erwartete Resultat. In einer der Fallstudien wurde empirisches Datenmaterial für die Verspätungsdaten genutzt, in den weiteren das mikroskopische Simulationsprogramm RailSys. In einer der Studien wurde die Analyse mit dem makroskopischen Fahrplanungsprogramm TVEM (Lindfeldt, 2010) kombiniert. Die Eigenschaften der untersuchten Linien wurden mithilfe der gewählten Indikatoren analysiert. Weiterhin wurde die Relevanz verschiedener Methoden und Variablen für den Vergleich von Fahrten oder der Beurteilung von Änderungen in Fahrplänen beschrieben. Die gewählte Bewertungsmethode kombiniert Simulation und Fahrplananalyse um die benötigten Werte zu bestimmen. Mithilfe einer analytischen Funktion sollen die Variablen durch Anwenden von traditionellen Werten für die Zusammenhänge in einen Leistungsindex (PI) umgewandelt werden. Basierend auf einem PI für jede geplante Fahrplantrasse (TSPI) kann der Wert für den gesamten Fahrplan (TTPI) bestimmt werden. Dieser Index übersetzt die Qualität des Fahrplans in Fahrtzeit, das heißt resultiert in einer Zeit, die mit der fahrplanmäßigen Fahrtzeit für eine Fahrt vergleichbar ist, aber zusätzliche Information enthält. Diese Methode ermöglicht es, komplexe Fahrpläne bezüglich Robustheit gegen Störungen auszuwerten, was wertvoll für die Berechnung der Wirtschaftlichkeit von Maßnahmen im Bahnnetz ist. Wie eine der Fallstudien gezeigt hat, ist die Qualität in Form von Pünktlichkeit und Zuverlässigkeit wichtig für die Reisenden. Gleichzeitig beeinflusst die Ausformung des Fahrplans diese Eigenschaften deutlich. Fahrplananalyse und Simulation sind geeignete Methoden um die Werte der Variablen, die diese Eigenschaften beschreiben, zu bestimmen. Auswertung auf diese Weise wird empfohlen. Die Konfiguration des Models beeinflusst das Ergebnis, weshalb es wichtig ist geeignete Variablen und Parameter zu benutzen. Wird das berücksichtigt, kann die entwickelte Methode effizient für das Verbessern von Fahrplänen angewandt werden und die Wahl der besten Alternative unterstützen, z.B. bei geplanten Änderungen im Fahrplan oder der Wahl zwischen unterschiedlichen Trassen. / <p>QC 20160902</p>
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Lean Manufacturing Production Management Model using the Johnson Method Approach to Reduce Delivery Delays for Printing Production Lines in the Digital Graphic Design IndustryGomero-Campos, A., Mejia-Huayhua, R., Leon-Chavarri, C., Raymundo-Ibañez, C., Dominguez, F. 06 April 2020 (has links)
Several factors compel graphic design companies to improve efficiency and competitiveness in their production lines. However, these companies are not prepared to take on this challenge, as they report delays in 20% of their deliveries, caused by high setup times, low machine availability, and poor work scheduling. In this context, this study proposes a new production management model fed by the interaction of lean manufacturing tools and the Johnson scheduling method. This model has been validated by direct application at the SISSA. The results obtained were the reduction of the setup time to 15 minutes, increased machine availability up to 24%, and an efficient scheduling of its tasks. All of these reduced the percentage of delivery delays from 20% to 6%.
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Impact of Storage and Cryoprotectants on the Function of Cord Blood Hematopoietic Stem CellsJahan, Suria 30 March 2020 (has links)
Cord blood (CB) has emerged as a significant source of hematopoietic stem cells (HSC) for transplantation. Large distances between collection and processing sites combined with staff availability can lead to long processing delays of CB unit (CBU). Standard agencies limit CBU storage at room temperature (RT) to a maximum of 48 hours from collection to freezing. Slow-engraftment and graft failure are major issues related to CB transplantation. I hypothesized that prolonged storage at RT reduces the engraftment activities of CBU due to the loss in HSC numbers. I set to test my hypothesis by performing serial and limiting-dilution transplantation assays in immunodeficient mice. My results showed that the engraftment activity of CBU was significantly perturbed by prolonged storage (>40 hours) at RT. In line with my hypothesis, the transplantation assays suggested that the engraftment deficit originates from loss in HSC numbers. My findings provide results for CB banks to make an informed decision on how long CBU can be stored at RT before processing.
Conversely, CBU must be cryopreserved before use, and loss of function can occur due to osmotic shock and mechanical damage from uncontrolled ice-crystal growth (ice-recrystallization) during freezing and thawing. Current cyroprotectants like dimethyl-sulfoxide fail to inhibit ice-recrystallization. However, a novel class of small ice-recrystallization inhibitor (IRI) molecules (N-aryl-D-aldonamides) have been developed. I hypothesized that supplementation of cryopreservation solution with IRIs will improve the post-thaw viability and engraftment activity of CBU. Herein, I identified two IRIs (IRI 2 and IRI 6) that improved the post-thaw recovery of hematopoietic clonogenic and multipotent progenitors. Moreover, supplementation of CB graft with IRI 2 was beneficial to engraftment and had no negative impact on the differentiation and self-renewal activities of HSCs. Taken together, my results demonstrate for the first time that IRI may be beneficial to the engraftment activity of HSC graft and support further investigation.
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Predicting Bipolar Mood Disorder using LongShort-Term Memory Neural NetworksHafiz, Saeed Mubasher January 2022 (has links)
Bipolar mood disorder is a severe mental condition that has multiple episodesof either of two types: manic or depressive. These phases can lead patients tobecome hyperactive, hyper-sexual, lethargic, or even commit suicide — all ofwhich seriously impair the quality of life for patients. Predicting these phaseswould help patients manage their lives better and improve our ability to applymedical interventions. Traditionally, interviews are conducted in the evening topredict potential episodes in the following days. While machine learningapproaches have been used successfully before, the data was limited tomeasuring a few self-reported parameters each day. Using biometrics recordedat short intervals over many months presents a new opportunity for machinelearning approaches. However, phases of unrest and hyperactivity, which mightbe predictive signals, are not only often experienced long before the onset ofmanic or depressive phases but are also separated by several uneventful days.This delay and its aperiodic occurrence are a challenge for deep learning. In thisthesis, a fictional dataset that mimics long and irregular delays is created andused to test the effects of such long delays and rare events. LSTMs, RNNs, andGRUs are the go-to models for deep learning in this situation. However, theydiffer in their ability to be trained over a long time. As their acronym suggests,LSTMS are believed to be easier to train and to have a better ability to remember(as their name suggests) than their simpler RNN counterparts. GRUs representa compromise in complexity between RNNs and LSTMs. Here, I will show that,contrary to the common assumption, LSTMs are surprisingly forgetful and thatRNNs have a much better ability to generalize over longer delays with shortersequences. At the same time, I could confirm that LSTMs are easily trained ontasks that have more prolonged delays.
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Strategies to Reduce Cost Overruns and Schedule Delays in Construction ProjectsAl-Keim, Ali 01 January 2017 (has links)
Senior managers fail to control time and costs of construction projects despite available advanced project management tools. Based on project management theory, the objective of this multiple case study was to explore the strategies senior managers use to reduce cost overruns and schedule delays in construction projects. Primary data were obtained from semistructured interviews with 3 senior managers from different construction project management companies who have successfully managed construction projects in Qatar. Data analysis process included a modified Van Kaam method. The transcribed interviews were interpreted and coded to generate themes and were validated through member checking and archival documents. The most centralized themes included (a) master planning, (b) processes and procedures, (c) managing design stage, (d) procurement management, (e) use of proper software, (f) setting project cost and time, and (g) deciding clear scope. A construction project may not succeed without appropriate planning for all stages of the project lifecycle. Managing the approval of the project components during the design stage contributes to reducing changes during construction, which is helpful to control cost and time. The project processes and procedures are meaningful roadmaps for the managers and decision makers. The implications for positive social change include the potential to maintain a cleaner Earth by reducing design and construction wastes. Reducing wastes improves the cost of construction and provides opportunities for people to own property at more affordable costs.
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The Influence of Medicaid Expansion Under The Affordable Care Act On Opioid-Related TreatmentMackey, Kerry, 0000-0002-5654-3982 January 2022 (has links)
The U.S. Department of Health and Human Services has declared the misuse of opioid prescription drugs as a public health emergency. The Affordable Care Act’s Medicaid expansion expanded the number of people with insurance and increased the demand for services related to substance abuse treatment. In the first part of this study, the researcher examines whether the Medicaid expansion reduced the likelihood of treatment delay. The second part of this study explores whether the length of stay for opioid use disorder treatment is significantly different in states that adopted Medicaid expansion versus states that did not. In both studies, the researcher analyzes administrative data from the Substance Abuse and Mental Health Services Administration to discover any treatment delays associated with the opioid treatments for the states that adopted the expansion versus the states that did not, and to determine whether there was a difference in the length of stay in the states that adopted the Medicaid versus the states that did not. A difference-in-difference approach is used in both studies to compare the states which adopted an optional Medicaid expansion to those non-adoption states. The evidence suggests that demand for opioid treatment services increased in expansion states as there is a decreased probability of obtaining treatment on the first day for initial requests for outpatient treatment. In addition, evidence suggests that Medicaid expansion increased the likelihood of staying longer in outpatient facilities, but not inpatient facilities. / Business Administration/Risk Management and Insurance
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Potential of Smart Contract in Business to BusinessVattikutti, Avinash January 2018 (has links)
The implementation of smart contract technology with their plausible applications in a business to business are explored. The thesis work shows how Blockchain technology works on the concept of decentralized system which is beneficial to eliminate the need for central authority. The thesis focuses on elimination of challenges pertaining to the selected departments in an organization. The thesis resolves challenges pertaining to lack of transparency, traceability and significant time-delays while in the process of decision making. The influence of blockchain technology and smart contract technology to eliminate these challenges are discussed. Logic of the smart contract and working of the blockchain pertaining to a specific industrial case study are demonstrated. Methodology to set up a smart contract interface in a business to business setting is investigated in this thesis. An observation study has been done in order to show how transparency, traceability and time delay in decision making is achieved by using smart contract interface. This thesis also shows how the blockchain and smart contract technology tries to implement coordination theory.
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Stacking Ensemble Classification applied to US flight delay prediction during the COVID-19 pandemicSchwarz, Patrick January 2022 (has links)
This thesis aims to show that a Stacking Ensemble of multiple base-learners can provide a more accurate prediction of commercial flight delays between the ten largest US airports than the individual prediction models. Three types of machine learning models, namely LASSO, Random Forests and Neural Networks are used as base-learners with different hyper- parameters. A Stacking Ensemble is created by using LASSO as meta-learner. The Stacking Ensemble and the base-learners that performed best on the training data are then evaluated on a test data set. The results are compared by the metrics accuracy, ROC AUC, MCC and F1 Score. It is shown that the Stacking Ensemble is able to provide superior predictions for flight delays in comparison to the best individual models.
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Exponential Stability of Intrinsically Stable Dynamical Networks and Switched Networks with Time-Varying Time DelaysReber, David Patrick 01 April 2019 (has links)
Dynamic processes on real-world networks are time-delayed due to finite processing speeds and the need to transmit data over nonzero distances. These time-delays often destabilize the network's dynamics, but are difficult to analyze because they increase the dimension of the network.We present results outlining an alternative means of analyzing these networks, by focusing analysis on the Lipschitz matrix of the relatively low-dimensional undelayed network. The key criteria, intrinsic stability, is computationally efficient to verify by use of the power method. We demonstrate applications from control theory and neural networks.
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The Effect Of Pre-k Early Intervention Duration On Academic Achievement And Socialization Opportunities Of 3rd Grade Students Who Were Eligible For Special Education Services At Ages 3 To 5: An Exploratory Study Of Children With Developmental DelaysLin, Mike Chang-Hui 01 January 2005 (has links)
The study focuses on young children with developmental delays (DD) in a large school district and explores the effects of Pre-Kindergarten Exceptional Student Education (Pre-K ESE) duration on 136 students' 3rd grade academic achievement and socialization opportunities. This study specifically examines the 2003 statewide assessment (i.e. Florida Comprehensive Assessment Test, FCAT) results of children with DD and their 3rd grade special education status. The literature review showed that providing early intervention services for young children ages 3 through 5 with special needs in the public school system has become the movement of both the federal and state educational policies. However, the empirical studies regarding the effects of Pre-K early intervention programs provided within the public school system are few. A multivariate analysis of covariance (MANCOVA) was conducted to examine the effect of the Pre-K duration (1 year vs. 2 years) on students' 3rd grade performance as measured by FCAT Reading scores, FCAT Math scores, and socialization opportunities (i.e. weekly Non-ESE minutes) while controlling for students' socioeconomic status (i.e. free/reduced price lunch status) and gender. Moreover, a paired sample t test was conducted to examine the difference of the Matrix of Services scores between Pre-K and 3rd grade evaluations. The results of this study provide an insightful picture of Florida Pre-K intervention duration on the performance of children with special needs in public schools.
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