Dissertationen zum Thema „Prioritization factors“

Purpose - The subject of green management and its connection to motivational factors is relatively unexplored in existing literature, especially regarding SMEs in the Nordic Countries. The paper aims to investigate frequencies of motivational factors as SMEs present them, suggest the theoretical prioritization of motivational factors for green management practices, and factors impact on different levels of green management. The reason for this is to help SMEs to better understand what motivational factors to prioritize to further their green management development.                          Design/Method - The chosen research method of this paper is quantitative, and the empirical data is collected through questionnaires distributed using business networks in the Nordic Countries. Furthermore, the research takes an abductive approach, with a positivist paradigm, and a mixture of ontological, epistemological, and method research assumption. Findings - This paper has found that at different levels of green management practices specific factors of motivation should theoretically be prioritized based on a regression model. Furthermore, the suggested prioritization is different from presented by the sample of this paper.                                                          Research Implications - Theoretically, the thesis suggests a conceptual map of existing frameworks and the motivational factors presented. Practically, SMEs can draw from this study to see if their prioritised motivation for implementation of green management is effective or if they can further improve it.

Kravprioritering är ett av de viktigaste och mest inflytelserika stegen vid tillverkning av en mjukvaruprodukt. Processen är iterativ; den sker under hela produktens agila mjukvaruutvecklingsprocess. Genom kravprioritering beslutas det om vilka krav som ska utvecklas, i vilken ordning och varför.  Målet med denna studie är att undersöka hur mjukvaruutvecklande företag gör för att kravprioritera, samt identifiera vilka prioriteringsmetoder de eventuellt använder sig av. Studiens syfte är att få en förståelse för varför en väl avvägd prioritering är viktig, vilka särskilda prioriteringsfaktorer som ger värde till en produkt och att se hur dessa faktorer är relaterade till resultatet. Syftet är även att undersöka vilka svårigheter som finns i en prioriteringsprocess, samt att skapa en översikt över några av de mest vedertagna prioriteringsmetoderna inom agil mjukvaruutveckling.  Studien utförs i samarbete med mjukvaruföretaget Monitor ERP för att analysera företagets prioriteringsprocesser som används för att utveckla deras affärssystem Monitor. Metoden som används är en kvalitativ undersökning som består av observationer av möten kring prioriteringsarbete och semi-strukturerade intervjuer. Bearbetning av insamlat material skedde genom att organisera, analysera och sammanställa resultat enligt begrepp och kategorier som framkom utifrån litteraturstudien. Resultatet redovisar arbetsprocesser, gemensamma mål, prioriteringsaspekter och utmaningar i prioriteringsarbetet hos Monitor ERP. En väl avvägd prioritering visade sig vara viktigt för att kunna leverera rätt funktionalitet i tid, för att kunna ge trovärdiga estimeringar om utvecklingen och det i sin tur leder till att kunder får förtroende för både produkten och företaget. En rad olika prioriteringsfaktorer som ger värde till programvaran Monitor identifierades, varav många bidrar till att öka kundnöjdheten och kvaliteten på produkten. Monitor ERP använder inte några särskilda prioriteringsmetoder, utan utvecklingsfilosofin Minimum Viable Product används som grund till deras prioriteringsval. Under prioriteringsarbetet upplevdes utmaningar såsom begränsade resurser, oförutsägbara uppgifter, svårigheter med tidsestimering och en utmaning i balansen mellan kundnytta och kundfokus.
Prioritizing requirements is one of the most important and influential steps in the creation of a software product. The process is iterative; it takes place during the entire agile software development. Through prioritizing requirements, it is decided which requirements are to be developed, in which order, and why.  The aim of this study is to investigate how companies that design software prioritize requirements and to identify which prioritization methods they might use during this process. The purpose of this study is to gain an understanding for why a well-balanced prioritization is important, which specific prioritization factors give value to a product, as well as identifying how these factors are related to the result. The purpose is also to investigate the difficulties that exist in a prioritization process, and to create an overview of some of the most used prioritization methods in agile software development.  This study is conducted in collaboration with the software company Monitor ERP in order to analyze the company's prioritization processes used to develop their business management system Monitor. The method used is a qualitative study that consists of observations of meetings about prioritization processes, and semi-structured interviews. Processing of collected material was done by organizing, analyzing, and compiling results according to concepts and categories that emerged from the literature study. The results documents work processes, common goals, prioritization aspects and challenges in the requirements prioritization at Monitor ERP.  A well-balanced prioritization proved to be important to be able to deliver the right functionality on time and to be able to provide dependable estimates of development, which in turn leads to customers gaining confidence in both the product and the company. A number of prioritization factors that give value to the Monitor software were identified, many of which contribute to increasing customer satisfaction and product quality. Monitor ERP does not use any specific prioritization methods, but the development philosophy Minimum Viable Product is used as a basis for their prioritization choices. During the prioritization process, challenges such as limited resources, unpredictable tasks, difficulties with time estimation, and a challenge in balancing customer value and customer focus were experienced.

This study investigated the knowledge level of secondary building-level administrators and secondary teachers regarding adolescent suicidal risk factors and warning signs. Additionally, this study contributed a social mediation component, to explore whether educators believe that they have the potential to be change agents for youth in their school communities. Three hundred forty-three participants (318 teachers, 18 assistant principals and 7 principals) from the middle and high schools in a local public school district in the Mid-Atlantic Region of the United States completed a survey pertaining to information on adolescent suicide. Data analyses were conducted through detailed cross-tabulations and analysis of variances to examine educator knowledge. Despite a wide variability in scores, findings suggest that the majority of educators acknowledge having moderate to low knowledge levels in most critical content domains of youth suicide. Additionally, educators believe that they have the ability to be social mediators of change for youth in the school setting.

Klimatkrisen är idag en stor samhällsfråga som berör den hållbara utvecklingen i världen och Sverige. Bostäder och service står för 40% av Sveriges slutliga totala energianvändning. På senare tid har det blivit vanligare att miljöcertifiera byggnader, där certifieringen Miljöbyggnad är den mest förekommande. I Sverige är det totala marknadsvärdet för fastighetsbeståndet cirka 10 804 miljarder kronor. En betydande storlek om jämförelse görs med Sveriges BNP år 2017 på cirka 4 600 miljarder kronor. Vidare har det framgått från tidigare studier att miljöcertifierade byggnader har ett högre marknadsvärde kontra konventionella byggnader. Värderare har med andra ord ett stort ansvar att prissätta fastigheter korrekt där flera tidigare studier gjorts kring dem bakomliggandende hårda faktorerna som hyresnivå, vakans, driftkostnad, riskpremie och deras påverkan på marknadsvärdet. Vidare finns studier som indikerar att mjuka faktorer som inomhusklimat, strävan efter minskad klimatpåverkan, hälsa, estetik, social status, kvalitet på byggnad, varumärke och säkerhet har en inverkan på marknadsvärdet. Vad som inte undersökts är hur dessa faktorer prioriteras av fastighetsvärderarna. Denna studie syftar till att undersöka dem mjuka värdena med inverkan på värderingen avMiljöbyggnads-certifierade fastigheter samt hur fastighetsvärderare prioriterar dessa vid en värdering. Genom att först granska tidigare studier skapades en förståelse för dem mjuka faktorerna och dess kopplingar till värdering. Därefter utgjordes studien av en enkätundersökning som besvarades av fastighetsvärderare från banker samt olika fastighets- och rådgivningsbolag. Där värderarna fick poängsätta de olika mjuka faktorernas prioritet. Enkätsvaren jämfördes därefter genom medelpoäng och korrelation för att få en generell uppfattning av fastighetsvärderarnas inställning och likheterna mellan de mjuka faktorernas prioritering. Resultatet från enkätstudien visar att den genomsnittliga fastighetsvärderaren prioriterar de mjuka faktorerna enligt följande, 1) kvalitet på byggnad, 2) varumärke, 3) estetik, 4) säkerhet,5) strävan efter minskad klimatpåverkan, 6) social status, 7) ljuskvalitet, luftkvalitet och termisk kvalitet (delad prioritering) och sist 8) hälsa.
The climate crisis is today a major societal issue that affects sustainable development in the world and Sweden. Housing and services account for 40% of Sweden’s final total energy use.In recent times, it has become more common to certify buildings environmentally, where the certification Miljöbyggnad is the most common. In Sweden, the total market value of the property portfolio is approximately SEK 10,804 billion. A significant size if we were to compare with Sweden's GDP in 2017 of approximately SEK 4,600 billion. It has emerged from previous studies that environmentally certified buildings have a higher market value compared to conventional buildings. In other words, valuers have a great responsibility to appraise properties correctly where several previous studies have been done on the underlying hard factors such as rent level, vacancy, operating costs, risk premium, and their impact on market value. Furthermore, some studies indicate that soft factors such as indoor climate, the pursuit of reduced climate impact, health, aesthetics, social status, quality of building, brand and safety have an impact on the market value. What has not yet been investigated is how these factors are prioritized by the property valuers. This study aims to examine those soft values with an impact on the valuation of Miljöbyggnad certified properties and how property valuers prioritize these in a valuation. By first reviewing previous studies an understanding of the soft factors and their links to valuation was created. Subsequently the study consisted of a survey that was answered by property valuers from banks and various real estate and consulting companies. Where the valuers had to score the priority of the various soft factors. The survey results were then compared through average scores and correlation to get a general idea of the property valuers attitude and the similarities between the prioritization of the soft factors. The result of the survey shows that the average property appraiser prioritizes the soft factors as follows: 1) quality of building, 2) brand, 3) aesthetics, 4) safety, 5) the pursuit of reduced climate impact, 6) social status, 7) light quality, air quality and thermal quality (shared priority) and finally 8) health.

The Highway Safety Manual (HSM) estimates roadway safety performance based on predictive models that were calibrated using national data. Calibration factors are then used to adjust these predictive models to local conditions for local applications. The HSM recommends that local calibration factors be estimated using 30 to 50 randomly selected sites that experienced at least a total of 100 crashes per year. It also recommends that the factors be updated every two to three years, preferably on an annual basis. However, these recommendations are primarily based on expert opinions rather than data-driven research findings. Furthermore, most agencies do not have data for many of the input variables recommended in the HSM. This dissertation is aimed at determining the best way to meet three major data needs affecting the estimation of calibration factors: (1) the required minimum sample sizes for different roadway facilities, (2) the required frequency for calibration factor updates, and (3) the influential variables affecting calibration factors. In this dissertation, statewide segment and intersection data were first collected for most of the HSM recommended calibration variables using a Google Maps application. In addition, eight years (2005-2012) of traffic and crash data were retrieved from existing databases from the Florida Department of Transportation. With these data, the effect of sample size criterion on calibration factor estimates was first studied using a sensitivity analysis. The results showed that the minimum sample sizes not only vary across different roadway facilities, but they are also significantly higher than those recommended in the HSM. In addition, results from paired sample t-tests showed that calibration factors in Florida need to be updated annually. To identify influential variables affecting the calibration factors for roadway segments, the variables were prioritized by combining the results from three different methods: negative binomial regression, random forests, and boosted regression trees. Only a few variables were found to explain most of the variation in the crash data. Traffic volume was consistently found to be the most influential. In addition, roadside object density, major and minor commercial driveway densities, and minor residential driveway density were also identified as influential variables.

Major accidents in the process industries occurred mostly as an outcome of multiple failures in different safety barriers and their interrelation with unsafe acts by frontline operators. This has become the reason why safety analyses in terms of plant technical aspects cannot be performed independently from analysing human response to the changing technology. Unsafe acts and errors by operators must be seen as a symptom of system insufficiencies and underlying problems, rather than as the cause of an accident. With this paradigm, the need to optimally configure the system and the whole working condition to understand human’s limitation and requirements becomes very evident. It is too naive to desire that human operators make zero error by asking them to change their behaviour and to perfectly adapt to the system. Human Factors (HF) attempts to cope with the need to understand the interrelation between human operators, the technology they are working with and the management system, with the aim to increase safety and efficiency. In achieving this goal, HF must be incorporated into the whole plant lifecycle, from the earliest design stage to plant operation and modifications. Moreover, HF analysis must comprise all kinds of operators’ activities and responsibilities in operating process plants, which can include manual works in field and supervisory control conducted remotely from a control centre/room. This work has developed techniques that provide systematic way to incorporate HF into process plant lifecycle. The new HF analysis technique, PITOPA-Design, in a combination with the classic PITOPA, is applicable for an implementation during design and operation of a plant. With the awareness that safety analysis and HF cannot be performed separately, an interconnection with HAZOPs is made possible by means of this new technique. Moreover, to provide a systematic analysis of operators’ work in control room, an additional technique, the PITOPA-CR was also developed. This HF technique can as well be integrated into a general HF analysis both during design phase and plant operation. In addition to it, results coming from PITOPA-CR will provide information required to optimally configure control and alarm system, as well as the whole alarm management system to better understand the limitation and requirements of control room operators. The structure of the development can be described as follows: i) Development of HAZOPA (the Hazards and Operator Actions Analysis), which provides the interconnection between HF analysis and HAZOPs, ii) Development of PITOPA-Design, a technique to incorporate HF consideration into design phase, which is differentiated into 3 stages to comprise the conceptual design, the basic engineering and the detail engineering phase, iii) Development of PITOPA-CR, a technique for HF analysis in control room, iv) Integration of PITOPA-CR into alarm management system, development of a technique for alarm prioritization
Schwere Unfälle in der Prozessindustrie erfolgen meist aus einem Zusammenspiel mehrerer verschiedener Fehler und der gleichzeitigen Wechselwirkung mit falschem menschlichem Handeln. Dabei sind diese Fehlhandlungen nicht als Unfallursache anzusehen, sondern sie resultieren aus Fehlern, die in dem System selbst zu finden sind. Aus diesem Grund kann bei der Sicherheitsanalyse die technische Analyse nicht unabhängig von der Betrachtung des Human Factors (HF) durchgeführt werden. Um eine Reduzierung der Fehlhandlungen zu erreichen, müssen das Anlagendesign, die Bedienbarkeit und die Arbeitsumgebung an die menschlichen Fähigkeiten angepasst werden. Human Factors (HF) betrachtet die Interaktion zwischen menschlichen, technischen und organisatorischen Aspekten einer Anlage, mit dem Ziel die Sicherheit und Effektivität der Anlage zu optimieren. Dafür ist eine Einbindung von HF in den gesamten Lebenszyklus einer Anlage notwendig. So müssen HF- Analysen nicht nur während des Betriebs einer Anlage und bei Prozessmodifikationen durchgeführt werden, sondern auch während des gesamten Design- Prozesses, da gerade in den frühen Design-Phasen das Optimierungspotential besonders hoch ist. Eine solche Analysemethode muss alle Aufgaben eines Operators erfassen, so dass zwischen manueller Arbeit und der Arbeit in der Leitwarte unterschieden werden muss. In dieser Arbeit wurden Analysentechniken entwickelt, die einen systematischen Ansatz zur Berücksichtigung des HF über den gesamten Lebenszyklus einer verfahrenstechnischen Anlage darstellen. Mit Hilfe der neuen Analysemethode, PITOPA-Design, können Untersuchungen sowohl während der Designphase als auch während des Betriebs einer Anlage durchgeführt werden. Da solche HF-Analyse immer in Verbindung mit einer klassischen Sicherheitsanalyse erfolgen muss, bindet die neue Methode die HAZOP-Analyse direkt ein. Darüber hinaus wurde ein weiterer Ansatz für die Analyse von Operatorhandlungen in einer Messwartenarbeit entwickelt. Diese neue Analysentechnik, PITOPA-CR, bildet die Grundlage für Verbesserungen im Alarmsystem und wird in das Alarmmanagementsystem eingebunden. Die Arbeit ist wie folgt strukturiert: i) Entwicklung von HAZOPA (the Hazards and Operator Actions Analysis). Diese Methode stellt die Einbindung der HF-Analyse in HAZOP dar. ii) Entwicklung von PITOPA-Design, zur HF-Analyse während des gesamten Designprozesses einer verfahrenstechnischen Anlage. Die Methode wurde in 3 Teile eingeteilt, um die drei Designsphasen Conceptual-, Basic-, und Detail-Design zu erfassen. iii) Entwicklung von PITOPA-CR, zur HF-Analyse in der Messwarte. iv) Einbindung von PITOPA-CR in das Alarmmanagementsystem und Entwicklung einer Technik zur Alarmpriorisierung

Riskbedömningar är ett betydande inslag för att arbeta förebyggande mot återfall i partnervåld. Denna studie syftade till att undersöka interbedömarreliabiliteten bland socialarbetares riskbedömningar för partnervåld gällande identifiering av risk-, sårbarhets- och skyddsfaktorer samt ärendeprioritering. Undersökningen genomfördes genom att sex socialarbetare, både individuellt och gemensamt, fick bedöma risk- sårbarhet- och skyddsfaktorer samt prioritering av ärendet i sex fiktiva fall. Resultaten påvisade att interbedömarreliabiliteten vid jämförelse av enskilda bedömare varierade beroende på vilken faktor som skulle identifieras samt vilken prioritering som skulle tillskrivas ärendet. Det samma gällde de gemensamma bedömningarna. Riskfaktorer påvisades inneha högst interbedömarreliabilitet och sårbarhetsfaktorer inneha lägst interbedömarreliabilitet. utslaget på samtliga fall. Det gällde även vid jämförelse av gemensam bedömning. Ärendeprioritering påvisade varierande interbedömarreliabilitet med måttlig samstämmighet mellan enskilda bedömare och något lägre samstämmighet i jämförelse med en gemensam bedömning, utslaget på samtliga fall. Vidare forskning rekommenderas i syfte att bistå i utvecklandet och användandet av manualer i bedömningar gällande partnervåld och förstå behovet av stöd till dess användare.
Risk assessments are an important element in preventing recidivism for intimate partner violence. This study aimed to investigate the inter-rater reliability of social workers' risk assessments for partner violence regarding the identification of risk, vulnerability and protective factors as well as case prioritization. The study was conducted by giving six social workers, both individually and jointly, the opportunity to assess risk-, vulnerability- and protective factors as well as prioritization of safety measures for six fictitious cases. The results showed that inter-rater reliability varied when comparing individual assessors depending on the factor that was to be identified and the priority to be attributed to the case. The same was true of the joint assessments. Risk factors were shown to have the highest inter-rater reliability and vulnerability factors to have the lowest inter-rater reliability averaged across all cases. The same was true when comparing joint assessments. Case prioritization showed varying inter-rater reliability with moderate agreement between individual assessors and somewhat lower agreement compared to a joint assessment, averaged across all cases. Further research is recommended in order to assist in the development and use of manuals in assessments of partner violence and in order to understand the need for support to its users.

Industrie-4.0 bringt eine wachsende Nachfrage an Netzwerkprotokollen mit sich, die es erlauben, Informationen vom Produktionsprozess einzelner Maschinen zu erfassen und verfügbar zu machen. Drahtlose Übertragung erfüllt hierbei die für industrielle Anwendungen benötigte Flexibilität, kann in herausfordernden Industrieumgebungen aber nicht immer zeitnahe und zuverlässige Übertragung gewährleisten. Die Beiträge dieser Arbeit behandeln schwerpunktmäßig Protokollentwurf und Protokollevaluation für industrielle Anwendungsfälle. Zunächst identifizieren wir Anforderungen für den industriellen Anwendungsfall und leiten daraus konkrete Entwufskriterien ab, die Protokolle erfüllen sollten. Anschließend schlagen wir Protokollmechanismen vor, die jene Entwurfskriterien für unterschiedliche Arten von Protokollen umsetzen, und die in verschiedenem Maße kompatibel zu existierenden Netzwerken und existierender Hardware sind: Wir zeigen, wie anwendungsfallspezifische Priorisierung von Netzwerkdaten dabei hilft, zuverlässige Übertragung auch unter starken Störeinflüssen zu gewährleisten, indem zunächst eine akkurate Vorschau von Prozessinformationen übertragen wird. Für deren Fehler leiten wir präziser Schranken her. Ferner zeigen wir, dass die Fairness zwischen einzelnen Maschinen durch Veränderung von Warteschlangen verbessert werden kann, wobei hier ein Teil der Algorithmen von Knoten innerhalb des Netzwerks durchgeführt wird. Ferner zeigen wir, wie Network-Coding zu unserem Anwendungsfall beitragen kann, indem wir spezialisierte Kodierungs- und Dekodierungsverfahren einführen. Zuletzt stellen wir eine neuartige Softwarearchitektur und Evaluationstechnik vor, die es erlaubt, potentiell proprietäre Protokollimplementierungen innerhalb moderner diskreter Ereignissimulatoren zu verwenden. Wir zeigen, dass unser vorgeschlagener Ansatz ausreichend performant für praktische Anwendungen ist und, darüber hinaus, die Validität von Evaluationsergebnissen gegenüber existierenden Ansätzen verbessert.
As smart factory trends gain momentum, there is a growing need for robust information transmission protocols that make available sensor information gathered by individual machines. Wireless transmission provides the required flexibility for industry adoption but poses challenges for timely and reliable information delivery in challenging industrial environments. This work focuses on to protocol design and evaluation aspects for industrial applications. We first introduce the industrial use case, identify requirements and derive concrete design principles that protocols should implement. We then propose mechanisms that implement these principles for different types of protocols, which retain compatibility with existing networks and hardware to varying degrees: we show that use-case tailored prioritization at the source is a powerful tool to implement robustness against challenged connectivity by conveying an accurate preview of information from the production process. We also derive precise bounds for the quality of that preview. Moving parts of the computational work into the network, we show that reordering queues in accordance with our prioritization scheme improves fairness among machines. We also demonstrate that network coding can benefit our use case by introducing specialized encoding and decoding mechanisms. Last, we propose a novel architecture and evaluation techniques that allows incorporating possibly proprietary networking protocol implementations with modern discrete event network simulators, rendering, among others, the adaption of protocols to specific industrial use cases more cost efficient. We demonstrate that our approach provides sufficient performance and improves the validity of evaluation results over the state of the art.

Network screening and countermeasure selection are two crucial steps in the highway improvement process. In network screening, potential improvement locations are ranked and prioritized based on a specific method with a set of criteria. The most common practice by transportation agencies has been to use a simple scoring method, which, in general, weighs and scores each criterion and then ranks the locations based on their relative overall scoring. The method does not deal well with criteria that are qualitative in nature, nor does it account for the impacts of correlation among the criteria. The introduction of Analytic Hierarchy Process (AHP) provides agencies with a method to include both quantitative and qualitative criteria. However, it does not address the issue on correlation. This dissertation explores the use of both Analytic Network Process (ANP) and Fuzzy Analytic Network Process (FANP) for their potential capabilities to address both issues. Using urban four-lane divided highways in Florida for bicycle safety improvements, both ANP and FANP were shown to provide more reasonable rankings than AHP, with FANP providing the best results among the methods. After the locations are ranked and prioritized for improvements, the next step is to evaluate the potential countermeasures for improvements at the selected top-ranked locations. In this step, the standard practice has been to use Crash Modification Factors (CMFs) to quantify the potential impacts from implementing specific countermeasures. In this research, CMFs for bicycle crashes on urban facilities in Florida were developed using the Generalized Linear Model approach with a Zero-Inflated Negative Binomial (ZINB) distribution. The CMFs were tested for their spatial and temporal transferability and the results show only limited transferability both spatially and temporally. The CMFs show that, in general, wider lanes, lower speed limits, and presence of vegetation in the median reduce bicycle crashes, while presence of sidewalk and sidewalk barrier increase bicycle crashes. The research further considered bicycle exposure using the bicycle activity data from the Strava smartphone application. It was found that increased bicycle activity reduces bicycle crash probabilities on segments but increases bicycle crash probabilities at signalized intersections. Also, presence of bus stops and use of permissive signal phasing at intersections were found to increase bicycle crash probabilities.

Cockpit Task Management (CTM) is the initiation, monitoring, prioritization, execution, and termination of multiple, concurrent tasks by night crews. The primary research question posed in the current research is what factors affect task prioritization on the modern day, commercial flight deck. The conventional CTM literature was reviewed as an introduction to CTM validation, its facilitation and its theoretical foundations. A human performance approach to CTM was explored through experimental psychology literature, with the objective of developing a deeper understanding of the prioritization process. Two experimental part-task simulator studies were performed using commercial airline pilots. The objective of the first study was to simply identify possible prioritization factors. The second study then gathered empirical evidence for actual use of these factors. From the results, a model of task prioritization emerged with Status, Procedure and Value as the primary factors that affect task prioritization.
Graduation date: 2000

Task Management (TM) refers to the function in which the human operator manages his/her available sensory and mental resources in a dynamic, complex, safety-critical environment in order to accomplish the multiple tasks competing for a limited quantity of attention. There is reason to believe that the level of automation on the commercial aircraft flight deck may effect TM, however to date there has been little research that directly addresses this effect. Thus, the primary objective of this study was to begin evaluating the relationship between TM of commercial airline pilots and the level of automation on the flight deck by determining how automation affects the frequency of Task Prioritization errors as reported in Aviation Safety Reporting System (ASRS) incident reports. The secondary objective of this study was to create a methodology that modeled an effective way to use ASRS incident report data in an inferential analysis. Two samples of ASRS incident reports were compared. The first sample was composed of 210 incident reports submitted by pilots flying advanced technology aircraft and the second sample was composed of 210 incident reports submitted by pilots flying traditional technology aircraft. To help avoid confounding effects, the two samples were further divided into three sub-samples each made up of 70 reports submitted during a specified time period: 1988-1989, 1990-1991, and 1992-1993. Each incident report was analyzed using an incident analysis form designed specifically for this study. This form allowed the analyst to classify the incident report as either containing a Task Prioritization error or not based on the narrative of the report. Twenty-eight incident reports from the advanced technology sample and 15 from the traditional technology sample were classified as containing Task Prioritization errors. Using the Chi Square (x��) test and a significance level of 0.05, this difference was found to be statistically significant.
Graduation date: 1998

abstract: Genes have widely different pertinences to the etiology and pathology of diseases. Thus, they can be ranked according to their disease-significance on a genomic scale, which is the subject of gene prioritization. Given a set of genes known to be related to a disease, it is reasonable to use them as a basis to determine the significance of other candidate genes, which will then be ranked based on the association they exhibit with respect to the given set of known genes. Experimental and computational data of various kinds have different reliability and relevance to a disease under study. This work presents a gene prioritization method based on integrated biological networks that incorporates and models the various levels of relevance and reliability of diverse sources. The method is shown to achieve significantly higher performance as compared to two well-known gene prioritization algorithms. Essentially, no bias in the performance was seen as it was applied to diseases of diverse ethnology, e.g., monogenic, polygenic and cancer. The method was highly stable and robust against significant levels of noise in the data. Biological networks are often sparse, which can impede the operation of associationbased gene prioritization algorithms such as the one presented here from a computational perspective. As a potential approach to overcome this limitation, we explore the value that transcription factor binding sites can have in elucidating suitable targets. Transcription factors are needed for the expression of most genes, especially in higher organisms and hence genes can be associated via their genetic regulatory properties. While each transcription factor recognizes specific DNA sequence patterns, such patterns are mostly unknown for many transcription factors. Even those that are known are inconsistently reported in the literature, implying a potentially high level of inaccuracy. We developed computational methods for prediction and improvement of transcription factor binding patterns. Tests performed on the improvement method by employing synthetic patterns under various conditions showed that the method is very robust and the patterns produced invariably converge to nearly identical series of patterns. Preliminary tests were conducted to incorporate knowledge from transcription factor binding sites into our networkbased model for prioritization, with encouraging results. Genes have widely different pertinences to the etiology and pathology of diseases. Thus, they can be ranked according to their disease-significance on a genomic scale, which is the subject of gene prioritization. Given a set of genes known to be related to a disease, it is reasonable to use them as a basis to determine the significance of other candidate genes, which will then be ranked based on the association they exhibit with respect to the given set of known genes. Experimental and computational data of various kinds have different reliability and relevance to a disease under study. This work presents a gene prioritization method based on integrated biological networks that incorporates and models the various levels of relevance and reliability of diverse sources. The method is shown to achieve significantly higher performance as compared to two well-known gene prioritization algorithms. Essentially, no bias in the performance was seen as it was applied to diseases of diverse ethnology, e.g., monogenic, polygenic and cancer. The method was highly stable and robust against significant levels of noise in the data. Biological networks are often sparse, which can impede the operation of associationbased gene prioritization algorithms such as the one presented here from a computational perspective. As a potential approach to overcome this limitation, we explore the value that transcription factor binding sites can have in elucidating suitable targets. Transcription factors are needed for the expression of most genes, especially in higher organisms and hence genes can be associated via their genetic regulatory properties. While each transcription factor recognizes specific DNA sequence patterns, such patterns are mostly unknown for many transcription factors. Even those that are known are inconsistently reported in the literature, implying a potentially high level of inaccuracy. We developed computational methods for prediction and improvement of transcription factor binding patterns. Tests performed on the improvement method by employing synthetic patterns under various conditions showed that the method is very robust and the patterns produced invariably converge to nearly identical series of patterns. Preliminary tests were conducted to incorporate knowledge from transcription factor binding sites into our networkbased model for prioritization, with encouraging results. To validate these approaches in a disease-specific context, we built a schizophreniaspecific network based on the inferred associations and performed a comprehensive prioritization of human genes with respect to the disease. These results are expected to be validated empirically, but computational validation using known targets are very positive.
Dissertation/Thesis
Ph.D. Computer Science 2011

La maladie de Lyme est la maladie vectorielle la plus fréquente dans les pays tempérés et est en émergence dans plusieurs régions du monde. Plusieurs stratégies de prévention existent et comprennent des interventions qui visent les individus, comme le port de vêtements protecteurs, et d’autres qui sont implantées au niveau collectif, dont des interventions de contrôle des tiques dans l’environnement. L’efficacité de ces stratégies peut être influencée par divers facteurs, dont des facteurs sociaux tels que les connaissances, les perceptions et les comportements de la population ciblée. Elles peuvent également avoir des impacts parallèles non désirés, par exemple sur l’environnement et l’économie, et ces derniers peuvent s’opposer aux bénéfices des interventions jusqu’à remettre en cause la pertinence de leur mise en œuvre. Aussi, ces facteurs sociaux et les impacts des interventions sont susceptibles de varier selon la population ciblée et en fonction du contexte épidémiologique et social. L’objectif de cette thèse était donc d’étudier les principaux facteurs sociaux et enjeux d’importance à considérer pour évaluer l’efficacité et prioriser des interventions de prévention pour la maladie de Lyme dans deux populations exposées à des contextes différents, notamment en ce qui concerne leur situation épidémiologique, soient au Québec, où l’incidence de la maladie de Lyme est faible mais en émergence, et en Suisse, où elle est élevée et endémique depuis plus de trois décennies. L’approche choisie et le devis général de l’étude sont basés sur deux modèles théoriques principaux, soient le modèle des croyances relatives à la santé et celui de l’aide à la décision multicritère. Dans un premier temps, les facteurs associés à la perception du risque pour la maladie de Lyme, c’est-à-dire l’évaluation cognitive d’une personne face au risque auquel elle fait face, ont été étudiés. Les résultats suggèrent que les facteurs significatifs sont différents dans les deux régions à l’étude. Ensuite, l’impact des connaissances, de l’exposition, et des perceptions sur l’adoption de comportements préventifs individuels et sur l’acceptabilité des interventions de contrôle des tiques (acaricides, modifications de l’habitat, contrôle des cervidés) a été comparé. Les résultats suggèrent que l’impact des facteurs varierait en fonction du type du comportement et des interventions, mais que la perception de l’efficacité est un facteur commun fortement associé à ces deux aspects, et pourrait être un facteur-clé à cibler lors de campagnes de communication. Les résultats montrent également que les enjeux relatifs aux interventions de contrôle des tiques tels que perçus par la population générale seraient communs dans les deux contextes de l’étude, et partagés par les intervenants impliqués dans la prévention de la maladie de Lyme. Finalement, un modèle d’analyse multicritère a été développé à l’aide d’une approche participative pour le contexte du Québec puis adapté pour le contexte suisse et a permis d’évaluer et de prioriser les interventions préventives selon les différentes perspectives des intervenants. Les rangements produits par les modèles au Québec et en Suisse ont priorisé les interventions qui ciblent principalement les populations humaines, devant les interventions de contrôle des tiques. L’application de l’aide à la décision multicritère dans le contexte de la prévention de la maladie de Lyme a permis de développer un modèle décisionnel polyvalent et adaptable à différents contextes, dont la situation épidémiologique. Ces travaux démontrent que cette approche peut intégrer de façon rigoureuse et transparente les multiples perspectives des intervenants et les enjeux de la prévention relatifs à la santé publique, à la santé animale et environnementale, aux impacts sociaux, ainsi qu’aux considérations économiques, opérationnelles et stratégiques. L’utilisation de ces modèles en santé publique favoriserait l’adoption d’une approche « Une seule santé » pour la prévention de la maladie de Lyme et des zoonoses en général. Mots-clés : maladie de Lyme, prévention, facteurs sociaux, perception du risque, comportements préventifs, acceptabilité, priorisation des interventions, contrôle des tiques, aide à la décision multicritère, analyse multicritère, Québec, Suisse, « Une seule santé »
Lyme disease is the most common vector-borne disease in temperate countries and is emerging in many parts of the world. Several prevention strategies exist and include strategies at the individual level, such as wearing protective clothing, and at the population level, including tick control interventions in the environment. The effectiveness of these strategies can be influenced by various factors, including social factors such as knowledge, perceptions and behaviors of the target population, and by their potential impacts on various sectors such as on the environment and on the economy. Also, these social factors and impacts are likely to vary according to the epidemiological and social context of the target population. The objective of this thesis was to study the main social factors and issues of importance to consider for the prioritization of preventive interventions for Lyme disease in two populations living in different contexts, particularly with regard to their epidemiological situation, that is in Quebec, where the incidence of Lyme disease is low, but emerging, and Switzerland, where it is high and has been endemic for more than three decades. The approach and the design of this study were based on two main theoretical models, namely the Health Belief Model and the multicriteria decision analysis approach. Factors associated with risk perception, that is the cognitive assessment of a person facing a risk, for Lyme disease were studied initially in the target populations. The results suggest that factors significantly associated with a high level of risk perception are different in the two regions. Then, the impact of knowledge on Lyme disease, exposure, perceptions on the adoption of individual preventive behavior and on the acceptability of tick control interventions were compared. The data suggest that the impact of these factors varies according to the type of behavior and interventions, but that the perception of efficacy is a common factor strongly associated with both aspects, and could be targeted in communication campaigns. The results also show that issues related to tick control interventions as perceived by the participants are common in both contexts, and shared by the stakeholders involved in the prevention of Lyme disease. Finally, a multi-criteria analysis model was developed using a participatory approach for the Quebec context, adapted to the Swiss context and allowed to prioritize preventive interventions according to different stakeholder perspectives. Rankings produced by these models prioritized interventions that primarily target human populations in preference to tick control interventions. Applying the multi-criteria decision analysis approach in the context of Lyme disease prevention led to the development of a versatile decision model that can be adapted to different contexts, including the epidemiological situation. These studies show that this approach can offer a rigorous and transparent way to integrate the multiple perspectives of stakeholders and issues of prevention including those relating to public health, animal and environmental health, social impacts, as well as economic, operational and strategic considerations. Their use in public health practices could facilitate the adoption of a practical and applied “One health” approach to Lyme disease and other zoonosis prevention. Keywords: Lyme disease, prevention, social factors, risk perception, acceptability, prioritization of interventions, tick control, Multi-criteria decision analysis, MCDA, Quebec, Switzerland, "One health"

Research in risk awareness has been relatively neglected in the health informatics literature, which tends largely to examine project managers’ perspectives of risk awareness; very few studies explicitly address the perspectives held by senior executives such as directors. Another limitation evident in the current risk literature is that studies are often based on American data and/or they are restricted to American culture. Both factors highlight the need to examine how senior executives (i.e., directors) who oversee or direct eHealth projects in Canada perceive risk awareness. This research explores and discusses the perspectives of risk awareness (i.e., identification, analysis, and prioritization) held by directors and project managers who implement Canadian eHealth projects. Semi-structured interviews with nine directors and project managers uncovered six key distinctions in these two groups’ awareness of risk. First, all project managers valued transparency over anonymity, whereas directors believed that an anonymous reporting system for communicating risks had merit. Secondly, most directors emphasized the importance of evidence-based planning and decision making when balancing risks and opportunities, an aspect none of the project managers voiced. Thirdly, while project managers noted that the level of risk tolerance may evolve from being risk-averse to risk-neutral, directors believed that risk tolerance evolved toward risk-seeking. Directors also noted the importance of employing risk officers, a view that was not shared by project managers. Directors also believed the risk of too little end-user engagement and change management was the most important risk, whereas project managers ranked it as the least important. Finally, when directors and project managers were asked to identify and define the root cause(s) of eHealth risks, directors identified the complexity of health care industry, while project managers attributed it to political pressure and a lack of resources where eHealth projects are concerned. This research proposes that the varied perspectives of risk awareness held by directors and project managers must be considered and integrated to properly align expectations and build partnerships for successful eHealth project outcomes. Understanding risk awareness offers a means to systematically identify and analyze the complex nature of eHealth projects by embracing uncertainties, thereby enabling forward thinking (i.e., staying one step ahead of risks) and the ability to prevent avoidable risks and seize opportunities.
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