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Integrating indigenous and scientific knowledge in community-based early warning system development for climate-related malaria risk reduction in Mopani District of South AfricaRamutsa, Brenda Nyeverwai January 2020 (has links)
PhD (Geography) / Department of Geography and Geo-Information Sciences / Malaria is a climate-change concatenated biological hazard that may, like any other natural hazard, can lead to a disaster if there is a failure in handling emergencies or risks. A holistic solution for malaria mitigation can be provided when indigenous knowledge is complemented with scientific knowledge. Malaria remains a challenge in South Africa and Limpopo province is the highest burdened malaria-endemic region. Specifically, Vhembe District is the highest burdened followed by Mopani District (Raman et al., 2016). This research sought to mitigate malaria transmissions in Mopani District through the integration of indigenous and scientific knowledge. The study was carried out in Mopani District of South Africa and 4 municipalities were involved. These are Ba-Phalaborwa, Greater Tzaneen, Greater Letaba, and Maruleng. A pragmatism philosophy was adopted hence the study took a mixed approach (sequential multiphase design). Data was collected from 381 selected participants through in-depth interviews, a survey and a focus group discussion. Participants for the in-depth interviews were obtained through snowballing and selected randomly for the survey, while for the focus group discussion purposive sampling was used. The study applied constructivist grounded theory to analyze qualitative data and to generate theory. Statistical Package for Social Sciences version 23.0 was used for quantitative data. Based on empirical findings, it was concluded that temperature and rainfall among other various factors exacerbate malaria transmission in the study area. Results of the study also show that people in Mopani District predict the malaria season onset by forecasting rainfall using various indigenous knowledge based indicators. The rainfall indicators mentioned by participants in the study were used in the developed early warning system. An Early warning system is an essential tool that builds the capacities of communities so that they can reduce their vulnerability to hazards or disasters. In the design of the system, Apache Cordova, JDK 1.8, Node JS, and XAMPP software were used. The study recommends malaria management and control key stakeholders to adopt the developed early warning system as a further mitigation strategy to the problem of malaria transmission in Mopani District. / NRF
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Adaptive Eyes: Driver Distraction and Inattention PreventionThrough Advanced Driver Assistance Systems and Behaviour-Based SafetyWege, Claudia 30 January 2014 (has links)
Technology pervades our daily living, and is increasingly integrated into the vehicle – directly affecting driving. On the one hand technology such as cell phones provoke driver distraction and inattention, whereas, on the other hand, Advanced Driver Assistance Systems (ADAS) support the driver in the driving task. The question is, can a driver successfully adapt to the ever growing technological advancements?
Thus, this thesis aimed at improving safe driver behaviour by understanding the underlying psychological mechanisms that influence behavioural change. Previous research on ADAS and human attention was reviewed in the context of driver behavioural adaptation. Empirical data from multiple data sources such as driving performance data, visual behaviour data, video footage, and subjective data were analyzed to evaluate two ADAS (a brake-capacity forward collision warning system, B-FCW, and a Visual Distraction Alert System, VDA-System).
Results from a field operational test (EuroFOT) showed that brake-capacity forward collision warnings lead to immediate attention allocation toward the roadway and drivers hit the brake, yet change their initial response later on by directing their eyes toward the warning source in the instrument cluster. A similar phenomenon of drivers changing initial behaviour was found in a driving simulator study assessing a Visual Distraction Alert System. Analysis showed that a Visual Distraction Alert System successfully assists drivers in redirecting attention to the relevant aspects of the driving task and significantly improves driving performance. The effects are discussed with regard to behavioural adaptation, calibration and system acceptance. Based on these findings a novel assessment for human-machine-interaction (HMI) of ADAS was introduced.
Based on the contribution of this thesis and previous best-practices, a holistic safety management model on accident prevention strategies (before, during and after driving) was developed. The DO-IT BEST Feedback Model is a comprehensive feedback strategy including driver feedback at various time scales and therefore is expected to provide an added benefit for distraction and inattention prevention. The central contributions of this work are to advance research in the field of traffic psychology in the context of attention allocation strategies, and to improve the ability to design future safety systems with the human factor in focus. The thesis consists of the introduction of the conducted research, six publications in full text and a comprehensive conclusion of the publications.
In brief this thesis intends to improve safe driver behaviour by understanding the underlying psychological mechanisms that influence behavioral change, thereby resulting in more attention allocation to the forward roadway, and improved vehicle control.:Abstract i
Zusammenfassung iii
List of included publications v
Acknowledgements vii
Previously published work ix
Table of contents xi
Preface xii
1 Chapter 1 Introduction 1
1.1 Outline 1
1.2 Objectives 2
1.3 Background 8
1.3.1 Behavioural adaption to ADAS 8
1.3.2 Driver distraction and inattention 9
2 Chapter 2 Paper I 23
3 Chapter 3 Paper II 47
4 Chapter 4 Paper III 61
5 Chapter 5 Paper IV 91
6 Chapter 6 Paper V 117
7 Chapter 7 Paper VI 143
8 Chapter 8 Conclusions and discussion 161
8.1. Contributions 161
8.2. Implications 171
8.3. Limitations and research needs 173
9 References 177
Curriculum Vitae 199
Eidesstattliche Erklärung 201 / Technologie durchdringt unser tägliches Leben und ist zunehmend integriert in Fahrzeuge – das Resultat sind veränderte Anforderungen an Fahrzeugführer. Einerseits besteht die Gefahr, dass er durch die Bedienung innovativer Technologien (z.B. Mobiltelefone) unachtsam wird und visuell abgelenkt ist, andererseits kann die Nutzung von Fahrerassistenzsystemen die den Fahrer bei der Fahraufgabe unterstützten einen wertvollen Beitrag zur Fahrsicherheit bieten. Die steigende Aktualität beider Problematiken wirft die Frage auf: "Kann der Fahrer sich erfolgreich dem ständig wachsenden technologischen Fortschritt anpassen?"
Das Ziel der vorliegenden Arbeit ist der Erkenntnisgewinn zur Verbesserung des Fahrverhaltens indem der Verhaltensänderungen zugrunde liegende psychologische Mechanismen untersucht werden. Eine Vielzahl an Literatur zu Fahrerassistenzsystemen und Aufmerksamkeitsverteilung wurde vor dem Hintergrund von Verhaltensanpassung der Fahrer recherchiert. Daten mehrerer empirischer Quellen, z. B. Fahrverhalten, Blickbewegungen, Videomitschnitte und subjektive Daten dienten zur Datenauswertung zweier Fahrerassistenzsysteme.
Im Rahmen einer Feldstudie zeigte sich, dass Bremskapazitäts-Kollisionswarnungen zur sofortigen visuellen Aufmerksamkeitsverteilung zur Fahrbahn und zum Bremsen führen, Fahrer allerdings ihre Reaktion anpassen indem sie zur Warnanzeige im Kombinationsinstrument schauen. Ein anderes Phänomen der Verhaltensanpassung wurde in einer Fahrsimulatorstudie zur Untersuchung eines Ablenkungswarnsystems, das dabei hilft die Blicke von Autofahrern stets auf die Straße zu lenken, gefunden. Diese Ergebnisse weisen nach, dass solch ein System unterstützt achtsamer zu sein und sicherer zu fahren.
Die vorliegenden Befunde wurden im Zusammenhang zu Vorbefunden zur Verhaltensanpassung zu Fahrerassistenzsystemen, Fahrerkalibrierung und Akzeptanz von Technik diskutiert. Basierend auf den gewonnenen Erkenntnissen wurde ein neues Vorgehen zur Untersuchung von Mensch- Maschine-Interaktion eingeführt. Aufbauend auf den Resultaten der vorliegenden Arbeit wurde ein ganzheitliches Modell zur Fahrsicherheit und -management, das DO-IT BEST Feedback Modell, entwickelt. Das Modell bezieht sich auf multitemporale Fahrer-Feedbackstrategien und soll somit einen entscheidenen Beitrag zur Verkehrssicherheit und dem Umgang mit Fahrerunaufmerksamkeit leisten. Die zentralen Beiträge dieser Arbeit sind die Gewinnung neuer Erkenntnisse in den Bereichen der Angewandten Psychologie und der Verkehrspsychologie in den Kontexten der Aufmerksamkeitsverteilung und der Verbesserung der Gestaltung von Fahrerassistenzsystemen fokusierend auf den Bediener. Die Dissertation besteht aus einem Einleitungsteil, drei empirischen Beiträgen sowie drei Buchkapiteln und einer abschliessenden Zusammenfassung.:Abstract i
Zusammenfassung iii
List of included publications v
Acknowledgements vii
Previously published work ix
Table of contents xi
Preface xii
1 Chapter 1 Introduction 1
1.1 Outline 1
1.2 Objectives 2
1.3 Background 8
1.3.1 Behavioural adaption to ADAS 8
1.3.2 Driver distraction and inattention 9
2 Chapter 2 Paper I 23
3 Chapter 3 Paper II 47
4 Chapter 4 Paper III 61
5 Chapter 5 Paper IV 91
6 Chapter 6 Paper V 117
7 Chapter 7 Paper VI 143
8 Chapter 8 Conclusions and discussion 161
8.1. Contributions 161
8.2. Implications 171
8.3. Limitations and research needs 173
9 References 177
Curriculum Vitae 199
Eidesstattliche Erklärung 201
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Empirical Data Based Predictive Warning System on an Automated Guided Vehicle / Empiriskt databaserat predikterande varningsystem för självkörande truckarBlåberg, Anton, Lindahl, Gustav January 2022 (has links)
An Automated Guided Vehicle (AGV) must follow protective regulations to avoidcrashing into people when autonomously driving in industries. These safety norms require AGVs to enable protective fields, which perform hard braking when objects enter aspecific area in front of the vehicle. Warning fields, or warning systems, are similar fieldsthat decrease the speed of the AGV before objects enter the protective fields to enable asteadier driving. Today at Toyota Material Handling Manufacturing Sweden (TMHMS),warning systems have been implemented but the systems are too sensitive to objects outside of the AGVs path.The purpose of this thesis is to develop a predictive warning system based on empiricaldata from previous driving scenarios. By storing previous positions, the warning systemcould estimate a trajectory based on simple statistics and deploy speed limiting decisionsif objects appear in the upcoming predicted path.The predictive warning system was compared to the current warning system and adeactivated warning system setup in driving performance and driving dynamics. Performance was measured by measuring time to finish an industry-like test track and dynamicswas subjectively rated from a group of experienced AGV developers from TMHMS. Results showed that a predictive warning system drove the test track faster and with betterdynamics than the current warning system and the no warning system setup.Key findings are that a predictive warning system based on empirical data performedbetter in most cases but has some extra requirements to function. Firstly, the method require the AGV to mostly drive on previously driven paths to produce good results. Secondly the warning system requires a somewhat powerful on board computer to handlethe computations. Finally, the warning system requires spatial awareness of pose for thevehicle, as well as structure and shape for deployed protective fields.
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Epidemiology and management of Phomopsis cane and leaf spot of grapeNita, Mizuho 12 September 2005 (has links)
No description available.
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金融預警、合併監理與分級管理制度之研究 / A Study on Early Warning System, Unified Financial Supervision, and Classified Regulatory Principle.鄭璟紘, Cheng, Ching Hung Unknown Date (has links)
本研究分析我國49家本國銀行、55家信用合作社、287家農會信用部及27家漁會信用部等四類金融機構之經營現況,並參照各國金融預警制度運作方式,選取適合的財務比率,運用SAS統計軟體及Z-score、Logistic等模型,分別找出造成各類金融機構經營失敗之顯著相關財務比率,評估各類金融機構之經營效率、失敗機率與模型之正確區別率,以建立預測金融機構失敗機率之預警模型。研究之樣本資料分別為:本國銀行49家、2001年第2季~2003年底共計11季25項財務比率,信用合作社55家、1998年底~2003年底共計21季26項財務比率,農會信用部287家1998年底~2003年底共計21季25項財務比率,漁會信用部27家1998年底~2003年底共計21季25項財務比率。
本研究之結論為:
一、彙整Z-Score模型對各類金融機構具有顯著性之財務變數,本國銀行有6項、信用合作社有7項、農會信用部有6項,漁會信用部有4項。
二、彙整Logistic模型對各類金融機構具有顯著性之財務變數,本國銀行、信用合作社各有6項,農會信用部有5項,漁會信用部有4項。
三、金融預警模型中,Logistic模型較Z-Score模型有較高的正確區別率。 / This research analyzes 49 domestic banks, 55 credit cooperative unions, 287 credit department of farmer associations and 27 credit department of fisherman associations above four kind of financial institution´s management situation, and refers the operation ways of various countries financial early warning system, selects suitable financial ratios , utilizes SAS statistics software and Z-score, Logistic models, it identifies the root cause of bankruptcy thus reveals finance of ratio the correlation, appraises management efficiency, the defeat probability each kind of financial institution if the correct difference rate. It appraises each kind of financial institution´s management efficiency, defeats probability and correct difference rate. It establishes early warning model that forecasts financial institutions failure rate. The research model and period: used 49 domestic banks from 2001 in 2nd season to the end of 2003 total 11 seasons and 25 items of finance ratio、55 credit cooperative associations from the end of 1998 to the end of 2003 total 21 seasons and 26 items of finance ratio、287 credit department of farmer associations and 27 credit department of fisherman associations from the end of 1998 to the end of 2003 total 21 seasons which used respectively 25 items of finance ratio.
The conclusion of this research are:
Firstly, it collects the entire Z-Score model to have significant financial indicator to each kind of financial institution, the domestic banks have 6 items, the credit cooperative associations have 7 items, the credit department of farmer associations have 6 items, and the credit department of fisherman associations have 4 items.
Secondly, it collects the entire Logistic model to have significant financial indicator to each kind of financial institution, the domestic banks and the credit cooperative associations have 6 items respectively, the credit department of farmer associations have 5 items, and the credit department of fisherman associations have 4 items.
Thirdly, in the financial early warning model, when comparing Z-Score with Logistic model , the latter appears to have a higher correct difference rate.
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