Laser assisted weapons, such as laser guided bombs, laser guided missiles and laser beam-riding missiles pose a significant threat to military assets in the modern battlefield. Laser beam-riding missiles are particularly hard to detect because they use low power lasers. Most laser warning systems produced so far can not detect laser beam-riding missiles because of their weak emissions which have signals less than 1% of laser range finder power . They are even harder to defeat because current counter-measures are not designed to work against this threat. The aim of this project is to examine the vulnerability of laser warning systems against guided weapons, to build an evaluation tool for laser warning sensors (LWS) and seekers, and try to find suitable counter-measures for laser beam-riding missiles that use low power lasers in their guidance systems. The project comes about because of the unexpected results obtained from extensive field trials carried out on various LWRs in the United Arab Emirates desert, where severe weather conditions may be experienced. The objective was to help find a solution for these systems to do their job in protecting the tanks and armoured vehicles crews from such a threat. In order to approach the subject, a computer model has been developed to enable the assessment of all phases of a laser warning receiver and missile seeker. MATLAB & SIMULINK software have been used to build the model. During this process experimentation and field trials have been carried out to verify the reliability of the model. This project will enable both the evaluation and design of any generic laser warning receiver or missile seeker and specific systems if various parameters are known. Moreover, this model will be used as a guide to the development of reliable countermeasures for laser beam-riding missiles.

This paper aims to find macroeconomic and financial variables with ability to predict financial crises. A dataset covering 17 developed countries over the period 1870-2013 have been investigated using a logit model. We found commonly used macroeconomic variables such as terms of trade and consumption to be strong predictors within our sample. Whereas private debt and house prices are frequently found to be strong predictors, we found loans to business to be at least as good in predicting financial crises. Multivariate models are constructed as warning systems and used to analyze Sweden from 1975 up until 2016. The most efficient warning system give a strong signal before the first and moderate signal before the second crisis. In extension, regarding today’s climate the warning system provides no signal, suggesting low current risk. Policy makers can benefit from observing certain variables that are found significant in this study to improve financial stability and reduce socio-economic costs.

In the course of past decades, the African Union has sought to strengthen continental security integration and joint governance, wherefore many early warning and security institutions emerged. However, little research has been done to explore the institutional landscape. This thesis aims to bridge the literacy gaps and investigate the ways African early warning institutions constitute challenges or prospects to security integration efforts. The continental level evaluates how integration is affected through various African early warning institutions. The regional level analyses how early warning institutions' methodologies influence sub-regional integration efforts. Lastly, the national level elaborates why African national intelligence and security sectors are determined by authoritarian governance. Similar to the three (continental, regional, national) research questions, this thesis is divided into three levels of analysis. First, the continental level evaluates the Continental Early Warning Systems' institutional struggle with its Regional Early Warning Systems and other organisations within and beyond the African Peace and Security Architecture. Second, the regional level examines the concepts and methodologies behind the six Regional Early Warning Systems for common features and differences....

Using an early warning system (EWS) methodology, this thesis analyses the predictability of stock market crises from the perspective of behavioural fnance. Specifcally, in our EWS based on the multinomial logit model, we consider in- vestor sentiment as one of the potential crisis indicators. Identifcation of the relevant crisis indicators is based on Bayesian model averaging. The empir- ical results reveal that price-earnings ratio, short-term interest rate, current account, credit growth, as well as investor sentiment proxies are the most rele- vant indicators for anticipating stock market crises within a one-year horizon. Our thesis hence provides evidence that investor sentiment proxies should be a part of the routinely considered variables in the EWS literature. In general, the predictive power of our EWS model as evaluated by both in-sample and out-of-sample performance is promising. JEL Classifcation G01, G02, G17, G41 Keywords Stock market crises, Early warning system, In- vestor sentiment, Crisis prediction, Bayesian model averaging Title Predicting stock market crises using investor sentiment indicators

Indiana University-Purdue University Indianapolis (IUPUI) / Floods are one of the worst disasters in the United States. Each year, the government allocates a tremendous amount of manpower and money on flood prevention initiatives. As the first defense line, levees provide protection from temporary flooding (Makhdoom, 2013). These embankments are broadly classified according to the areas they protect, which could either be urban or agricultural levees within floodplains. In the U.S., most of the levees are handled by government agencies such as the U.S. Army Corps of Engineers and the Federal Emergency Management Services. On the other hand, non-levee embankments created by individual farmers (Olson & Morton, 2013) or naturally formed levee-like structures may not be in the government database. The initial purpose of this research was to assist Polis center on the “Mapping of Non-Levee Embankments in the Indiana” project. The non-levee embankments are not certified or engineered levee-like structures. They, therefore, impose lateral constraints on flood flows, reducing the floodplain storage capacity and increasing the flood velocity. These non-levee embankments can cause stream erosion and downstream flooding. Therefore, it is important to know the locations of these features. The first part of the proposed method adapted the Empirical Bayesian theorem and the low pass filter techniques to extract elevated linear features from LiDAR elevation data – Digital Elevation Model (DEM). The second part of the proposed methods combined the Minimum Bounding Circle (MBC) method and the Youden Index to locate the optimal threshold value that can be used to determine whether the extracted features are levee-like structures. The focus of this study is not only limited to artificial levee-like structures, but also takes the natural levees, or any potential levee-like structures into account because this study assumes all embankments play important roles during flood events.

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第18563号 / 工博第3924号 / 新制||工||1603(附属図書館) / 31463 / 京都大学大学院工学研究科社会基盤工学専攻 / (主査)教授 藤田 正治, 教授 中川 一, 准教授 竹林 洋史 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第20344号 / 工博第4281号 / 新制||工||1663(附属図書館) / 京都大学大学院工学研究科社会基盤工学専攻 / (主査)教授 白土 博通, 教授 八木 知己, 教授 KIM Chul-Woo, 教授 杉浦 邦征 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

A new safety application, as part of ITS Advanced Rural Transportation System (ARTS), has been developed to be deployed on a two-lane rural road (Route 114), in Southwest Virginia. The route segment under study is subject to significant head-on accidents, as a result of two main conditions: 1- Illegal passing maneuvers crossing solid yellow line, and 2- A short passing sight distance due to the road vertical profile. The main objective of this research is to design a video detection-based warning system by installing an affordable and efficient system on the vertical crest curve on Route 114, capable of performing the following two main functions: 1.Detect vehicles that attempt to violate the no-passing zone restriction (i.e. when crossing into the opposing direction). 2.Warn the drivers violating the restriction in order to discourage them from continuing their maneuvers. System architecture as well as detailed system design was developed. A system simulation was conducted with the use of a special software program written with MATLAB. The simulation was applied for both "with" and "without" the system cases. The simulation runs showed that the system could virtually eliminate all head-on collisions, should violators obey the early warning messages displayed. Several sensitivity tests were made for different scenarios. Finally, the viability of the system was evaluated from economic point of view. The financial analysis revealed high economic indicators. / Ph. D.

Project schedules should mirror the project, as the project takes place. Accurate project schedules, when updated and revised, reflect the actual progress of construction as performed in the field. Various methods for monitoring progress of construction are successful in their representation of actual construction as it takes place. Progress monitoring techniques clearly identify when we are behind schedule, yet it is less obvious to recognize when we are going to slip behind schedule. This research explores how schedule performance measurement mechanisms are used to recognize construction projects that may potentially slip behind schedule, as well as what type of early warning they provide in order to take corrective action. Such early warning systems help prevent situations where the contractor and/or owner are in denial for a number of months that a possible catastrophe of a project is going to finish on time. This research develops the intellectual framework for schedule control systems, based on a review of control systems in the construction industry. The framework forms the foundation for the development of a schedule control technique for forecasting schedule slippage — the Required Performance Method (RPM). The RPM forecasts the required performance needed for timely project completion, and is based on the contractor's ability to expand future work. The RPM is a paradigm shift from control based on scheduled completion date to control based on required performance. This shift enables forecasts to express concern in terms that are more tangible. Furthermore, the shift represents a focus on what needs to be done to achieve a target completion date, as opposed to the traditional focus on what has been done. The RPM is demonstrated through a case study, revealing its ability to forecast impending schedule slippage. / Master of Science

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