abstract: Internet browsers are today capable of warning internet users of a potential phishing attack. Browsers identify these websites by referring to blacklists of reported phishing websites maintained by trusted organizations like Google, Phishtank etc. On identifying a Unified Resource Locator (URL) requested by a user as a reported phishing URL, browsers like Mozilla Firefox and Google Chrome display an 'active' warning message in an attempt to stop the user from making a potentially dangerous decision of visiting the website and sharing confidential information like username-password, credit card information, social security number etc. However, these warnings are not always successful at safeguarding the user from a phishing attack. On several occasions, users ignore these warnings and 'click through' them, eventually landing at the potentially dangerous website and giving away confidential information. Failure to understand the warning, failure to differentiate different types of browser warnings, diminishing trust on browser warnings due to repeated encounter are some of the reasons that make users ignore these warnings. It is important to address these factors in order to eventually improve a user’s reaction to these warnings. In this thesis, I propose a novel design to improve the effectiveness and reliability of phishing warning messages. This design utilizes the name of the target website that a fake website is mimicking, to display a simple, easy to understand and interactive warning message with the primary objective of keeping the user away from a potentially spoof website. / Dissertation/Thesis / Masters Thesis Computer Science 2015

In recent years, State Road Route 114 which is located in Montgomery County, Virginia, has gained a bad reputation because of numerous traffic accidents. Most of these accidents resulted in loss of lives and property. Although there are many suggestions and proposals designed to prevent these acidents, to date no actions is taken yet. The focus of this research is to explore a technology-based, low cost solution that will lower or eliminate the risk of accidents on this two-lane rural highway. / Master of Science

Keeping a safe distance from the forward-leading vehicle is an essential feature of modern Advanced Driver Assistant Systems (ADAS), especially for transportation companies with a fleet of trucks. We propose in this thesis a Forward Collision Warning (FCW) system, which collects visual information using smartphones attached for instance to the windshield of a vehicle. The basic idea is to detect the forward-leading vehicle and estimate its distance from the vehicle. Given the limited resources of computation and memory of mobile devices, the main challenge of this work is running CNN-based object detectors at real-time without hurting the performance. In this thesis, we analyze the bounding boxes distribution of the vehicles, then propose an efficient and customized deep neural network for forward-leading vehicle detection. We apply a detection-tracking scheme to increase the frame rate of vehicle detection and maintain good performance. Then we propose a simple leading vehicle distance estimation approach for monocular cameras. With the techniques above, we build an FCW system that has low computation and memory requirements that are suitable for mobile devices. Our FCW system has 49% less allocated memory, 7.5% higher frame rate, and 21% less battery consumption speed than popular deep object detectors. A sample video is available at https://youtu.be/-ptvfabBZWA.

Proximity Warning Systems are currently the focus of many research groups. Their goal is to produce a system that will reduce the number of run over incidents that occur in large mobile equipment operations. A majority of these incidents occur when the equipment starts from the In-rest state and begins to move. The addition of a transmission locking mechanism to a GPS based proximity warning system will prevent more run over incidents. This transmission locking mechanism will automatically prevent equipment from moving when there is a high risk for a potential run over incident to occur. Additional safety and optimization for surface equipment can be provided by utilizing GIS software for data analysis just by using the data collected from a GPS based proximity warning system. Combining these ideas and methods can provide better safety for large mobile equipment operations. / Master of Science

No description available.

Thesis (Ph.D.)--University of Delaware, 2007. / Principal faculty advisor: Havidan Rodriguez, Dept. of Sociology & Criminal Justice. Includes bibliographical references.

Nowadays, the trend towards globalization and internationalization of business has strong impact on companies’ strategy. When a company is thinking about strategy development, it needs to pay attention to variable aspects on micro- and macro-level. This study includes the overview of the factors which need to be considered while developing a strategy. Moreover, a significant emphasize is made on the contemporary deriving challenges at the market. The purpose of the study is to investigate a new approach to the strategic planning, named “Early warning system”. For that purpose, it was conducted qualitative research at the example of the Ukrainian telecommunication company – MTS Ukraine. I identified factors which influence the company and analyzed how company copes with deriving challenges. Moreover, it was found out the company’s strategic planning process is significantly influenced by specific market characteristics such as high level of bureaucracy, specific behavior of some competitors, growing market.

A new zone was added to the existing Livestock Early Warning System (LEWS), which is a subproject of the USAID Global Livestock Collaborative Research Support Program. LEWS uses the PHYGROW model and satellite imagery of weather and vegetation to estimate the availability of forage to livestock and wildlife. Drought advisories are then distributed to governments, development organizations, and pastoralists via the Internet, satellite radios, and written reports. The Laikipia zone was established in 2001 to provide drought early warning for the arid pastoral rangelands of the Ewaso Ngiro ecosystem in the Laikipia and southern Samburu Districts, Kenya. Field verification of PHYGROW estimates of standing crop was conducted in 2002. In addition, research was conducted to determine the ability of the warning system to provide significant advance notice of emerging drought conditions. Results of this study indicate that LEWS is capable of providing accurate estimates of forage availability on East African rangelands. There is also evidence that the use of LEWS advisories could accelerate drought response by pastoralists as much as three to seven weeks.

Due to the global competition, the survival of enterprises must face the major test. Since the poor management of the market will increase number of companies, so the crisis early warning model of business has the necessary to establish. The cause of financial crisis is the main source of financial situation of the deteriorating. Therefore, if we could analysis the facets and weights of potential affect factors through the financial and managerial situation of business to judge the crisis cause of a corporation and establish the early warning model is worth to discuss deeply. The precious year of companies¡¦ data that this study collecting are from the Taiwan Securities Exchange 2006/01/01-2008/12/31 which have been out of the open security market based on the analysis standards and omitting the less information and banking, have total 36 enterprises data for analysis. The application of total variables, this study pre-adapts the TEJ business credit risk indicators to integrate the documentation and analysis the fundamental variables. It can be seen that all the factors have the relationship with each other through this study. This highlights a very important message, and also to the crisis among the factors and normal company with a considerable fluctuations. The judging results of DEA-DA model show that most of the company might be affected with some important factors of interpretation in abnormal situation to let the company in crisis cluster. Through Logistic regression analysis results show that our study forecasting model has the great explanatory power to meet the behavior of interpretation with the crisis and normal companies. By the enterprises crisis model of this study building to assess and forecast the crisis situation have the same results with the simplified model constructing with key factors to affect the original model direction. This study shows a very important fact that the crisis forecasting models will not be simplified to change the outcome which also indicating to increase of variables won¡¦t change the results of the assessment. In accordance with this study proposed model, if value positive that would be show more and more vulnerable to crisis. By other words, if value negative that would be more small vulnerable to crisis.

Active traffic management is a hot topic for addressing issues of highway congestion. It is the use of intelligent transportation systems to provide real time traffic information on highway conditions. In Austin, the segment of Interstate 35 between Riverside Drive and State Highway 71 experiences both congestion and safety issues. This report provides an introduction into the application of active traffic management through the use of a proposed queue warning system in the area. First, select crash data on the region is highlighted to present the safety conditions, particularly the type of collision and crash severity involved. Next, a proposed queue warning system design is described. This includes a description of the equipment used, methodology for system deployment, and expected outcomes. Finally, a computer simulation testing the operational performance of the queue warning system is performed using VISSIM, and the results are reported. This report aims to demonstrate the role that queue warning system and active traffic management may play in addressing metropolitan traffic needs. / text