Surveillance Planning against Smart Insurgents in Complex Terrain

This study is concerned with finding a way to solve a surveillance system allocation problem based on the need to consider intelligent insurgency that takes place in a complex geographical environment. Although this effort can be generalized to other situations, it is particularly geared towards protecting military outposts in foreign lands. The technological assets that are assumed available include stare-devices, such as tower-cameras and aerostats, as well as manned and unmanned aerial systems. Since acquiring these assets depends on the ability to control and monitor them on the target terrain, their operations on the geo-location of interest ought to be evaluated. Such an assessment has to also consider the risks associated with the environmental advantages that are accessible to a smart adversary. Failure to consider these aspects might render the forces vulnerable to surprise attacks. The problem of this study is formulated as follows: given a complex terrain and a smart adversary, what types of surveillance systems, and how many entities of each kind, does a military outpost need to adequately monitor its surrounding environment? To answer this question, an analytical framework is developed and structured as a series of problems that are solved in a comprehensive and realistic fashion. This includes digitizing the terrain into a grid of cell objects, identifying high-risk spots, generating flight tours, and assigning the appropriate surveillance system to the right route or area. Optimization tools are employed to empower the framework in enforcing constraints--such as fuel/battery endurance, flying assets at adequate altitudes, and respecting the climbing/diving rate limits of the aerial vehicles--and optimizing certain mission objectives--e.g. revisiting critical regions in a timely manner, minimizing manning requirements, and maximizing sensor-captured image quality. The framework is embedded in a software application that supports a friendly user interface, which includes the visualization of maps, tours, and related statistics. The final product is expected to support designing surveillance plans for remote military outposts and making critical decisions in a more reliable manner

Case study in the selection of warehouse location for WFP in Ethiopia

Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2009.Includes bibliographical references (leaves 96-99).Humanitarian logistic organizations struggle to make strategic and tactical decisions due to their lack of resources, the unpredictability of humanitarian events and the lack of readily available information; the existing tools that assist optimal decision making require large amounts of precise information. As a consequence of all these challenges, most of the work in humanitarian logistics concentrates on the operational level that can only offer short term benefits. Alternatively, optimal strategic decisions maximize the resources of humanitarian organizations making them more flexible and effective in the long term; this directly impacts the ability to help the millions of people in need. This thesis presents a model that assists the largest humanitarian organization in the world, The World Food Programme, to make optimal strategic decisions. The model uses the Analytic Hierarchy Process, a multiple attribute decision tool that provides structure to decisions where there is limited availability of quantitative information. This methodology uses a framework that determines and prioritizes multiple criteria by using qualitative data and it scores each alternative based on these criteria. The optimal alternative will be the one that has the highest weighted score. This model solves the challenges that The World Food Programme, as any other humanitarian organization face when making complex strategic decisions. The model, not only works with easily acquired information but, it is also flexible in order to consider the ever-changing dynamics in the humanitarian field.(cont.) The application of this model focuses on the optimization of warehouse locations for the World Food Programme in the Somali region of Ethiopia. However, this model can easily be scaled in order to be used in any other decision making process in the humanitarian field.by Gina Malaver [and] Colin Regnier.M.Eng.in Logistic

人・ユーザー中心の移動サービスと群集マネジメントのためのモデリング，シミュレーションと最適化

Tohoku University博士（情報科学）thesi

Ergonomics of intelligent vehicle braking systems

The present thesis examines the quantitative characteristics of driver braking and pedal operation and discusses the implications for the design of braking support systems for vehicles. After the current status of the relevant research is presented through a literature review, three different methods are employed to examine driver braking microscopically, supplemented by a fourth method challenging the potential to apply the results in an adaptive brake assist system. First, thirty drivers drove an instrumented vehicle for a day each. Pedal inputs were constantly monitored through force, position sensors and a video camera. Results suggested a range of normal braking inputs in terms of brake-pedal force, initial brake-pedal displacement and throttle-release (throttle-off) rate. The inter-personal and intra-personal variability on the main variables was also prominent. [Continues.

AREAS OF KNOWLEDGE NEEDED BY SUPERINTENDENTS AND ARCHITECTS TO ENHANCE THEIR COLLABORATION IN THE SCHOOL DESIGN PROCESS

The purpose of the study was to identify perceptions of the contributions made by superintendents and architects respectively when programming a new school. Areas of collaboration were determined by a qualitative analysis of the responses of superintendents and architects to questions regarding their perceptions of areas to discuss when collaborating in the designing of a new school. Ninety-four Texas superintendents and forty-six architects participated in the survey. Major research findings from this study addressed the areas of knowledge needed to enhance the collaboration process. Budget is the driving force within the collaboration between superintendents and architects when designing a school. The superintendent is the key communicator in the design process. Architects are the individuals most concerned with using the instructional delivery methods used by teachers to guide the design process. Three main areas to address when designing a school to support student safety are accessibility, surveillance and visibility. Instructional specialists, specifically at the district-level, are often not included as a part of the facilities committee. Superintendents obtain knowledge and the skill to collaborate with architects on a school design process through on-the-job experience. Recommendations are made to further enhance the collaboration. Superintendents and architects need to view budgets as a way to prioritize needs rather than to limit possibilities when designing a school. Superintendents must continue to be aware that they are the lead communicator in the school design process and must continue to work to effectively communicate their district�s and community�s needs, expectations, and vision. Superintendents must be prepared to communicate instructional delivery methods and expectations to architects when designing a school. Superintendents and architects need to consider accessibility, camera surveillance, and visibility when designing a school to support student safety. Facilities committees should include district level curriculum experts as part of the school design process, as these individuals are knowledgeable of the district�s instructional vision. It is important for superintendents who are designing a school project to have prior experience in participating in the design process, or to collaborate with other superintendents with experience to guide and assist them in the process

Short-term custodial design is outdated: developing knowledge and initiatives for future research and a specialised strategic architecture for police custodial facilities.

This research explores the evolution of WA Police custodial facilities, which uniquely, temporary detain unsentenced people. Adaptation of incompatible spatial strategies have led to a police custodial typology that reflect outdated prison philosophies and design intended for sentenced prisoners. This research developed robust architectural theories derived through critical interdisciplinary investigation developing an understanding of the specialised spatial relationships and operational requirements of police custodial spaces that serve the needs of the custodian and those held

An Extension of BIM Using AI: a Multi Working-Machines Pathfinding Solution

Multi working-machines pathfinding solution enables more mobile machines simultaneously to work inside of a working site so that the productivity can be expected to increase evolutionary. To date, the potential cooperation conflicts among construction machinery limit the amount of construction machinery investment in a concrete working site. To solve the cooperation problem, civil engineers optimize the working site from a logistic perspective while computer scientists improve pathfinding algorithms’ performance on the given benchmark maps. In the practical implementation of a construction site, it is sensible to solve the problem with a hybrid solution; therefore, in our study, we proposed an algorithm based on a cutting-edge multi-pathfinding algorithm to enable the massive number of machines cooperation and offer the advice to modify the unreasonable part of the working site in the meantime. Using the logistic information from BIM, such as unloading and loading point, we added a pathfinding solution for multi machines to improve the whole construction fleet’s productivity. In the previous study, the experiments were limited to no more than ten participants, and the computational time to gather the solution was not given; thus, we publish our pseudo-code, our tested map, and benchmark our results. Our algorithm’s most extensive feature is that it can quickly replan the path to overcome the emergency on a construction site

Recent Trends in Computational Intelligence

Traditional models struggle to cope with complexity, noise, and the existence of a changing environment, while Computational Intelligence (CI) offers solutions to complicated problems as well as reverse problems. The main feature of CI is adaptability, spanning the fields of machine learning and computational neuroscience. CI also comprises biologically-inspired technologies such as the intellect of swarm as part of evolutionary computation and encompassing wider areas such as image processing, data collection, and natural language processing. This book aims to discuss the usage of CI for optimal solving of various applications proving its wide reach and relevance. Bounding of optimization methods and data mining strategies make a strong and reliable prediction tool for handling real-life applications

Observing and modeling drivers’ behavior in work zones using SHRP 2 naturalistic driving study data

The presence of a work zone increases disturbances to traffic flow and produces high cognitive workloads for drivers, which can increase the safety risks. There was an increase of about 11% in work zone-related fatalities from 2010 to 2014 despite a small decrease in non-work zone-related fatalities in the U.S. A number of studies concluded speeding and distractions are the main unsafe driver behaviors contributing to work zone crashes. Federal Highway Administration (FHWA) crash facts indicated speeding as a contributing factor for 28% of work zone crashes in 2014. A series of countermeasures have been used to get drivers’ attention to comply with work zone conditions. There is limited information about which safety features are the most effective in accomplishing this goal. The effectiveness of safety features can sometimes vary due to driver behavior that has not been truly investigated due to limited information in our traditional crash data. The Naturalistic Driving Study (NDS) data, developed by the Strategic Highway Research Program (SHRP) 2 provides a unique opportunity to observe actual driver behavior, to identify main contributing factors associated with crashes and near-crashes, and to understand how drivers negotiate work zones. The aim of this dissertation is to develop models that provide a better understanding of driver behavior in work zones. The additional objective is to determine the most effective safety features to get drivers’ attention in reducing their speed in work zones. The task was accomplished by conducting three studies. The first paper developed a logistic regression model using a number of explanatory variables which included driver behavior, work zone characteristics, and environmental conditions to predict the crash/near-crash event outcome. In the second paper, the speed trajectory time series data were used to develop models to accurately and efficiently estimate the location of changepoint in mean speed reacting to safety features utilized in work zones to encourage safe driving. The final paper utilized the methods of functional data analysis to understand and analyze driver behavior interacting with safety features applied in work zone with various characteristics. The methods were used to identify the effectiveness of various safety features