Random Finite Set Theory and Optimal Control of Large Collaborative Swarms

Controlling large swarms of robotic agents has many challenges including, but not limited to, computational complexity due to the number of agents, uncertainty in the functionality of each agent in the swarm, and uncertainty in the swarm's configuration. This work generalizes the swarm state using Random Finite Set (RFS) theory and solves the control problem using Model Predictive Control (MPC) to overcome the aforementioned challenges. Computationally efficient solutions are obtained via the Iterative Linear Quadratic Regulator (ILQR). Information divergence is used to define the distance between the swarm RFS and the desired swarm configuration. Then, a stochastic optimal control problem is formulated using a modified L2^2 distance. Simulation results using MPC and ILQR show that swarm intensities converge to a target destination, and the RFS control formulation can vary in the number of target destinations. ILQR also provides a more computationally efficient solution to the RFS swarm problem when compared to the MPC solution. Lastly, the RFS control solution is applied to a spacecraft relative motion problem showing the viability for this real-world scenario.Comment: arXiv admin note: text overlap with arXiv:1801.0731

The [flourishing] entrepreneur: a case for legislative intervention to support healthy SMME financial access in South Africa

This thesis presents human flourishment as the theoretical foundation from which to pursue social policy in the post-colony. Accepting this theoretical foundation, the purpose of this thesis is to reflect on the role and potential of small, micro and medium enterprises (SMMEs) in South Africa. Further, this thesis will consider in what manner the law can support the realisation of the potential of South African SMMEs. The main value of this thesis is to illustrate the positive distributional impact that a human flourishment approach to legal intervention can have for a property system, which has the objective of supporting the realisation of the capabilities of persons in society. This value is illustrated in this thesis by analysing the relationship between the South African SMME and retail banking sectors. This thesis has chosen to focus on the SMME sector because of the role identified for SMMEs in South Africa's growth strategy, the National Development Plan (NDP). This role includes recognising SMMEs as being an entry point for previously excluded persons into the mainstream economy. A recent report by the Small Enterprise Development Agency (SEDA) highlights that the potential of SMMEs in South Africa remain unrealised. The report identifies key barriers to SMME flourishment in South Africa. This thesis focuses on the following identified barriers in the report: (i) the existing legal framework with respect to SMMEs; (ii) existing government agency support available to SMMEs; and (iii) the ability of SMMEs to access finance and credit. A primary finding in this thesis is existing credit structures in the retail banking sector are negatively biased towards the black population group. This has an adverse impact on black entrepreneurs. It is suggested in this thesis that this negative bias is a consequence of apartheid. Apartheid had the effect of regulating the access that black people had to the mainstream economy and their ability to acquire and accumulate property. Recognising that SMMEs have an identified role to play in South Africa's growth strategy, this thesis finds that legislative intervention in the retail banking sector is needed in order to overcome this negative bias and to support increased SMME access to finance and credit. This thesis interprets the preamble to the Constitution, as well as the concept of transformative constitutionalism, as mandating a capabilities-approach to human development. It is for this reason that a property system with a distributional outcome that supports the realisation of the capabilities of persons in society is preferred by this thesis. It is only once there is a real commitment of moving the majority of South Africans into the mainstream economy will inroads to tackling inequality and poverty be made

City Of Coral Gables v. Wood, 305 So. 2d 261 (Fla. 3d Dist. Ct. App. 1974)

Zoning Ordinance-ENHANCEMENT OF AESTHETIC VALUES ALONE NOT SUFFICIENT BASIS FOR EXERCISE OF POLICE POWER IN FLORIDA

Decentralized Control of Large Collaborative Swarms using Random Finite Set Theory

Controlling large swarms of robotic agents presents many challenges including, but not limited to, computational complexity due to a large number of agents, uncertainty in the functionality of each agent in the swarm, and uncertainty in the swarm's configuration. The contribution of this work is to decentralize Random Finite Set (RFS) control of large collaborative swarms for control of individual agents. The RFS control formulation assumes that the topology underlying the swarm control is complete and uses the complete graph in a centralized manner. To generalize the control topology in a localized or decentralized manner, sparse LQR is used to sparsify the RFS control gain matrix obtained using iterative LQR. This allows agents to use information of agents near each other (localized topology) or only the agent's own information (decentralized topology) to make a control decision. Sparsity and performance for decentralized RFS control are compared for different degrees of localization in feedback control gains which show that the stability and performance compared to centralized control do not degrade significantly in providing RFS control for large collaborative swarms.Comment: arXiv admin note: text overlap with arXiv:1810.0069

Impact of COVID-19 on Service Utilization by Those Experiencing Homelessness in Detroit

Background: Current research has demonstrated increased levels of fear and anxiety due to the Coronavirus pandemic. While fear can have a significant impact on any individual, fear among individuals experiencing homelessness is particularly impactful as this may affect service utilization and thus the ability of to access basic necessities such as food, shelter and water. This study seeks to understand the impact of fear of contracting COVID on service utilization among those experiencing homelessness in Detroit, MI. Methods and Results: From July-August 2020, 35 individuals who self-identified as homeless participated in a multiple-choice survey. 40% of surveyed individuals stated that they experienced fear of contracting COVID-19. None of the individuals who primarily stayed in shelters over the last six months reported such fear, whereas 48% of rough sleepers reported experiencing fear. 83% of those who did not stay in a shelter stated that they chose not to stay in a shelter that they otherwise would have due to fear of COVID-19. Of those who primarily relied on community resources for food, 23% stated that they did not use these resources during March, April or May of 2020, and 60% of these individuals said that this decision was due to fear of contracting COVID. Conclusions: Fear of contracting COVID-19 is present among the homeless population and impacted the use of community resources in Detroit. Specifically, individuals who normally rely on community shelters and food distributions chose not to frequent these services out of fear of contracting the coronavirus

The Structure and Content of Online Child Exploitation Networks

The emergence of the Internet has provided people with the ability to find and communicate with others of common interests. Unfortunately, those involved in the practices of child exploitation have also received the same benefits. Although law enforcement continues its efforts to shut down websites dedicated to child exploitation, the problem remains uncurbed. Despite this, law enforcement has yet to examine these websites as a network and determine their structure, stability and susceptibleness to attack. We extract the structure and features of four online child exploitation networks using a custom-written webpage crawler. Social network analysis is then applied with the purpose of finding key players – websites whose removal would result in the greatest fragmentation of the network and largest loss of hardcore material. Our results indicate that websites do not link based on the hardcore content of the target website; however, blogs do contain more hardcore content per page than non-blog websites

Comparing Methods for Detecting Child Exploitation Content Online

The sexual exploitation of children online is seen as a global issue and has been addressed by both governments and private organizations. Efforts thus far have focused primarily on the use of image hash value databases to find content. However, recently researchers have begun to use keywords as a way to detect child exploitation content. Within the current study we explore both of these methodologies. Using a custom designed web-crawler, we create three networks using the hash value method, keywords method, and a hybrid method combining the first two. Results first show that the three million images found in our hash value database were not common enough on public websites for the hash value method to produce meaningful result. Second, the small sample of websites that were found to contain those images had little to no videos posted, suggesting a need for different criteria for finding each type of material. Third, websites with code words commonly known to be used by child pornographers to identify or discuss exploitative content, were found to be much larger than others, with extensive visual and textual content. Finally, boy-centered keywords were more commonly found on child exploitation websites than girl-centered keywords, though not at a statistically significant level. Applications for law enforcement and areas for future research are discussed

Finding the Key Players in Online Child Exploitation Networks

The growth of the Internet has been paralleled with a similar growth in online child exploitation. Since completely shutting down child exploitation websites is difficult (or arguably impossible), the goal must be to find the most efficient way of identifying the key targets and then to apprehend them. Traditionally, online investigations have been manual and centered on images. However, we argue that target prioritization needs to take more than just images into consideration, and that the investigating process needs to become more systematic. Drawing from a web crawler we specifically designed for extracting child exploitation website networks, this study 1) examines the structure of ten child exploitation networks and compares it to a control group of sports-related websites, and 2) provides a measure (network capital) that allows for identifying the most important targets for law enforcement purposes among our sample of websites. Results show that network capital — a combination between severity of content (images, videos, and text) and connectivity (links to other websites) — is a more reliable measure of target prioritization than more traditional measures of network centrality taken alone. Policy implications are discussed