Towards an Iterative Algorithm for the Optimal Boundary Coverage of a 3D Environment

This paper presents a new optimal algorithm for locating a set of sensors in 3D able to see the boundaries of a polyhedral environment. Our approach is iterative and is based on a lower bound on the sensors' number and on a restriction of the original problem requiring each face to be observed in its entirety by at least one sensor. The lower bound allows evaluating the quality of the solution obtained at each step, and halting the algorithm if the solution is satisfactory. The algorithm asymptotically converges to the optimal solution of the unrestricted problem if the faces are subdivided into smaller part

A two-armed bandit based scheme for accelerated decentralized learning

The two-armed bandit problem is a classical optimization problem where a decision maker sequentially pulls one of two arms attached to a gambling machine, with each pull resulting in a random reward. The reward distributions are unknown, and thus, one must balance between exploiting existing knowledge about the arms, and obtaining new information. Bandit problems are particularly fascinating because a large class of real world problems, including routing, QoS control, game playing, and resource allocation, can be solved in a decentralized manner when modeled as a system of interacting gambling machines. Although computationally intractable in many cases, Bayesian methods provide a standard for optimal decision making. This paper proposes a novel scheme for decentralized decision making based on the Goore Game in which each decision maker is inherently Bayesian in nature, yet avoids computational intractability by relying simply on updating the hyper parameters of sibling conjugate priors, and on random sampling from these posteriors. We further report theoretical results on the variance of the random rewards experienced by each individual decision maker. Based on these theoretical results, each decision maker is able to accelerate its own learning by taking advantage of the increasingly more reliable feedback that is obtained as exploration gradually turns into exploitation in bandit problem based learning. Extensive experiments demonstrate that the accelerated learning allows us to combine the benefits of conservative learning, which is high accuracy, with the benefits of hurried learning, which is fast convergence. In this manner, our scheme outperforms recently proposed Goore Game solution schemes, where one has to trade off accuracy with speed. We thus believe that our methodology opens avenues for improved performance in a number of applications of bandit based decentralized decision making

Digital Simulation for Automobile Maneuvers

A new all-digital simulation of automobile handling allows severe maneuvers involving braking or accel eration and cornering. A novel feature is the in corporation of closed-loop control based on a mathematical model of the human driver. The program is modular and well-documented. The model includes provisions for nonlinear tire and suspension forces and moments; it also allows the user to switch off the nonlinearities and to include an antilock brake system.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68886/2/10.1177_003754978103700304.pd

Microplastics Detected in Groundwater

Low concentrations of microplastics are present in Illinois’ karst groundwater, according to a preliminary study completed in spring 2018. This is the first time that microplastics have been detected in groundwater. The study was conducted in collaboration with scientists at the Illinois State Geological Survey, Illinois State Water Survey, Loyola University Chicago, and ISTC. Full study results published in Panno, S.V., Kelly, W.R., Scott, J., Zheng, W., McNeish, R.E., Holm, N., Hoellein, T.J. and Baranski, E.L. (2019), Microplastic Contamination in Karst Groundwater Systems. Groundwater, 57: 189-196. doi:10.1111/gwat.12862.League of Women Voters of Jo Daviess County; Illinois State Geological Survey; Illinois State Water Survey; Illinois Sustainable Technology Center (Hazardous Waste Research Fund);. Illinois-Indiana Sea Grant (National Oceanic and Atmospheric Administration ; 074483-15907); National Science Foundation (CAREER 1553835).Ope

Corporate reporting on corruption: an international comparison

Building on an institutionalist framework of the various organizational field-level pressures on firms to engage with the challenge of corruption, we analyse anti-corruption disclosures across a sample of 933 sustainability reports. Such reporting complements anti-corruption initiatives, as it allows the company to demonstrate its commitment. Our results show clear country- and sector-level differences in the extent to which companies communicate their anti-corruption engagement. However, the more a company is exposed to corruption, the less likely it appears to openly communicate its anti-corruption engagement. Hence, our results cast doubt on the effectiveness of anti-corruption disclosures as part of wider sustainability reporting

Law, politics and the governance of English and Scottish joint-stock companies 1600-1850

This article examines the impact of law on corporate governance by means of a case study of joint-stock enterprise in England and Scotland before 1850. Based on a dataset of over 450 company constitutions together with qualitative information on governance practice, it finds little evidence to support the hypothesis that common-law regimes such as England were more supportive of economic growth than civil-law jurisdictions such as Scotland: indeed, levels of shareholder protection were slightly stronger in the civil-law zone. Other factors, such as local political institutions, played a bigger role in shaping organisational forms and business practice

Branch-and-lift algorithm for deterministic global optimization in nonlinear optimal control

This paper presents a branch-and-lift algorithm for solving optimal control problems with smooth nonlinear dynamics and potentially nonconvex objective and constraint functionals to guaranteed global optimality. This algorithm features a direct sequential method and builds upon a generic, spatial branch-and-bound algorithm. A new operation, called lifting, is introduced, which refines the control parameterization via a Gram-Schmidt orthogonalization process, while simultaneously eliminating control subregions that are either infeasible or that provably cannot contain any global optima. Conditions are given under which the image of the control parameterization error in the state space contracts exponentially as the parameterization order is increased, thereby making the lifting operation efficient. A computational technique based on ellipsoidal calculus is also developed that satisfies these conditions. The practical applicability of branch-and-lift is illustrated in a numerical example. © 2013 Springer Science+Business Media New York

The Impact of Interorganizational Imitation on New Venture International Entry and Performance

We examine the impact of interorganizational imitation on new venture international entry and subsequent performance. Using a sample of 150 U.S.-based publicly held new ventures, we find that new venture international entry is in part an imitative response to the internationalization of other firms in the venture\u27s home country industry and/or subsets of firms with certain traits or outcomes. We also find that interorganizational imitation moderates the relationship between new venture international entry and profitability, but not the relationship between new venture international entry and sales growth. These findings contribute to the growing body of literature on new venture internationalization

Mental models of high reliability systems

Reliable performance in complex systems is determined in part by the ade quacy with which mental models of the system capture accurately the dimen sions of system coupling and system complexity. Failure to register coupling and complexity leads the observer to intervene into an imagined technology that does not exist and to convert opportunities for error into actual errors. To decrease the frequency with which this conversion occurs, people can make their models more complex or the systems they monitor less complex. Neither type of change is as daunting as it may appear, and this is illustrated by an analysis of the mental model and system design associated with the invasion of Grenada.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68652/2/10.1177_108602668900300203.pd

A Mechanism-Based Explanation of the Institutionalization of Semantic Technologies in the Financial Industry

Part 3: Creating Value through ApplicationsInternational audienceThis paper explains how the financial industry is solving its data, risk management, and associated vocabulary problems using semantic technologies. The paper is the first to examine this phenomenon and to identify the social and institutional mechanisms being applied to socially construct a standard common vocabulary using ontology-based models. This standardized ontology-based common vocabulary will underpin the design of next generation of semantically-enabled information systems (IS) for the financial industry. The mechanisms that are helping institutionalize this common vocabulary are identified using a longitudinal case study, whose embedded units of analysis focus on central agents of change—the Enterprise Data Management Council and the Object Management Group. All this has important implications for society, as it is intended that semantically-enabled IS will, for example, provide stakeholders, such as regulators, with better transparency over systemic risks to national and international financial systems, thereby mitigating or avoiding future financial crises