Information-theoretic analysis of human-machine mixed systems

Many recent information technologies such as crowdsourcing and social decision-making systems are designed based on (near-)optimal information processing techniques for machines. However, in such applications, some parts of systems that process information are humans and so systems are affected by bounded rationality of human behavior and overall performance is suboptimal. In this dissertation, we consider systems that include humans and study their information-theoretic limits. We investigate four problems in this direction and show fundamental limits in terms of capacity, Bayes risk, and rate-distortion. A system with queue-length-dependent service quality, motivated by crowdsourcing platforms, is investigated. Since human service quality changes depending on workload, a job designer must take the level of work into account. We model the workload using queueing theory and characterize Shannon's information capacity for single-user and multiuser systems. We also investigate social learning as sequential binary hypothesis testing. We find somewhat counterintuitively that unlike basic binary hypothesis testing, the decision threshold determined by the true prior probability is no longer optimal and biased perception of the true prior could outperform the unbiased perception system. The fact that the optimal belief curve resembles the Prelec weighting function from cumulative prospect theory gives insight, in the era of artificial intelligence (AI), into how to design machine AI that supports a human decision. The traditional CEO problem well models a collaborative decision-making problem. We extend the CEO problem to two continuous alphabet settings with general rth power of difference and logarithmic distortions, and study matching asymptotics of distortion as the number of agents and sum rate grow without bound

Outer Bounds on the CEO Problem with Privacy Constraints

We investigate the rate-distortion-leakage region of the Chief Executive Officer (CEO) problem with a passive eavesdropper and privacy constraints, considering a general distortion measure. While an inner bound directly follows from the previous work, an outer bound is newly developed in this paper. To derive this bound, we introduce a new lemma tailored for analyzing privacy constraints. As a specific instance, we demonstrate that the tight bound for discrete and Gaussian sources is obtained when the eavesdropper can only observe the messages under logarithmic loss distortion. We further investigate the rate-distortion-leakage region for a scenario where the eavesdropper possesses the messages and side information under the same distortion, and provide an outer bound for this particular case. The derived outer bound differs from the inner bound by only a minor quantity that appears in the constraints associated with the privacy-leakage rates, and it becomes tight when the distortion is large.Comment: 14 pages, 4 figure

Quantization in acquisition and computation networks

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (p. 151-165).In modern systems, it is often desirable to extract relevant information from large amounts of data collected at different spatial locations. Applications include sensor networks, wearable health-monitoring devices and a variety of other systems for inference. Several existing source coding techniques, such as Slepian-Wolf and Wyner-Ziv coding, achieve asymptotic compression optimality in distributed systems. However, these techniques are rarely used in sensor networks because of decoding complexity and prohibitively long code length. Moreover, the fundamental limits that arise from existing techniques are intractable to describe for a complicated network topology or when the objective of the system is to perform some computation on the data rather than to reproduce the data. This thesis bridges the technological gap between the needs of real-world systems and the optimistic bounds derived from asymptotic analysis. Specifically, we characterize fundamental trade-offs when the desired computation is incorporated into the compression design and the code length is one. To obtain both performance guarantees and achievable schemes, we use high-resolution quantization theory, which is complementary to the Shannon-theoretic analyses previously used to study distributed systems. We account for varied network topologies, such as those where sensors are allowed to collaborate or the communication links are heterogeneous. In these settings, a small amount of intersensor communication can provide a significant improvement in compression performance. As a result, this work suggests new compression principles and network design for modern distributed systems. Although the ideas in the thesis are motivated by current and future sensor network implementations, the framework applies to a wide range of signal processing questions. We draw connections between the fidelity criteria studied in the thesis and distortion measures used in perceptual coding. As a consequence, we determine the optimal quantizer for expected relative error (ERE), a measure that is widely useful but is often neglected in the source coding community. We further demonstrate that applying the ERE criterion to psychophysical models can explain the Weber-Fechner law, a longstanding hypothesis of how humans perceive the external world. Our results are consistent with the hypothesis that human perception is Bayesian optimal for information acquisition conditioned on limited cognitive resources, thereby supporting the notion that the brain is efficient at acquisition and adaptation.by John Z. Sun.Ph.D

Essays in Executive Compensation

This dissertation focuses on how executive compensation is designed and its implications for corporate finance and government regulations. Chapter 2 analyzes several proposals to restrict CEO compensation and calibrates two models of executive compensation that describe how firms would react to different types of restrictions. We find that many restrictions on CEO compensation would have unintended consequences. Restrictions on total realized (ex-post) payouts lead to higher average compensation, higher rewards for mediocre performance, lower risk-taking incentives, and the fact that some CEOs would be better off with a restriction than without it. Restrictions on total ex-ante pay lead to a reduction in the firm's demand for CEO talent and effort. Restrictions on particular pay components, and especially on cash payouts, can be easily circumvented. Chapter 3 examines how executive dividend protection affects corporate payout policy. I find that the dividend protection on executive restricted stock and option grants is associated with higher dividend payouts and lower share repurchases. Using the 2003 tax reform as an exogenous shock in dividend payouts, I provide further evidence that executive dividend protection causes changes in dividend payout policies. Chapter 4 studies a special subset of CEOs who works for a one-dollar annual salary. Rather than being the sacrificial acts they are projected to be, our findings suggest that some adoptions of one-dollar CEO salaries are opportunistic behavior of the wealthier, more overconfident, influential CEOs. Overall, these findings support the literature which claims that CEOs employ camouflage in compensation schemes to reduce the likelihood of public outrage over private benefits

Technology needs assessment of an atmospheric observation system for tropospheric research missions, part 1

The technology advancements needed to implement the atmospheric observation satellite systems for air quality research were identified. Tropospheric measurements are considered. The measurements and sensors are based on a model of knowledge objectives in atmospheric science. A set of potential missions and attendant spacecraft and sensors is postulated. The results show that the predominant technology needs will be in passive and active sensors for accurate and frequent global measurements of trace gas concentration profiles

Nonlinear Constitutive Relations for High Temperature Applications

The topics of discussion addressed were material behavior, design analysis, deformation kinetics, metallurgical characterization, mechanical subelement models, stress analysis, fracture mechanics, viscoplasticity, and thermal loading

Statistical energy analysis of engineering structures

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.This thesis examines the fundamental equations of the branch of linear oscillatory dynamics known as Statistical Energy Analysis (SEA). The investigation described is limited to the study of two, point coupled multi-modal sub-systems which form the basis for most of the accepted theory in this field. Particular attention is paid to the development of exact classical solutions against which simplified approaches can be compared. These comparisons reveal deficiencies in the usual formulations of SEA in three areas, viz., for heavy damping, strong coupling between sub-systems and for systems with non-uniform natural frequency distributions. These areas are studied using axially vibrating rod models which clarify much of the analysis without significant loss of generality. The principal example studied is based on part of the structure of a modem warship. It illustrates the simplifications inherent in the models adopted here but also reveals the improvements that can be made over traditional SEA techniques. The problem of heavy damping is partially overcome by adopting revised equations for the various loss factors used in SEA. These are shown to be valid provided that the damping remains proportional so that inter-modal coupling is not induced by the damping mechanism. Strong coupling is catered for by the use of a correction factor based on the limiting case of infinite coupling strength, for which classical solutions may be obtained. This correction factor is used in conjunction with a new, theoretically based measure of the transition between weakly and strongly coupled behaviour. Finally, to explore the effects of non-uniform natural frequency distributions, systems with geometrically periodic and near-periodic parameters are studied. This important class of structures are common in engineering design and do not posses the uniform modal statistics commonly assumed in SEA. The theory of periodic structures is used in this area to derive more sophisticated statistical models that overcome some of these limitations

Opportunity costs of trade-related capacity development in Sub-Saharan Africa

Includes bibliographical references.Recent studies have documented the impact of institutions and infrastructure development on trade flows. This paper studies these issues in the context 010n90in9 trade-related capacity building initiatives and evaluates the opportunity cost of different trade-related capacity building policy mixes. Trade-related technical assistance and capacity building was recognized in 2001 by the World Trade Organisation Doha Ministerial Declaration as a core element of the development dimension of the multilateral trading system and commitments were set out in those areas. The extentof trade-related technical assistance and capacity building to help developing and least developed countries participate more efficiently in international trade has increased by 50% between 2001 and 2004. The purpose of this thesis is to address the question of whether the weights assigned to different components of trade-related capacity building in existing trade-related capacity building programmes are economically justified. To do this the paper evaluates the opportunity costsof different trade-related capacity building policy mixes with specific reference to Sub-Saharan Africa, excluding South Africa. We use a number of variables from both theoretical and empirical literature to come up with composite indicators for trade-related institutions, infrastructure and human capital. The analysis is also informed by interviews with trade experts in Geneva as well as a review of relevant background documents. In the empirical analysis we use 2005 trade patterns for a data set of 117 countries of which 24 are in sub-Saharan Africa. Making use ofa gravity equation augmented with trade-related capacity building variables we run a series of Heckman's two-step selection regressions and estimate the marginal impacts of these trade-related capacity building indicators on trade as measured by value of total exports. To evaluate opportunity costs. we do policy simulations and estimate how much trade flows will be increased under various policy scenarios with respect to improved trade-related capacity building indicators in Sub-Saharan Africa. We examine scenarios that focus on improved institutions. infrastructure and human capital as they move in the direction of comparability with the rest of the world. The world's average level is used as the baseline for each of these composite indicators in the policy simulations. The results show that trade flows exhibit different levels of sensitivity to different trade-related capacity building policy options with the exporter's infrastructure being the most significant with an average elasticity of approximately 3.0. The findings also suggest that complementing improvements in the quality of human capital and infrastructure will provide the greatest bilateral trade flow benefit to Sub-Saharan Africa; while non-Sub-Saharan Africa countries gain the most from complementing infrastructure and institutions. Such a finding contradicts the current focus of ongoing TReB programmes that put emphasis on human capital development only. Building on both Grossman and Helpman (1991),s trade model and Barro (1990) s' growth model, the paper argues that the theoretical propositions are inadequate to address the dynamics associated with trade-related capacity building policy. The paper further argues that analyzing the impact of rReB using these standard frameworks underestimates the impact since policy dynamics are not addressed in that framework. This could contribute to explaining why there has not been consensus in the trade-growth empirical literature, with some authors finding a positive and significant impact of trade on growth, while others argue that the impact is not significant Hence, the paper proposes improvements in the specification of the standard growth model to take into account policy dynamics, specifically assumptions regarding substitutability among TRee investments