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Abstract This book provides a framework for info-metrics—the science of modeling, inference, and reasoning under conditions of noisy and insufficient information. Info-metrics is an inherently interdisciplinary framework that emerged from the intersection of information theory, statistical inference, and decision-making under uncertainty. It allows us to process the available information with minimal reliance on assumptions that cannot be validated. This book focuses on unifying all information processing and model building within a single constrained optimization framework. It provides a complete framework for modeling and inference, rather than a problem-specific model. The framework evolves from the simple premise that our available information is often insufficient to provide a unique answer for decisions we wish to make. Each decision, or solution, is derived from the available input information along with a choice of inferential procedure. The book contains many multidisciplinary applications that demonstrate the simplicity and generality of the framework in real-world settings: These include initial diagnosis at an emergency room, optimal dose decisions, election forecasting, network and information aggregation, weather pattern analyses, portfolio allocation, inference of strategic behavior, incorporation of prior information, option pricing, and modeling an interacting social system. This book presents simple derivations of the key results that are necessary to understand and apply the fundamental concepts to a variety of problems. Derivations are often supported by graphical illustrations. The book is designed to be accessible for graduate students, researchers, and practitioners across the disciplines, requiring only basic quantitative skills and a little persistence.

A powerful integrated fan-out (InFO) wafer level system integration (WLSI) technology has been developed to integrate application processor chip with memory package for smart mobile devices. This novel InFO technology is the first high performance Fan-Out Wafer Level Package (FO_WLP) with multi-layer high density interconnects proposed to the industry. In this paper we present the detailed comparison of InFO packages on package (InFO_PoP) with several other previously proposed 3D package solutions. Result shows that InFO_PoP has more optimized overall results on system performance, leakage power and area (form factor) than others, to meet the ever-increasing system requirements of mobile computing. InFO technology has been successfully qualified on package level with robust component and board level reliability. It is also qualified at interconnect level with high electromigration resistance. With its high flexibility and strong capability of multi-chips integration for both homogeneous and heterogeneous sub-systems, InFO technology not only provides a system scaling solution but also complements the chip scaling and helps to sustain the Moore's Law for the smart mobile as well as internet of things (IoT) applications.

This article reports on the data collected on one of the most ambitious government-sponsored environmental data acquisition projects of all time, the Risk Management Plan (RMP) data collected under section 112(r) of the Clean Air Act Amendments of 1990. This RMP Rule 112(r) was triggered by the Bhopal accident in 1984 and led to the requirement that each qualifying facility develop and file with the U.S. Environmental Protection Agency a Risk Management Plan (RMP) as well as accident history data for the five-year period preceding the filing of the RMP. These data were collected in 1999-2001 on more than 15,000 facilities in the United States that store or use listed toxic or flammable chemicals believed to be a hazard to the environment or to human health of facility employees or off-site residents of host communities. The resulting database, RMP*Info, has become a key resource for regulators and researchers concerned with the frequency and severity of accidents, and the underlying facility-specific factors that are statistically associated with accident and injury rates. This article analyzes which facilities actually filed under the Rule and presents results on accident frequencies and severities available from the RMP*Info database. This article also presents summaries of related results from RMP*Info on Offsite Consequence Analysis (OCA), an analytical estimate of the potential consequences of hypothetical worst-case and alternative accidental releases on the public and environment around the facility. The OCA data have become a key input in the evaluation of site security assessment and mitigation policies for both government planners as well as facility managers and their insurers. Following the survey of the RMP*Info data, we discuss the rich set of policy decisions that may be informed by research based on these data.

This geologic map was prepared as a part of a study of digital methods and techniques as applied to complex geologic maps. The geologic map was digitized from the original scribe sheets used to prepare the published Geologic Map of Colorado (Tweto 1979). Consequently the digital version is at 1:500,000 scale using the Lambert Conformal Conic map projection parameters of the state base map. Stable base contact prints of the scribe sheets were scanned on a Tektronix 4991 digital scanner. The scanner automatically converts the scanned image to an ASCII vector format. These vectors were transferred to a VAX minicomputer, where they were then loaded into ARC/INFO. Each vector and polygon was given attributes derived from the original 1979 geologic map. This database was developed on a MicroVAX computer system using VAX V 5.4 nd ARC/INFO 5.0 software. UPDATE: April 1995, The update was done solely for the purpose of adding the abilitly to plot to an HP650c plotter. Two new ARC/INFO plot AMLs along with a lineset and shadeset for the HP650C design jet printer have been included. These new files are COLORADO.650, INDEX.650, TWETOLIN.E00 and TWETOSHD.E00. These files were created on a UNIX platform with ARC/INFO 6.1.2. Updated versions of INDEX.E00, CONTACT.E00, LINE.E00, DECO.E00 and BORDER.E00 files that included the newly defined HP650c items are also included. * Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Descriptors: The Digital Geologic Map of Colorado in ARC/INFO Format Open-File Report 92-050

We formulate an info-clustering paradigm based on a multivariate information measure, called multivariate mutual information, that naturally extends Shannon’s mutual information between two random variables to the multivariate case involving more than two random variables. With proper model reductions, we show that the paradigm can be applied to study the human genome and connectome in a more meaningful way than the conventional algorithmic approach. Not only can info-clustering provide justifications and refinements to some existing techniques, but it also inspires new computationally feasible solutions.

Everyone makes decisions, but not everyone is a decision analyst. A decision analyst uses quantitative models and computational methods to formulate decision algorithms, assess decision performance, identify and evaluate options, determine trade-offs and risks, evaluate strategies for investigation, and so on. This book is written for decision analysts. The term "decision analyst" covers an extremely broad range of practitioners. Virtually all engineers involved in design (of buildings, machines, processes, etc.) or analysis (of safety, reliability, feasibility, etc.) are decision analysts, usually without calling themselves by this name. In addition to engineers, decision analysts work in planning offices for public agencies, in project management consultancies, they are engaged in manufacturing process planning and control, in financial planning and economic analysis, in decision support for medical or technological diagnosis, and so on and on. Decision analysts provide quantitative support for the decision-making process in all areas where systematic decisions are made. This second edition entails changes of several sorts. First, info-gap theory has found application in several new areas - especially biological conservation, economic policy formulation, preparedness against terrorism, and medical decision-making. Pertinent new examples have been included. Second, the combination of info-gap analysis with probabilistic decision algorithms has found wide application. Consequently "hybrid" models of uncertainty, which were treated exclusively in a separate chapter in the previous edition, now appear throughout the book as well as in a separate chapter. Finally, info-gap explanations of robust-satisficing behavior, and especially the Ellsberg and Allais "paradoxes", are discussed in a new chapter together with a theorem indicating when robust-satisficing will have greater probability of success than direct optimizing with uncertain models. * New theory developed systematically. * Many examples from diverse disciplines. * Realistic representation of severe uncertainty. * Multi-faceted approach to risk. * Quantitative model-based decision theory.

This document proposes an extension to the Session Initiation Protocol (SIP). This extension adds the INFO method to the SIP protocol. The intent of the INFO method is to allow for the carrying of session related control information that is generated during a session. One example of such session control information is ISUP and ISDN signaling messages used to control telephony call services.

This study compares two widely used approaches for robustness analysis of decision problems: the info-gap method originally developed by Ben-Haim and the robust decision making (RDM) approach originally developed by Lempert, Popper, and Bankes. The study uses each approach to evaluate alternative paths for climate-altering greenhouse gas emissions given the potential for nonlinear threshold responses in the climate system, significant uncertainty about such a threshold response and a variety of other key parameters, as well as the ability to learn about any threshold responses over time. Info-gap and RDM share many similarities. Both represent uncertainty as sets of multiple plausible futures, and both seek to identify robust strategies whose performance is insensitive to uncertainties. Yet they also exhibit important differences, as they arrange their analyses in different orders, treat losses and gains in different ways, and take different approaches to imprecise probabilistic information. The study finds that the two approaches reach similar but not identical policy recommendations and that their differing attributes raise important questions about their appropriate roles in decision support applications. The comparison not only improves understanding of these specific methods, it also suggests some broader insights into robustness approaches and a framework for comparing them.

Purpose To study the effect of Knightian uncertainty – as opposed to statistical estimation error – in the evaluation of value‐at‐risk (VaR) of financial investments. To develop methods for augmenting existing VaR estimates to account for Knightian uncertainty. Design/methodology/approach The value at risk of a financial investment is assessed as the quantile of an estimated probability distribution of the returns. Estimating a VaR from historical data entails two distinct sorts of uncertainty: probabilistic uncertainty in the estimation of a probability density function (PDF) from historical data, and non‐probabilistic Knightian info‐gaps in the future size and shape of the lower tail of the PDF. A PDF is estimated from historical data, while a VaR is used to predict future risk. Knightian uncertainty arises from the structural changes, surprises, etc., which occur in the future and therefore are not manifested in historical data. This paper concentrates entirely on Knightian uncertainty and does not consider the statistical problem of estimating a PDF. Info‐gap decision theory is used to study the robustness of a VaR to Knightian uncertainty in the distribution. Findings It is shown that VaRs, based on estimated PDFs, have no robustness to Knightian errors in the PDF. An info‐gap safety factor is derived that multiplies the estimated VaR in order to obtain a revised VaR with specified robustness to Knightian error in the PDF. A robustness premium is defined as a supplement to the incremental VaR for comparing portfolios. Practical implications The revised VaR and incremental VaR augment existing tools for evaluating financial risk. Originality/value Info‐gap theory, which underlies this paper, is a non‐probabilistic quantification of uncertainty that is very suitable for representing Knightian uncertainty. This enables one to assess the robustness to future surprises, as distinct from existing statistical techniques for assessing estimation error resulting from randomness of historical data.

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Integrated fan-out wafer-level packaging (InFO-WLP) technology with state-of-the-art inductors (quality factor of 42 and self-resonance frequency of 16 GHz) has been demonstrated for heterogeneous integration of digital and radio frequency (RF) systems. InFO-WLP promises superior form factor, pin count, and thermal performance to existing flip-chip ball grid array (FC-BGA) packages. In addition, InFO-WLP's high Q inductors can enhance electrical performance and lower power consumption in RF circuit applications.

Summary Info‐gap decision theory ( IGDT ) seeks to provide a framework for rational decision‐making in situations of severe uncertainty. The theory proposes non‐probabilistic models of uncertainty and requires relatively small information inputs when compared to alternative theories of uncertainty. Info‐gap decision theory has been criticised because it is based upon models that do not guarantee good decisions in situations of severe uncertainty, where severe means a ‘very large’ uncertainty space and very poor initial estimates of the unknown elements in this space. This paper reviews the use of this method in ecology where it is receiving interest in applied environmental management applications. Paradoxically, ecological applications of IGDT focus almost exclusively on only one source of uncertainty in ecological problems, model parameter uncertainty, and typically ignore other sources, particularly model structure uncertainty and dependence between parameters, that can be just as severe. Ecologists and managers contemplating the use of IGDT should carefully consider its strengths and weaknesses, reviewed here, and not turn to it as a default approach in situations of severe uncertainty, irrespective of how this term is defined. We identify four areas of concern for IGDT in practice: sensitivity to initial estimates, localised nature of the analysis, arbitrary error model parameterisation and the ad hoc introduction of notions of plausibility.

MOTIVATION: The structure of RNA molecules is often crucial for their function. Therefore, secondary structure prediction has gained much interest. Here, we consider the inverse RNA folding problem, which means designing RNA sequences that fold into a given structure. RESULTS: We introduce a new algorithm for the inverse folding problem (INFO-RNA) that consists of two parts; a dynamic programming method for good initial sequences and a following improved stochastic local search that uses an effective neighbor selection method. During the initialization, we design a sequence that among all sequences adopts the given structure with the lowest possible energy. For the selection of neighbors during the search, we use a kind of look-ahead of one selection step applying an additional energy-based criterion. Afterwards, the pre-ordered neighbors are tested using the actual optimization criterion of minimizing the structure distance between the target structure and the mfe structure of the considered neighbor. We compared our algorithm to RNAinverse and RNA-SSD for artificial and biological test sets. Using INFO-RNA, we performed better than RNAinverse and in most cases, we gained better results than RNA-SSD, the probably best inverse RNA folding tool on the market. AVAILABILITY: www.bioinf.uni-freiburg.de?Subpages/software.html.

Abstract The application PERMAKART of the glaciological information system KRYO on ARC/INFO plots supposed mountain permafrost distribution on any topographical map. Results of fieldwork since 1970 and surface analyses based on a digital terrain model (DTM) are used. In Switzerland PERMAKART could become a planning tool for decisions about possible occurrence of mountain permafrost because the DTM RIMINI is available for the entire country.

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Wireless networking is becoming an increasingly important communication means, yet high wide--area wireless data connectivity is difficult to achieve due to technological and physical limitations. To alleviate these problems we experiment with an alternative by placing many high bandwidth local "islands" of info--stations dispersed throughout the low bandwidth wide--area wireless network. The location and distribution of the individual stations is crucial for the network's overall effectiveness, as demonstrated by our investigations. The info--stations are deployed in a transparent manner, often not geographically visible to the user. Applications must be designed to be mobile--aware and able to account for changing network characteristics by optimally utilizing the available network resources. We simulate alternative network layouts and determine their effectiveness by experimenting with an incremental map downloading application for road travelers that uses intelligent prefetching to...