Automation literature: A brief review and analysis

Current thought and research positions which may allow for an improved capability to understand the impact of introducing automation to an existing system are established. The orientation was toward the type of studies which may provide some general insight into automation; specifically, the impact of automation in human performance and the resulting system performance. While an extensive number of articles were reviewed, only those that addressed the issue of automation and human performance were selected to be discussed. The literature is organized along two dimensions: time, Pre-1970, Post-1970; and type of approach, Engineering or Behavioral Science. The conclusions reached are not definitive, but do provide the initial stepping stones in an attempt to begin to bridge the concept of automation in a systematic progression

Effect of flow pattern at pipe bends on corrosion behaviour of low carbon steek and its challenges

Recent design work regarding seawater flow lines has emphasized the need to identify, develop, and verify critical relationships between corrosion prediction and flow regime mechanisms at pipe bend. In practice this often reduces to an pragmatic interpretation of the effects of corrosion mechanisms at pipe bends. Most importantly the identification of positions or sites, within the internal surface contact areas where the maximum corrosion stimulus may be expected to occur, thereby allowing better understanding, mitigation, monitoring and corrosion control over the life cycle. Some case histories have been reviewed in this context, and the interaction between corrosion mechanisms and flow patterns closely determined, and in some cases correlated. Since the actual relationships are complex, it was determined that a risk based decision making process using selected ‘what’ if corrosion analyses linked to ‘what if’ flow assurance analyses was the best way forward. Using this in methodology, and pertinent field data exchange, it is postulated that significant improvements in corrosion prediction can be made. This paper outlines the approach used and shows how related corrosion modelling software data such as that available from corrosion models Norsok M5006, and Cassandra to parallel computational flow modelling in a targeted manner can generate very noteworthy results, and considerably more viable trends for corrosion control guidance. It is postulated that the normally associated lack of agreement between corrosion modelling and field experience, is more likely due to inadequate consideration of corrosion stimulating flow regime data, rather than limitations of the corrosion modelling. Applications of flow visualization studies as well as computations with the k-ε model of turbulence have identified flow features and regions where metal loss is a maximu

Survey Evidence on the Rationality of Business Expectations: Implications from the Malaysian Agricultural Sector

The rational expectations hypothesis (REH) serves as an appealing mechanism in forming expectations compared to that of extrapolative or adaptive frameworks because of its consistency with the basic principles of maximizing behavior. This argument is particularly true as the basic idea of REH maintains that expectations in an uncertain world are formed under assumptions where no systematic errors and information are fully utilized. However, empirical findings from the present study showed diverse evidence of rationality in business operational forecasts formed by Malaysian agriculture firms, as capital expenditure expectations were found to be irrational but gross revenue expectations were supportive of the REH proposition. This implies that the survey of business forecasts may not work well in reflecting the true business outlook, specifically in value-related operational forecasts, which in turn would directly influence investment decisions as well as the capital budgeting process.Rational Expectations Hypothesis; Unbiasedness Test; Non-serial Correlation Test; Weak-form Efficiency Test

Rational Expectations in the Macro Model

macroeconomics, macro model

Prediction of the impact of network switch utilization on application performance via active measurement

Although one of the key characteristics of High Performance Computing (HPC) infrastructures are their fast interconnecting networks, the increasingly large computational capacity of HPC nodes and the subsequent growth of data exchanges between them constitute a potential performance bottleneck. To achieve high performance in parallel executions despite network limitations, application developers require tools to measure their codes’ network utilization and to correlate the network’s communication capacity with the performance of their applications. This paper presents a new methodology to measure and understand network behavior. The approach is based in two different techniques that inject extra network communication. The first technique aims to measure the fraction of the network that is utilized by a software component (an application or an individual task) to determine the existence and severity of network contention. The second injects large amounts of network traffic to study how applications behave on less capable or fully utilized networks. The measurements obtained by these techniques are combined to predict the performance slowdown suffered by a particular software component when it shares the network with others. Predictions are obtained by considering several training sets that use raw data from the two measurement techniques. The sensitivity of the training set size is evaluated by considering 12 different scenarios. Our results find the optimum training set size to be around 200 training points. When optimal data sets are used, the proposed methodology provides predictions with an average error of 9.6% considering 36 scenarios.With the support of the Secretary for Universities and Research of the Ministry of Economy and Knowledge of the Government of Catalonia and the Cofund programme of the Marie Curie Actions of the 7th R&D Framework Programme of the European Union (Expedient 2013BP_B00243). The research leading to these results has received funding from the European Research Council under the European Union’s 7th FP (FP/2007-2013) /ERC GA n. 321253. Work partially supported by the Spanish Ministry of Science and Innovation (TIN2012-34557)Peer ReviewedPostprint (author's final draft

Assessing, Managing, and Financing Extreme Events: Dealing with Terrorism

This paper discusses new challenges we face with terrorism as a catastrophic risk by focusing on risk assessment, risk management as well as risk financing issues. The special characteristics of terrorism compared with major natural hazards call for the development of public-private partnerships, as recognized in November 2002 when the Terrorism Risk Insurance Act of 2002 (TRIA) was passed. This paper shows, however, that the temporary insurance system established by TRIA is neither a complete answer nor a definitive one. It raises fundamental questions for U.S. insurers as to how they will estimate the risk in order to set premiums for terrorist coverage that they now must offer to their clients. We discuss some of the most recent developments of terrorism models for helping insurers and reinsurers assess the premiums they should charge and how much coverage they can assume as well as for firms to better understand their exposure. Since the passage of TRIA, the current level of demand for insurance coverage has remained low and we discuss some factors that may contribute to it. After presenting alternative foreign public-private partnerships and discussing the potential role for terrorist catastrophe bonds, we provide some features of a more sustainable program for terrorism insurance in the U.S. after December 31, 2005.

Exploiting variability for energy optimization of parallel programs

In this paper we present optimizations that use DVFS mechanisms to reduce the total energy usage in scientific applications. Our main insight is that noise is intrinsic to large scale parallel executions and it appears whenever shared resources are contended. The presence of noise allows us to identify and manipulate any program regions amenable to DVFS. When compared to previous energy optimizations that make per core decisions using predictions of the running time, our scheme uses a qualitative approach to recognize the signature of executions amenable to DVFS. By recognizing the "shape of variability" we can optimize codes with highly dynamic behavior, which pose challenges to all existing DVFS techniques. We validate our approach using offline and online analyses for one-sided and two-sided communication paradigms. We have applied our methods to NWChem, and we show best case improvements in energy use of 12% at no loss in performance when using online optimizations running on 720 Haswell cores with one-sided communication. With NWChem on MPI two-sided and offline analysis, capturing the initialization, we find energy savings of up to 20%, with less than 1% performance cost

The Advantage of Custom Microprocessors for Stochastic Gradient Descent in Graph-Based Robot Localization and Mapping

Simultaneous Localization and Mapping (SLAM) describes a class of problems facing a large and growing field of autonomous systems -- from self-driving cars, to interplanetary rovers, to home automation products. Unfortunately this is a complex task where sophisticated algorithms and data structures are required to navigate a wide range of uncharted environments. Furthermore, most mobile robots need to run these tasks near real-time onboard an embedded controller with limited power and compute resources. To address this problem we explore the stochastic gradient descent (SGD) variant of graph solvers for SLAM and observe a tradeoff between various execution architectures and overall execution speed. Based on these observations, we propose a custom multiprocessor design that relaxes memory-coherency constraints between parallel cores while avoiding divergent behavior. We introduce a specialized streaming-tree interconnect that provides increased performance while using fewer resources compared to state-of-art GPU/CPU implementations of SGD. Finally, we discuss applications of unconventional architectural paradigms like over-provisioned “dark processors” and specialized data partitioning that provided a unique performance advantage for our particular design

Grand challenges in social physics: in pursuit of moral behavior

Methods of statistical physics have proven valuable for studying the evolution of cooperation in social dilemma games. However, recent empirical research shows that cooperative behavior in social dilemmas is only one kind of a more general class of behavior, namely moral behavior, which includes reciprocity, respecting others' property, honesty, equity, efficiency, as well as many others. Inspired by these experimental works, we here open up the path toward studying other forms of moral behavior with methods of statistical physics. We argue that this is a far-reaching direction for future research that can help us answer fundamental questions about human sociality. Why did our societies evolve as they did? What moral principles are more likely to emerge? What happens when different moral principles clash? Can we predict the break out of moral conflicts in advance and contribute to their solution? These are amongst the most important questions of our time, and methods of statistical physics could lead to new insights and contribute toward finding answers

Macrosociology, rational choice theory and time: a theoretical perspective on the empirical analysis of social processes

"In the first part of this paper, Blossfeld discusses some of the historical reasons why the explosion of rational choice scholarship in the social sciences has had surprisingly little influence on macro-sociological data analysis. In the second part, he shows that any theoretically powerful sociological analysis of a macro-sociological problem must pay attention to both structural- and micro-Ievel issues but not in the usual static way. Any macro-micro framework must recognize that time is significant in this relationship. It must identify the particular historical structures and processes that dominate the changes occurring in a given population, and it must specify the causal mechanisms that allow us to trace the encounters of intentionally acting individuals with the flow of history as a series of choice processes."Die Studie diskutiert einige der vorwiegend historischen Gründe, warum das explosionsartige Anwachsen des rational-choice-Ansatzes in den Sozialwissenschaften bisher nur einen relativ geringen Einfluß auf die makrosoziologische Datenanalyse hat. In kritischer Auseinandersetzung mit dem rational-choice-Ansatz weist der Autor darauf hin, daß eine theoretisch fruchtbare Analyse makrosoziologischer Probleme nicht auf dem bisher üblichen statistischen Weg erfolgen kann. Jeder Makro-Mikro-Ansatz hat den Zeitfaktor zu berücksichtigen, der die Beziehung der Ebenen signifikant beeinflußt. Dazu müssen die besonderen historischen Strukturen und Prozesse in einer gegebenen Gesellschaft bzw. Population erfaßt und der spezifische kausale Mechanismus identifiziert werden, der die Intentionen von individuellen Akteuren mit dynamischen historischen Prozessen auf der Makroebene vermittelt. Am Beispiel des Heiratsverhaltens werden einige der theoretischen Annahmen demonstriert. (pre