Optimistic Make

The notion of encapsulations is introduced as the basic construct used to support optimistic make (a software tool). The authors describe the implementation of optimistic make in the V-System on a collection of SUN workstations. Statistics measured from this implementation are used to synthesize a workload for a discrete-event simulation, and to validate the simulation's results. The simulation shows a speedup distribution over pessimistic make with a median of 1.72 and a mean of 8.28. The speedup distribution is strongly dependent on the ratio between the target out-of-date times and the command execution times. With faster machines the median of the speedup distribution grows to 5.1, and then decreases agai

Do Happy People Make Optimistic Investors?

Do happy people predict future risk and return differently from unhappy people, or do individuals rely only on economic facts? We survey investors on their subjective sentiment-creating factors, return and risk expectations, and investment plans. We find that non-economic factors systematically affect return and risk expectations, where the return effect is more profound. Investment plans are also affected by non-economic factors. Sports results and general feelings significantly affect predictions. Sufferers from seasonal affective disorder have lower return expectations in the autumn than in other seasons, supporting the Winter Blues hypothesis

Performance of Optimistic Make

Optimistic make is a version of make that executes the commands necessary to bring targets up-to-date prior to the time the user types a make request. Side effects of these optimistic computations (such as file or screen updates) are concealed until the make request is issued. If the inputs read by the optimistic computations are identical to the inputs the computation would read at the time the make request is issued, the results of the optimistic computations are used immediately, resulting in improved response time. Otherwise, the necessary computations are reexecuted. We have implemented optimistic make in the V-System on a collection of SUN-3 workstations. Statistics collected from this implementation are used to synthesize a workload for a discrete-event simulation and to validate its results. The simulation shows a speedup distribution over pessimistic make with a median of 1.72 and a mean of 8.28. The speedup distribution is strongly dependent on the ratio between the target out-of-date times and the command execution times. In particular, with faster machines the median of the speedup distribution grows to 5.1, and then decreases again. The extra machine resources used by optimistic make are well within the limit of available resources, given the large idle times observed in many workstation environment

Load sharing for optimistic parallel simulations on multicore machines

Parallel Discrete Event Simulation (PDES) is based on the partitioning of the simulation model into distinct Logical Processes (LPs), each one modeling a portion of the entire system, which are allowed to execute simulation events concurrently. This allows exploiting parallel computing architectures to speedup model execution, and to make very large models tractable. In this article we cope with the optimistic approach to PDES, where LPs are allowed to concurrently process their events in a speculative fashion, and rollback/ recovery techniques are used to guarantee state consistency in case of causality violations along the speculative execution path. Particularly, we present an innovative load sharing approach targeted at optimizing resource usage for fruitful simulation work when running an optimistic PDES environment on top of multi-processor/multi-core machines. Beyond providing the load sharing model, we also define a load sharing oriented architectural scheme, based on a symmetric multi-threaded organization of the simulation platform. Finally, we present a real implementation of the load sharing architecture within the open source ROme OpTimistic Simulator (ROOT-Sim) package. Experimental data for an assessment of both viability and effectiveness of our proposal are presented as well. Copyright is held by author/owner(s)

Optimal Time-Inconsistent Beliefs: Misplanning, Procrastination, and Commitment

We develop a structural theory of beliefs and behavior that relaxes the assumption of time consistency in beliefs. Our theory is based on the trade-off between optimism, which raises anticipatory utility, and objectivity, which promotes efficient actions. We present it in the context of allocating work on a project over time, develop testable implications to contrast it with models assuming time-inconsistent preferences, and compare its predictions to existing evidence on behavior and beliefs. Our predictions are that (i) optimal beliefs are optimistic and time inconsistent; (ii) people optimally exhibit the planning fallacy; (iii) incentives for rapid task completion make beliefs more optimistic and worsen work smoothing, whereas incentives for accurate duration prediction make beliefs less optimistic and improve work smoothing; (iv) without a commitment device, beliefs become less optimistic over time; and (v) in the presence of a commitment device, beliefs may become more optimistic over time, and people optimally exhibit preference for commitment

Multimedia information technology and the annotation of video

The state of the art in multimedia information technology has not progressed to the point where a single solution is available to meet all reasonable needs of documentalists and users of video archives. In general, we do not have an optimistic view of the usability of new technology in this domain, but digitization and digital power can be expected to cause a small revolution in the area of video archiving. The volume of data leads to two views of the future: on the pessimistic side, overload of data will cause lack of annotation capacity, and on the optimistic side, there will be enough data from which to learn selected concepts that can be deployed to support automatic annotation. At the threshold of this interesting era, we make an attempt to describe the state of the art in technology. We sample the progress in text, sound, and image processing, as well as in machine learning

The planning fallacy and group predictions: Are groups more or less biased than individuals?

Research on the “planning fallacy shows that people tend to make overly optimistic predictions about the time it will take to complete a task,despite knowing that similar tasks in the past have exceeded predicted completion times. Although the planning fallacy has been well documented in individuals, few researchers have examined how groups make predictions interactively. The main purposes of this thesis are to examine whether people make overly optimistic predictions for group projects and whether group discussion exacerbates this optimistic bias. In three studies, participants were asked to make predictions for an upcoming collaborative task alter engaging in group discussion (discussion condition) or silent thought (no discussion condition). In Study 1, participants overestimated how long it would take to complete a puzzle together in a laboratory setting. A plausible explanation is that inexperience with the task led to this pessimistic bias. In Study 2, participants again completed a puzzle together; however, this time they were given information about previous completion times and a monetary incentive to finish quickly. In Study 3, participants were given an incentive to complete a group take-home assignment. In addition, half of the participants in Studies 2 and 3 made an initial, private prediction prior to the group discussion manipulation. In both of these studies, participants tended to underestimate how long the task would take, and group discussion led to more optimistic predictions. Overall, the results of these studies suggest that group discussion may ofien heighten rather than attenuate optimistic biases in task prediction

Doing Too Little or Too Much to Recover from Product Failure:

This study investigated differences between optimistic and pessimistic customers in their responses to recovery strategies for defective goods and services. We found that optimistic customers are more lenient, stay more loyal; not only when offered replacement of the defective product, but also when provided only a quick fix. When a token gift is added to a replacement, pessimistic but not optimistic customers respond with greater leniency. When a token gift is added to a quick fix, optimistic customers respond with lesser leniency. We suggest that companies can make the error of doing too much, not just the error of doing too little