Resilience: Enhancing well-being through the positive cognitive triad.

The present study tested whether the relationships among resilience, life satisfaction, and depression could be explained by positive views toward the self, the world, and the future (positive cognitive triad). Structural equation modeling and mediation analyses were conducted based on 1,419 college students in Hong Kong. The model of positive cognitive triad as mediator between resilience and well-being fit the data (comparative fit index = .94, Tucker–Lewis index = .93, root-mean-square error of approximation = .08). Findings showed resilience to be significantly related to positive cognitions about the self, the world, and the future. Individuals who had higher level of resilience held significantly more positive cognitions and reported significantly higher levels of life satisfaction and lower levels of depression. The utility of the positive cognitive triad as the mechanism through which resilience enhances well-being was supported. Applications in cultivating resilience and positive cognitions in counseling services are discussed. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Preparation and characteristics of fine-grained ferroelectric glass-ceramic composites via a modified hybrid route at low temperature sintering

Dense, homogeneous and fully developed fine-grained ferroelectric Pb(Zr_0.53Ti_0.47)O₃?Cbased glass-ceramics have been successfully prepared at a low-sintering temperature of 850?C900°C by a modified hybrid process in air. The influence of the PbO-B₂O₃-SiO₂ (abbreviated as PBS) glass-gel content on the microstructure, dielectric, and ferroelectric properties of such glass-ceramics has been investigated. The temperature dependence of the dielectric constant indicated that the fine-grained Pb(Zr_0.53Ti_0.47)O₃ (abbreviated as PZT(53/47)) based glass-ceramic shows the characteristic dispersion at the Curie point. Ferroelectric hysteresis loop analyses have been performed to manifest the ferroelectric nature of the highly crystallized PZT(53/47) phase prepared by this modified novel hybrid process despite containing higher wt% glass-gel contents. The best dielectric and ferroelectric properties in a typical sample with 5% by weight of glass-gel content were found to have dielectric constant and loss tangent of 920 and 0.02 at 1 kHz, respectively. The saturation polarization (P _s ), and remanent polarization (P _r ) as well as the coercive field (E _c ) are 21.9 ??C/cm², 10.8 ??C/cm² and 2.19 kV/mm, respectively.     

Quay crane scheduling in container terminals

The problem of scheduling identical quay cranes moving along a common linear rail to handle containers for a ship is studied. The ship has a number of container-stacking compartments called bays, and only one quay crane can work on a bay at the same time. The objective of the scheduling problem is to find the work schedule for each quay crane which minimizes the ship’s stay time in port. Finding the optimal solution of the scheduling problem is computationally intractable and a heuristic is proposed to solve it. The heuristic first decomposes the difficult multi-crane scheduling problem into easier subproblems by partitioning the ship into a set of non-overlapping zones. The resulting subproblems for each possible partition are solved optimally by a simple rule. An effective algorithm for finding tight lower bounds is developed by modifying and enhancing an effective lower-bounding procedure proposed in the literature. Computational experiments were carried out to evaluate the performance of the heuristic on a set of test problems randomly generated based on typical terminal operations data. The computational results show that the heuristic can indeed find effective solutions for the scheduling problem, with the heuristic solutions on average 4.8% above their lower bounds.     

An effective heuristic for scheduling a yard crane to handle jobs with different ready times

In land-constrained port container terminals, yard cranes are commonly used for handling containers in a container yard to load containers onto or unload containers from trucks. However, yard cranes are bulky, slow and need to move frequently between their work locations. As it is common that the container flow in a terminal is bottlenecked by yard crane operations, effective work schedules of yard cranes are needed to increase the terminal’s throughput. This article studies the problem of scheduling a yard crane to perform a given set of container handling jobs with different ready times. The objective is to minimize the sum of job waiting times. It is noted that the scheduling problem is NP-complete. This research develops a heuristic to solve the scheduling problem and an algorithm to find lower bounds for benchmarking the schedules found by the heuristic. The performance of the heuristic is evaluated by a set of test problems generated on the basis of real-life terminal operations data. Indeed, the computational results show that the proposed heuristic can find effective solutions for the scheduling problem.     

Distributed project scheduling with information sharing in supply chains: part I—an agent-based negotiation model

Distributed project scheduling problem (DPSP) in supply chains is concerned with configuration and scheduling of multiple projects in a network of independent and autonomous enterprises. Individual enterprises must collaborate with each other during two main stages: the configuration of a project—selection of contractors for performing project operations and the project scheduling—determining when the operations start. However, the collaboration is especially difficult because none of these enterprises holds the global information about the entire supply chain and all constituent enterprises. Instead, they have to capitalize whatever information is shared between them in order to solve their own local problems in a distributed and autonomous fashion. It is essential for the solution process to strike an overall balance between effectiveness and efficiency. The research, reported in this two-part paper, is aimed at proposing a negotiation-based algorithm for solving DPSP. Its emphasis is how to improve the convergence and quality of the solution by taking advantage of inter-enterprise information sharing especially the sharing of schedule flexibility information (SFI). The first part of this paper describes a new agent-based approach to DPSPs in supply chains while the second part will present detailed discussion on the theoretical and experimental analysis.     

Machine learning for multimodality genomic signal processing

This paper discusses how machine learning can be applied to genomic signal processing, particularly via fusion of multiple biological or algorithmic modalities, to improve prediction performance.     

An empirical measure of element contribution in neural networks

A frequent complaint about neural net models is that they fail to explain their results in any useful way. The problem is not a lack of information, but an abundance of information that is difficult to interpret. When trained, neural nets will provide a predicted output for a posited input, and they can provide additional information in the form of interelement connection strengths. This latter information is of little use to analysts and managers who wish to interpret the results they have been given. We develop a measure of the relative importance of the various input elements and hidden layer elements, and we use this to interpret the contribution of these components to the outputs of the neural net     

The collaborative information portal and NASA's Mars Rover mission

NASA Ames Research Center and the Jet Propulsion Laboratory jointly developed the collaborative information portal for NASA's Mars exploration rover mission. Mission managers, engineers, scientists, and researchers used this Internet-based enterprise software application to view current staffing and event schedules, download data and image files generated by the rovers, send and receive broadcast messages, and get accurate times in various Mars and Earth time zones. This article describes the application's features, architecture, and implementation, and conveys the lessons learned from its deployment.