Pessimistic Strategy Research Articles

Predicting Ordination, Early-Career Mobility, and Career Adaptation from Ministerial Applicants’ Psychological Assessment Results

The occupational group of ordained ministers is currently facing two types of change: the role of religion in Western societies is transforming, and the boundaryless work culture is expanding even further. As the profession is becoming more demanding, leaving clergy has become a worldwide problem across denominations. Churches are therefore increasingly applying psychological assessments to screen their applicants for ministry. Surprisingly, no studies have yet looked into the connections of these assessment results and later job-person fit: eventual ordination, early-career turnover and commitment, or early-career job performance and job satisfaction. In this study, personality metatraits (stability and plasticity), general mental ability, and social and attributional strategies were assessed for 785 persons heading for ordination in the Evangelical Lutheran Church in Finland during 2006-2010. In a follow-up in 2012 (n = 314, 40 %), career mobility and career adaptation were inspected. The results indicate that the most influential feature is the determination of the applicant. Other aspects related to a successful career pattern were stability and absence of pessimistic strategies. The study confirms that personality metatraits are an applicable approach in selection assessment. Overall, the study provides an outlook on the entry stage recruitment to a vocational religious occupation in the boundaryless age of work.

Diagnosable evaluation of enhanced optical transpose interconnection system networks

The process of identifying faulty processors is called diagnosis of the system. Several models of diagnosis have been proposed, the most popular being the PMC (Preparata, Metze and Chien) diagnostic model proposed by Preparata et al. in 1967. The precise strategy correctly identifies all faulty processors while the pessimistic strategy isolates all faulty processors within a set containing at most one fault-free processor. For a multiprocessor system, diagnosability is critical to measure its performance. The enhanced optical transpose interconnection system (enhanced OTIS), network has important applications in parallel processing. In this network architecture, n2 processors are divided into n groups of n processors; processors in the same group are connected by electronic links while the groups are simultaneously connected by optical links. An enhanced OTIS network is regular if its base graph G is regular. In this paper, we discuss fault diagnosis in an enhanced OTIS network, including both the precise strategy and pessimistic strategy under the PMC diagnostic model.

A Fast Pessimistic Diagnosis Algorithm for Hypercube-Like Networks under the Comparison Model

Diagnosis by comparison is a realistic approach to detect faults of multiprocessor systems. This paper considers a pessimistic diagnostic strategy for hypercube-like multiprocessor systems under the comparison model. The pessimistic strategy is a diagnostic process whereby all faulty nodes can be correctly identified and at most one fault-free node may be misjudged as a faulty node. We propose a pessimistic diagnosis algorithm based on the largest component in the faulty system. For a system with <inline-formula><tex-math notation="LaTeX">$N=2^n$</tex-math></inline-formula> nodes and <inline-formula> <tex-math notation="LaTeX">$n\ge 5$</tex-math></inline-formula> , when the number of faulty nodes is bounded by <inline-formula> <tex-math notation="LaTeX">$2n-2$</tex-math></inline-formula> , the algorithm can correctly identify all nodes except at most one node left undiagnosed. The time complexity of the algorithm is <inline-formula><tex-math notation="LaTeX">$O(Nlog_2N)$</tex-math> </inline-formula> .

Abstraction refinement guided by a learnt probabilistic model

The core challenge in designing an effective static program analysis is to find a good program abstraction -- one that retains only details relevant to a given query. In this paper, we present a new approach for automatically finding such an abstraction. Our approach uses a pessimistic strategy, which can optionally use guidance from a probabilistic model. Our approach applies to parametric static analyses implemented in Datalog, and is based on counterexample-guided abstraction refinement. For each untried abstraction, our probabilistic model provides a probability of success, while the size of the abstraction provides an estimate of its cost in terms of analysis time. Combining these two metrics, probability and cost, our refinement algorithm picks an optimal abstraction. Our probabilistic model is a variant of the Erdos--Renyi random graph model, and it is tunable by what we call hyperparameters. We present a method to learn good values for these hyperparameters, by observing past runs of the analysis on an existing codebase. We evaluate our approach on an object sensitive pointer analysis for Java programs, with two client analyses (PolySite and Downcast).

A Method to Determine Generalized Basic Probability Assignment in the Open World

Dempster-Shafer evidence theory (D-S theory) has been widely used in many information fusion systems since it was proposed by Dempster and extended by Shafer. However, how to determine the basic probability assignment (BPA), which is the main and first step in D-S theory, is still an open issue, especially when the given environment is in an open world, which means the frame of discernment is incomplete. In this paper, a method to determine generalized basic probability assignment in an open world is proposed. Frame of discernment in an open world is established first, and then the triangular fuzzy number models to identify target in the proposed frame of discernment are established. Pessimistic strategy based on the differentiation degree between model and sample is defined to yield the BPAs for known targets. If the sum of all the BPAs of known targets is over one, then they will be normalized and the BPA of unknown target is assigned to0; otherwise the BPA of unknown target is equal to1minus the sum of all the known targets BPAs. IRIS classification examples illustrated the effectiveness of the proposed method.

A Hybrid Concurrency Control Strategy for Mobile Database Systems

The inherent limitations of mobile database systems makes concurrency control an important problem. Several pessimistic and optimistic strategies for achieving concurrency control in mobile database systems are presented in literature. The pessimistic strategies achieve concurrency however they face the problem of blocking, whereas the optimistic strategies may not always keep the data consistent. The conflict resolution strategies may result in starvation of some of the mobile requests. This paper presents a hybrid concurrency control strategy by using the good properties of both pessimistic and optimistic approaches. The results specify that the proposed strategy performs better as compared to both pessimistic and optimistic strategies and reduces the starvation of transaction requests of various mobile devices.

System Reliability Evaluation Based on Convex Combination Considering Operation and Maintenance Strategy

The approaches to the system reliability evaluation with respect to the cases, where the components are independent or the components have interactive relationships within the system, were proposed in this paper. Starting from the higher requirements on system operational safety and economy, the reliability focused optimal models of multiobjective maintenance strategies were built. For safety-critical systems, the pessimistic maintenance strategies are usually taken, and, in these cases, the system reliability evaluation has also to be tackled pessimistically. For safety-uncritical systems, the optimistic maintenance strategies were usually taken, and, in these circumstances, the system reliability evaluation had also to be tackled optimistically, respectively. Besides, the reasonable maintenance strategies and their corresponding reliability evaluation can be obtained through the convex combination of the above two cases. With a high-speed train system as the example background, the proposed method is verified by combining the actual failure data with the maintenance data. Results demonstrate that the proposed study can provide a new system reliability calculation method and solution to select and optimize the multiobjective operational strategies with the considerations of system safety and economical requirements. The theoretical basis is also provided for scientifically estimating the reliability of a high-speed train system and formulating reasonable maintenance strategies.

A Linear Time Pessimistic Diagnosis Algorithm for Hypermesh Multiprocessor Systems under the PMC Model

In microprocessor-based systems, such as the cloud computing infrastructure, high reliability is essential. As multiprocessor systems become more widespread and increasingly complex, system-level diagnosis will increasingly be adopted to determine their robustness. In this paper, we consider a pessimistic diagnostic strategy for hypermesh multiprocessor systems under the PMC model. The pessimistic strategy is a diagnostic process whereby all faulty processors are correctly identified and at most one fault-free processor may be misjudged to be a faulty processor. We first determine the pessimistic diagnosability of a hypermesh to be ${2}{{n}}({{k}} - {1}) - {{k}}$ . We then propose an efficient pessimistic diagnostic algorithm to identify at most ${ 2}{{n}}({{k}} - { 1}) - {{k}}$ faults in ${{O}}({{N}})$ time, where ${\mbi{k}}$ is the radix, ${\mbi{n}}$ is the number of dimensions, and ${{N}} = {{k^n}}$ is the total number of processors. This result is superior to the best precise diagnostic algorithm, which runs in ${{O}}({{N}}{\log _{{k}}}{{N}})$ time. Furthermore, the Cartesian product network, a subgraph of the hypermesh and the proposed algorithm can be employed to determine faults in the product network.

Design of optimal groundwater remediation systems under flexible environmental-standard constraints.

In developing optimal groundwater remediation strategies, limited effort has been exerted to solve the uncertainty in environmental quality standards. When such uncertainty is not considered, either over optimistic or over pessimistic optimization strategies may be developed, probably leading to the formulation of rigid remediation strategies. This study advances a mathematical programming modeling approach for optimizing groundwater remediation design. This approach not only prevents the formulation of over optimistic and over pessimistic optimization strategies but also provides a satisfaction level that indicates the degree to which the environmental quality standard is satisfied. Therefore the approach may be expected to be significantly more acknowledged by the decision maker than those who do not consider standard uncertainty. The proposed approach is applied to a petroleum-contaminated site in western Canada. Results from the case study show that (1) the peak benzene concentrations can always satisfy the environmental standard under the optimal strategy, (2) the pumping rates of all wells decrease under a relaxed standard or long-term remediation approach, (3) the pumping rates are less affected by environmental quality constraints under short-term remediation, and (4) increased flexible environmental standards have a reduced effect on the optimal remediation strategy.

A Fast Fault-Identification Algorithm Tailored for Optical Interconnection Networks in High-Performance Computers

Due to integrated positive features of both hypercube and tori, optical multi-mesh hypercube (OMMH) networks in high-performance computers are regarded as a class of promising optical inter-connection networks. This paper firstly derive that the diagnosability of OMMH under the pessimistic strategy is (2n+6)/(2n+6), which shows that the OMMH possesses strong self-diagnosingability. With the improved cycle decomposition method by Yang in J. Parall. Distrib. Comput. [10], a fast diagnosis algorithm to identify all faulty nodes tailored for OMMH, which runs in O(Nlog2N) time is also proposed, where N is the number of the processors of an OMMH.

A multiobjective optimization framework for optimal selection of supplier portfolio

Supplier selection problem has been a typical concern of optimization where good supplier selection is essential for firms in the context of supply chain management. If a firm networks with different suppliers, each one having its own advantages over the others, then there is great opportunity to reduce a firm’s risk arising from supply concentration and also to provide it with the opportunity to leverage its comparative strength. In this paper, we propose a new approach referred to as Supplier Portfolio Optimization (SPO) that improves the state of the art of supplier selection by incorporating the benefits of supplier diversification using the trade-offs between the criteria of expected unit price, expected score of quality and expected score of delivery. We present three different optimization models with interval coefficients to model the uncertain SPO problem corresponding to optimistic, pessimistic and combination strategies. Further, using lower and upper bonds for fractions of order quantity, we ensure supplier portfolio diversification and also avoidance of the situation of impractical fraction of quantity ordered. Numerical experiments conducted on a dataset of a multinational firm are provided to demonstrate the applicability and efficiency of the SPO models to real-world applications of supplier selection.

Exploring multi-criteria decision strategies in GIS with linguistic quantifiers: an extension of the analytical network process using ordered weighted averaging operators

Many real-world spatial planning and management problems give rise to a geographical information system (GIS)-based multi-criteria decision-making. Analytical network process (ANP) provides a comprehensive methodology for representing complex multi-criteria decision-making problems as a network of criteria and alternatives, where feedback and interdependence relationships may exist within and between all the criteria and alternatives. Experts’ experiences are used to estimate relative magnitudes of tangible and intangible factors through paired comparisons in order to make rational and consistent decisions. However, the GIS-based ANP, an adoption of weighted linear aggregation rule, typically employed a high trade-off decision strategy and neglected other decision strategies. This paper develops a novel GIS-based multi-criteria evaluation (MCE) procedure by extending the ANP using fuzzy quantifiers-guided ordered weighted averaging (OWA) operators. This extension, which generalizes the aggregation process used in the ANP, would provide a generic powerful decision-making tool that allows decision-makers to define a decision strategy on a continuum between pessimistic (risk-averse) and optimistic (risk-taking) strategies. By changing the linguistic quantifiers, the GIS-based ANP–OWA can generate a wide range of decision strategies taking into accounts the level of risk the decision-makers wish to assume in their MCE. A land-use suitability analysis in a region of Saudi Arabia is presented to demonstrate the application of the proposed procedure.

Fault isolation and identification in general biswapped networks under the PMC diagnostic model

Processor fault identification in a multiprocessor system plays an important role in reliable computing. The process of identifying faulty processors is called the diagnosis of the system. Several diagnostic models have been proposed, the most popular being the PMC (Preparata, Metze and Chen) diagnostic model proposed in 1967. The precise strategy and the pessimistic strategy are two classical diagnostic strategies based on the PMC model. The precise strategy correctly identifies all faulty nodes. The pessimistic diagnosis strategy isolates all faulty nodes within a set containing at most one fault-free node. General biswapped networks were proposed in 2007 as interconnection networks amenable to implementation using a mix of electronic and optical communication links. The model is inspired by and extended from biswapped networks and OTIS networks. In this paper, we focus on the diagnosabilities of general biswapped networks under the precise and pessimistic strategies based on the PMC diagnostic model. It is proved that the general biswapped network Gbsw(G,H) with δ(G)⩾1 and δ(H)⩾1 is t-diagnosable and t1/t1-diagnosable under the precise and the pessimistic strategies, respectively, where t is the minimum node degree of the network and t1 is the minimum number of neighbors of any pair of nodes. In addition, a pessimistic diagnosis algorithm for general biswapped networks is proposed and the algorithm can run in O(t1N) time where N denotes the total number of nodes in the network.

A Quick Pessimistic Diagnosis Algorithm for Hypercube-Like Multiprocessor Systems under the PMC Model

Processor fault diagnosis is an essential subject for the reliability of a multiprocessor system. The precise strategy and the pessimistic strategy are two classical diagnostic strategies which are based on the well-known PMC model. The precise strategy problem of fault diagnosis is discussed widely and demands that all processors be identified correctly, specifically that all fault-free processors are identified as "fault free” and all faulty processors are identified as "faulty.” The pessimistic diagnosis strategy is a process to diagnose faults that allows all faulty processors to be isolated within a set that contains at most one fault-free processor. In this paper, we study the pessimistic diagnosis strategy under the PMC model for hypercube-like multiprocessor systems. The contribution is to propose an efficient pessimistic diagnosis algorithm for hypercube-like multiprocessor systems. If we denote by N the total number of processors in the hypercube-like system to be diagnosed, the algorithm can run in O(N) time.

Amphicarpy in Trifolium argentinense: morphological characterisation, seed production, reproductive behaviour and life strategy

Trifolium argentinense Speg. is an amphicarpic species that occurs naturally in native pastures of Rio Grande do Sul, southern Brazil. Amphicarpy is a rare mode of reproduction in which aerial and subterranean seeds are produced by the same individual. In the present paper, we compare morphology, anther number, pollen viability, seed production and mode of reproduction of T. argentinense flowers, and comment on the life strategy of the species. Plants grown from aerial seeds and from the regrowth of storage roots of aerial plants had longer stolons and a larger plant diameter than did those grown from subterranean plants. Plants grown from seeds were also taller than plants grown from storage roots. More resources were allocated to subterranean reproduction in plants of subterranean origin than in those of aerial origin. Aerial flowers produced more seeds, presented more anthers and produced more pollen grains than did the subterranean ones. T. argentinense is a versatile species, self- and cross-pollinated, consistent with the values of high polymorphism information content. T. argentinense adopts the ‘pessimistic strategy’ (early allocation of energy to large subterranean propagules), common in amphicarpic species when growing in disturbed habitats, such as the native pastures of Rio Grande do Sul, where intense grazing and trampling, as well as long seasonal dry spells, may periodically destroy the aerial plants, thus assuring survival by germination of subterranean seeds and regrowth of storage roots.

The diagnosability of the k-ary n-cubes using the pessimistic strategy

The pessimistic strategy, also called the t 1/t 1-diagnosis strategy, allows to contain all faulty vertices and at most one fault-free vertex. However, the degree of the diagnosability of a system increases quickly using the pessimistic strategy. In this paper, we consider the k-ary n-cube, which is an important hypercube variant, and show that the 3-ary n-cube and k-ary n-cube with k≥4 are (4n−3)/(4n−3)-diagnosable and (4n−2)/(4n−2)-diagnosable, respectively. Finally, we obtain the degree of the diagnosability of the tori using the pessimistic strategy.

Confronting the Past

Confronting the Past

Pessimistic attributions and coping strategies as predictors of depressive symptoms in people with coronary heart disease

This two-wave longitudinal study examines the ability of pessimistic attributional style and coping strategies to predict depressive symptoms in a sample of 99 patients with coronary heart disease (CHD). After the cardiac episode, the globality dimension of this style was associated with increased depressive symptoms, and this association was mediated by the low use of effective coping strategies. Stability and globality dimensions of pessimistic attributional style could also predict depressive symptoms eight weeks later. Cardiac intervention programmes should include the treatment of these symptoms and promote effective coping strategies as well as the modification of these stable and global attributions.

Trajectories of depressive symptoms during emerging adulthood: Antecedents and consequences

In order to examine what kinds of trajectories of depressive symptoms young adults show during emerging adulthood, and their antecedents and consequences, 297 university students completed the revised Beck's depression inventory seven times over a 10-year period, and other measures at the beginning and the end of the study. The growth mixture modelling for depressive symptoms ended up in a 3-group solution: 23% of the participants were typified by a low level of symptoms, 61% showed a moderate level, and 16% fell into the third group with high and increasing levels of depressive symptoms during emerging adulthood. Those on the high-depressive trajectory had a poorer quality of relationships, and they reported more pessimistic and avoidant strategies at the beginning of the study than the others. Moreover, later on, they suffered more from burnout, earned less, and used more dysfunctional strategies.

The t/k-diagnosability of the BC graphs

Processor fault diagnosis takes an important role in fault-tolerant computing on multiprocessor systems. There are two classical diagnosis strategies - the precise strategy and the pessimistic strategy, both of which are based on the well-known PMC diagnostic model. Nevertheless, the degree of diagnosability of the system is limited under these two strategies. A better method, called the t/k-diagnosis strategy, is proposed by Somani and Peleg, in which the identified fault-set is allowed to contain at most k fault-free processors. Using this diagnosis strategy, the degree of diagnosability of the hypercube increases greatly as the number of the fault-free processors in the fault-set increases. We study the t/k-diagnosability of so-called BC graphs that include hypercubes, crossed cubes, Mobius cubes, and twisted cubes, etc. We show that any n-dimensional BC graph is t(n, k)/k-diagnosable when n/spl ges/4 and 0/spl les/k/spl les/n, where t(n,k)=(k+1)n-1/2(k+1)(k+2)+1. Therefore, the crossed cube, the Mobius cube, and the twisted cube all have the same t/k-diagnosability as the hypercube. As a result, the algorithms developed for diagnosis on the hypercube may also be used to diagnose multiprocessor systems whose network topologies are based on BC graphs.