Lagrangian relaxation hybrid with evolutionary algorithm for short-term generation scheduling

Short-term generation scheduling is an important function in daily operational planning of power systems. It is defined as optimal scheduling of power generators over a scheduling period while respecting various generator constraints and system constraints. Objective of the problem includes costs associated with energy production, start-up cost and shut-down cost along with profits. The resulting problem is a large scale nonlinear mixed-integer optimization problem for which there is no exact solution technique available. The solution to the problem can be obtained only by complete enumeration, often at the cost of a prohibitively computation time requirement for realistic power systems. This paper presents a hybrid algorithm which combines Lagrangian Relaxation (LR) together with Evolutionary Algorithm (EA) to solve the problem in cooperative and competitive energy environments. Simulation studies were carried out on different systems containing various numbers of units. The outcomes from different algorithms are compared with that from the proposed hybrid algorithm and the advantages of the proposed algorithm are briefly discussed.     

On the Subjective Quality of Social Justice: The Role of Affect as Information in the Psychology of Justice Judgments.

This article argues that it is not uncommon for people forming justice judgments to lack information that is most relevant in the particular situation. In information-uncertain conditions, people may therefore construct justice judgments by relying on how they feel about the events they have encountered, and justice judgments may hence be strongly influenced by affect information. Findings show that in information-uncertain conditions, the affective states that people had been in prior and unrelated to the justice event indeed strongly influenced their justice judgments. These findings thus reveal that in situations of information uncertainty, people's judgments of justice can be very subjective, susceptible to affective states that have no logical relationship with the justice judgments they are constructing. Implications for the social psychology of justice and the literature on social cognition and affect are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Methodological Challenges in Union Commitment Studies.

Methodological problems in studies of union commitment were identified and illustrated with data from 4,641 members and 479 stewards in 297 local teachers' unions. Using a 20-item union commitment scale, results confirmed the existence of 3 substantive factors and 1 method factor at the individual level of analysis: loyalty to the union, responsibility to the union, willingness to work for the union, and a factor of negatively worded items. Tests of measurement invariance showed that the scale captured commitment for rank-and-file members but not for union stewards. The authors also found partial measurement invariance between long-time and newer members and full measurement invariance between men and women. Finally, the authors found that violation of the statistical assumption of independence reduced model fit when individual commitment scores were analyzed without attention to the hierarchical nature of the data. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Nodal ant colony optimization for solving profit based unit commitment problem for GENCOs

This paper proposes a nodal ant colony optimization (NACO) technique to solve profit based unit commitment problem (PBUCP). Generation companies (GENCOs) in a competitive restructured power market, schedule their generators with an objective to maximize their own profit without any regard for system social benefit. Power and reserve prices become important factors in decision process. Ant colony optimization that mimics the behavior of ants foraging activities is suitably implemented to search the UCP search space. Here a search space consisting of optimal combination of binary nodes for unit ON/OFF status is represented for the movement of the ants to maintain good exploration and exploitation search capabilities. The proposed model help GENCOs to make decisions on the quantity of power and reserve that must be put up for sale in the markets and also to schedule generators in order to receive the maximum profit. The effectiveness of the proposed technique for PBUCP is validated on 10 and 36 generating unit systems available in the literature. NACO yields an increase of profit, greater than 1.5%, in comparison with the basic ACO, Muller method and hybrid LR-GA.     

Perceived control over caregiving outcomes: Implications for child abuse.

We predicted low perceived caregiver control over caregiving failure to be related to (a) coercive or abusive parenting and (b) affective reactions to "difficult" children. On the basis of a multidimensional scaling analysis of the Parent Attribution Test (Study 1), we constructed a scale (PCF) that assessed perceived balance of control over caregiving failure (attributed control to caregivers vs attributed control to children). In Study 2, we found low PCF to predict abusiveness and nonabusive coerciveness among mothers in counseling at a child abuse agency. Additionally, we found low PCF to predict experienced annoyance/irritation among unrelated mothers interacting with children at relatively high risk for abuse (compared with their lower-risk siblings). We interpreted results as demonstrating the potential importance of low perceived control as a moderator of negative affect in response to difficult children. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Paving the way for CRM success: The mediating role of knowledge management and organizational commitment

Customer relationship management (CRM) has become one of the most influential technologies in the world, and companies are increasingly implementing it to create value. However, despite significant investment in CRM technology infrastructure, empirical research offers inconsistent support for its positive impact on performance. This study develops and tests a research model analyzing the process through which CRM technology infrastructure translates into organizational performance, drawing on the resource-based view (RBV) and the knowledge-based view (KBV) of the firm. Based on an international sample of 125 hotels, the results suggest that organizational commitment and knowledge management fully mediate this process.     

知识型员工工作态度与离职倾向关系的实证研究

采用实证法研究了知识型员工工作态度总体水平及各维度与离职倾向的关系,并建立了关系模型。研究结果表明：工作态度及其维度均与离职倾向显著负相关,且组织承诺对离职倾向的影响大于工作满意度;规范承诺、内在满意度、情感承诺、外在满意度、持续承诺依次成为影响知识型员工离职倾向的主要因素,均负相关。     

ID-based trapdoor mercurial commitment under one-way functions assumptions

The notion of identity-based trapdoor mercurial commitment incorporates the advantages of both identity-based trapdoor commitment and trapdoor mercurial commitment. So far, the existing identity-based trapdoor mercurial commitment schemes are based on the strong Diffie-Hellman assumption or computational Diffie-Hellman assumption. One-way function existence is one of the fundamental assumptions in the cryptography. In this paper, we first propose a general construction for identity-based trapdoor mercurial commitment based on the one-way function. Meanwhile, we give a concrete instantiation based on the Boneh-Boyen signature scheme.     

Which symbol grounding problem should we try to solve?

Floridi and Taddeo propose a condition of ‘zero semantic commitment’ for solutions to the grounding problem, and a solution to it. I argue briefly that their condition cannot be fulfilled, not even by their own solution. After a look at Luc Steel's very different competing suggestion, I suggest that we need to re-think what the problem is and what role the ‘goals’ in a system play in formulating the problem. On the basis of a proper (syntactic) understanding of computing, I come to the conclusion that the only sensible grounding problem is how we can explain and re-produce the behavioural ability and function of meaning in artificial computational agents.