营造积极的校园户外交往空间

以西南交大新校区图书馆东面广场作为研究对象,通过统计分析的方法对问卷进行分析得出评价结果,总结了广场的优点与不足,并且提出了相应的改进建议,对校园景观设计起到借鉴和启发意义。     

Using hybrid scheduling for the semi-autonomous formation of expert teams

Selecting and scheduling human experts to cooperatively solve a problem can be a highly complex task, given various constraints (such as what expertise is needed and when) and preferences (such as which expertise an expert most prefers to exercise). Computational agents can thus greatly help users form and schedule expert teams. This paper introduces a new formulation of the team formation and scheduling problem as a Hybrid Scheduling Problem (HSP) and compares the performance of an agent using the HSP formulation to a prior agent-based approach. We empirically demonstrate the promise of the HSP formulation and highlight how the application of HSP techniques to this problem has led us to identify important modifications to mechanisms that improve HSP solving. Finally, we summarize how the HSP formulation can support human-agent collaboration during the process of forming and scheduling expert teams.     

BOSSA: a multidimensional post-occupancy evaluation tool

Research findings point to three methodological shortcomings of current post-occupancy evaluation (POE) tools: (1) contextualizing results, (2) adding instrumental data side by side to survey results and (3) producing meaningful feedback to its key stakeholders. This paper introduces the holistic BOSSA (Building Occupants Survey System Australia) and tools developed under this project's scope in close collaboration with industry. It aims to present and discuss the statistical analysis used in the BOSSA tool, distilling the survey results down to nine indoor environmental quality (IEQ) dimensions and their association with four overall indices. Principal component analysis (PCA) extracted nine IEQ dimensions that were uncorrelated with each other: spatial comfort, indoor air quality, personal control, noise distraction and privacy, connection to the outdoor environment, building image and maintenance, individual space, thermal comfort, and visual comfort. Four separate multiple regression analyses were conducted, one for each global evaluation item as an independent variable: work area comfort, building satisfaction, productivity and health. This statistical analysis provided the rational basis of BOSSA's scoring system, designed to simplify how occupant survey results are communicated to key stakeholders from the property industry and researchers.     

Effects of perceived indoor temperature on daylight glare perception

This research investigates the effects of perceived indoor temperature on glare sensation. A laboratory experiment was carried out where volunteers (n?=?19) performed an office-like computer task. Three scenarios with sunspots over the desk were evaluated: a cold scenario, a comfort scenario and a hot scenario. All had the same vertical illuminance at the eye and luminance ratios. Discomfort glare was measured with the predictive daylight glare probability (DGP) model; actual perception of glare was assessed with glare sensation vote (GSV) scale; while thermal comfort was evaluated with thermal sensation vote (TSV) scale. In order to know how much the perceived temperature contributes to the model, an ordinal regression was performed. The result showed a Nagelkerke pseudo-R²?=?0.52, p =?0.001, indicating that the perceived temperature affected glare predictions. This is an improvement in the understanding of daylight glare, which will allow researchers and practitioners to make informed decisions about sustainable design and occupant comfort. In conclusion, a more comprehensive glare model should include perceived temperature as a variable of the current glare model. Also, the results suggest that DGP should be used only when the person is in thermal comfort.     

Intelligent customer complaint handling utilising principal component and data envelopment analysis (PDA)

In this study, we consider customer to be a company's crucial asset. In order to have a fast, efficient decision-making process, it is vital that a customer relationship management (CRM) decision-maker condenses and abstracts the existing information. A questionnaire survey was conducted among respondents in order to obtain the required data. The questionnaire contains nine categories of satisfaction variables. To perform the analysis, we used principal component analysis (PCA) and data envelopment analysis (DEA). PDA has been utilised as an abbreviation for the integration of these two methods. To effectively analyse the procedure, PCA was utilised to assign a number to each category of questions related to each satisfaction variable. To achieve optimal precision, DEA was applied to the three categories of customers (‘most important’, ‘important’ and ‘ordinary’ customers) in order to determine the strengths and weaknesses of customer services from these customers’ perspectives. Customers were clustered and then DEA was used to determine their viewpoints. Using DEA, we have optimised our recognition of customers’ complaints and then provided recommendations and remedial actions to resolve the current issues in logistics and transport industry in general, and at Fremantle port in particular.SignificanceThe current study integrates soft computing and optimisation technique in order to build the CRM recommender system. It demonstrates the hybrid soft computing strengthens in area of CRM as the relevance solution. The significance of the proposed algorithm is three fold. First, it integrates soft computing and optimisation technique in order to build the CRM recommender system. Second, it utilises the most standard CRM variables in its decision making process. Third, it is an optimising algorithm because it integrates DEA with PCA technique.     

Customer satisfaction evaluation method for customized product development using Entropy weight and Analytic Hierarchy Process

Providing customized products with high customer satisfaction (CS) has become an inevitable trend for modern customized companies to remain competitive. This study proposes a CS evaluation method for customized product development using Entropy weight and Analytic Hierarchy Process (AHP). Firstly, customer requirements are identified based on Voice-of-Customer (VoC), and classified into four categories (positive, negative, must-be and fuzzy attributes) according to the characteristics of CS criteria. Then, CS evaluation model and its solution method are introduced in detail. This study especially focuses on the quantitative methods for each category of the evaluation criteria through formulating several mathematical models, and criteria weights are obtained through integrating Entropy weight and AHP method. Finally, a case study of applying the proposed methodology to customized portrait-based product industry demonstrates the functionality of the proposed methodology.     

Multi-way versus one-way constraints in user interfaces: Experience with the deltablue algorithm

The efficient satisfaction of constraints is essential to the performance of constraint-based user interfaces. In the past, most constraint-based user interfaces have used one-way rather than multi-way constraints because of a widespread belief that one-way constraints were more efficient. In this paper we argue that many user interface construction problems are handled more naturally and elegantly by multi-way constraints than by one-way constraints. We present pseudocode for an incremental multi-way constraint satisfaction algorithm, DeltaBlue, and describe experience in using the algorithm in two user interface toolkits. Finally, we provide performance figures demonstrating that multi-way constraint solvers can be entirely competitive in performance with one-way constraint solvers.     

Psychotherapy Outcome and Satisfaction: Methods Applied to Intensive Outpatient Programming in a Private Practice Setting.

This study evaluated an Intensive Outpatient Program (IOP) in a private practice setting. Patients received the Symptom Checklist-90--Revised pre- and posttreatment and the Client Satisfaction Questionnaire-8 posttreatment, which were used to measure symptom change and client satisfaction. Reliable Change Indices and Clinically Significant change scores were calculated for each individual (N=225) using several variables from therapist and clinician perspectives. Highly significant improvement rates on client symptom ratings were also validated by clinician global assessment of functioning ratings, client satisfaction, and discharge rates to lower levels of care. This IOP was demonstrated to be more effective than psychotherapy in clinically representative studies, randomized clinical trials, and controlled clinical trials as well as comparable to many widely used medical interventions. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Partition search for non-binary constraint satisfaction

Previous algorithms for unrestricted constraint satisfaction use reduction search, which inferentially removes values from domains in order to prune the backtrack search tree. This paper introduces partition search, which uses an efficient join mechanism instead of removing values from domains. Analytical prediction of quantitative performance of partition search appears to be intractable and evaluation therefore has to be by experimental comparison with reduction search algorithms that represent the state of the art. Instead of working only with available reduction search algorithms, this paper introduces enhancements such as semijoin reduction preprocessing using Bloom filtering.     

基于满意度大规模含整变量多目标决策方法

针对具有块角结构的大规模含整变量多目标决策问题，提出一种基于目标满意度的交互式分解协调方法。定义了若干概念，给出了若干定理，介绍了交互式决策方法的具体步骤，并对其软件实现作了说明。