Attribute Importance Ranking Research Articles

THE VOLUNTARINESS OF DISPUTANTS IN CONSTRUCTION MEDIATION

Mediation has been promoted to resolve construction disputes due to much-heralded time and cost advantages. Formal introduction was affected in early 20’s after several successful pro bono mediation pilots. In Hong Kong, immense promotional efforts have been directed to make mediation the mainstream mechanism for alternative dispute resolution. Despite promotional efforts, a disheartening decline in use of mediation was noted after an initial surge. For wider adoption, there has been an ongoing debate on before disputing parties resorting other forms of dispute resolution, whether courts should compel them to attempt mediation. This study examines pillars of successful mediation and seeks to reveal the root causes of Hong Kong's sluggish uptake of construction. Review of literature informed key mediation attributes and manifestations of voluntariness in construction dispute mediation. Scale rating by construction professionals was employed to establish mediation attribute importance ranking as well as representativeness of manifestation of voluntary participation. "The exchange of critical information is effective" and "The disputant considers the mediator trustworthy" were ranked as the two most important mediation attributes, suggesting the importance of having a conducive environment for genuine communication. It is therefore proposed that voluntary participation is a necessary condition to create a collegial atmosphere. “Working cooperatively with the mediator” and “Preparing settlement options before attending the mediation” were the top two ranked manifestations of voluntary participation. Most research on mediation mainly focus on the advantages of mediation. Findings of this study raise the caveat when disputants are asked to attempt mediation that erodes voluntary participation.

AN INTELLIGENT POSTOPERATIVE CHRONIC PAIN PREDICTION SYSTEM (I-POCPP)

Objective: Postoperative Chronic Pain (POCP) affects the quality of patients’ lives. Machine learning and its applications provide significant contributions to pain research. The aim of this study is to predict the POCP status of patients based on perioperative data by developing an “Intelligent POCP Prediction System (I-POCPP)” using the best performing machine learning algorithm. Material and Method: The dataset for this multi-centered study was collected from 5 tertiary hospitals in Turkey and included 733 patients who had undergone elective surgeries attended by an anesthesiologist in the operating room. Several machine learning prediction algorithms were used. POCP status of the patients diagnosed by the anesthesiologists and the prediction results of the models were compared to evaluate the performance of the models. Results: It was found that the k-Nearest Neighbour (kNN), Random Forest (RF), and C5.0 models were able to predict the POCP status of a patient with an accuracy higher than 80%. The performance of RF was considered, while the kNN algorithm has no stable model. According to RF and Classification and Regression Tree (CART) algorithms’ attribute importance ranking, “Incision site”, “Age”, and “Primary diagnosis for operation” are common attributes. Since the attribute importance ranking obtained as a result of the C5.0 algorithm was not consistent with the RF and CART models, the results of this model were not evaluated. The best result among all models was obtained by RF, and I-POCPP has been developed accordingly. Conclusion: Fast, accurate, and efficient treatment of POCP provided by I-POCPP could allow the patient to return to daily life earlier.

THE VOLUNTARINESS OF DISPUTANTS IN CONSTRUCTION MEDIATION

Mediation has been promoted to resolve construction disputes due to much-heralded time and cost advantages. Formal introduction was affected in early 20’s after several successful pro bono mediation pilots. In Hong Kong, immense promotional efforts have been directed to make mediation the mainstream mechanism for alternative dispute resolution. Despite promotional efforts, a disheartening decline in use of mediation was noted after an initial surge. For wider adoption, there has been an ongoing debate on before disputing parties resorting other forms of dispute resolution, whether courts should compel them to attempt mediation. This study examines pillars of successful mediation and seeks to reveal the root causes of Hong Kong's sluggish uptake of construction. Review of literature informed key mediation attributes and manifestations of voluntariness in construction dispute mediation. Scale rating by construction professionals was employed to establish mediation attribute importance ranking as well as representativeness of manifestation of voluntary participation. "The exchange of critical information is effective" and "The disputant considers the mediator trustworthy" were ranked as the two most important mediation attributes, suggesting the importance of having a conducive environment for genuine communication. It is therefore proposed that voluntary participation is a necessary condition to create a collegial atmosphere. “Working cooperatively with the mediator” and “Preparing settlement options before attending the mediation” were the top two ranked manifestations of voluntary participation. Most research on mediation mainly focus on the advantages of mediation. Findings of this study raise the caveat when disputants are asked to attempt mediation that erodes voluntary participation.

Perceived Quality Attributes Importance Ranking Methodology in the Automotive Industry: A Case Study on Geometry Appearance Attributes at CEVT.

Implementation of methods for perceived quality evaluation is an integral part of the automotive manufacturers’ strategic development plans. The correct definition of perceived quality requirements is one of the significant factors influencing customer’s purchase intention. This study seeks to understand how customers perceive and prioritize attributes that are associated with the geometrical and materials quality of a premium car market segment. We applied the Perceived Quality Attributes Importance Ranking (PQAIR) methodology to understand the importance of different perceived quality attributes form a customer perspective. Such an understanding can contribute to the effectiveness of the design processes in the early product development phases. This approach is tested on 144 respondents representing customer’s target group and performed in collaboration with China Euro Vehicle Technology (CEVT) technical experts. Our results verify the rationality and feasibility of the applied method and indicate the improvement of engineering practices regarding complex product development.

XGBoost algorithm-based prediction of concrete electrical resistivity for structural health monitoring

For structural health monitoring, electrical resistivity measurement (ERM) method is commonly employed for the detection of concrete's durability, as indicated by the chloride permeability and the corrosion of steel reinforcement. However, according to previous experimental studies, ERM results are susceptible to significant uncertainties due to multiple influencing factors such as concrete water/cement ratio and structure curing environment as well as their complex interrelationships. The present study therefore proposes an XGBoost algorithm-based prediction model which considers all potential influential factors simultaneously. A database containing 800 experimental instances composed of 16 input attributes is constructed according to existing reported studies and utilized for training and testing the XGBoost model. Statistical scores (RMSE, MAE and R2) and the GridsearchCV feature are applied to evaluate and optimize the established model respectively. Results show that the proposed XGBoost model achieves satisfactory predictive performance as demonstrated by high coefficients of regression fitting lines (0.991 and 0.943) and comparatively low RMSE values (4.6 and 11.3 kΩ·cm) for both training and testing sets respectively. The analyses of the attribute importance ranking also reveal that curing age and cement content have the greatest influence on ERM results.

Design of the top tether component for the premium car market segment: Case study of Volvo Cars

The positive correlation between successful car design and high perceived quality is indisputable. In the highly competitive premium car market segment, the implementation of methods for perceived quality evaluation is an integral part of the strategic development plans of car manufacturers. However, to correctly define the perceived quality requirements and address market opportunities, the car manufacturers need to capture diverse customer demands. This study seeks to understand how customers perceive and prioritize attributes that are associated with the perceived quality of the premium car market segment. During the study, we evaluated the next generation top tether design concepts for Volvo Cars sedan models S60 and S90. The top tether is the part of an ISOFIX system used to connect a forward-facing child seat in a car and is a critical safety component significantly reducing potential injuries. We applied the Perceived Quality Attributes Importance Ranking (PQAIR) methodology to understand the importance of different perceived quality attributes from a customer perspective. In other words, we investigated the meaning of “premiumness” for the customers, applied to the specific car component. This approach was tested on 200 respondents representing the customer target group and was performed in collaboration with Volvo Cars technical experts. Our results verify the rationality of the applied method and indicate the improvement of engineering practices regarding the evaluation of perceived quality.

Understanding light. A study on the perceived quality of car exterior lighting and interior illumination

Illumination, or lighting, is one of the complex product attributes that significantly influences the perception of any motor vehicle. Car manufacturers are aiming to create a meaningful experience induced by the vehicle’s lighting. This study seeks a deeper understanding of customer preferences regarding the perceived quality of illumination. We applied the Perceived Quality Attributes Importance Ranking (PQAIR) methodology to understand the importance of perceived quality attributes related to the lighting perception. The approach was tested on 79 respondents and was performed in collaboration with China Euro Vehicle Technology (CEVT). Our results contribute to the effectiveness of the design processes in the early product development phases.

Perceived quality of products: a framework and attributes ranking method

ABSTRACTPerceived quality is one of the most critical aspects of product development that defines the successful design. This paper presents a new approach to perceived quality assessment by examining its elements, decomposed into a structure with the bottom-up sensory approach from the level of basic (‘ground’) attributes, covering almost every aspect of quality perception from the engineering viewpoint. The paper proposes a novel method for perceived quality attributes relative importance ranking, resulting in the balanced perceived quality of the final product within the given conditions. The proposed method helps to reach the equilibrium of the product’s quality equation from the perspective of design effort, time, and costs estimations. The authors introduce the Perceived Quality Framework (PQF), which is the taxonomy system for perceived quality attributes and the core of the attributes importance ranking (PQAIR) method. The research outcomes are based on findings of the qualitative exploratory study, including European and North American premium and luxury automotive manufacturers. An empirical structural validity test was performed to assess the usability and rigour of the proposed method. The results indicate that perceived quality evaluation can be significantly improved during all stages of product development.Abbreviations: PQF: Perceived Quality Framework; PQAIR: Perceived Quality Attributes Importance Ranking; TPQ: Technical Perceived Quality; VPQ: Value-based Perceived Quality; OEM: Original Equipment Manufacturer.

Perceived Quality Evaluation with the Use of Extended Reality

AbstractIf designers want to communicate quality aspects of the product, there is a need to bring these characteristics into the measurable space of perceived quality (PQ) attributes. To illustrate the solution for designers' dilemma of the “best design choice” in this study we applied the PQ attributes importance ranking (PQAIR) method, with the example of a bread toaster. We choose for evaluation three PQ attributes which can significantly influence visual quality of a product: Gap, Flush and Parallelism. We performed the experiment measuring subjective preferences over the toaster designs of two respondent's groups - “Designers” and “Customers.” We used sequentially: (i) web-survey (still images); (ii) desktop system; and (iii) fully immersive head-mounted display system (Virtual Reality).Consequently, we conducted a post-experiment survey regarding subjective preferences, related to the PQ communication channels that have been implemented during the study. Our results indicate advantages and drawbacks for each PQ communication method that we applied in this experiment and encourage further research in the area of products' perceived quality assessment

Orderly Roulette Selection Based Ant Colony Algorithm for Hierarchical Multilabel Protein Function Prediction

Ant colony optimization (ACO) algorithms have been successfully applied to identify classification rules in data mining. This paper proposes a new ant colony optimization algorithm, named hmAntMinerorder, for the hierarchical multilabel classification problem in protein function prediction. The proposed algorithm is characterized by an orderly roulette selection strategy that distinguishes the merits of the data attributes through attributes importance ranking in classification model construction. A new pheromone update strategy is introduced to prevent the algorithm from getting trapped in local optima and thus leading to more efficient identification of classification rules. The comparison studies to other closely related algorithms on 16 publicly available datasets reveal the efficiency of the proposed algorithm.

Investigating the complementary value of discrete choice experiments for the evaluation of barriers and facilitators in implementation research: a questionnaire survey

BackgroundThe potential barriers and facilitators to change should guide the choice of implementation strategy. Implementation researchers believe that existing methods for the evaluation of potential barriers and facilitators are not satisfactory. Discrete choice experiments (DCE) are relatively new in the health care sector to investigate preferences, and may be of value in the field of implementation research. The objective of our study was to investigate the complementary value of DCE for the evaluation of barriers and facilitators in implementation research.MethodsClinical subject was the implementation of the guideline for breast cancer surgery in day care. We identified 17 potential barriers and facilitators to the implementation of this guideline. We used a traditional questionnaire that was made up of statements about the potential barriers and facilitators. Respondents answered 17 statements on a five-point scale ranging from one (fully disagree) to five (fully agree). The potential barriers and facilitators were included in the DCE as decision attributes. Data were gathered among anaesthesiologists, surgical oncologists, and breast care nurses by means of a paper-and-pencil questionnaire.ResultsThe overall response was 10%. The most striking finding was that the responses to the traditional questionnaire hardly differentiated between barriers. Forty-seven percent of the respondents thought that DCE is an inappropriate method. These respondents considered DCE too difficult and too time-consuming. Unlike the traditional questionnaire, the results of a DCE provide implementation researchers and clinicians with a relative attribute importance ranking that can be used to prioritize potential barriers and facilitators to change, and hence to better fine-tune the implementation strategies to the specific problems and challenges of a particular implementation process.ConclusionThe results of our DCE and traditional questionnaire would probably lead to different implementation strategies. Although there is no 'gold standard' for prioritising potential barriers and facilitators to the implementation of change, theoretically, DCE would be the method of choice. However, the feasibility of using DCE was less favourable. Further empirical applications should investigate whether DCE can really make a valuable contribution to the implementation science.

Data dimensionality reduction with application to simplifying rbf network structure and improving classification performance

For high dimensional data, if no preprocessing is carried out before inputting patterns to classifiers, the computation required may be too heavy. For example, the number of hidden units of a radial basis function (RBF) neural network can be too large. This is not suitable for some practical applications due to speed and memory constraints. In many cases, some attributes are not relevant to concepts in the data at all. In this paper, we propose a novel separability-correlation measure (SCM) to rank the importance of attributes. According to the attribute ranking results, different attribute subsets are used as inputs to a classifier, such as an RBF neural network. Those attributes that increase the validation error are deemed irrelevant and are deleted. The complexity of the classifier can thus be reduced and its classification performance improved. Computer simulations show that our method for attribute importance ranking leads to smaller attribute subsets with higher accuracies compared with the existing SUD and Relief-F methods. We also propose a modified method for efficient construction of an RBF classifier. In this method we allow for large overlaps between clusters corresponding to the same class label. Our approach significantly reduces the structural complexity of the RBF network and improves the classification performance.