Eliciting and measuring hesitance in decision-making

Hesitance is an innate human psychological phenomenon pervasive in our daily life. Although it is very complex and still not fully understood, there have been many studies related to this interesting topic. In this study, we proposed two fundamental problems about hesitance: the first is the generating problem, which is related to how to elicit hesitance information from human thinking; the second is the measuring problem, which is related to how to devise effective and reasonable methods to measure hesitance degrees from given hesitance information. With these two fundamental questions, we first discussed and analyzed several examples in real life involving hesitance, showing that it can indeed be recorded and represented. Then we roughly classified the hesitance information into two major classes: static hesitance and dynamic hesitance. Some simple and interesting methods were proposed to elicit hesitance, and more reasonable methods were proposed to measure the hesitance degree from the two classes of hesitance information. All methods that have been discussed in this study try to avoid complexity in every aspect while reserving strictness and reasonability; therefore, the present study provides suitable information for practitioners with different backgrounds.     

Distance and similarity measures of Pythagorean fuzzy sets based on the Hausdorff metric with application to fuzzy TOPSIS

Pythagorean fuzzy sets (PFSs) were proposed by Yager in 2013 to treat imprecise and vague information in daily life more rigorously and efficiently with higher precision than intuitionistic fuzzy sets. In this paper, we construct new distance and similarity measures of PFSs based on the Hausdorff metric. We first develop a method to calculate a distance between PFSs based on the Hasudorff metric, along with proving several properties and theorems. We then consider a generalization of other distance measures, such as the Hamming distance, the Euclidean distance, and their normalized versions. On the basis of the proposed distances for PFSs, we give new similarity measures to compute the similarity degree of PFSs. Some examples related to pattern recognition and linguistic variables are used to validate the proposed distance and similarity measures. Finally, we apply the proposed methods to multicriteria decision-making by constructing a Pythagorean fuzzy Technique for Order Preference by Similarity to an Ideal Solution and then present a practical example to address an important issue related to social sector. Numerical results indicate that the proposed methods are reasonable and applicable and also that they are well suited in pattern recognition, linguistic variables, and multicriteria decision-making with PFSs.     

破碎围岩回采巷道锚网索支护参数优化

针对镇城底煤矿8"煤层工作面巷道围岩破碎、支护困难等问题,分析了原有巷道支护方式失效的原因,进而针对性的优化了巷道支护参数,采用①20 mm X 2500 mm左旋螺纹钢锚杆,①17.8 mm X 6500 mm锚索,并进行了验算。最后通过现场实测巷道顶板离层量得到有效的控制,实现了安全髙效开采。     

Self-learning residual model for fast intra CU size decision in 3D-HEVC

As an extension of the High Efficiency Video Coding (HEVC) standard, 3D-HEVC requires to encode multiple texture views and depth maps, which inherits the same quad-tree coding structure as HEVC. Due to the distinct properties of texture views and depth maps, existing fast intra prediction approaches were presented for the coding of texture views and depth maps, respectively. To further reduce the coding complexity of 3D-HEVC, a self-learning residual model-based fast coding unit (CU) size decision approach is proposed for the intra coding of both texture views and depth maps. Residual signal, which is defined as the difference between the original luminance pixel and the optimal prediction luminance pixel, is firstly extracted from each CU. Since residue signal is strongly correlated with the optimal CU partition, it is used as the feature of each CU. Then, a self-learning residual model is established by intra feature learning, which iteratively learns the features of the previously encoded coding tree unit (CTU) generated by itself. Finally, a binary classifier is developed with the self-learning residual model to early terminate CU size decision of both texture views and depth maps. Experimental results show the proposed fast intra CU size decision approach achieves 33.3% and 49.3% encoding time reduction on average for texture views and depth maps with negligible loss of overall video quality, respectively.     

Numerical study of flow distribution uniformity for the optimization of gradient porosity configuration of porous copper fiber sintered felt for hydrogen production through methanol steam reforming micro-reactor

A macroscopic numerical method is proposed to study the flow distribution uniformity of a novel porous copper fiber sintered felt (PCFSF), which has gradient porosities and was developed as the methanol steam reforming micro-reactor catalyst support for hydrogen production for fuel cell applications. The macroscopic porous media developed by the ANSYS/FLUENT software is used to represent the PCFSF. Our results indicate that the gradient porosity can reshape the flow distribution of PCFSFs greatly, thus producing significant influence on their performance. It is further revealed that, for a PCFSF with a determined gradient porosity configuration but different reactant feed directions, the velocity uniformity can be used as a quantitative criterion to evaluate the performance of hydrogen production. Furthermore, new gradient PCFSFs are produced according to the flow distribution of original gradient PCFSFs. The preliminary experimental results of the new gradient PCFSFs of 0.8-0.9-0.7 and 0.7-0.9-0.8 exhibit better methanol conversion and H₂ flow rate. This indicates that the numerical method can be used for the optimization of PCFSFs' gradient porosity configuration, which consists of the shape and position of the interfaces between different porosity portions, the number of interfaces and the porosity distribution in different portions.     

航空装备保障智能化发展认识与探讨

自新一代人工智能技术迅猛发展以来，世界各国在智能领域动作频繁，军事化应用明显有加速之势，给装备保障带来了变革性发展的机遇。紧密围绕作战-装备-技术-保障之间的依托关系，从作战需求、装备特点、装备设计、诊断测试和技术驱动等五个角度梳理了装备保障发展的关键因素，给出了装备保障60余载发展历程的诸多原因和显著成果；通过对未来作战模式和未来作战平台保障需求的前瞻性判断，分析了未来作战需求和装备牵引装备保障转变的典型技术特征；并在装备保障领域人工智能技术的发展和应用现状总结分析的基础上，系统地提出了装备保障智能化发展的建设性意见和建议，为国内装备保障智能化发展探索了一个可能的技术方向。     

Some picture fuzzy Bonferroni mean operators with their application to multicriteria decision making

In this paper, we extend the Bonferroni mean (BM) operator with the picture fuzzy numbers (PFNs) to propose novel picture fuzzy aggregation operators and demonstrate their application to multicriteria decision making (MCDM). On the basis of the algebraic operational rules of PFNs and BM, we introduce some aggregation operators: the picture fuzzy Bonferroni mean, the picture fuzzy normalized weighted Bonferroni mean, and the picture fuzzy ordered weighted Bonferroni mean. Then, a new picture fuzzy MCDM method is proposed with the help of the proposed operators. Lastly, a practical application of proposed model is given to verify the developed model and related results of the proposed model is compared with the results of the existing models to indicate its applicability.     

多次动压影响下的煤柱巷道围岩控制技术

针对岳城矿煤柱巷道受叠加应力、多次动压影响、围岩控制难度大、支护效果不理想等现状,提出了高压注浆配合强力锚索补强的综合加固方案。现场矿压监测结果表明,加固后的巷道围岩保持了较好的完整性,顶板下沉量、两帮移近量都控制在设计要求之内,说明该方案能够显著提高巷帮破碎围岩的整体塑性,确保巷道安全掘进。     

User-friendly search interface for older adults: supporting search goal refreshing in working memory to improve information search strategies

ABSTRACT

This study investigates how a search interface that displays users’ ultimate query (i.e. users’ current search goal) can cope with the age-related decrease of fluid abilities and support older users’ search behaviours. 30 young and 18 older adults completed 9 search problems with a regular web browser or with the experimental search interface. Results showed that older adults spent longer time on the search engine result pages, they needed more time to reformulate, and they had more difficulties exploring the search paths elaborated. Age-differences also appeared as soon as the beginning of the search. The support tool helped older users reformulate their queries more rapidly and elaborate more flexible search strategies at the beginning of the activity. Indeed, older adults who interacted with the support tool switched to the processing of a new search path more rapidly instead of exploiting their initial query (i.e. they visited fewer websites for the initial query produced and reformulated a query instead of keeping on conducting a deeper investigation of the search results provided in the search engine result page). Implications of these findings for the design of effective support tools for older users are discussed.     

A one-class peeling method for multivariate outlier detection with applications in phase I SPC

In phase I of statistical process control (SPC), control charts are often used as outlier detection methods to assess process stability. Many of these methods require estimation of the covariance matrix, are computationally infeasible, or have not been studied when the dimension of the data, $p$, is large. We propose the one-class peeling (OCP) method, a flexible framework that combines statistical and machine learning methods to detect multiple outliers in multivariate data. The OCP method can be applied to phase I of SPC, does not require covariance estimation, and is well suited to high-dimensional data sets with a high percentage of outliers. Our empirical evaluation suggests that the OCP method performs well in high dimensions and is computationally more efficient and robust than existing methodologies. We motivate and illustrate the use of the OCP method in a phase I SPC application on a $N=354$, $p=1917$ dimensional data set containing Wikipedia search results for National Football League (NFL) players, teams, coaches, and managers. The example data set and R functions, OCP.R and OCPLimit.R, to compute the respective OCP distances and thresholds are available in the supplementary materials.