Subjective Preference Research Articles

HDR or SDR? A Subjective and Objective Study of Scaled and Compressed Videos.

We conducted a large-scale study of human perceptual quality judgments of High Dynamic Range (HDR) and Standard Dynamic Range (SDR) videos subjected to scaling and compression levels and viewed on three different display devices. While conventional expectations are that HDR quality is better than SDR quality, we have found subject preference of HDR versus SDR depends heavily on the display device, as well as on resolution scaling and bitrate. To study this question, we collected more than 23,000 quality ratings from 67 volunteers who watched 356 videos on OLED, QLED, and LCD televisions, and among many other findings, observed that HDR videos were often rated as lower quality than SDR videos at lower bitrates, particularly when viewed on LCD and QLED displays. Since it is of interest to be able to measure the quality of videos under these scenarios, e.g. to inform decisions regarding scaling, compression, and SDR vs HDR, we tested several well-known full-reference and no-reference video quality models on the new database. Towards advancing progress on this problem, we also developed a novel no-reference model called HDRPatchMAX, that uses a contrast-based analysis of classical and bit-depth features to predict quality more accurately than existing metrics.

Comfortable living in urban environments: implications for agricultural development and sustainable societies

The article analyzes the genesis of the phenomenon of comfort of living in the urban environment, the influence of objective factors and subjective needs on determining the level of comfort of residents, including in the context of the relationship with agriculture. An objective assessment is carried out on the basis of calculations of indicators of the quality of the urban environment, the provision of the population with the necessary set of services. Assessment of the quality of urban environment, as an objective indicator, demonstrates the effectiveness of public and municipal officials. For the current urban methodology to assess the quality of urban environment, the author proposed ten additional evaluation indicators. The concept of comfort is determined not only by economic welfare, but also by other indicators. Further research shows that no less significant for a full-fledged assessment of comfort is the consideration of subjective preferences of citizens. However, taking into account different historical and cultural traditions, national preferences, natural and climatic conditions and ecological situation, as well, it is difficult to quantitatively calculate a universal level of comfort. Accumulating previous studies, taking into account modern realities, the author offers an interpretation of the concept of “comfort of living”. Developing Layard’s theory, the author has developed a “Dial” of comfort of living, which takes into account the indicators “housing”, “environment” and “digital culture”. To calculate a quantitative assessment of the level of comfort of living, it is advised to use a combined method, taking into account both objectively established factors and subjective preferences of residents, as well. Thus, the issue of assessing the level of comfort of living should be further studied, taking into account the factors of housing, environment, digital communication tools and, possibly, new, emerging over time, factors of influence.

Learning Diverse Tone Styles for Image Retouching.

Image retouching, aiming to regenerate the visually pleasing renditions of given images, is a subjective task where the users are with different aesthetic sensations. Most existing methods adopt a deterministic model to learn the retouching style from a specific expert, making it less flexible to meet diverse subjective preferences. Besides, the intrinsic diversity of an expert due to the targeted processing of different images is also deficiently described. To circumvent such issues, we propose to learn diverse image retouching with normalizing flow-based architectures. Unlike current flow-based methods which directly generate the output image, we argue that learning in a one-dimensional style space could 1) disentangle the retouching styles from the image content, 2) lead to a stable style presentation form, and 3) avoid the spatial disharmony effects. For obtaining meaningful image tone style representations, a joint-training pipeline is delicately designed, which is composed of a style encoder, a conditional RetouchNet, and the image tone style normalizing flow (TSFlow) module. In particular, the style encoder predicts the target style representation of an input image, which serves as the conditional information in the RetouchNet for retouching, while the TSFlow maps the style representation vector into a Gaussian distribution in the forward pass. After training, the TSFlow can generate diverse image tone style vectors by sampling from the Gaussian distribution. Extensive experiments on MIT-Adobe FiveK and PPR10K datasets show that our proposed method performs favorably against state-of-the-art methods and is effective in generating diverse results to satisfy different human aesthetic preferences. Source codeterministic and pre-trained models are publicly available at https://github.com/SSRHeart/TSFlow.

Secondary School Students' Preferences for STEM Subjects as University Study Options

Secondary School Students' Preferences for STEM Subjects as University Study Options

ЭВОЛЮЦИЯ МОДЕЛИ ЭКОНОМИЧЕСКОГО ПОВЕДЕНИЯ ЧЕЛОВЕКА В УСЛОВИЯХ ЦИФРОВОЙ ТРАНСФОРМАЦИИ

The development of information and communication technologies and the rapid digitalization of public life are driving fundamental transformations of socio-economic systems into a knowledge society and a digital economy. The speed of change in recent decades leads to the fact that “traditional” economic models are losing their methodological sufficiency for the modern level of science and need to be rethought. As a result, the purpose of the article is to propose an updated model of human economic behavior in the context of digital transformation based on an analysis of the evolution of economic behavior models. To achieve the goal of the study, the following tasks were set: to analyze models of human economic behavior in economics and the humanities; highlight key aspects of digitalization that significantly influence changes in the socio-economic sphere of public life; characterize changes in human economic behavior generated by the digital transformation of society. As a result of the study, factors determining economic behavior in the digital economy were identified. These include: facilitating access to information as a basic consumption product; the emergence of a new form of property (intellectual property) and new objects of property (information products); changing relations between producers and consumers, employers and employees; the formation of a “sharing” economy as an innovative form of trade. The article shows the significant impact of the digital economy on changing the model of human economic behavior. A model of economic behavior is understood as a system, the elements of which determine the guidelines and choices of a person in the economic sphere. These include: the presence of objective limitations and subjective preferences of the individual, the ability to assess possible behavior options, analysis of information, choice of behavior model. In addition to these constant determinants of economic behavior, the model also contains variable factors influencing economic choice. These include: attitude towards information and the ability to access it, motivation for economic activity, rationality of actions and irrationality in decision making, goal setting as a system-forming function of the individual. Variable elements undergo significant transformations, which must be taken into account in the updated model of the behavior of “economic homo.”

Subjective preferences, liquidity constraints and price risk management under large-scale farm management

PurposeLarge-scale farm management in China has developed rapidly in recent years. Large-scale farmers face substantial operating risks, requiring extensive price risk management. However, the agricultural insurance and futures markets in China are incomplete. This study aims to analyze the price-risk-management behaviors of large-scale farmers under incomplete market conditions, with a focus on the interconnections between large scale farmers' subjective preferences (risk preferences, time preferences), liquidity constraints and their price risk management.Design/methodology/approachThe authors construct an analysis framework to reveal the impact of large-scale farmers' risk preferences, time preferences and liquidity conditions on their price-risk-management behaviors under incomplete market conditions. Using data from field surveys and subjective preference experiments involving 409 large-scale grain farmers in China, an empirical analysis was conducted using the bivariate probit model.FindingsThe results show that risk-averse farmers will use risk transfer (such as contract farming) and risk diversification (such as multi-period sales) to avoid price risk. However, farmers subject to liquidity constraints and strong time preferences will not choose risk diversification, and the interaction between time preferences and liquidity constraints will strengthen this decision. The larger the farm-management scale, the greater the impact.Originality/valueThe authors focus on rapidly developed large-scale farm management in China. Appropriate price risk management is required by large-scale farmers due to their substantial operating risks. Considering the incomplete conditions of agricultural insurance and futures markets, the results of this study will help identify behavioral characteristics of large-scale farmers and optimize their price-risk-management strategies, further stabilizing large-scale farm management.

The visual preference and physiological response to Sierpinski triangle acoustic diffuser: An experimental study using VR technique

Diffusive surfaces should be optimally designed for acoustic and aesthetic purposes. Fractals are commonly used to adapt to the parametric demands of interface design combining mathematical calculation and artistic creation. The author’s previous study proposed an improved fractal acoustic structure based on the Sierpinski-triangle building rule. However, there is insufficient research on quantifying the physiological and visual benefits of such fractal features. Focusing on fractal iteration and randomness of module arrangement as fractal parameters, this study investigates in 3D-virtual reality meeting rooms and identifies the influence of fractal diffusion structures on visual preferences and physiological responses. Variance analysis is used to construct models of fractal parameters, subjective preference factors, and physiological indicators. Results suggest that the Sierpinski-triangle pattern iterated twice with mid-high complexity (quantified by the fractal dimension D = 1.58) is significantly more visually preferred than other fractals. When the modules are at low randomness (quantified by P = 0.25), more random module arrangements elicited better beneficial outcomes. However, as the degree of randomness increased, effects became increasingly irregular. Subjective evaluation factors and physiological indicators show a strong correlation. To sum up, the use of the medium to mid-high complexity fractals in interior spaces would help enhance the visual preferences and stress relief of occupants.

Automated image quality assessment for selecting among multiple magnetic resonance image acquisitions in the German National Cohort study

In magnetic resonance imaging (MRI), the perception of substandard image quality may prompt repetition of the respective image acquisition protocol. Subsequently selecting the preferred high-quality image data from a series of acquisitions can be challenging. An automated workflow may facilitate and improve this selection. We therefore aimed to investigate the applicability of an automated image quality assessment for the prediction of the subjectively preferred image acquisition. Our analysis included data from 11,347 participants with whole-body MRI examinations performed as part of the ongoing prospective multi-center German National Cohort (NAKO) study. Trained radiologic technologists repeated any of the twelve examination protocols due to induced setup errors and/or subjectively unsatisfactory image quality and chose a preferred acquisition from the resultant series. Up to 11 quantitative image quality parameters were automatically derived from all acquisitions. Regularized regression and standard estimates of diagnostic accuracy were calculated. Controlling for setup variations in 2342 series of two or more acquisitions, technologists preferred the repetition over the initial acquisition in 1116 of 1396 series in which the initial setup was retained (79.9%, range across protocols: 73–100%). Image quality parameters then commonly showed statistically significant differences between chosen and discarded acquisitions. In regularized regression across all protocols, ‘structured noise maximum’ was the strongest predictor for the technologists’ choice, followed by ‘N/2 ghosting average’. Combinations of the automatically derived parameters provided an area under the ROC curve between 0.51 and 0.74 for the prediction of the technologists’ choice. It is concluded that automated image quality assessment can, despite considerable performance differences between protocols and anatomical regions, contribute substantially to identifying the subjective preference in a series of MRI acquisitions and thus provide effective decision support to readers.

DEA cross-efficiency models with prospect theory and distance entropy: An empirical study on high-tech industries

Cross-efficiency evaluation with the data envelopment analysis (DEA) model is an effective way to assess performance and provide a complete ranking of decision-making units. However, it is generally assumed that decision makers are perfectly rational in the cross-efficiency model, which fails to consider the subjective preferences of decision-makers. Moreover, the arithmetic average method is usually adopted to aggregate efficiency scores in traditional cross-efficiency methods, which underestimates the importance of self-evaluation. To address these issues, we extend cross-efficiency with the DEA model by incorporating prospect theory and the distance entropy function. First, we calculate the prospect values of decision-making units to describe the non-rational subjective preferences under the risk of decision-makers. Second, based on prospect cross-efficiency, a new distance entropy function is developed to aggregate the ultimate prospect cross-efficiency values. More specifically, some traditional cross-efficiency evaluation models can be considered special cases of prospect cross-efficiency models with appropriate adjustments to the parameters. Finally, an empirical example is used to evaluate the prospect cross-efficiency results with the high-tech industries of 29 provinces in China to illustrate the applicability and effectiveness of the proposed model in ranking observations.

A Study on a New Way of Thinking Based on Linear Programming to Analyze Civic Education in Colleges and Universities

Abstract This paper intends to construct a new multi-dimensional preference analysis model for learners by using the improved linear programming method of multi-dimensional preference analysis (LINMAP) to get the weight vector of attributes under the situation that the weights of attributes are completely unknown and for the uncertain multi-attribute decision-making problem that the elements of decision-making matrix are triangular fuzzy numbers, and the preference information is ordered pairs. The data of subjective or objective Civics education learning preferences are aggregated, and the statistical analysis of the data is carried out using SPSS.21 to generate the Civics education learning preference input degree weighting system. The results show that the offline behavioral input weight in the college Civics course is 0.5769, which is greater compared to the online input. And the attribute weights of course Civics preference are calculated to get Z max = 2.29, Z min = 0.73. Multiple feasible solutions can be obtained by taking any value between [0,1]. Based on the development law of the times, this paper makes a new thinking on ideological and political education and actively explores a new road suitable for the development of ideological and political education in colleges and universities.

Effects of indoor lighting conditions on subjective preferences of task lighting and room aesthetics in an Indian tertiary educational institution

Indoor lighting conditions influence the psychology of pupils in academic institutions and it is expedient to investigate how subjective experiences are modulated by differences in lighting conditions. This study was conducted in a tertiary educational institute in West Bengal, India with twenty-four student participants, divided into three groups of eight each, to assess how the appraisals of task lighting and room aesthetics varied under three ambient lighting conditions. Spread across nine sessions of 1 h each, the groups performed pre-defined tasks and recorded their responses upon copies of a formulated questionnaire at the conclusion of each session. Moreover, blood pressure and heart rate measurements of the participants were made at an interval of 20 min. Statistical analysis with Kruskal-Wallis and Friedman tests implied that there were significant differences among the lighting conditions with respect to several dependent variables of task lighting and room aesthetics appraisal. Artificial lighting was deemed to be uniform, pleasant for task performance, and comfortable for book reading. Daylighting with the concomitant window view was construed as brighter, glaring, dramatic, more contrasting, and less uniform. A combination of natural and artificial lighting was bright, mildly contrasting, dramatic, softer in luminosity, and comfortable. Withal, daylighting with the concomitant window view appeared to regulate participants’ blood pressure and heart rate. Thus, this study implies that the balance and holistic synergy between artificial and natural light can create an enlivening and salubrious indoor environment, and building service professionals should conscientiously harness the same for upgrading current practices in indoor lighting.

Protecting Infrastructure Networks: Solving the Stackelberg Game with Interval-Valued Intuitionistic Fuzzy Number Payoffs

Critical infrastructure is essential for the stability and development of modern society, and a combination of complex network theory and game theory has become a new research direction in the field of infrastructure protection. However, existing studies do not consider the fuzziness and subjective factors of human judgment, leading to challenges when analyzing strategic interactions between decision makers. This paper employs interval-valued intuitionistic fuzzy numbers (IVIFN) to depict the uncertain payoffs in a Stackelberg game of infrastructure networks and then proposes an algorithm to solve it. First, we construct IVIFN payoffs by considering the different complex network metrics and subjective preferences of decision makers. Next, we propose a lexicographic algorithm to solve this game based on the concept of a strong Stackelberg equilibrium (SSE). Finally, we conduct experiments on target scale-free networks. Our results illustrate that in an SSE, for the defender in a weak position, it is better to defend nodes with high degrees. The experiments also indicate that taking fuzziness into account leads to higher SSE payoffs for the defender. Our work aims to solve a Stackelberg game with IVIFN payoffs and apply it to enhance the protection of infrastructure networks, thereby improving their overall security.

How rejected recommendations shape recommenders' future product intentions

AbstractWhen a consumer (a recommender) recommends a product to another consumer (a recommendee), it is not uncommon to learn whether the recommendee chose the recommended option (i.e., accepted the recommendation) or a different option (i.e., rejected the recommendation). Our research examines how rejected recommendations affect recommenders' subsequent intentions toward the originally recommended product. We find that upon learning one's recommendation was rejected, recommenders are less likely to repurchase or choose the product in the future. This negative effect emerges because recommenders question their knowledge about the recommended product (i.e., self‐perceived expertise is reduced). Such questioning is more likely to occur when the recommendee is a close other and less likely to occur when the recommended product is perceived to primarily differ from alternatives due to subjective preferences (i.e., horizontal differentiation is salient). Importantly, this rejected recommendation effect is shown to be distinct from a social proof account. The current research contributes to WOM theory by identifying a novel outcome of recommendation interactions—rejected recommendations—and by demonstrating that this outcome can cause consumers to shift away from a product despite having felt positively enough about the product to recommend it to others.

Competitive resource allocation in an attacker-defender game: When citizens become targets of being ingratiated

In the realm of counterterrorism, the role of citizens is crucial. In certain scenarios, such as during epidemics or political conflicts, citizens can become targets of being ingratiated between governments and terrorists. Notably, citizen targets possess distinct characteristics compared to other target types. This article centers on the competitive allocation of resources by the defender and the attacker on citizen targets. First, we incorporate utility functions into contest success functions to capture the subjective preferences of citizen targets. Subsequently, we construct a sequential game model of the defender and the attacker, considering their respective budget constraints. Furthermore, we examine how the investment effectiveness of both players impacts the likelihood of a successful attack, optimal resource allocations, and defense losses. Additionally, we model the relationship between the investment effectiveness and the inherent defense levels of citizen targets. Finally, we present a case study to demonstrate the practical applicability of our proposed model. The article’s findings indicate that (i) achieving the optimal resource allocation should consider a combination of factors, including the effectiveness of defender and attacker investments, the inherent defense levels of citizen targets, and the population sizes of these targets and (ii) acknowledging the positive correlation between inherent defense levels and defense effectiveness, enhancing the inherent defense levels of citizen targets can substantially reduce defense losses. This article provides valuable methods and insights that can benefit government agencies worldwide in efficiently allocating resources to protect vulnerable citizen populations from terrorism risks.

Comparison of volumetric modulated arc therapy and helical tomotherapy for prostate cancer using Pareto fronts.

Studies comparing different radiotherapy treatment techniques-such as volumetric modulated arc therapy (VMAT) and helical tomotherapy (HT)-typically compare one treatment plan per technique. Often, some dose metrics favor one plan and others favor the other, so the final plan decision involves subjective preferences. Pareto front comparisons provide a more objective framework for comparing different treatment techniques. A Pareto front is the set of all treatment plans where improvement in one criterion is possible only by worsening another criterion. However, different Pareto fronts can be obtained depending on the chosen machine settings. To compare VMAT and HT using Pareto fronts and blind expert evaluation, to explain the observed differences, and to illustrate limitations of using Pareto fronts. We generated Pareto fronts for twenty-four prostate cancer patients treated at our clinic for VMAT and HT techniques using an in-house script that controlled a commercial treatment planning system. We varied the PTV under-coverage (100%-V95%) and the rectum mean dose, and fixed the mean doses to the bladder and femoral heads. In order to ensure a fair comparison, those fixed mean doses were the same for the two treatment techniques and the sets of objective functions were chosen so that the conformity indexes of the two treatment techniques were also the same. We used the same machine settings as are used in our clinic. Then, we compared the VMAT and HT Pareto fronts using a specific metric (clinical distance measure) and validated the comparison using a blinded expert evaluation of treatment plans on these fronts for all patients in the cohort. Furthermore, we investigated the observed differences between VMAT and HT and pointed out limitations of using Pareto fronts. Both clinical distance and blind treatment plan comparison showed that VMAT Pareto fronts were better than HT fronts. VMAT fronts for 10 and 6MV beam energy were almost identical. HT fronts improved with different machine settings, but were still inferior to VMAT fronts. That VMAT Pareto fronts are better than HT fronts may be explained by the fact that the linear accelerator can rapidly vary the dose rate. This is an advantage in simple geometries that might vanish in more complex geometries. Furthermore, one should be cautious when speaking about Pareto optimal plans as the best possible plans, as their calculation depends on many parameters.

Measurement-based Auralisation to Predict Room Acoustics Quality of a Large Mosque with a Pyramid-Shaped Ceiling in Bandar Lampung

Acoustic standards in mosques are available, but most people have a lack of understanding of these measures. Auralisation is an audio technology that uses impulse responses, dry sounds and convolution software to create authentic auditory experiences. In Indonesia, objective room acoustic parameters are still unknown and the potential of auralisation is underexplored. The study aims to predict acoustic quality and people’s preference for auralisation in a pyramid-shaped ceiling using field measurements and subjective ratings. The methodology includes pre-survey, RIR measurement, dry sound recording, auralisation, and subjective surveys. Background noise, T30, D50, and C80 were measured, while auralised samples of lectures and Quran recitations were evaluated. Respondents’ preferences generally correlated with T30, especially D50 (47%) for lectures and C80 (44%) for Quran recitations. In conclusion, the study demonstrates the interplay between subjective preferences and objective measurements and suggests that these parameters can predict acoustic quality in pyramid-shaped dome mosques, paving the way for better design practices and improved listening experiences.

To the question of the need to improve the financial planning mechanism when making investment decisions

The article focuses on the key problems of improving the financial planning mechanism when making investment decisions by organizations Based on the proposed methodology of financial planning as a systematized set of basic principles and methods of financial planning, applied indicators, impact measures necessary for the implementation of the financial plan, its monitoring, etc., the structure of this mechanism aimed at making investment decisions is substantiated, as well as the functions and tasks of the financial planning process of investment activity are defined. The authors substantiate that financial planning of investment activity is one of the most complex areas of financial planning, which is largely due to the complexity of making investment decisions, during which the state of the macroeconomic environment, objective limitations of investment activity, alternative investment opportunities, the state of the internal environment of the organization, its subjective investment preferences and other external and internal factors should be taken into account. To solve these problems, it is proposed to use such tools of the financial planning mechanism as budgeting of investment activities.

The Significance of Subject Preferences, Self-Efficacy Beliefs, and Gender for the Further Study Field Interests of Finnish General Upper Secondary School Students

The Significance of Subject Preferences, Self-Efficacy Beliefs, and Gender for the Further Study Field Interests of Finnish General Upper Secondary School Students

Comparison of Elicitation Approaches in Early Stage HTA Applied on Artificial Thymus for Patients with DiGeorge Syndrome.

This paper focuses on research in expert elicitation as a part of the early stage health technology assessment (eHTA). The current state of affairs is analysed and two elicitation approaches are compared-the four fixed intervals method and the histogram method-as applied to an example of early assessment of clinical effectiveness of artificial thymus for patients with DiGeorge syndrome. A survey was carried out consisting of four questions concerning the topic, with the aim to apply the elicitation methods. Eight experts answered the questions using both elicitation methods. Based on their answers, the methods were compared visually and by means of statistical tests. In order to compare the perception of the two elicitation methods, the survey also included questions regarding the experts' subjective preferences. The results of the comparison of the two elicitation approaches did not clearly confirm which method was more beneficial and better; however, it was possible to indicate which of the two methods is better suited for different types of experts. Before selecting an elicitation method as a part of eHTA, it is advisable to effectively consider the technology to be assessed and the type of experts to be invited to share their opinion.

Enhancing energy efficiency and comfort with a multi-domain approach: Development of a novel human thermoregulatory model for occupant-centric control

Occupant Centric Control (OCC) strategies aims to achieve a more personalized and comfortable indoor environment, translating occupants' comfort requirements into real environmental conditions. This strategy relies on a multilevel non-linear programming optimization procedure to determine optimal thermo-hygrometric setpoints. The objective is to minimize space heating and cooling requirements while addressing multi-domain comfort concerns related to individual thermal sensations and perceived air quality. To facilitate this process, this study adopts a novel Personal Comfort Model (PCM), incorporating physiological factors to predict occupants' thermal sensations and CO2 intakes. The PCM's reliable predictive capabilities are confirmed through validation with real experimental data from a test room at the University of Perugia. For detailed energy analyses, considering occupants' subjective comfort preferences, the PCM is seamlessly integrated into DETECt, an in-house building energy performance simulation tool developed by the University of Naples Federico II, for the design of advanced control algorithms and energy efficiency strategies. To effectively manage the HVAC system, a model predictive control is implemented, using the determined setpoints to ensure mechanical ventilation and maximize cost savings. The proof of concept for the developed methodology involves simulating experimental tests using the thermal model of the human body and the new facility management system, to be simulated and optimized by means of the enhanced building energy performance simulation tool, exploited for the design and operation of more occupant-centric and sustainable buildings. The proposed study demonstrates that through the developed OCC strategy enables a significant reduction in thermal discomfort (40 % and 60 % less than the occupation time for test 1 and test 2, respectively) compared to reference scenarios. Additionally, energy analysis reveals high efficiency, achieving savings of 12.8 % and 7.8 % of electricity consumed for HVAC system operation.