Terms Of Set Research Articles

Mean–variance optimization under affine GARCH: A utility-based solution

Affine GARCH models have recently been explored in the context of portfolio optimization, although in a quite narrow setting in terms of utility functions and risk aversion. This work notably extends existing results, accommodating a richer class of objective functions for a large family of GARCH models. In particular, our approach allows for connections to constant proportion portfolio insurance (CPPI) and mean–variance portfolio strategies. We explore the latter numerically based on S&P 500 market data, revealing that a GARCH model clearly outperforms a homoscedastic variant in terms of the efficient frontier.

Consensus-based probabilistic hesitant intuitionistic linguistic Petri nets for knowledge-intensive work of superheat degree identification

Superheat degree identification of aluminum electrolysis cell is a typical knowledge-intensive work which is the precondition of efficient production. However, existing methods have application limitations, and the large cognitive differences among experts are ignored in the existing methods. To address these issues, we propose the consensus-based probabilistic hesitant intuitionistic linguistic Petri nets (CPHILPNs). The truth values of places in CPHILPNs are represented by probabilistic hesitant intuitionistic linguistic term sets (PHILTSs), which can enrich the experts’ expression and improve the efficiency of dealing with uncertainties. The proposed probabilistic hesitant intuitionistic linguistic consensus optimization model can reduce the deviation of individual preferences to reach a consensus. Then the obtained experts’ weights and decision assessments will be more accurate and comprehensive with objective evaluations. The order weighted averaging PHILTSs concurrent reasoning algorithm is proposed to enhance the inference efficiency. Finally, the usefulness and validity of the proposed CPHILPNs are verified by conducting comparisons and actual experiments in a real-world plant.

On Proper Separation Theorems by Means of the Quasi-Relative Interior with Applications

In this paper, we establish several proper separation theorems for an element and a convex set and for two convex sets in terms of their quasi-relative interiors. Then, we prove that the separation theorem given by [Cammaroto, F and B Di Bella (2007). On a separation theorem involving the quasi-relative. Proceedings of the Edinburgh Mathematical Society, 50(3), 605–610] in Theorem 2.5, is in fact a proper separation theorem for two convex sets in which the classical interior is replaced by the quasi-relative interior. Besides, we extend some known results in the literature, such as [Adán, M and V Novo (2004). Proper efficiency in vector optimization on real linear spaces. Journal of Optimization Theory and Applications, 121, 515–540] in Theorem 2.1 and [Edwards, R (1965). Functional Analysis: Theory and Applications. New York: Reinhart and Winston] in Corollary 2.2.2, through the quasi-relative interior and the quasi-interior, respectively. As an application, we provide Karush–Kuhn–Tucker multipliers for quasi-relative solutions of vector optimization problems. Several examples are given to illustrate the obtained results.

Historical summary of terminologies in community ecology

This article highlights the importance of terminology in ecology as a fundamental tool for clear and objective communication among scientists, as well as for standardizing study methods and techniques used by ecologists. Terminology refers to a set of terms, concepts, and definitions that are established and accepted by professionals in the field, enabling precise descriptions of species, ecosystems, and ecological processes. However, it is important to note that terminology in ecology is constantly evolving, and it is essential for ecological professionals to stay up to date with changes to contribute to the advancement of science. Understanding the historical process of ecological terminologies is also necessary to comprehend their meanings and how their interactions can affect the understanding of ecology itself. In this sense, we have provided a historical contextualization of several important concepts in community ecology, such as biodiversity, trophic levels, ecological niches, ecological guilds, and functional groups. We have also made comparisons and differentiations between these concepts throughout the history of these terms.

Risk assessment based on failure mode and effects analysis (FMEA) and WASPAS methods under probabilistic double hierarchy linguistic term sets

Failure mode and effects analysis (FMEA) is regarded as an efficient tool in identifying and eliminating system failures and important tool in safety and reliability analysis. However, the traditional FMEA method has some drawbacks, for example, in the process of risk assessment, traditional FMEA method usually ignores the influence factors of weight. Simultaneously, when represent risk assessment information, crisp numbers and fuzzy sets cannot represent complex linguistic information forms accurately. Moreover, the traditional FMEA method ranks risk failures through simple product. Thus, based on these disadvantages, this paper aims to present an improved FMEA method combines with the Weighted Aggregates Sum Product Assessment (WASPAS) method and weight determination method to address the risk assessment problems under probabilistic double hierarchy linguistic (PDHL) environment. In assessment process, the probabilistic double hierarchy linguistic term sets (PDHLTSs) can indicate the probability distribution as a linguistic tool to describe the information reasonably and precisely. The contribution s of this paper can be incarnated as below. Firstly, the PDHLTSs are utilized to provide the linguistic information of failure modes and construct risk evaluation model in risk assessment. Secondly, FMEA method is combined with WASPAS method to overcoming some drawbacks existing in traditional FMEA such as without consideration of the weight of three aspects in Severity (S), Occurrence (O) and Detection (D) and too simple to evaluate the risk factors using Risk Priority Number (RPN) values. Meanwhile, in response to the issue of traditional FMEA method neglecting expert weights, weight determination method is established based on the SNA method under the PDHL context. Additionally, the FMs are ranked through the multi-attribute decision-making method WASPAS, and the final risk ranking result is obtained. Finally, the proposed method is applied to the marine risk assessment faced in the development of marine economy. Based on the assessment results, suggestions are given for the risk problems. In addition, we also carried out sensitivity analysis and accuracy analysis on the evaluation results. At the same time, comparison analysis with existing methods is given to illustrate the superiority of the proposed method.

Numberings, c.e. oracles, and fixed points

The Arslanov completeness criterion says that a c.e. set A is Turing complete if and only there exists an A-computable function f without fixed points, i.e. a function f such that W f ( x ) ≠ W x for each integer x. Recently, Barendregt and Terwijn proved that the completeness criterion remains true if we replace the Gödel numbering x ↦ W x with an arbitrary precomplete computable numbering. In this paper, we prove criteria for noncomputability and highness of c.e. sets in terms of (pre)complete computable numberings and fixed point properties. We also find some precomplete and weakly precomplete numberings of arbitrary families computable relative to Turing complete and non-computable c.e. oracles respectively.

Reproductive psychiatric advance directives: promoting autonomy for perinatal people with serious mental illness diagnoses.

People with serious mental illness (SMI) diagnoses who become pregnant are particularly vulnerable to symptom recurrence and resulting potential lack of decision-making capacity (Taylor et al. J Psychiatr Res 104:100-107, 2018; Bagadia et al. Int J Soc Psychiatry 66:792-798, 2020). In these situations, prenataland behavioral health providers have little legally viable guidance on what medical and/or psychiatric care the patient desires (Aneja and Arora Indian J Med Ethics V:133-139, 2020). We created a "Reproductive Psychiatric Advance Directive (PAD)," grounded in Reproductive Justice principles, that promotes patient autonomy by proactively articulating perinatal medical and psychiatric care preferences. We conducted a medical and legal literature review using two sets of terms related to (1) PADs and (2) reproductive health. We convened an expert working group of legal, medical, psychiatric, peer, and advocacy leaders and community-based organizations to develop a Reproductive PAD. Our literature review yielded no results about Reproductive PADs. We created de novo a Reproductive PAD template with sections on medical and psychiatric history, informed consent for critical medical and psychiatric care, family planning and custody preferences, and optional sections on abortion and on electroconvulsive therapy. The Reproductive PAD provides a possible legal mechanism for people of childbearing age with SMI diagnoses to articulate their medical and psychiatric care choices around reproduction and pregnancy. Future research should evaluate the Reproductive PAD as an effective tool for protecting patient autonomy during pregnancy and postpartum and guiding medical and psychiatric providers.

Attitude- and cost-driven consistency optimization model for decision-making with probabilistic linguistic preference relation

Probabilistic linguistic term set (PLTS) conveys the preference for a linguistic term by assigning a probability distribution, which can more correctly and flexibly reflect the decision-maker (DM)’s evaluation information and make the decision outcome more scientific and rational. Probabilistic linguistic preference relation (PLPR) allows the DM to represent decision information for pairwise comparison of alternatives with PLTS, allowing a more comprehensive representation of the DM’s valid preferences. Consistency is essential in the preference decision-making process and directly influences the dependability of the final results. Therefore, this paper develops a minimum cost consistency adjustment mechanism based on attitudes and emotions for solving the decision-making problem with PLPR. Firstly, a new PLTS normalization model is proposed to handle the unknown information, considering the DM’s preferred attitude and emotional tone. Secondly, the expected parametric multiplicative consistency index for PLPR is defined, and parameter settings improve the flexibility and relevance of the consistency. Then, the concepts of linguistic hesitancy, probabilistic uncertainty, and probabilistic incompleteness are defined for the PLTS that can reflect the psychological characteristics of DMs’ hesitancy; they are then used to measure hesitation and unit consistency adjustment costs. Next, a new distance measure is established between the two PLTSs to measure the difference between the preference information. Subsequently, a direction-guided minimum cost consistency optimization model with unacceptable consistency is constructed for the PLPR. Finally, the usefulness of the suggested decision-making method with PLPR is tested using a numerical example of talent selection, and parametric sensitivity analysis and comparative analysis are utilized to show the benefits of the suggested methodology.

On the first subharmonic bifurcations in a branch of Stokes water waves

Steady surface waves in a two-dimensional channel are considered. We study bifurcations, which occur on a branch of Stokes water waves starting from a uniform stream solution. Two types of bifurcations are considered: bifurcations in the class of Stokes waves (Stokes bifurcation) and bifurcations in a class of periodic waves with the period M times the period of the Stokes wave (M-subharmonic bifurcation). If we consider the first Stokes bifurcation point then there are no M-subharmonic bifurcations before this point and there exists M-subharmonic bifurcation points after the first Stokes bifurcation for sufficiently large M, which approach the Stokes bifurcation point when M→∞. Moreover the set of M-subharmonic bifurcating solutions is a closed connected continuum. We give also a more detailed description of this connected set in terms of the set of its limit points, which must contain extreme waves, or overhanging waves, or solitary waves or waves with stagnation on the bottom, or Stokes bifurcation points different from the initial one.

Personalized fuzzy semantic model of PHFLTS: Application to linguistic group decision making

The proportional hesitant fuzzy linguistic term set (PHFLTS) has been effectively employed in analyzing the group’s hesitancy in linguistic group decision making (LGDM). The application of PHFLTS assists in capturing the individual’s hesitancy across diverse time periods. It is acknowledged that a single word could potentially convey various meanings to different decision makers, such differences can be proficiently managed by utilizing personalized individual semantic (PIS) models. Previous approaches for calculating PIS failed to incorporate the individual’s updating preference information over time, which increases the risk that the computation of PIS is affected by random factors in a specific moment. In our current research, individual linguistic preference gathered over a time period are leveraged to form the PHFLTS. Additionally, a consistency driven optimization model based on PHFLTS is formulated to obtain PIS of linguistic terms. Subsequently, a fuzzy representation model termed as the fuzzy envelope of PHFLTS is introduced to facilitate the computation with words processes, integrating PHFLTS in LGDM. The practicality and legitimacy of these proposed models are evaluated through a comparative analysis. Lastly, these proposed models are tested and applied in a dedicated case study to further prove their usefulness and efficacy.

A hybrid multi-criteria decision-making framework of EWM-BWM-TODIM based on Linguistic Pythagorean fuzzy environment

Linguistic Pythagorean fuzzy set (LPFS) combines Pythagorean fuzzy sets and linguistic term sets, which can effectively deal with fuzzy information in multi-criteria decision-making (MCDM). The entropy weight method (EWM) can reflect the objectivity of decision information, while the best-worst method (BWM) can reflect the subjectivity of decision-makers. The interactive multi-criteria decision-making (TODIM) method can describe the different preferences of decision-makers for gains and losses. In this paper, EWM, BWM, and TODIM are combined and applied to LPFS for the first time. First, we calculate the objective weight and subjective weight of each criterion through EWM and BWM and combine them to get the final weight to balance subjectivity and objectivity. Then, this paper selects the best scheme through TODIM sorting. In conclusion, the LPFS-EWM-BWM-TODIM model is established in this paper. Finally, the paper applies this model to the selection of corporate investment strategy and green mine, verifies the effectiveness of the method, and carries out comparative analysis and sensitivity analysis, proving the rationality and robustness of the model.

A multiattribute financial time series forecast model based on double hierarchy fuzzy linguistic term set

Based on the double hierarchy linguistic term sets (DHLTS), a novel forecasting model is proposed considering both the internal fluctuation rules and the external correlation of different time series. The innovative aspects of this model consist of: (i) It can expresses more internal fluctuation and external correlation information, providing guarantees for improving the predictive performance of the model. (ii) The equivalent transformation function of DHLTS reduces the fuzzy granularity and improves the prediction accuracy. (iii) The application of similarity measures can extract the closest rules from historical states based on the distance operators of DHLTS. In addition, experiments on TAIEX considering the impact of the U.S. stock market and other data show that the model has good predictive performance.

Configuration optimization of product-service system design requirements based on hesitant information axiom

Product-service system (PSS) has attracted attention of manufacturers to shift from product-providing to solution-providing, which is a marketable set of products and services. The existing researches emphasize the fulfillment of individualized customer requirements through different PSS configurations. The PSS planning phase is of high importance in generating conceptual schemes, which translates customer requirements (CRs) to design requirements (DRs). In this paper, a systematic decision-making approach based on QFD is put forward aiming to configure the PSS design requirements (DRs). To address the uncertainty and hesitancy in QFD modeling, a hesitant fuzzy linguistic term sets (HFLTSs) is applied to elicit the experts’ linguistic preferences in evaluating the importance of CRs and the relationships between CRs and DRs. To dealing with the group decision-making problems concerning the HFLTSs, the min-upper operator and the max-lower operator assemble the experts’ evaluation results into a linguistic interval, and then the numerical results can be obtained by using the 2-tuple linguistic representation model and the interval preference degree computation. A non-linear 0-1 programming model is proposed to select the target DRs’ specifications for maximizing customer satisfaction under cost constraint. In order to objectively determine the satisfaction degree of each optional specification of DR, the information axiom is introduced to construct the objective function via information content computation. To deal with the qualitative DRs, HFLTSs and information axiom are combined and hesitant information axiom (HIA) is proposed. Finally, a DRs optimization model is established using HIA and the imprecision method. A case study is carried out to demonstrate the effectiveness of the optimal PSS planning approach developed.

A fuzzy group decision-making framework for computer network security evaluation with probabilistic linguistic information

The computer network security evaluation is a classical multiple attribute group decision making (MAGDM) problems. Recently, the Exponential TODIM TODIM (ExpTODIM) method has been used to cope with MAGDM issues. The probabilistic linguistic term sets (PLTSs) are used as a tool for characterizing uncertain information during the computer network security evaluation. In this manuscript, the probabilistic linguistic ExpTODIM (PL-ExpTODIM) is built to solve the MAGDM under PLTSs. In the end, a numerical case study for computer network security evaluation is given to validate the proposed method. The main contribution of this paper is constructed: (1) the Exponential TODIM TODIM (ExpTODIM) method is extended to the PLTSs; (2) the probabilistic linguistic ExpTODIM (PL-ExpTODIM) method is defined to solve the MAGDM under PLTSs; (3) In the end, a numerical case study for computer network security evaluation is given to validate the proposed method.

ALP-LEFT Interference and the Muon (g − 2)

The low-energy effective field theory (LEFT) provides the appropriate framework to describe particle interactions below the scale of electroweak symmetry breaking, μw ~ v. By matching the Standard Model onto the LEFT, non-zero Wilson coefficients of higher-dimensional operators are generated, suppressed by the corresponding power of 1/v. An axion or axion-like particle (ALP) with mass ma ≪ μw that interacts with the Standard Model via classically shift-invariant dimension-five operators would also contribute to the LEFT Wilson coefficients, since it can appear as a virtual particle in divergent Green’s functions and thus has an impact on the renormalization of the LEFT operators. We present the full set of one-loop ALP-induced source terms modifying the renormalization-group evolution equations of the LEFT Wilson coefficients up to dimension-six order. Our framework allows for model-independent ALP searches at low energies from current bounds on LEFT Wilson coefficients. As a concrete application, we present an improved prediction for ALP effects on the anomalous magnetic moment of the muon.

A New Approach for Product Quality Check Based on Social Networks Opinions Analysis

In this paper, we aim to enhance the relevance of e-commerce web sites by a prior quality checking of proposed products. This checking is done by analyzing social networks and YouTube videos comments.
 To achieve this objective, we have broken down the work into a few steps. The first one consists in scraping text from social networks groups and storing it in a NoSQL graph database. Each scraped word is linked to one or many reactions that are coming from the social network. Therefore, we can utilize the database as a knowledge source that associates each set of terms with a specific type of reaction: positive, negative or neutral. Afterwards, we use a TF-IDF based filtering method to keep only relevant words and eliminate those which are a connected to all reactions. The advantage of this stage is the presence of a knowledge source that can be used for product quality checking.
 In the e-commerce web site, data are coming from multiple e-commerce websites. The latter, offer products without quality checking. Concretely, we aim to allow users to check quality by a simple check button which call an implemented web service using human reactions and comments. After evaluating our approach, we have obtained an accuracy of 0,75. This result means that our method gives a three quarter of chance to have a good product.

Framing availability and usability of transportation for people with disabilities

Transportation planning researchers use the term “accessibility” to characterize the ability of people to reach jobs, school, healthcare and other services and activities. Disability scholars use that term to characterize the ability of people with disabilities to use transportation modes where and when present. In the United States of America (US), transportation policymakers’ use of the latter definition only for minimal legal compliance at the expense of the former definition, without synthesizing both definitions, has led to real-world negative consequences for transportation for people with disabilities, including when new train lines lead to consolidation of bus routes and in regulatory debates about how ridehailing services may serve people with disabilities. Thus, in the context of transportation policy, we propose a new set of terms that, when used consistently, can more accurately distinguish these concepts. These terms are “provider-view availability”, referring to where & when a transportation mode is present or legal to use, “immediate usability”, referring to the ease of interacting with a vehicle or (physical or digital) infrastructure upon encountering it, “user-view availability”, referring to how some people cannot start trips on a given mode due to severe problems with immediate usability, and “cumulative usability”, referring to the challenges that users of a certain mode may face more often as trip times or distances increase. We argue that transportation policymakers in the US could more accurately characterize holistic problems with transportation facing people with disabilities by consistently using these terms and thereby mitigate similar negative consequences going forward.

What are patients asking and reading online? An analysis of online patient searches for rotator cuff repair.

Patients undergoing rotator cuff surgery often search the internet for information regarding the procedure. One popular source, Google, compiles frequently asked questions and links to websites that may provide answers. This study provides an analysis of the most frequently searched questions associated with rotator cuff surgery. We hypothesize that there will be distinct search patterns associated with online queries about rotator cuff surgery that could provide unique insights into patient concerns. A set of search terms were entered into Google Web Search using a clean-install Google Chrome browser. Frequently associated questions and their webpages were extracted to a database via a data mining extension. Questions were categorized by topics relevant for rotator cuff arthroscopy. Websites were categorized by source and scored for quality using the JAMA Benchmark Criteria. Pearson's χ2 tests were used to analyze nominal data. Student t tests were performed to compare JAMA Benchmark Scores. Of the 595 questions generated from the initial search, 372 unique questions associated with 293 websites were extracted and categorized. The most popular question topics were activities/restrictions (20.7%), pain (18.8%), and indications/management (13.2%). The 2 most common websites searched were academic (35.2%) and medical practice (27.4%). Commercial websites were significantly more likely to be associated with questions about cost (57.1% of all cost questions, P=.01), anatomy/function (62.5%, P=.001), and evaluation of surgery (47.6%, P<.001). Academic websites were more likely to be associated with questions about technical details of surgery (58.1%, P<.001). Medical practice and social media websites were more likely associated with activities/restrictions (48.1%, P<.001, and 15.6%, P<.001, respectively). Government websites were more likely associated with timeline of recovery (12.8%, P=.01). On a scale of 0-4, commercial and academic websites had the highest JAMA scores (3.06 and 2.39, respectively). Patients seeking information regarding rotator cuff repair primarily use the Google search engine to ask questions regarding postoperative activity and restrictions, followed by pain, indications, and management. Academic websites, which were associated with technical details of surgery, and medical practice websites, which were associated with activities/restrictions, were the 2 most commonly searched resources. These results emphasize the need for orthopedic surgeons to provide detailed and informative instructions to patients undergoing rotator cuff repair, especially in the postoperative setting.

Repetitive research: a conceptual space and terminology of replication, reproduction, revision, reanalysis, reinvestigation and reuse in digital humanities

This article is motivated by the ‘reproducibility crisis’ that is being discussed intensely in fields such as Psychology or Biology but is also becoming increasingly relevant to Artificial Intelligence, Natural Language Processing and Digital Humanities, not least in the context of Open Science. Using the phrase ‘repetitive research’ as an umbrella term for a range of practices from replication to follow-up research, and with the objective to provide clarity and help establish best practices in this area, this article focuses on two issues: First, the conceptual space of repetitive research is described across five key dimensions, namely those of the research question or hypothesis, the dataset, the method of analysis, the team, and the results or conclusions. Second, building on this new description of the conceptual space and on earlier terminological work, a specific set of terms for recurring scenarios of repetitive research is proposed. For each scenario, its position in the conceptual space is defined, its typical purpose and added value in the research process are discussed, the requirements for enabling it are described, and illustrative examples from the domain of Computational Literary Studies are provided. The key contribution of this article, therefore, is a proposal for a transparent terminology underpinned by a systematic model of the conceptual space of repetitive research.

A multi-stage group decision making approach for sustainable supplier selection based on probabilistic linguistic time-ordered incentive operator.

This study proposes a novel multi-stage multi-attribute group decision making method under a probabilistic linguistic environment considering the development state and trend of alternatives. First, the probabilistic linguistic term set (PLTS) is used by decision makers (DMs) to describe qualitative evaluation information. Subsequently, the weights of DMs for different attributes in different periods are determined by the credibility degree, which is combined with the hesitancy degree and the similarity degree. The evaluations of different DMs for alternatives and the evaluations of DMs' intentions to reward or punish are then aggregated. Later, the trend change level and the trend change stability of alternatives are measured through the means of reward and punishment incentives. Additionally, the probabilistic linguistic time-ordered incentive operator is proposed to aggregate the development state evaluation information and development trend evaluation information in different periods, and alternatives are prioritized by the extended TOPSIS method in the probabilistic linguistic environment. Finally, the practical use of the proposed decision framework is validated by using a sustainable supplier selection problem, and the effectiveness and the applicability of the framework are discussed through comparative analysis. The results show that the proposed approach can select suitable sustainable suppliers by considering their development state and trend in multiple stages.