Uncertainty Ambiguity Research Articles

TRANSFORMASI ORGANISASI DI ERA SOCIETY 5.0: INOVASI, ADAPTASI, DAN KETERLIBATAN MANUSIA DALAM REVOLUSI TEKNOLOGI

In a volatile environment, organizations are challenged with increased uncertainty in various areas that can disrupt organizational sustainability. There is fear that there will be a complex and ambiguous uncertainty that an invasion could erode human character values. Human resources are the most valuable asset owned by an organization. The role of HR has urgency in contributing to increasing organizational development. To prepare ourselves to take part in inviting the time of society 5.0. This is an anticipation of disruption caused by Industrial Revolution 4.0. the scientific work results from a literature study that describes the important role of organizational development in preparing human resources in the technological era. thus, improving organizational development requires superior human resources which are considered the driving force of an organization that collectively contributes to achieving performance. To prepare oneself to face the contemporary era, two things should be done: adaptation and competence in mastering technology, being able to fundamentally, be imaginative, communicate, collaborate, and have problem-solving capasities.

Estimation of missing data in intuitionistic fuzzy soft matrix (IFSM) with application in MCDM

The theory of fuzzy soft as well as intuitionistic soft set generally depends on complete information. But there are situations in which the complete information is not available due to various different reasons like data erroneous, in sufficiency of data, lacking of evidence and illegibility of data. Missing data restrict fuzzy soft matrix and intuitionistic fuzzy soft matrix and that causes more ambiguous uncertainty in the process of decision making. Thus, estimation of incomplete information data plays an important role in multi criteria decision making process which has been developed recently. Here, a novel method of missing data estimation in intuitionistic fuzzy soft matrix is described. Firstly, we estimate the missing values using the information given in data. After estimation the missing values in IFSM thus obtained is applied in a multi-criteria decision-making problem with illustration by an example.

Utilization Of Biogas As An Effort To Mitigate & Adapt To Climate Change In Indonesia

The preparation of this paper is a form of implementation related to the paper entitled Navigating Amid Uncertainty in Spatial Planning by Zandvoort, M., and friends in 2017. The paper contains the form of uncertainty faced by planners in the planning process. Uncertainty is divided into 3 types, namely ontic uncertainty which does not know a phenomenon to a certain degree, while epistemic uncertainty is a phenomenon that can be known to a certain level, and ambiguity uncertainty is knowledge and different perceptions of a phenomenon. One form of uncertainty that occurs in planning is climate change. The phenomenon of climate change is a phenomenon caused by human activities either directly or indirectly. This activity triggers changes in the composition of gases in the atmosphere within a certain time. The countermeasures are in the form of mitigation and adaptation measures. One form of climate change mitigation and adaptation is the utilization of biogas. Biogas is a gas that comes from anaerobic activity (fermentation) from organic materials such as animal manure. The state of Indonesia has a large number of livestock and of course, produces manure. If left unchecked it will become pollution. For that, it needs processing to become something useful. Biogas has benefits as a new energy that can be utilized. Besides that, biogas can fight the greenhouse effect, which triggers climate change. In Indonesia, not all provinces where people process livestock manure into biogas for daily use.

Research on the risk evaluation of urban wastewater treatment projects based on an improved fuzzy cognitive map

To address the issues of ambiguous uncertainty and conflicting evidence in risk evaluation of wastewater treatment public-private partnership (PPP) project, a risk evaluation approach based on an evidence-based reasoning (ER)-improved fuzzy cognitive map (FCM) and 15 secondary evaluation indexes system are proposed. Then, ER is used to fuse expert opinions to obtain a correlation matrix. Finally, the rank evaluation results are obtained by FCM inference. External environmental risk (S), investment and financing risk (F) are the risk factors that have the greatest impact and sensitiveness on PPP wastewater treatment projects. For predictive analysis, the maximum project risk value was 0.5523 when the S value was set to 1, followed by the project risk value when the F value was set to 1. For diagnostic analysis, the greatest change in S value converged to 0.4978 when all risk factors were set to a neutral value of 0.5, while the greatest change in project risk was observed when all risk factors were set to 1. In addition, policy and legal risk, economic risk and market risk are the most sensitive risk factors among all secondary risk factors. The results are able to provide reliable project risk assessment solutions for project decision makers.

RIS-Aided Ground-Aerial NOMA Communications: A Distributionally Robust DRL Approach

A reconfigurable intelligent surface (RIS) aided air-to-ground uplink non-orthogonal transmission framework is investigated for next generation multiple access. Occupying the same spectrum resource, unmanned aerial vehicle (UAV) users and ground users (GUs) are connected to terrestrial cellular networks via the uplink non-orthogonal multiple access (NOMA) protocol. As the flight safety is important for employing UAVs in civil airspace, the collision avoidance mechanism has to be considered during the flight. Therefore, a joint optimization problem of the UAV trajectory design, RIS configuration, and uploading power control is formulated for maximizing the network sum rate, while ensuring the UAV’s fight safety and satisfying the minimum data rate requirements of both the UAV and GU. The resultant problem is a sequential decision making one across multiple coherent time slots. Besides, the unknown locations of obstacles bring uncertainties into the decision making process. To tackle this challenging problem, a sample-efficient deep reinforcement learning (DRL) algorithm is proposed to optimize the UAV trajectory, RIS configuration, and power control simultaneously. Moreover, considering the ambiguous uncertainties in the environment, a distributionally robust DRL algorithm is further proposed to provide the worst-case performance guarantee. Numerical results demonstrate that the two proposed DRL algorithms outperform the conventional ones in terms of learning efficiency and robustness. It is also shown that the network sum rate is significantly improved by the proposed RIS-NOMA scheme compared to the conventional RIS-orthogonal multiple access (OMA) scheme and the case where no RIS is deployed.

A survey comparative analysis of cartesian and complexity science frameworks adoption in financial risk management of Zimbabwean banks

<abstract> <p>Traditionally, financial risk management is examined with cartesian and interpretivist frameworks. However, the emergence of complexity science provides a different perspective. Using a structured questionnaire completed by 120 Risk Managers, this paper pioneers a comparative analysis of cartesian and complexity science theoretical frameworks adoption in sixteen Zimbabwean banks, in unique settings of a developing country. Data are analysed with descriptive statistics. The paper finds that overally banks in Zimbabwe are adopting cartesian and complexity science theories regardless of bank size, in the same direction and trajectory. However, adoption of cartesian modeling is more comprehensive and deeper than complexity science. Furthermore, due to information asymmetries, there is diverging modeling priorities between the regulator and supervisor. The regulator places strategic thrust on Knightian risks modeling whereas banks prioritise ontological, ambiguous and Knightian uncertainty measurement. Finally, it is found that complexity science and cartesianism intersect on market discipline. From these findings, it is concluded that complexity science provides an additional dimension to quantitative risk management, hence an integration of these two perspectives is beneficial. This paper makes three contributions to knowledge. First, it adds valuable insights to theoretical perspectives on Quantitative Risk Management. Second, it provides empirical evidence on adoption of two theories from developing country perspective. Third, it offers recommendations to improve Quantitative Risk Management policy formulation and practice.</p> </abstract>

Mesenchymal tumors and tumor-like lesions of the gastrointestinal tract: an overview

Mesenchymal tumors and tumor-like lesions of the gastrointestinal (GI) tract are uncommon. They vary from reactive tumefactive lesions and benign neoplasms to highly aggressive sarcomas. Among them, GI stromal tumors (GISTs) are most common, followed, with less frequency, by smooth muscle and neurogenic tumors. The major challenge resides in correctly identifying GISTs and providing acomprehensive report (including risk assessment and genotyping) that represents the basis for an optimized surgical-oncological treatment and/or adjuvant therapy. On the other hand, the challenge of benign lesions is to find agood name (well understandable and reproducible diagnostic term) that helps avoid diagnostic ambiguity and prognostic uncertainty so that overprognostication and overtreatment can be prevented. Moreover, several recently described genetically defined benign and malignant entities need be correctly diagnosed due to their special "targeted" therapeutic options and to further characterize their clinicopathological and biological properties in the future. These recent entities include aggressive epithelioid inflammatory myofibroblastic sarcoma (ALK-RANBP2-driven), malignant gastrointestinal neuroectodermal tumor (EWSR1-ATF1/CREB-related), NTRK-rearranged neoplasms, and, most recently, colorectal NUTM1-rearranged sarcomas. This review highlights the major clinicopathological features of gastrointestinal mesenchymal lesions in light of recent developments.

Coping with academic stress: Ambiguity and uncertainty tolerance in college students

Objective: Stress is a barrier to academic success for college students and the unique resilience effects of ambiguity and uncertainty tolerance have yet to be explored. We hypothesized that tolerance of ambiguity and tolerance of uncertainty relate to academic stress differently. Participants: We recruited 158 undergraduate participants from a medium-size public university in the Midwestern United States. Method: Participants completed measures of ambiguity tolerance, uncertainty tolerance, and academic stress coping strategies. Three separate regression analyses were conducted to predict approach coping, avoidance coping, and social support coping. Results: Results indicated that intolerance of ambiguity is a stronger predictor of approach and avoidance academic stress coping strategies compared to intolerance of uncertainty. Conclusion: These findings will allow for a better understanding of the dynamics underlying coping with academic stress that will be helpful to consider in vocational as well as mental health counseling for college students.

Optimal contracting under mean-volatility joint ambiguity uncertainties

We examine a continuous-time principal-agent problem under mean-volatility joint ambiguity uncertainties. Both the principal and the agent exhibit Gilboa–Schmeidler’s extreme ambiguity aversion with exponential utilities. We distinguish between expost realized and exante perceived volatilities, and argue that the second-best contract necessarily consists of two sharing rules: one for realized outcome and the other for realized volatility. The outcome-sharing rule is for uncertainty sharing and work incentives, as usual, and the volatility-sharing rule is to align the agent’s worst prior with that of the principal. At optimum, their worst priors are symmetrized, and realized compensation is positively related to realized volatility. This theoretical positive relation can be consistent with popular managerial compensation practices such as restricted stock plus stock option grants. A closed-form solution to a linear-quadratic example is provided.

A measure of ambiguity (Knightian uncertainty)

Uncertain or ambiguous events cannot be objectively measured by probabilities, i.e. different decision-makers may disagree about their likelihood of occurrence. This paper proposes a new decision-theoretical approach on how to measure ambiguity (Knightian uncertainty) that is analogous to axiomatic risk measurement in finance. A decision-theoretical measure of ambiguity is a function from choice alternatives (acts) to non-negative real numbers. Our proposed measure of ambiguity is derived from a novel assumption that ambiguity of any choice alternative can be decomposed into a left-tail ambiguity (uncertainty in the realization of relatively undesirable outcomes) and a right-tail ambiguity (uncertainty in the realization of relatively desirable outcomes). This decomposability assumption is combined with two standard assumptions: ambiguity sources (events) are independent (separable) from outcomes (consequences) and any elementary increase in uncertainty (increasing a more desirable outcome in a binary act) necessarily increases ambiguity.

A modified exchange algorithm for distributional robust optimization and applications in risk management

AbstractConvex semi‐definite semi‐infinite programming problems (SDSIP) represent a special class of distributionally robust optimization (DRO) problems with a wide range of applications in engineering and economics. In this paper, we propose a modified exchange algorithm for convex SDSIP that arises from DRO with matrix moment constraints. We first explore the convergence results of the modified exchange algorithm and perform the efficiency analysis based on a set of benchmark tests. In addition, we apply the SDSIP framework to investigate an optimized certainty bound risk with an ambiguity uncertainty set and implement the algorithm to solve a practical risk minimization problem in portfolio selection. The empirical results show both the efficiency of the algorithm and the robustness of the risk measure.

A scenario-based hybrid robust and stochastic approach for joint planning of relief logistics and casualty distribution considering secondary disasters

This paper proposes a scenario-based three-stage hybrid robust and stochastic model that optimally designs the response network and distributes casualties effectively under uncertain combinational scenarios of primary and secondary disasters. Following the stochastic severity of combinational disasters, the robust counterparts are derived against the ambiguous uncertainty of evacuee scales and transportation time, respectively. A customized progressive hedging algorithm based on the augmented Lagrangian relaxation is developed to solve the problem. We decompose the problem based on the scenario and iteratively solve the adaptively penalized sub-problems with decision variables independent of stages. The results of an illustrative example show that incorporating secondary disaster scenarios can contribute to improving relief coverage. The proposed algorithm is competitive with some benchmarks.

Effects of personality traits on user trust in human–machine collaborations

Data analytics-driven solutions are widely used in various intelligent systems, where humans and machines make decisions collaboratively based on predictions. Human factors such as personality and trust have significant effects on such human–machine collaborations. This paper investigates effects of personality traits on user trust in human–machine collaborations under uncertainty and cognitive load conditions. A user study of 42 subjects in a repeated factorial design experiment found that uncertainty presentation led to increased trust but only under low cognitive load conditions when users had sufficient cognitive resources to process the information. Presentation of uncertainty under high load conditions led to a decrease in trust. When further drilling down into personality trait groups of users, overall, users with low Openness showed the highest trust. Furthermore, under the low cognitive load condition, it was found that the trust was enhanced under ambiguity uncertainty with low Agreeableness, low Neuroticism, high Extraversion, high Conscientiousness, and high Openness. Under the high cognitive load condition, high Neuroticism and low Extraversion benefitted the trust without the uncertainty presentation. The results demonstrated that different personality traits affected trust differently under uncertainty and cognitive load conditions. A framework of user trust feedback loop was set up to incorporate the study results into human–machine collaborations for the meaningful participatory design.

An Optimum Volumetric Array Design Approach for Both Azimuth and Elevation Isotropic DOA Estimation

In this study, a new volumetric array design approach is presented for both azimuth and elevation isotropic direction of arrival (DOA) estimation. The presented method uses a minimum number of additional sensors to extend the given arrays to a volumetric array which has equal values for the Cramér-Rao lower bound (CRLB) for the entire azimuth and elevation angles. This approach can be applied to all arbitrary linear and planar arrays. Moreover, the design approach also takes into account the electromagnetic mutual coupling (MC) effect between the array elements and both the azimuth and elevation angular ambiguity uncertainties in an optimum manner while extending the array. It has been verified both analytically and with simulations that the designed volumetric arrays satisfy the two dimensional (2-D) isotropic DOA estimation conditions. The proposed approach is applied to Uniform Linear Arrays (ULA), Uniform Circular Arrays (UCA), V-shaped Arrays, and an arbitrary planar array to extend to optimum volumetric arrays with considerable results.

The Functional Roles of the Amygdala and Prefrontal Cortex in Processing Uncertainty.

Decisions under uncertainty distinguish between those made under risk (known probabilities) and those made under ambiguity (unknown probabilities). Despite widespread interest in decisions under uncertainty and the successful documentation that these distinct psychological constructs profoundly-and differentially-impact behavior, research has not been able to systematically converge on which brain regions are functionally involved in processing risk and ambiguity. We merge a lesion approach with computational modeling and simultaneous measurement of the arousal response to investigate the impact the medial prefrontal cortex (mPFC), lateral prefrontal cortex (lPFC), and amygdala have on decisions under uncertainty. Results reveal that the lPFC acts as a unitary system for processing uncertainty: Lesions to this region disrupted the relationship between arousal and choice, broadly increasing both risk and ambiguity seeking. In contrast, the mPFC and amygdala appeared to play no role in processing risk, and the mPFC only had a tenuous relationship with ambiguous uncertainty. Together, these findings reveal that only the lPFC plays a global role in processing the highly aversive nature of uncertainty.

Соціокомунікативний підхід до проблеми запозичень в українській податковій термінології

The influence of scientific terminology on the formation of the national language is manifested in the expansion of the terminological vocabulary of the Ukrainian language at the expense of words associated with new types of mental and practical activity, in interaction with the lexical system of living, spoken language, in categorical differentiation of lexemes (belonging to different categories – names processes, objects, phenomena, individuals, institutions), in the formation of the first system formations on the disparate terms basis. Tax terminology belongs to the ancient layers of the lexical system, its formation depends on many linguistic and extra-linguistic factors. The functioning of the tax vocabulary as a certain integral system, its development and ordering were the least studied of Ukrainian Linguistic issues. The least studied in linguistic-Ukrainian studies were the questions of the functioning of the tax vocabulary as a certain integral system, its development and organization. The analysis of the historical background of economic activity in the Ukrainian language aspect, is closely linked to the Ukrainian political history. In addition, we take into account the geopolitical situation that arose as a result of the distribution of Ukrainian lands for several centuries between different states, where Ukrainians followed to legislations of these countries, where the rights and status of the Ukrainian language manifested itself in different ways. Different linguistic and political orientations of the regions of Ukraine had influenced on the formation of the tax terminology on the Dnieper and Dniester territories. As follows, there were extralinguistic factors of analyzed terms borrowing which had the main influence on the process, such as: Integration processes in science, the high level of development of this science-applied discipline in the countries of Western Europe. The long existence of Ukraine in conditions of economic, socio-political and cultural dependence on neighbouring states. As a result of the historical and political factors, the stages of free, natural development of terminology, dominance in all spheres of special language, specifically Ukrainian vocabulary, as alternating with the stages of artificial Russification, polonization or Germanization of the economic vocabulary of the Ukrainian language with parallel withdrawal from the circulation of terms created on its own linguistic basis. The sources of the Ukrainian tax terminology were such languages as Latin, Greek, French, German, Lithuanian, Italian, English, Turkish, Arabic, Polish. The situation of uncertainty and ambiguity of approaches that has developed in Ukraine in the field of scientific language (scientific style in general) requires serious linguistic analysis and developing of specific recommendations for the creation and use of terms due to their solidity in science and the language, convenience, and the correspondence of the Ukrainian language system. That is why particular importance is the question of the correlation of the national language and foreign languages terms, the role of borrowing in the system of development modern Ukrainian terminology. The best option is to use national terms if they correspond to the optimal aesthetic, linguistic and cultural characteristics, psychological characteristics. The situation of uncertainty ambiguity of approaches which has developed in Ukraine in the field of the scientific language, (the scientific style in general),needs serious linguistic analysis and making specific recommendations as for creating and using terms, considering on their solidity in science and language, convenience, compliance with the Ukrainian language system.

Very Broad Laws

Extremely broad laws offend due process. Although the problem has not been lost on courts, their solution to date has been haphazard: casting breadth as a species of uncertainty—ambiguity or vagueness—and repurposing uncertainty-focused doctrine accordingly. The trouble is, breadth and uncertainty are not the same. They have different analytic features and raise distinct concerns, making the tools designed to resolve uncertainty ill-suited to reining in breadth. Vague and ambiguous laws deprive people of notice about what the law requires. They evoke the Star Chamber and Kafka stories—the dread of inhabiting an incomprehensible legal order. With broad laws, the issue is not notice but reach. Broad statutes can be plenty clear about what they require. The problem is they sweep in too much everyday conduct, arousing worry about outsized power and arbitrary enforcement. Here, the literary specter is not Kafka, but Orwell, and the nightmare is not an opaque legal system; it is a police state. Extremely broad laws, in this sense, are problematic for the same basic reason as general warrants: they afford state officials practically boundless justification to interfere with private life. After expounding the problem abstractly, I close by exploring how courts might tackle the breadth problem in practice—and I ultimately suggest that judges should be empowered to hold statutes “void-for-breadth.”

Managerial Compensation and Outcome Volatility

We present a simple discrete-time version of the continuous-time agency model under mean-volatility joint ambiguity uncertainties, which conveniently captures a number of important properties of optimal contracts without having to rely on complex continuous-time mathematical issues. The volatility ambiguity introduces two different volatilities: ex-ante perceived, and ex-post realized volatilities. The ex-post volatility in turn consists of ex-ante predictable and ex-ante purely ambiguous components. As seen in the continuous-time model, the second-best contract consists two sharing rules: one for the outcome and the other for the realized volatility. We argue that the second-best contract can help reconcile Aggarwal and Samwick (1999) and Core and Guay (2002), the two seemingly contradictory empirical studies on relationship between CEO pay and outcome volatility.

Who gets the benefit of the doubt? The impact of causal reasoning depth on how violations of gender stereotypes are evaluated

SummaryA large body of research demonstrates that women encounter severe penalties for violating gender stereotypes. In this paper, we explore the conditions under which the reverse is true—when being subject to a stereotype can actually benefit a woman compared to a man who is not subject to the same stereotype. In particular, we suggest that in situations of causal ambiguity—uncertainty about the reasons that a behavior occurred—differences in how men and women are evaluated will be moderated by the extent to which observers engage in a low or a high level of deliberative causal reasoning. In 3 experimental studies, participants were asked to make judgments about an employee who violated a female gender stereotype by failing to provide help to a coworker when asked to do so, but the reasons for this behavior were unclear. When participants were prompted to engage in deliberative causal reasoning, women were evaluated more positively than men, but not in the absence of such a prompt. Moreover, when participants did engage in deliberative causal reasoning, the more positive evaluations of women compared to men were driven by participants' beliefs that women's behavior was due more to situational constraints than the same behavior by men.

Perception and translation of numbers: the case of a health campaign in Denmark

This article explores the translation of numeric health communications from the authorities to ordinary citizens. Based on qualitative interviews and document analysis, it follows the life of a Danish health campaign called ‘6 a day’ from its initiation to its dissemination, and finally to its place in the perceptions and health practices of citizens. While the definition of the target of ‘6 a day’ was clearly anchored in social and scientific contexts, it incorporated considerable ambiguity and scientific uncertainty, flaws which were deliberately kept from citizens. The number ‘6’ was meant to appear unquestionable. We suggest that this way of making and disseminating numeric health campaigns may best be understood as a process of creating a mould and offering it to citizens to fill with their own health practices. Such a process is rife with translations and the article analyses both these and their impact on citizens’ health practices and perceptions. We conclude that the success of the campaign lies in its implicit logic and the agency it fosters, rather than its ability to improve health literacy or make citizens aspire to specific health targets. The article thereby contributes to an understanding of the effects of numeric health communications. Health communicators may also gain from an increased awareness of the processes of translation involved in health messages created as moulds.