Judgments Of Decision Makers Research Articles

IS THERE A CAUSAL RELATIONSHIP BETWEEN FINANCIAL PERFORMANCE AND PREMIUM PRODUCTION? EVIDENCE FROM TURKISH INSURANCE INDUSTRY

This study aims at determining the causal link between financial performance and premium production of non-life insurance companies. The relation between the financial performance and premium production is explored employing data from the 2011-2019 period for eight Turkish non-life insurance companies. In the first stage of the analysis, a hybrid model including LOPCOW, SWARA II, and MARCOS methods is proposed to determine companies’ financial performance values. In this stage, a novel integrated weighting method for calculating criterion weights is applied based on objective information and judgements of decision-makers. In the second stage, the association between financial performance and premium production is investigated by correlation analysis. In the last stage, the causality linkage between the two variables is estimated using a panel causality test developed by Dumitrescu and Hurlin (2012). According to the results obtained from the panel causality test, the bidirectional causality relation exists between financial performance and premium production. Besides, the individual panel causality results reveal that bidirectional causality is valid for only Allianz and Anadolu insurance companies, which had an average share of over 35% in total non-life premium production during the analysis period. The paper provides fresh evidence on the association between the financial performance and premium production, particularly from the Turkish context.

Joint Effects of Accuracy and Equity on Fairness: Judgments of Algorithmic and Human Decisions

Joint Effects of Accuracy and Equity on Fairness: Judgments of Algorithmic and Human Decisions

An integrated fuzzy AHP and fuzzy TOPSIS approach for screening backfill materials for contaminant containment in slurry trench cutoff walls

The inclusion of backfill material is crucial for the effective containment of contaminants in a slurry trench cutoff wall. However, selecting the optimal backfill material is complex and involves multiple criteria. This study aimed to develop a new approach to assist in the selection process by rationally dealing with the subjective judgment of decision makers. The approach employed fuzzy analytic hierarchy process (AHP) and fuzzy technique for order preference by similarity to ideal solution (TOPSIS) methods. Initially, consistent judgment matrices were established based on a unique consulting questionnaire. The fuzzy AHP method used Buckley's method to calculate the fuzzy weights of pairwise comparisons. The fuzzy TOPSIS method was then employed to rank and evaluate four different backfill materials. The proposed methodology was successfully implemented at a real contaminated site in China to select the appropriate backfill material for construction of a slurry trench cutoff wall. Based on the proposed integrated methodology, fiber reinforced reactive magnesia-activated slag-soil-bentonite (FMSB) was determined as the most appropriate backfill materials for contaminant containment in slurry trench cutoff walls at the site reported in this study.

Autonomous intelligent control of earth pressure balance shield machine based on deep reinforcement learning

In order to reduce the construction risk caused by human operation error and improve the geological adaptive ability of the shield machine, an autonomous intelligent control method is proposed for shield machine within the framework of interaction–judgment–decision based on Deep Deterministic Policy Gradient (DDPG) deep reinforcement learning in this study. Due to the strong nonlinear relationship between the shield machine's tunneling parameters, this research builds a deep reinforcement learning environment using mechanism model of sealed cabin pressure. DDPG agent model of the shield machine is established to replace the shield machine to interact and train with the geological environment. By minimizing the difference between the target pressure setting value and the sealed cabin pressure value, the dynamic balance between the sealed cabin pressure and the pressure on the excavation surface is realized, and the best strategy is obtained. Through real-time interaction with the geological environment, the method in this paper can dynamically adjust the tunneling parameters, accurately control the sealed cabin pressure, and has a strong geological adaptive ability. By realizing the intelligent decision-making of the tunneling parameters, it greatly improves the independent decision-making ability of the shield machine system, reduces the inaccuracy of human operation, and provides an effective guarantee for the efficient and safe operation of the shield machine. This study applies deep reinforcement learning technology to the control field of earth pressure balance shield machine, promotes AI technology, and provides a new idea for the development of AI construction technology in engineering field.

A procedure for risk assessment of check dam systems: A case study of Wangmaogou watershed.

Flood-based hydrodynamic damage to check dam systems on the Loess Plateau of China occurs frequently, and there is a strong desire to carry out risk assessments of such check dam systems. This study proposes a weighting method that combines the analytic hierarchy process, entropy method, and TOPSIS to assess the risk of check dam systems. The combined weight-TOPSIS model avoids weight calculation only considers the influence of subjective or objective preference and the bias of the single weighting method. The proposed method is capable of multi-objective risk ranking. It is applied to the Wangmaogou check dam system located in a small watershed on the Loess Plateau. The result of risk ranking matches the reality of the situation. The gray correlation theory model is utilized to rank the risks in the same research area and compared with the results of the combined weight-TOPSIS model. The combined weight-TOPSIS model is more favorable to risk assessment than the gray correlation theory model. The resolution level and decisive judgment of the combined weight-TOPSIS model are more advantageous. These results are in line with the actual conditions. It proves that the combined weight-TOPSIS model can provide a technical reference for the risk assessment of check dam systems in small watersheds.

Biomechanical Analysis of Mawashi-Geri Kick Motion on Kenshi Shorinji Kempo Jambi Province

In randori Shorinji Kempo, various variations of attacks are used to get a high number of scores. Mawashi-Geri is the kick most often used by kenshi. Mawashi-Geri has the privilege of a certain randori due to her strong capacity to obtain higher match score scores. The purpose of this study is to collect accurate information and data about the examination or analysis of the speed, precision, biomechanics of Mawashi-Geri kicks, angles of body segments, as well as how to perform them. The subjects of this study were four athletes with different amounts of body weight. This research was conducted using descriptive research type analysis with qualitative and quantitative methods. A qualitative approach was used to describe the biomechanical phase of the Mawashi-Geri kick. While the quantitative approach using the Kinovea software program is related to measuring the angle of body parts, the speed of motion of the Mawashi-Geri kick biomechanics, measurements and calculations are presented systematically to facilitate understanding and drawing conclusions. From the results of research and discussion as well as expert judgment decisions, it can be concluded the speed, accuracy and angle of body segments, it can be said that the kick of Mawashi-Geri kenshi Shorinji Kempo Jambi province with the fastest biomechanical average speed is kenshi B Kicking biomekanics with the first speed is 24m/s, for Mawashi-Geri's slowest biomechanical kick is kenshi A's biomechanics from the second kick, at a speed of 13.5m/s. As for the speed of hitting the target momentary kick with one kick, the biomechanical speed of the first kick kenshi C is 76.2m/s, and the slowest is the biomechanical kenshi A fourth kick, which has a speed of 45.8 m/s. The results of angular analysis of each segment's body of the subject during the biomechanical process of the Mawashi-Geri kick showed the angle of the leg opening between and 128,2 and 142,8 degrees. And the angle of inclination of the body is between 146.0 and 158.9 degrees. The angle of rotation of the pedestal leg is between 119.4 and 178.9 degrees, and the biomechanics of the hip and foot to kick in between 96.3 and 135.6 degrees. Based on the results of the analysis, it can be concluded that excessive angles have little effect on the biomechanics of Mawashi-Geri's kick slowdown. However, with the angle of inclination of the body and the rotation of the footrest, as well as the biomechanical rotation of the hips and feet when kicking, the angle of the leg opening will be more optimal.

What does it mean to have an equal say?

AbstractDemocracy is the form of government in which citizens have an equal say in political decision-making. But what does this mean precisely? Having an equal say is often defined either in terms of equal power to influence political decision-making or in terms of appropriate consideration, i.e., as a matter of attributing appropriate deliberative weight to citizens’ judgement in political decision-making. In this paper I argue that both accounts are incomplete. I offer an alternative view according to which having an equal say is having a say as an equal. That is, having an equal say is to be defined in terms of citizens’ occupying a role of political decision-makers, i.e., the political office of the democratic co-ruler of the polity, such that no citizen is a secondary or auxiliary decision-maker; they rule together as equals. This view aligns with the traditional understanding of democracy as rule by the people while providing a coherent conceptual framework for specifying what it means for democratic citizens to have an equal say which incorporates the strengths of alternative accounts and overcomes some of their challenges.

Public reactions to instances of workplace gender discrimination.

The number of people witnessing or experiencing gender discrimination at work is still high around the globe. While the existing literature has investigated potential mechanisms underlying gender discrimination and the consequences of experiencing gender discrimination at work, it remains unclear how third-party observers-as opposed to employees or coworkers-react to specific instances of workplace gender discrimination. The results of six experiments demonstrate that (a) people in general judge organizational decisions that discriminate against individual male (vs. female) workers as more legitimate and (b) this difference in legitimacy judgments is significantly greater among women than men. This discrepancy in legitimacy judgments occurs because women (more than men) consider the collective situation of female and male workers when judging the legitimacy of organizational decisions that discriminate against individual workers based on gender. These findings document how group-level concerns shape people's legitimacy judgments of organizational decisions discriminating against individuals and equip organizations and policymakers with a better understanding of people's polarized opinions regarding gender discrimination at the workplace. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The named entity recognition of vessel power equipment fault using the multi-details embedding model

The fault diagnosis of vessel power equipment is established by the manual work with low efficiency. The knowledge graph(KG) usually is applied to extract the experience and operation logic of controllers into knowledge, which can enrich the means of fault judgment and recovery decision. As an important part of KG building, the performance of named entity recognition (NER) is critical to the following tasks. Due to the challenges of information insufficiency and polysemous words in the entities of vessel power equipment fault, this study adopts the fusion model of Bidirectional Encoder Representations from Transformers (BERT), revised Convolutional neural network (CNN), bidirectional long short-term memory (BiLSTM), and conditional random field (CRF). Firstly, the adjusted BERT and revised CNN are respectively adopted to acquire the multiple embeddings including semantic information and contextual glyph features. Secondly, the local context features are effectively extracted by adopting the channel-wised fusion structures. Finally, BiLSTM and CRF are respectively adopted to obtain the semantic information of the long sequences and the prediction sequence labels. The experimental results show that the performance of NER by the proposed model outperforms other mainstream models. Furthermore, this work provides the foundation of the tasks of intelligent diagnosis and NER in other fields.

Credit Risk Analysis Using Fuzzy Logic with Machine Learning Models

Credit Risk is an important issue in the Banking Industry. Credit risk Prediction and assessment of credit is a difficult task for credit managers. Banking Industry has large amount of data related to the behavior of the customer and their credit history, but this raw data is not useful for making correct judgment in credit decisions. The banking industry is need of a correct credit decision making system, to distinguish between good customers and default customers. The data mining domain is suitable for assessing credit risk and making good decisions on credit. Feature selection is one of the main pre-processing step in the data mining. This paper use FuzzyRoughSetTheory (FRST) for finding feature subset. Four other feature selection methods are used to find the optimal feature subset. The four feature selection methods are Information Gain, Relief, Chi-Squared and Wrapper subset model. These different feature selection methods are compared in terms of accuracy and efficiency.

Unique Moral Judgements of Psychopathic Individuals

Emotions are important in human moral judgment and behavioral decision making. In the case of psychopaths, emotional deficits due to low fear response and dysregulated control prevent them from feeling the consequences of wrong behaviors, and therefore they cannot fully understand social moral behaviors or internalize the public's social moral system. Thus psychopathic individuals have their own unique moral judgment system based on their emotional deficits.

Throwing and manipulating and cheating with a DNA nano-dice

Artificial molecular machines have captured the imagination of researchers, given their clear potential to mimic and influence human life. Key to behavior simulation is to reproduce the specific properties of physical or abstract systems. Dice throwing, as a stochastic model, is commonly used for result judgment or plan decision in real life. In this perspective we utilize DNA cube framework for the design of a dice device at the nanoscale to reproduce probabilistic events in different situations: equal probability, high probability, and low probability. We first discuss the randomness of DNA cube, or dice, adsorbing on graphene oxide, or table, and then explore a series of events that change the probability through the way in which the energy released from entropy-driven strand displacement reactions or changes in intermolecular forces. As such, the DNA nano-dice system provides guideline and possibilities for the design, engineering, and quantification of behavioral probability simulation, a currently emerging area of molecular simulation research.

Indicator of suitability for evaluating the aquifer thermal energy storage using the GIS-based MCDA technique in the Halabja-Khurmal sub-basin

Thermal energy is one of the eco-friendly sources of energy used worldwide for storing heat and cold between seasons. The aquifer thermal energy storage system effectively reduces carbon dioxide emission gas in the Halabja governorate. It is an economical way to be used in cooling and heating applications. This study evaluates the suitability of aquifer thermal energy storage in the Halabja-Khurmal sub-basin. Six critical criteria were selected: the type of aquifers, groundwater recharge, fresh/saline groundwater, groundwater quality, seepage velocity, and mean annual temperature by applying decision-maker judgment. The hydrogeological and climate criteria analysis combination has a consistency ratio of 0.008 in AHP. As a result, the Aquifer thermal energy storage suitability map in the Halabja-Khurmal sub-basin displays a surface area of 62.1% as strongly suitable, 7.7% as suitable in northern and southern parts, 29.2% as weakly suitable in southwestern, east, southeast, and northeast, and 1% as not suitable for aquifer thermal energy storage system.

On the importance of working memory in the driving safety field: A systematic review

In recent years, many studies have used poor cognitive functions to explain risk safety differences among drivers. Working memory is a cognitive function with information storage and attentional control that plays a crucial role in driver information processing. Furthermore, it is inextricably linked to parameters such as driving performance, driving eye movements and driving neurophysiology, which have a significant impact on drivers' risky behavior and crash risk. In particular, crash risk is a serious risk to social safety and economic development. For this reason, it is necessary to understand how risk-related working memory affects driving so that pre-driving safety pre-training programs and in-vehicle safety assistance systems for driving can be developed accordingly, contributing to the development of semi-autonomous vehicles and even autonomous vehicles. In this paper, a systematic search of the literature over the past 23 years resulted in 78 articles that met the eligibility criteria and quality assessment. The results show that higher working memory capacity, as measured neuropsychologically, is associated with more consistent and safer driving-related parameters for drivers (e.g., lane keeping) and may be related to pupil dilation during risk perception while driving, which is associated with driving outcomes (tickets, pull-overs, penalty points and fines,and driving accidents) is closely related to the perceived usefulness of the human–machine interface, reaction time, standard deviation of steering wheel corners, etc. when the autonomous driving takes over. In addition, higher working memory load interference was associated with more inconsistent and unsafe driving-related parameters (including but not limited to eye movements, electrophysiology, etc.), with higher working memory load being associated with easier driver concentration on the road, faster heart rate, lower heart rate variability, and lower oxyhemoglobin (OxyHb) and deoxyhemoglobin (DeoxyHb). Only a limited number of studies have simultaneously investigated the relationship between working memory capacity, working memory load and driving, showing an interaction between working memory capacity and working memory load on lane change initiation and lane change correctness, with working memory capacity acting as a covariate that mediated the effect of working memory load on braking reaction time. In addition, working memory-related cognitive training had a transfer effect on improving driving ability. Overall, working memory capacity determines the upper limit of the number of working memory attention resources, while working memory load occupies part of the working memory attention resources, thus influencing information perception, decision judgment, operational response, and collision avoidance in driving. Future effective interventions for safe driving can be combined with capacity training and load alerting. These findings contribute to our understanding of the role of working memory in driving and provide new insights into the design of driver safety training programs and automated driving personalized in-vehicle safety systems and roadside devices such as signage.

Key technologies of smart factory machine vision based on efficient deep network model

Most of the existing smart space machine vision technologies are oriented to specific applications, which are not conducive to knowledge sharing and reuse. Most smart devices require people to participate in control and cannot actively provide services for people. In response to the above problems, this research proposes a smart factory based on a deep network model, which is capable of data mining and analysis based on a huge database, enabling the factory to have self-learning capabilities. On this basis, tasks such as optimization of energy consumption and automatic judgment of production decisions are completed. Based on the deep network model, the accuracy of the model for image analysis is improved. Increasing the number of hidden layers will cause errors in the neural network and increase the amount of calculation. The appropriate number of neurons can be selected according to the characteristics of the model. When the IoU threshold is taken as 0.75, its performance is improved by 1.23% year-on-year. The residual structure composed of asymmetric multiple convolution kernels not only increases the number of feature extraction layers, but also allows the asymmetric image details to be better preserved. The recognition accuracy of the trained deep network model reaches 99.1%, which is much higher than other detection models, and its average recognition time is 0.175s. In the research of machine vision technology, the smart factory based on the deep network model not only maintains a high recognition accuracy rate, but also meets the real- time requirements of the system.

Conflicts of interest in medicine. CETREMI recommendations.

Conflicts of interest are situations in which judgment and integrity of medical decisions or actions are influenced by a secondary interest, often of an economic nature. The Committee of Ethics and Transparency in the Physician-Industry Relationship of the National Academy of Medicine of Mexico recognizes that these conflicts occur in health professionals' daily life, but also in public and private institutions that provide health services, as well as in the academy and in research activities. Therefore, it is necessary to identify conflicting situations and always act in accordance with the patient's interest.

루마니아 과거청산에 관한 연구

This paper attempts to analyze the case of past liquidation in Romania’s ‘execution model’ with two dimensions: investigation and reflection on past problems. Like other former communist countries in Eastern Europe, Romania has transformed into a democracy. Despite the 42 years of the Romanian communist regime between 1947 and 1989, the past liquidation mainly focused on the 25-year dictatorship of Ceausescu’s iron-fist, which was dependent on the secret police called Securitate. Once democratized, Romania's past liquidation was implemented in two aspects: past investigation and past reflection. The past investigation was conducted in the form of executions during the December 1989 Revolution. Ceausescu, his family, and his aides were heavily sentenced, including death and life imprisonment in the military trial. However, most Securitate agents received no punishment. The Romanian government has implemented very limited legal measures to compensate or remedy victims' honor. Past reflections have progressed even more slowly. This is because the National Salvation Front, the main revolutionary force, served as a sidekick to the formal communist regime. A criminal investigation body was only set up in 2006, 16 years after democratization. Romania’s lack of decisive judgments and limited systematic past reflection still remain a heavy legacy in social turbulences in Romania. It will have significant implications for the policy of Korean unification in the future.

Evaluation of Sleep Quality of Anesthesiologists Working in Turkey

Objective: Sleep is one of the basic daily activities that are important for an individual with physical, mental, social, and intellectual needs to be in good physical and mental health. Although many definitions are made, sleep; is a complex and physiological event affected by pathophysiological, physical, psychological, and environmental factors. Anesthesiologists often work in closed environments and with long working hours, which can cause severe, chronic sleep loss and sleep disruption. Sleeplessness and low sleep quality can cause decreased attention during the day, impaired judgment, and delays in decision-making. This study, it is aimed to determine the sleep quality of Anesthesiology and Reanimation specialists working in Turkey. Methods: The study included all anesthesiologists whose e-mail addresses were registered with the Turkish Society of Anesthesiology and Reanimation and who worked in Turkey. Survey questions, which the participants can answer electronically, were sent to the participant's e-mail addresses. To increase the number of participants, a reminder email was sent three weeks after the first email. The data were expressed as a number, percentage, mean, and standard deviation and the correlation between the parameters will be evaluated at a 95% confidence interval by performing Pearson correlation analysis; p< 0.05 was accepted as significant. Results: Due to seven people with sleep disorders being excluded from the study, 210 out of 217 people who answered the questionnaires sent by email to the anesthetists who are members of the Turkish Society of Anesthesiology and Reanimation were included in the study. Of the respondents who worked in the following fields: 30% (n = 63) State Hospital, 33.3% (n = 70) University Hospital, 17.1% (n = 36) Ministry of Health Affiliate Hospital, 19.5% (n = 41) Private Hospital, and 73.3% (n = 154) at the Operating Room, 10% (n = 21) at the Intensive Care, 15.2% (n = 32) at the Operating Room + Intensive Care, and 1.4% (n = 3) at other departments, 48.4% (n = 105) were male, 51.6% (n = 112) were female, with a mean age of 41.5±7.6 years. The average hourly shift for the participants, 61% of whom were on the night shift, was 50 hours per month, and 25% were working more than 45 hours per week. Conclusion: The sleep quality of anesthesiologists is poor, which causes daytime dysfunction. It is thought that the reason for poor sleep quality, in general, is the adverse effects of their duties and responsibilities, working environment, and operating conditions on sleep quality.

Walking the line in times of crisis: EU fundamental rights, the foundational value of the rule of law and judicial response to the rule of law backsliding

The research focus of the paper is on the relation between general principles, fundamental rights and the rule of law in the EU. The role of the judiciary is evaluated through the prism of the jurisprudence of the Court of Justice of the EU (CJEU) with a particular focus on the formula, introduced in the Associação Sindical dos Juízes Portugueses judgment and subsequent decisions by the CJEU, related to the rule of law and independence of the judiciary. A thorough assessment of the relation between fundamental rights, foundational values of the EU such as the rule of law and effective judicial protection through the methodological evaluation of the effectiveness and functional interpretation is included. The core of the research reflects the functional approach of the CJEU with respect to judicial independence as the condition for effective protection of fundamental rights and EU law. Especially crucial is the role of national courts for upholding the rule of law on EU level. The role of the EU’s Rule of Law Report mechanism, introduced in 2020, is analysed as judicial independence forms an essential part of the reports. The EU Rule of Law reports serve as illustrations of the underlying problems, related to the rule of law and in particular the independence of the judiciary and effective judicial protection and related enforcement and implementation issues.

Simplifying the Complexity in the Problem of Choosing the Best Private-Sector Partner

Governments frequently partner with the private sector to provide infrastructure and public services. These cooperations, known as public–private partnerships (PPPs), have often failed. Sometimes, due to the problem’s complexity, the public sector cannot choose the right partner for these projects, which is one of the main reasons for failures. Complexity in such problems is associated with a large number of indicators, imprecise judgments of decision-makers or problem owners, and the unpredictability of the environment (under conditions of uncertainty). Therefore, presenting a simplified algorithm for this complicated process is the primary goal of the current research so that it can consider the problem’s various dimensions. While many researchers address the critical risk factors (CRFs) and others focus on key performance indicators (KPIs), this research has considered both CRFs and KPIs to choose the best private-sector partner. In addition, we used single-valued neutrosophic sets (SVNSs) to collect decision-makers’ views, which can handle ambiguous, incomplete, or imprecise information. Next, by defining the ideal alternative and using the similarity measure, we specified the ranks of the alternative. Additionally, to face the uncertain environment, we examined the performance of options in four future scenarios. The steps of the proposed algorithm are explained in the form of a numerical example. The results of this research showed that by employing a simple algorithm, even people who do not have significant operations research knowledge could choose the best option by paying attention to the dimensions of the problem complexity.