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Purpose: To compare occlusal schemes with condylar inclination and anterior guidance in dentate individuals. Materials and Methods: A total of 26 dentate patients of Indian origin between the ages of 18 and 30 with canine-guided occlusion and 26 patients with group function occlusion were included in the study. The School of Articulator Munich (SAM) Axioquick system was used to assess the condylar guidance and eccentric tracings of the patients. For analyses, Student t test was used. For quantitative data, the means and SDs were calculated. For statistical analyses, the probability of type-I error of .05 was considered statistically significant. Results: The mean condylar guidance for canine-guided and group function occlusion was 38.4 ± 12.7 degrees and 30.5 ± 12.5 degrees on the right side, respectively. On the left side it was 36.5 ± 13.0 degrees and 27.5 ± 12.0 degrees for canine-guided and group function occlusion, respectively, with a statistically significant difference (P = .01). The condylar guidance, incisal guidance, Bennett angle, protrusion, left lateral and right lateral movement, and left and right lateral angles were analyzed statistically between the two types of occlusions. The results showed a statistically significant difference between the two groups for all parameters except right condylar guidance. Furthermore, all parameters were higher in the canine-guided occlusion group over group function occlusion. Conclusions: Within the study limitations, it was concluded that the condylar guidance was steeper in canine-guided occlusion than in group function occlusion. The eccentric parameters were steeper in canine-guided occlusion than in group function occlusion. This study showcases that the condylar guidance might not play a major role in determining the occlusal scheme but that the incisal guidance determines the occlusal scheme predominantly in Class 1 occlusion patients. [ABSTRACT FROM AUTHOR]

Summary: In this paper, a non‐orthogonal multiple access (NOMA)‐based precoded quadrature spatial modulation (PQSM) technique (NOMA‐PQSM) has been proposed for the downlink scenario. In NOMA‐PQSM, two intended receiving antennas are activated at any time instant. One antenna is activated for the in‐phase component of the transmitted signal, and another one is activated for the quadrature phase component, on the basis of data bits. NOMA‐PQSM provides benefits like improved spatial diversity and spectral efficiency in comparison with spatial modulation. This work uses zero forcing (ZF) precoding over downlink flat fading Rayleigh multiple input multiple output (MIMO) channels, to limit the channel's deteriorating effect on transmitted signal, assuming perfect channel state information (CSI) at the transmitter. A low complexity receiver based on the successive interference cancellation is used. An expression for the upper bound of average bit error probability is derived. Moreover, the expressions for the sum mutual information of users and its lower bound are also derived. The proposed scheme is compared with the preprocessing aided spatial modulation (PSM)‐based counterpart. Monte Carlo simulations reveal that the NOMA‐PQSM scheme outperforms its orthogonal counterpart and the PSM scheme. [ABSTRACT FROM AUTHOR]

In order to save on test costs, the optimal truncated sequential test (OTST) for the parameter of the exponential distribution is studied. According to Bayes decision theory, dynamic programming methods and procedures are established to solve the OTST. Through comparison with the test plans provided by international standard IEC 61124 and Russian national standard GOST R 27.402, the results show that the OTSTs solved by our new method can control the error probabilities strictly and save more synthetical expected test time (SETT). The OTSTs are also compared with the near-optimal ones solved by the sample space sorting method (SSSM). The results show that the test plans solved by these two methods are almost consistent. However, our new method is much faster in computation, especially when the maximum sample size (MSS) of a truncated sequential test increases. It can save 74.23% of the computational time compared with SSSM when the MSS equals 15. At last, the MSS of OTST is optimized. By optimizing the MSS, the corresponding OTST can save about 5% of the SETT compared to the one with the minimum MSS. [ABSTRACT FROM AUTHOR]

ABSTRACT The spectrum sensing is a major significant task in cognitive radio networks (CRNs) to avoid the unacceptable interference to primary users (PUs). Here, the threshold value determines the effectiveness of spectrum sensing and regarded as a sensing system. The fixed threshold used by the current energy detection‐based spectrum sensing (SS) techniques does not provide sufficient safety for the main users. The threshold is determined by lowering the complete probability of decision error in addition to these guidelines. Therefore, an energy detection using nonparametric amplitude quantization optimized with arithmetic optimization algorithm for enhanced spectrum sensing in CRNs (ED‐NAQ‐AOA‐SS CRN) is proposed in this paper to acquire the ideal threshold for decreasing the total error probability. The proposed method achieves greater probability of detection of 99.67%, 98.38%, 92.34%, and 97.45%, lower settling time of 98.33%, 89.34%, 83.12%, and 88.96%, and lower error rate of 93.15%, 91.25%, 79.90%, and 92.88% compared with existing techniques, like intelligent spectrum sharing and sensing in CRN with adaptive rider optimization algorithm (AROA), a novel technique for spectrum sensing in CRN utilizing fractional gray wolf optimization with the cuckoo search optimization (GWOCS), and adaptive neuro‐fuzzy inference scheme depending on cooperative spectrum sensing optimization in CRNs (ANFIS). [ABSTRACT FROM AUTHOR]

Biosensing techniques are progressing rapidly, promising the emergence of sophisticated virtual reality (VR) headsets with versatile biosensing enabling an objective, yet unobtrusive way to monitor the user's physiology. Additionally, modern artificial intelligence (AI) methods provide interpretations of multimodal data to obtain personalised estimations of the users' oculomotor behaviour, visual perception, and cognitive state, and their possibilities extend to controlling, adapting, and even creating the virtual audiovisual content in real-time. This article proposes a visionary approach for personalised virtual content adaptation via novel and precise oculomotor feature extraction from a freely moving user and sophisticated AI algorithms for cognitive state estimation. The approach is presented with an example use-case of a VR flight simulation session explaining in detail how cognitive workload, decrease in alertness level, and cybersickness symptoms could be modified in real-time by using the methods and embedded stimuli. We believe the envisioned approach will lead to significant cost savings and societal impact and will thus be a necessity in future VR setups. For instance, it will increase the efficiency of a VR training session by optimizing the task difficulty based on the user's cognitive load and decrease the probability of human errors by guiding visual perception via content adaptation. [ABSTRACT FROM AUTHOR]

Mixed shock model is an explicit construction method of failure probability model based on component independent failure, system nonfatal shock, and fatal shock failure, which considers common cause failure (CCF) in redundant system. For aerospace systems, a modified mixed shock model is proposed, which considers several components may fail independently and simultaneously in operation. In order to solve the issue that the parameters of the mixed shock model cannot be solved directly based on the failure probability data, a parameter solving method based on particle swarm optimization (PSO) algorithm is proposed. Additionally, the relationship between the failure probability and the gradient of the parameter change is deduced, and the reduced‐order (RO) solution based on the gradient of the parameter change is proposed to improve the efficiency of the solution. A fitness function construction method based on the relative error of the solution probability and the true probability is proposed to improve the probability solution accuracy of multicomponent failure. The nonlinear inertia factor optimization method combined with fitness change is studied to improve the particle swarm dynamics. The accuracy of the results of different parameters solving sequence and different PSO methods are compared, and the effectiveness of the RO solution is verified. The results of the mixed shock model before and after modification are compared with the different CCF data, which verifies the effectiveness and wide applicability of the modified mixed shock model. The results show that the modified mixed shock model for CCF and its parameter solution method can significantly improve the probability solution accuracy of all components failure, and also provide a new theoretical basis and solution method for the quantitative analysis of multiredundant system failure. [ABSTRACT FROM AUTHOR]

A new optical diagnostic method that predicts the global fuel–air equivalence ratio of a swirl combustor using absorption spectra from only three optical paths is proposed here. Under normal operation, the global equivalence ratio and total flow rate determine the temperature and concentration fields of the combustor, which subsequently determine the absorption spectra of any combustion species. Therefore, spectra, as the fingerprint for a produced combustion field, were employed to predict the global equivalence ratio, one of the key operational parameters, in this study. Specifically, absorption spectra of water vapor at wavenumbers around 7444.36, 7185.6, and 6805.6 cm–1 measured at three different downstream locations of the combustor were used to predict the global equivalence ratio. As it is difficult to find analytical relationships between the spectra and produced combustion fields, a predictive model was a data-driven acquisition. The absorption spectra as an input were first feature-extracted through stacked convolutional autoencoders and then a dense neural network was used for regression prediction between the feature scores and the global equivalence ratio. The model could predict the equivalence ratio with an absolute error of ±0.025 with a probability of 96%, and a gradient-weighted regression activation mapping analysis revealed that the model leverages not only the peak intensities but also the variations in the shape of absorption lines for its predictions. [ABSTRACT FROM AUTHOR]

In visual search tasks in the lab and in the real world, people routinely miss targets that are clearly visible: so-called look but fail to see (LBFTS) errors. If search displays are shown to the same observer twice, we can ask about the probability of joint errors, where the target is missed both times. If errors are "deterministic," then the probability of a second error on the same display–given that the target was missed the first time–should be high. If errors are "stochastic," the probability of joint errors should be the product of the error rate for first and second appearances. Here, we report on two versions of a T among Ls search with somewhat degraded letters to make search more difficult. In Experiment 1, Ts could either appear amidst crowded "clumps" of Ls or more in isolation. Observers made more errors when the T was in a clump, but these errors were mainly stochastic. In Experiment 2, the task was made harder by making Ts and Ls more similar. Again, errors were predominantly stochastic. If other, socially important errors are also stochastic, this would suggest that "double reading," where two observers (human or otherwise) look at each stimulus, could reduce overall error rates. [ABSTRACT FROM AUTHOR]

Item response theory (IRT) models the relationship between the possible scores on a test item against a test taker's attainment of the latent trait that the item is intended to measure. In this study, we compare two models for tests with polytomously scored items: the optimal scoring (OS) model, a nonparametric IRT model based on the principles of information theory, and the generalized partial credit (GPC) model, a widely used parametric alternative. We evaluate these models using both simulated and real test data. In the real data examples, the OS model demonstrates superior model fit compared to the GPC model across all analyzed datasets. In our simulation study, the OS model outperforms the GPC model in terms of bias, but at the cost of larger standard errors for the probabilities along the estimated item response functions. Furthermore, we illustrate how surprisal arc length, an IRT scale invariant measure of ability with metric properties, can be used to put scores from vastly different types of IRT models on a common scale. We also demonstrate how arc length can be a viable alternative to sum scores for scoring test takers. [ABSTRACT FROM AUTHOR]

Optical code division multiple access (OCDMA) is one of the promising technologies to be implemented using all-optical networks. The OCDMA system performance is substantially determined by the particular encoding codes. Due to the different transmitter and receiver design considerations, selecting the right code family and code dimension is critical. In this research, 2D codes based on permutation vectors' (PV) codes are presented to overcome the Multiple Access Interference (MAI) problem and system complexity. Consequently, the research work focused on two-dimensional unipolar codes to mitigate the probability error and cardinality of the optical CDMA system. A fast wavelength-hopping/time-spreading (FWHTS) is introduced as an encoding technique. The FWHTS is used for code construction design, and it achieves cardinality in upper bound theory without sacrificing good auto-and-cross correlation properties. Accordingly, hybrid codes with serial elimination interference receivers are presented to estimate the error probability of 2D optical codes. The proposed method is simulated using Python software. The performance metrics are flexibility, bit rate, minimum temporal length, computational complexity, cardinality and wavelength. The proposed method is compared with the existing 2D balanced incomplete block design (BIBD) technique and multidiagonal (MD) codes. The performance of the proposed method is approximately 4% higher than these existing methods. Subsequently, in the future work, a SAC-OCDMA code construction design shall be presented and the decoding techniques can be introduced, which can reduce the receiver noise and other phase intensity induced noise, respectively. [ABSTRACT FROM AUTHOR]

Structural Reliability theory provides the means for managing uncertainties in modern codified structural design. Yet, historical records show that most structural collapses occur due to uncertainties not explicitly considered in reliability calculations, such as gross errors in design and execution, unanticipated loading, poor understanding of phenomena, new technology, etc. Recently, it has been shown that neglecting the above ‘non-technical’ factors in reliability-based optimisation leads to non-redundant optimal designs, with negative impacts on structural robustness. Surprisingly, the observed collapse frequency of structures was recently found to be smaller than calculated failure probabilities. This reveals that structural reliability calculations are conservative with respect to technical factors, while grossly overlooking non-technical factors. Population wise, the two independent errors may be partially offsetting each other. The discussion herein covers significant ‘open issues’ to be addressed by the Structural Safety community, before risk-based performance metrics can be incorporated into structural design practice. [ABSTRACT FROM AUTHOR]

The dual-functional radar-communication (DFRC) integrated system presents an ideal solution to address the challenge of spectrum resource congestion in future networks. This paper explores an adaptive power allocation technique based on beamforming to enhance the word error probability (WEP) performance of the DFRC system. Initially, a joint optimization model is developed to minimize the WEP while adhering to constraints on radar signal-to-interference-noise ratio (SINR), peak-to-average-power ratio, sidelobe level, and total transmit power. This model incorporates dual-function transmit beam, radar, and communication receive beam patterns. Subsequently, the proposed subproblem convex relaxation alternating update (SCRAU) algorithm is introduced to achieve a locally optimal solution for multi-carrier power allocation. This algorithm decomposes the original non-convex optimization problem into three sub-problems with lower complexity and iteratively optimizes them. Simulation experiments validate that the SCRAU algorithm can simultaneously fulfill radar and communication functions. The SCRAU algorithm demonstrates superior WEP performance compared to current advanced algorithms. [ABSTRACT FROM AUTHOR]

In health technology assessment, matching‐adjusted indirect comparison (MAIC) is the most common method for pairwise comparisons that control for imbalances in baseline characteristics across trials. One of the primary challenges in MAIC is the need to properly account for the additional uncertainty introduced by the matching process. Limited evidence and guidance are available on variance estimation in MAICs. Therefore, we conducted a comprehensive Monte Carlo simulation study to evaluate the performance of different statistical methods across 108 scenarios. Four general approaches for variance estimation were compared in both anchored and unanchored MAICs of binary and time‐to‐event outcomes: (1) conventional estimators (CE) using raw weights; (2) CE using weights rescaled to the effective sample size (ESS); (3) robust sandwich estimators; and (4) bootstrapping. Several variants of sandwich estimators and bootstrap methods were tested. Performance was quantified on the basis of empirical coverage probabilities for 95% confidence intervals and variability ratios. Variability was underestimated by CE + raw weights when population overlap was poor or moderate. Despite several theoretical limitations, CE + ESS weights accurately estimated uncertainty across most scenarios. Original implementations of sandwich estimators had a downward bias in MAICs with a small ESS, and finite sample adjustments led to marked improvements. Bootstrapping was unstable if population overlap was poor and the sample size was limited. All methods produced valid coverage probabilities and standard errors in cases of strong population overlap. Our findings indicate that the sample size, population overlap, and outcome type are important considerations for variance estimation in MAICs. [ABSTRACT FROM AUTHOR]

Although the helicopter to ship transfer operation is rarely applied in ports around the world, some of the hub ports have encouraged it. The operational process poses challenges to safety due to the nature of the work to be completed by the ship crew. This article performs a systematic human error prediction to ensure safe helicopter to ship transfer operations under different circumstances since the human factor is becoming a significant contributor to maritime accidents. To accomplish this, the article addresses a cognitive reliability and error analysis method (CREAM) under the evidential reasoning (ER) approach. In the proposed approach, the CREAM provides a comprehensive human error prediction tool and ER is capable of supporting experts’ judgment in decision-making. The findings of the research show that ‘Secure the loose objects within or adjacent to the operating area’ poses a high human error probability (4.50E–02) during helicopter to ship transfer operations. [ABSTRACT FROM AUTHOR]

The differential privacy (DP) literature often centers on meeting privacy constraints by introducing noise to the query, typically using a pre-specified parametric distribution model with one or two degrees of freedom. However, this emphasis tends to neglect the crucial considerations of response accuracy and utility, especially in the context of categorical or discrete numerical database queries, where the parameters defining the noise distribution are finite and could be chosen optimally. This paper addresses this gap by introducing a novel framework for designing an optimal noise probability mass function (PMF) tailored to discrete and finite query sets. Our approach considers the modulo summation of random noise as the DP mechanism, aiming to present a tractable solution that not only satisfies privacy constraints but also minimizes query distortion. Unlike existing approaches focused solely on meeting privacy constraints, our framework seeks to optimize the noise distribution under an arbitrary (ϵ , δ) constraint, thereby enhancing the accuracy and utility of the response. We demonstrate that the optimal PMF can be obtained through solving a mixed-integer linear program. Additionally, closed-form solutions for the optimal PMF are provided, minimizing the probability of error for two specific cases. Numerical experiments highlight the superior performance of our proposed optimal mechanisms compared to state-of-the-art methods. This paper contributes to the DP literature by presenting a clear and systematic approach to designing noise mechanisms that not only satisfy privacy requirements but also optimize query distortion. The framework introduced here opens avenues for improved privacy-preserving database queries, offering significant enhancements in response accuracy and utility. [ABSTRACT FROM AUTHOR]

In order for computer-aided drug design to fulfil its long held promise of delivering new medicines faster and cheaper, extensive development and validation work must be done first. This pertains particularly to molecular dynamics force fields where one important aspect–the hydration free energy (HFE) of small molecules–is often insufficiently analyzed. While most benchmarking studies report excellent accuracies of calculated hydration free energies–usually within 2 kcal/mol of experimental values–we find that deeper analysis reveals significant shortcomings. Herein, we report a dependence of HFE prediction errors on ligand molecular weight–the higher the weight, the bigger the prediction error and the higher the probability the calculated result is erroneous by a large amount. We show that in the drug-like molecular weight region, HFE predictions can easily be off by 5 kcal/mol or more. This is likely to be highly problematic in a drug discovery and development setting. We make our HFE results and molecular descriptors freely and fully available in order to encourage deeper analysis of future molecular dynamics results and facilitate development of the next generation of force fields. [ABSTRACT FROM AUTHOR]

Purpose: In the context of clinical research, there is an increasing need for new study designs that help to incorporate already available data. With the help of historical controls, the existing information can be utilized to support the new study design, but of course, inclusion also carries the risk of bias in the study results. Methods: To combine historical and randomized controls we investigate the Fill-it-up-design, which in the first step checks the comparability of the historical and randomized controls performing an equivalence pre-test. If equivalence is confirmed, the historical control data will be included in the new RCT. If equivalence cannot be confirmed, the historical controls will not be considered at all and the randomization of the original study will be extended. We are investigating the performance of this study design in terms of type I error rate and power. Results: We demonstrate how many patients need to be recruited in each of the two steps in the Fill-it-up-design and show that the family wise error rate of the design is kept at 5 % . The maximum sample size of the Fill-it-up-design is larger than that of the single-stage design without historical controls and increases as the heterogeneity between the historical controls and the concurrent controls increases. Conclusion: The two-stage Fill-it-up-design represents a frequentist method for including historical control data for various study designs. As the maximum sample size of the design is larger, a robust prior belief is essential for its use. The design should therefore be seen as a way out in exceptional situations where a hybrid design is considered necessary. [ABSTRACT FROM AUTHOR]

For mathematically identical risky decisions, different choices can be made depending on whether information about outcomes and their probabilities is learned by description or by experience, known as the description–experience gap. However, it is unclear whether different ways of obtaining information lead to different representation forms of probability, resulting in a description–experience gap. The current study investigates the representation formats of the alternative options' probability for decisions from description and decisions from experience. The experiments measured the relative error of probability estimation in percentage and frequency forms for the two types of decisions in low and medium-to-large probability situations. The results demonstrate that for decisions from description in medium-to-large probability scenarios, the estimation error was lower in percentage form than in frequency form, with equally near-perfect estimates in small-probability scenarios. Nevertheless, in decisions from experience, the accuracy of estimation in percentage form was lower than in frequency form in both low and medium-to-large probability situations. This suggests that decision makers in decisions from description tend to represent the probability information in percentage form. However, in decisions from experience, they tend to represent probability in frequency form. The utilization of different formats for probability representation is one of the factors that contribute to the description–experience gap. [ABSTRACT FROM AUTHOR]

Understanding the relationship between intraspecific trait variability (ITV) and its biotic and abiotic drivers is crucial for advancing population and community ecology. Despite its importance, there is a lack of guidance on how to effectively sample ITV and reduce bias in the resulting inferences. In this study, we explored how sample size affects the estimation of population‐level ITV, and how the distribution of sample sizes along an environmental gradient (i.e., sampling design) impacts the probabilities of committing Type I and II errors. We investigated Type I and II error probabilities using four simulated scenarios which varied sampling design and the strength of the ITV‐environment relationships. We also applied simulation scenarios to empirical data on populations of the small mammal, Peromyscus maniculatus across gradients of latitude and temperature at sites in the National Ecological Observatory Network (NEON) in the continental United States. We found that larger sample sizes reduce error rates in the estimation of population‐level ITV for both in silico and Peromyscus maniculatus populations. Furthermore, the influence of sample size on detecting ITV‐environment relationships depends on how sample sizes and population‐level ITV are distributed along environmental gradients. High correlations between sample size and the environment result in greater Type I error, while weak ITV–environmental gradient relationships showed high Type II error probabilities. Therefore, having large sample sizes that are even across populations is the most robust sampling design for studying ITV‐environment relationships. These findings shed light on the complex interplay among sample size, sampling design, ITV, and environmental gradients. [ABSTRACT FROM AUTHOR]

Situational awareness (SA) is regarded as one of the important non-technical skills in constructing the seafarers’ ability in daily decision-making and performing tasks, especially in Engine Resources Management (ERM). In maritime accidents that are mainly human error, insufficient SA is the specific factor that contributes to most of incidents. To quantitatively assess SA reliability, a Bayesian network of seafarers’ performance in attaining SA in engine supervisory control is constructed. The adaptation of simulator data helped as combination along using subject matter expert input, which is a common practice in constructing human reliability analysis. Additionally, the simulator data can serve as the updating function when new data is observed. The result shows that the model can provide promising results as compared with expert expectation. Such kind of model can support the evaluation of the engine operation onboard, and mitigation can be provided to reduce the probability of human error. [ABSTRACT FROM AUTHOR]

Navigational accidents are one of the most common types of maritime accidents, and they can result from various factors, including human error, adverse weather conditions, technical issues with the ship, or a combination of these factors. In this study, navigational accidents, including collision and grounding, that occurred in Germany were analysed using the MAART method. The novelty of this research lies in its detailed examination of the Human Error Probability (HEP) result, which has yet to be explored in previous studies. There are 47 collision cases and 15 grounding cases in the 13-year occurrence period. In total, 290 causal factors were found in the analysis. Furthermore, it is found that management, media, and machines are the main causal factors in navigational accidents in Germany. In collision accidents, management factors had the highest number of contributing factors, followed by media and machine factors. Contrary to grounding accidents, based on the results of the EPC, the machine factor had the highest number of contributing factors to accidents, followed by media and management. Finally, the human error probability values for collision accidents range from 0.06 to 1, averaging 0.54. In contrast, the HEP values for grounding accidents range from 0.0048 to 1, averaging 0.26. [ABSTRACT FROM AUTHOR]

In the search for scalable, fault-tolerant quantum computing, distributed quantum computers are promising candidates. These systems can be realized in large-scale quantum networks or condensed onto a single chip with closely situated nodes. We present a framework for numerical simulations of a memory channel using the distributed toric surface code, where each data qubit of the code is part of a separate node, and the error-detection performance depends on the quality of four-qubit Greenberger–Horne–Zeilinger (GHZ) states generated between the nodes. We quantitatively investigate the effect of memory decoherence and evaluate the advantage of GHZ creation protocols tailored to the level of decoherence. We do this by applying our framework for the particular case of color centers in diamond, employing models developed from experimental characterization of nitrogen-vacancy centers. For diamond color centers, coherence times during entanglement generation are orders of magnitude lower than coherence times of idling qubits. These coherence times represent a limiting factor for applications, but previous surface code simulations did not treat them as such. Introducing limiting coherence times as a prominent noise factor makes it imperative to integrate realistic operation times into simulations and incorporate strategies for operation scheduling. Our model predicts error probability thresholds for gate and measurement reduced by at least a factor of three compared to prior work with more idealized noise models. We also find a threshold of 4 × 10 2 in the ratio between the entanglement generation and the decoherence rates, setting a benchmark for experimental progress. [ABSTRACT FROM AUTHOR]

The melting of Arctic ice has facilitated the successful navigation of merchant ships through the Arctic route, often requiring icebreakers for assistance. To reduce the risk of accidents between merchant vessels and icebreakers stemming from human errors during operations, this paper introduces an enhanced human reliability assessment approach. This method utilizes the Dynamic Bayesian Network (DBN) model, integrated with the information, decision, and action in crew context (IDAC) framework. First, a qualitative analysis of crew maneuvering behavior in scenarios involving a collision with the preceding vessel during icebreaker assistance is conducted using the IDAC model. Second, the D–S evidence theory and cloud models are integrated to process multi-source subjective data. Finally, the human error probability of crew members is quantified using the DBN. The research results indicate that during convoy operations, the maximum probability that the officer on watch (OOW) chooses an incorrect deceleration strategy is 8.259 × 10 − 2 and the collision probability is 4.129 × 10 − 3 . Furthermore, this study also found that the factors of Team Effectiveness and Knowledge/Abilities during convoy operations have the greatest impact on collision occurrence. This research provides important guidance and recommendations for the safe navigation of merchant ships in the Arctic waters. By reducing human errors and adopting appropriate preventive measures, the risk of collisions between merchant ships and icebreakers can be significantly decreased. [ABSTRACT FROM AUTHOR]

In order to explore more spectrum resources to support sensors and their related applications, cognitive wireless sensor networks (CWSNs) have emerged to identify available channels being underutilized by the primary user (PU). To improve the detection accuracy of the PU signal, cooperative spectrum sensing (CSS) among sensor paradigms is proposed to make a global decision about the PU status for CWSNs. However, CSS is susceptible to Byzantine attacks from malicious sensor nodes due to its open nature, resulting in wastage of spectrum resources or causing harmful interference to PUs. To suppress the negative impact of Byzantine attacks, this paper proposes a beta distribution function (BDF) for CSS among multiple sensors, which includes a sequential process, beta reputation model, and weight evaluation. Based on the sequential probability ratio test (SPRT), we integrate the proposed beta reputation model into SPRT, while improving and reducing the positive and negative impacts of reliable and unreliable sensor nodes on the global decision, respectively. The numerical simulation results demonstrate that, compared to SPRT and weighted sequential probability ratio test (WSPRT), the proposed BDF has outstanding effects in terms of the error probability and average number of samples under various attack ratios and probabilities. [ABSTRACT FROM AUTHOR]

In this paper we will analyze one linear code from the theoretical point of view. Namely, the code definition is based on linear quasigroups. In the previous work we classified the quasigroups of order 4 according to their probability of undetected errors. Now, in this paper we will conclude whether the linear quasigroups that are in the same class in this classification obtain equal number of surely detected incorrectly transmitted bits. Also, we will classify the linear quasigroups of order 4 according to the number of errors that the code surely detects when they are used for coding. At the end we will make conclusion which quasigroups of order 4 are overall best for coding having in mind both important parameters for every code for error detection: the number of errors that the code surely detects and the probability of undetected errors. [ABSTRACT FROM AUTHOR]

A novel structural reliability analysis method that combines the improved beluga whale optimization (IBWO) and the arctangent function‐based maximum entropy method (AMEM) is proposed in this paper. It aims to augment the accuracy of failure probability prediction in structural reliability analysis based on the traditional maximum entropy method (MEM). First, the arctangent function is introduced to avoid the effects of truncation error and numerical overflow in the traditional MEM. The arctangent function can nonlinearly transform the structural performance function defined on the infinite interval into a transformed performance function defined on the bounded interval. Subsequently, the undetermined Lagrange multipliers in the maximum entropy probability density function (MEPDF) of the transformed performance function are obtained using IBWO at a swifter convergence speed with heightened convergence accuracy. Finally, the MEPDF of the transformed performance function can be obtained by combining the IBWO and AMEM, and the structural failure probability can be predicted. The analysis of the metro bogie frame as an engineering example reveals that compared with the traditional MEM using the genetic algorithm to solve the Lagrange multipliers, the proposed method diminishes the relative error in failure probability prediction from 20.51% to only 0.09%. This method significantly enhances the prediction accuracy of failure probability. [ABSTRACT FROM AUTHOR]

In this article, we propose a computer-oriented method of construction of optimal group sequential hypothesis tests with variable group sizes. In particular, for independent and identically distributed observations, we obtain the form of optimal group sequential tests which turn to be a particular case of sequentially planned probability ratio tests (SPPRTs, see Schmitz 1993). Formulas are given for computing the numerical characteristics of general SPPRTs, like error probabilities, average sampling cost, etc. A numerical method of designing the optimal tests and evaluation of the performance characteristics is proposed, and computer algorithms of its implementation are developed. For a particular case of sampling from a Bernoulli population, the proposed method is implemented in R programming language, the code is available in a public GitHub repository. The proposed method is compared numerically with other known sampling plans. [ABSTRACT FROM AUTHOR]

Tool holders are one of the most important structures in transferring machine tools and energy for manufacturing in CNC lathe. Power servo tool holders influence kinematic accuracy and machining accuracy and so are vital to the transposition system. Reliability evaluation is also critical to guaranteeing and maintaining the accuracy of the transposition system. The first four statistical moments are derived to depict the transmission error and system characteristics. Considering the Edgeworth expansion with higher terms, reliability and reliability-based sensitivity evaluations using moments are proposed to assess system accuracy. Compared with different methods, the proposed method can represent higher statistical characteristics, helping to avoid underestimations of system reliability. Also, results calculated with the proposed method for the transposition system are in agreement with the results from the Monte Carlo simulation with 107 samples. The relative error of failure probability is 4.32%. Considering the plus–minus sign and values of results, reliability-based sensitivity represents the effects of the parameters' dispersions on system reliability. The reliability-based sensitivity indices can be utilized to optimize the system structure and to improve system accuracy, which can increase the system reliability from 98.34% to 99.99% in the transposition system of the power servo tool holder. [ABSTRACT FROM AUTHOR]

Summary Perfect detection of unused/underutilized frequency band of the primary user (PU) in the cognitive radio communication systems is an essential component for its efficient utilization by the secondary/cognitive user (CU) without any interference. In the cooperative spectrum sensing scenario, the presence or absence of PU is determined by analyzing the decisions of each CU engaged in the collaboration. In this paper, we have emphasized on the significance of spectrum sensing duration in the optimal threshold selection approach in the cooperative spectrum sensing scenarios for a range of the received PU signal signal‐to‐noise ratio (SNR) from low to high values. The sensing duration parameter is taken as ts = 2.5 ms in the higher SNR environment, whereas in the lower SNR environment when the optimal threshold condition fails, ts is kept dynamic to satisfy minimum target values of sensing performance parameters. We have computed the spectrum sensing performance parameters and throughput using the same approach and compared the results with those obtained from the constant false‐alarm rate (CFAR), constant detection rate (CDR), and minimized error probability (MEP) threshold selection approaches. The spectrum sensing performance computed by the proposed approach is significantly improved as compared with the other reported approaches. At SNR = −24 dB, global probability of false alarm Qf = 0.002 and global probability of detection Qd = 0.999 are achieved. However, the throughput is relatively less for low SNR values. [ABSTRACT FROM AUTHOR]

The single-letter characterization of the entanglement-assisted capacity of a quantum channel is one of the seminal results of quantum information theory. In this paper, we consider a modified communication scenario in which the receiver is allowed an additional, "inconclusive" measurement outcome, and we employ an error metric given by the error probability in decoding the transmitted message conditioned on a conclusive measurement result. We call this setting postselected communication and the ensuing highest achievable rates the postselected capacities. Here, we provide a precise single-letter characterization of postselected capacities in the setting of entanglement assistance as well as the more general nonsignaling assistance, establishing that they are both equal to the channel's projective mutual information — a variant of mutual information based on the Hilbert projective metric. We do so by establishing bounds on the one-shot postselected capacities, with a lower bound that makes use of a postselected teleportation-based protocol and an upper bound in terms of the postselected hypothesis testing relative entropy. As such, we obtain fundamental limits on a channel's ability to communicate even when this strong resource of postselection is allowed, implying limitations on communication even when the receiver has access to postselected closed timelike curves. [ABSTRACT FROM AUTHOR]

The paper proposes an innovative methodology of Human Cognitive Reliability-Cognitive Reliability and Error Analysis Method (HCR-CREAM) coupled with A search and genetic algorithm (GA) to tackle ship cabin equipment layout considering human factor reliability optimization with the goal of minimizing human error probability (HEP) subjected to practical requirements. After establishing the mathematical model of cabin equipment inspection tasks in ship cabin equipment layout problem through HCR-CREAM and equipment geometric simplification, a method of the horizontal movement based on minimum distance is presented to avoid the equipment overlapping, then A search is used for planning inspection paths and GA with selection, crossover, and mutation operators is applied to solve equipment layout results. A case of equipment layout in a certain ship engine room has been taken to carry out parameter sampling experiments by Latin Hypercube for GA. The results show the solution effect of GA is less affected by its parameter variation. And through the comparison with the initial equipment layout, the indicators influencing the HEP of the optimized result have been improved, thus significantly reducing HEP. [ABSTRACT FROM AUTHOR]

Human reliability analysis (HRA) is approaching nearly 60 years of reliance on key aspects of the original HRA method Technique for Human Error Rate Prediction (THERP), including its process for analyzing dependency. Despite advances in computational abilities and HRA-relevant techniques, the conceptualization, modeling, and quantification of dependency have remained largely unchanged since the introduction of THERP. As a result, current HRA methods do not consider dependency in a realistic manner, and there remain foundational gaps related to the definition, lack of causality, and quantification for HRA dependency. In this paper, we review the current conceptualization of dependency and demonstrate that current research in dependency is not addressing all of the technical gaps. To address the outstanding technical gaps in HRA dependency, we propose a set of fundamental dependency structures (HRA dependency idioms) that capture the spectrum of relationships possible between HRA variables. The idioms provide a robust logical structure for HRA dependency that emphasizes causality and is based on a causal Bayesian network modeling architecture. The idioms conceptualize and model HRA dependency in an objective, traceable, and causally informed manner that facilitates data-based quantification of HRA dependency. [ABSTRACT FROM AUTHOR]

One of the key advantages of terahertz (THz) communication is its potential for energy efficiency, making it an attractive option for green communication systems. Coherent THz transmission technology has recently been explored in the literature. However, there exist few error performance results for such a wireless link employing coherent THz technology. In this paper, we explore a comprehensive terrestrial channel model designed for wireless line-of-sight communication using THz frequencies. The performance of coherent THz links is analyzed, and it is found to be notably affected by two significant factors, atmospheric turbulence and pointing errors. These could occur between the terahertz transmitter and receiver in terrestrial links. The exact and asymptotic solutions are derived for bit error rate and interrupt probability for binary phase-shift keying coherent THz systems, respectively, over log-normal and Gamma–Gamma turbulent channels. The asymptotic outage probability analysis is also performed. It is shown that the presented results offer a precise estimation of coherent THz transmission performance and its link budget. [ABSTRACT FROM AUTHOR]

In this work, a scalable quantum gate‐based algorithm for accelerating causal inference is introduced. Specifically, the formalism of causal hypothesis testing presented in [Nat Commun 10, 1472 (2019)] is considered. Through the algorithm, the existing definition of error probability is generalized, which is a metric to distinguish between two competing causal hypotheses, to a practical scenario. The results on the Qiskit validate the predicted speedup and show that in the realistic scenario, the error probability depends on the distance between the competing hypotheses. To achieve this, the causal hypotheses are embedded as a circuit construction of the oracle. Furthermore, by assessing the complexity involved in implementing the algorithm's subcomponents, a numerical estimation of the resources required for the algorithm is offered. Finally, applications of this framework for causal inference use cases in bioinformatics and artificial general intelligence are discussed. [ABSTRACT FROM AUTHOR]

Space teleoperation systems, as complex giant systems, feature performance-influencing factors that are interrelated. Accurately describing the dependence between these factors is crucial for constructing a human factor reliability assessment (HRA) model. Moreover, data scarcity has consistently been a challenge in space HRA. There are primarily two types of data in this domain: expert judgment data and empirical data (simulation data, actual reports), each with complementary effects. The expert judgment data, although subjective, are readily accessible, while empirical data provide robust objectivity but are difficult to obtain. Addressing these challenges, this paper constructs an HRA model for space teleoperation that combines Interpretive Structural Modeling (ISM) with a two-stage Bayesian update method. This model reflects the dependencies between factors and accommodates multisource data (expert judgment and experimental data). With more empirical data, the model can be continuously updated and refined to yield increasingly accurate evaluations of human error probability (HEP). The validity of the model was verified through the analysis of 52 space incidents using the N-K model. The study provides a methodological foundation for HRA in other space missions. [ABSTRACT FROM AUTHOR]

The integration of large intelligent surfaces (LIS) with non-orthogonal multiple access (NOMA) networks has emerged as a promising solution to enhance the capacity and coverage of wireless communication systems. In this study, we analyse the performance of a NOMA network with the assistance of LIS. We propose a system model where a base station (BS) equipped with a LIS serves multiple users. The LIS consists of many passive elements that can influence the wireless channel by adjusting the reflection coefficients. We consider a downlink scenario where the BS transmits to multiple users simultaneously using NOMA, and the LIS helps to improve the signal quality and coverage. We additionally evaluate the efficiency of the suggested LIS-assisted NOMA network. In addition, we evaluate the efficiency of the LIS-assisted NOMA network in comparison to conventional NOMA systems that do not utilize LISs. The findings indicate that the LIS has a notable impact on enhancing the system's performance in terms of diversity gain, probability of error, and pairwise error probability (PEP). Moreover, the suggested LIS-assisted NOMA network is shown to be superior to conventional NOMA systems through comparison. These findings offer useful insights into the performance analysis of LIS-assisted NOMA networks. They also serve as inspiration and motivation for future research and development in this new subject, with the potential to revolutionize wireless communication systems. [ABSTRACT FROM AUTHOR]

Lifeboats are life-saving equipment used when it is necessary to abandon a ship or, in some ships, for man-overboard situations (to collect persons from water). Every seafarer onboard a ship has a task related to lifeboat operation in an emergency. In order to master and practise the assigned tasks, be ready to react at any moment, and efficiently use life-saving equipment and appliances, seafarers on ships perform drills at prescribed intervals. Effective drill performance is of paramount importance, as it improves safety and enables crew members to practise lifeboat operations. However, although their primary role is life-saving, lifeboat drills have resulted in numerous accidents, causing injuries and fatalities, besides equipment damage. Therefore, it is necessary to prevent such unwanted events and discover their root causes. As the human factor is considered a significant cause of marine accidents, this paper aims to quantify human error probability (HEP) during lifeboat drills. In addition, because lifeboat drill accident data are scarce, this study adopted the Success Likelihood Index Method (SLIM) for human reliability analysis (HRA). Based on expert judgments, the tasks with the highest probability of human error and factors significantly influencing human performance during lifeboat drills are identified. According to the study results, the recovery of the lifeboat is the most hazardous phase with the highest HEP. In addition, the BN-SLIM is adopted to estimate the probability of human error during the recovery of the lifeboat. The task with the largest HEP is confirming the release lever is properly rested and hooks locked (HEP = 4.5%). Furthermore, the design and condition of equipment and Crew Competence are identified as the most important Performance-Shaping Factors (PSFs) that affect crew members' performance. The BN-SLIM model was verified utilising a sensitivity analysis and validated by analysing real-life lifeboat drill accidents that occurred during lifeboat recovery. The results confirmed that the model could be used to analyse lifeboat accidents and for proactive preventive measures because most influencing factors are recognised, and acting on them can significantly reduce the HEP of the overall task, improve lifeboat safety, and save lives at sea. [ABSTRACT FROM AUTHOR]

Summary This article proposes a novel angle representation method for floating‐point number, which eliminates the need for DSP (Digital Signal Processor) resources and reduces the resource usage when performing floating‐point multiplication. Compared with the implementation of floating‐point multiplier using IP cores, the implementation of approximate multiplication based on lookup tables can achieve an average reduction of 58.2% in LUTs (look‐up tables) and an average increase of 20.4% in frequency for mantissa widths ranging from 3 to 12 bits. Additionally, it can also save an average of 23.2% in registers. Analysis of PDP (power‐delay product)/LUT to MRED (mean relative error distance)/PRED (probability of relative error distance) among other approximate multipliers shows that the proposed design extends the Pareto front. At last, simulation of a three‐level inverter is implemented to verify the effectiveness of the multiplier. [ABSTRACT FROM AUTHOR]

The occurrence of probabilistic common cause errors (PCCEs) in man‐machine systems can lead to multiple human errors being affected by common causes and will contribute greatly to the reliability of the system. In this paper, A reliability modeling method based on event tree (ET)‐fault tree (FT) model for man‐machine systems subjected to PCCEs is proposed. Under the influence of PCCEs, risk factors in the system are not independent, and human errors affected by the same common cause will occur with different probabilities. To describe the dependencies among risk factors, a PCCE gate is proposed to extend FTs in the ET‐FT model. To analyze the impact of common causes on the human error probabilities and quantify the extended FT, an explicit method and an implicit method based on the Cognitive Reliability and Error Analysis Method are proposed. The proposed quantification methods consider the different relationships among multiple common causes in a single model. Finally, the proposed methods are validated in the reliability assessment of the emergency response system under malfunction of the solar wing mechanism. [ABSTRACT FROM AUTHOR]

• The moment similarity is explained qualitatively and quantitatively. • The positional accuracy reliability at any position is calculated based on the moment similarity. • An optimal position with the lowest failure probability can be searched in a cubic space. A new positional accuracy reliability analysis method of industrial robots is proposed based on the statistical moment similarity of positional error. The first-two order statistical moments of positional error at some positions are accurately obtained through the differential kinematics method to reduce the computational cost of the proposed method. In practical engineering, the statistical moments of positional error can also be obtained from the limited experimental data. Then, the statistical moment similarity of positional error is quantified by the semivariance function. Besides, the first-two order moments of positional error at any position can be calculated according to the statistical moment similarity. Thus, the positional accuracy reliability analysis of any position can be realized by the first-two order moments according to the saddlepoint approximation method. Besides, an optimal position with the lowest failure probability of positional error can be searched based on the statistical moment similarity. The effectiveness of the proposed method is manifest through calculating the positional accuracy reliability and the optimal position with the lowest failure probability of a 6-degree-of-freedom (6-DoF) industrial robot in a cubic space. [ABSTRACT FROM AUTHOR]

Two-wave with diffuse power (TWDP) is one of the most promising distributions for describing multipath fading in the emerging millimeter-wave (mmWave) band. However, traditional error performance analysis in these channels is mostly based on the approximate expressions, accurate only for specific combinations of TWDP parameters that describe particular channel conditions. Considering the aforementioned, this paper begins with an extensive literature overview of the existing average bit/symbol error probability (ABEP/ASEP) expressions in TWDP channels, revealing the absence of the exact expressions that could be used to accurately evaluate error performance in all channel conditions, for most modulation and diversity techniques. Next, the exact ASEP expressions are derived for M-ary rectangular quadrature amplitude modulation with coherent detection and for M-ary differential phase shift keying modulation. These expressions are then used to derive corresponding computationally simple closed-form asymptotic ASEPs, which accurately evaluate error performance for signal-to-noise ratios (SNR) greater than 30 dB. All the results are verified through Monte-Carlo simulation. [ABSTRACT FROM AUTHOR]

The evolution of the mechanism of human behavior formation analysis has significantly influenced the development of human reliability analysis (HRA), which aims to calculate human error probability (HEP) with performance shaping factors (PSFs). This paper reviews the typical HRA methods in different generations, the role of PSFs, and their interrelation‐ships in human risk modeling, with the background of nuclear power plants (NPPs). In a retrospective of typical HRA methods, PSF plays a fundamental role in assessing human performance during task operation. However, the subjectivity in defining and evaluating PSFs often leads to a partial representation of human behavior characteristics and human risk evolution, resulting in the neglect of PSF inter‐relationships and conservative HEP estimation. Recent studies have emphasized employing simulation platforms to simulate the task process and obtain data relevant to PSFs that can enable the exploration of the mutual effects to support the calculation of HEP more accurately. Compared to certain previous methods involving over‐simplification and inappropriate assumptions resulting in inaccurate results, current HRA methods are prone to the construction of HEP models based on objective data acquisition and dynamic calculations with process models. This shift enables a better illustration of the intricate relationships among PSFs. Reflecting on the current trend of HRA methodology, this paper proposes a possible PSF quantification based on physiological measurement providing accessible and objective data. It improves the shortcomings in data scarcity and time‐invariance of HEP calculation, thus more accurately and realistically responds to the accumulation and fluctuation of human risks throughout a task. [ABSTRACT FROM AUTHOR]

Summary: In this paper, an event‐triggered adaptive tracking control strategy is proposed for strict‐feedback stochastic nonlinear systems with predetermined finite‐time performance. Firstly, a finite‐time performance function (FTPF) is introduced to describe the predetermined tracking performance. With the help of the error transformation technique, the original constrained tracking error is transformed into an equivalent unconstrained variable. Then, the unknown nonlinear functions are approximated by using the multi‐dimensional Taylor networks (MTNs) in the backstepping design process. Meanwhile, an event‐triggered mechanism with a relative threshold is introduced to reduce the communication burden between actuators and controllers. Furthermore, the proposed control strategy can ensure that all signals of the closed‐loop system are bounded in probability and the tracking error is within a predefined range in a finite time. In the end, the effectiveness of the proposed control strategy is verified by two simulation examples. [ABSTRACT FROM AUTHOR]

Internal quality control in clinical chemistry laboratories are based on analyzing samples of stable control materials among the patient samples. The control results are interpreted by using quality control rules that usually are designed to detect systematic errors. The best rules have a high probability of error detection (Ped), i.e. to detect the maximal allowable (critical) systematic error and a low probability of false rejection (Pfr, false alarm). In this work we show that quality control rules can be represented by points on a ROC curve which appears when Ped is plotted against Pfrand only the control limit is varied. Further, we introduce a new method for choosing the optimal control limit, analogous to choosing the optimal operating point on the ROC curve of a diagnostic test. This decision needs knowledge of the pretest probability of a critical systematic error, the benefit of detecting it when it occurs and the cost of false alarm. The ROC curve analysis showed that if rules based on N = 2 are used, mean rules outperform Westgard rules because the ROC curve of the mean rules was lying above the ROC curves of the Westgard rules. A mean rule also had a lower maximum expected increase in the number of unacceptable patient results reported during the presence of an out-of-control error condition (Max E(NUF)) than comparable Westgard rules. [ABSTRACT FROM AUTHOR]

A central challenge in hypothesis testing (HT) lies in determining the optimal balance between Type I (false positive) and Type II (non-detection or false negative) error probabilities. Analyzing these errors' exponential rate of convergence, known as error exponents, provides crucial insights into system performance. Error exponents offer a lens through which we can understand how operational restrictions, such as resource constraints and impairments in communications, affect the accuracy of distributed inference in networked systems. This survey presents a comprehensive review of key results in HT, from the foundational Stein's Lemma to recent advancements in distributed HT, all unified through the framework of error exponents. We explore asymptotic and non-asymptotic results, highlighting their implications for designing robust and efficient networked systems, such as event detection through lossy wireless sensor monitoring networks, collective perception-based object detection in vehicular environments, and clock synchronization in distributed environments, among others. We show that understanding the role of error exponents provides a valuable tool for optimizing decision-making and improving the reliability of networked systems. [ABSTRACT FROM AUTHOR]

Selection strategies prove to be a valuable approach in mitigating complexity associated with antenna selection (AS) and relay selection (RS), optimizing signal transmission through a streamlined number of antennas/relays, and enhancing overall system performance. This paper offers a comprehensive analysis, deriving closed-form expressions for the outage probability (OP) and throughput in proposed scenarios that leverage the best relay selection (BRS) and transmit antenna selection (TAS) protocol for cooperative non-orthogonal multiple access (CNOMA), along with partial relay selection (PRS) and TAS protocol for CNOMA. The study extends to Rayleigh fading channels, considering practical impairments such as successful interference cancellation (SIC) error, channel estimation error (CEE), and feedback delay error. In comparing the proposed system to conventional CNOMA, our findings highlight the substantial impact of SIC, CEE, and feedback delay imperfections on the performance of both proposed scenarios. Notably, the application of BRS-based TAS protocol outperforms PRS-based TAS in terms of OP and throughput. The close alignment between analytical, asymptotic, and simulation results attests to the credibility of conducted analysis. [ABSTRACT FROM AUTHOR]

Human reliability analysis (HRA) is widely used to evaluate the impact of human errors on various complex human–machine systems for enhancing their safety and reliability. Nevertheless, it is hard to estimate the human error probability (HEP) in reality due to the uncertainty of state assessment information and the complex relations among common performance conditions (CPCs). In this paper, we aim to present a new integrated cognitive reliability and error analysis method (CREAM) to solve the HRA problems under probabilistic linguistic environment. First, the probabilistic linguistic term sets (PLTSs) are utilized to handle the uncertain task state assessments provided by experts. Second, the minimum conflict consensus model (MCCM) is employed to deal with conflict task state assessment information to assist experts reach consensus. Third, the entropy weighting method is used to determine the relative objective weights of CPCs. Additionally, the CPC effect indexes are introduced to assess the overall effect of CPCs on performance reliability and obtain the HEP estimation. Finally, the reliability of the proposed CREAM is demonstrated via a healthcare practical case. The result shows that the new integrated CREAM can not only effectively represent experts' uncertain task state assessments but also determine more reliable HEP estimation in HRA. [ABSTRACT FROM AUTHOR]