Evidential Approach Research Articles

Rapid Motion Segmentation of LiDAR Point Cloud Based on a Combination of Probabilistic and Evidential Approaches for Intelligent Vehicles.

Point clouds from light detecting and ranging (LiDAR) sensors represent increasingly important information for environmental object detection and classification of automated and intelligent vehicles. Objects in the driving environment can be classified as either or depending on their movement characteristics. A LiDAR point cloud is also segmented into and points based on the motion properties of the measured objects. The segmented motion information of a point cloud can be useful for various functions in automated and intelligent vehicles. This paper presents a fast motion segmentation algorithm that segments a LiDAR point cloud into and points in real-time. The segmentation algorithm classifies the motion of the latest point cloud based on the LiDAR’s laser beam characteristics and the geometrical relationship between consecutive LiDAR point clouds. To accurately and reliably estimate the motion state of each LiDAR point considering the measurement uncertainty, both probability theory and evidence theory are employed in the segmentation algorithm. The probabilistic and evidential algorithm segments the point cloud into three classes: , , and . Points are placed in the class when LiDAR point cloud is not sufficient for motion segmentation. The point motion segmentation algorithm was evaluated quantitatively and qualitatively through experimental comparisons with previous motion segmentation methods.

Strong Evidence for an Intraspecific Metabolic Scaling Coefficient Near 0.89 in Fish.

As an example of applying the evidential approach to statistical inference, we address one of the longest standing controversies in ecology, the evidence for, or against, a universal metabolic scaling relationship between metabolic rate and body mass. Using fish as our study taxa, we curated 25 studies with measurements of standard metabolic rate, temperature, and mass, with 55 independent trials and across 16 fish species and confronted this data with flexible random effects models. To quantify the body mass – metabolic rate relationship, we perform model selection using the Schwarz Information Criteria (ΔSIC), an established evidence function. Further, we formulate and justify the use of ΔSIC intervals to delineate the values of the metabolic scaling relationship that should be retained for further consideration. We found strong evidence for a metabolic scaling coefficient of 0.89 with a ΔSIC interval spanning 0.82 to 0.99, implying that mechanistically derived coefficients of 0.67, 0.75, and 1, are not supported by the data. Model selection supports the use of a random intercepts and random slopes by species, consistent with the idea that other factors, such as taxonomy or ecological or lifestyle characteristics, may be critical for discerning the underlying process giving rise to the data. The evidentialist framework applied here, allows for further refinement given additional data and more complex models.

A Response to John Frame’s Presuppositional Approach to Faith and Reason

AbstractPresuppositionalism is popular among certain groups of Reformed Christians today, and John Frame is one of its leading proponents. In contrast with the Evidential Approach concerning faith and reason, which affirms experiences and reason as starting points, Presuppositionalists assume the truth of scripture as starting point in their assessment of the truth-claims of Christianity. They appeal to Christians by emphasizing the authority of scripture, by criticizing autonomous human reason, and by highlighting the noetic effects of sin. I address these considerations, show that Frame’s approach is self-defeating and unacceptably circular, and answer his objections to the Evidential Approach.

Identifying Core Parts in Complex Mechanical Product for Change Management and Sustainable Design

Changes in customer needs are unavoidable during the design process of complex mechanical products, and may bring severely negative impacts on product design, such as extra costs and delays. One of the effective ways to prevent and reduce these negative impacts is to evaluate and manage the core parts of the product. Therefore, in this paper, a modified Dempster-Shafer (D-S) evidential approach is proposed for identifying the core parts. Firstly, an undirected weighted network model is constructed to systematically describe the product structure. Secondly, a modified D-S evidential approach is proposed to systematically and scientifically evaluate the core parts, which takes into account the degree of the nodes, the weights of the nodes, the positions of the nodes, and the global information of the network. Finally, the evaluation of the core parts of a wind turbine is carried out to illustrate the effectiveness of the proposed method in the paper. The results show that the modified D-S evidential approach achieves better performance regarding the evaluation of core parts than the node degree centrality measure, node betweenness centrality measure, and node closeness centrality measure.

Two‐step evidential fusion approach for accurate breast region segmentation in mammograms

In mammograms, the breast skin line often appears ambiguous and poorly defined. This is mainly due to the breast organ compression during the image acquisition process along with the inherent low density of the tissue in that area. The accurate delimitation of the breast region becomes a challenging task to conventional segmentation techniques. In this study, the authors propose a new segmentation approach allowing to overcome this challenge. This approach is based on the application of two complementary segmentation techniques exploring each, respectively, the grey-scale intensities and the local-homogeneity domains. The knowledge resulting from each segmentation technique is considered as a knowledge source and is modelled using the belief functions formalism. The two considered knowledge sources are then fused using an iterative process. The obtained results show the efficiency of the proposed evidential approach especially in terms of ambiguity removal and decision quality improvement for accurate breast border delimitation (which is often under-segmented and assimilated to the background by most of the existing segmentation techniques).

A risk-based fuzzy evidential framework for FMEA analysis under uncertainty: An interval-valued DS approach

Failure Modes and Effects Analysis (FMEA) is a common technique used in several manufacturing and service industries for eliminating failures and potential problems using the evaluation of failure modes of a new or an existing product, process, or system. The risk analysis is carried out by calcula ting the Risk Priority Number (RPN), which is a product of three factors, Occurrence (O), Severity (S), and Detection (D). In the literature, modeling uncertainties are used to improve the FMEA process and overcome the inefficiencies of traditional RPN. One of the common uncertainties in FMEA is the epistemic uncertainty that is essentially modeled using the Dempster-Shafer theory (DST). In this study, a novel risk-based fuzzy evidential approach is proposed by using interval-valued DST and fuzzy axiomatic design (FAD) to assess the risk of failure modes with fuzzy belief structures. The efficiency of the proposed model was investigated with the help of an example and the results are compared with riskless evaluations. Reviewing the results shows the information content of failure modes decrease relatively when risk is taken into account, in fact failure modes become relatively more critical than those in the case where no risk is considered.

An Evidential approach on Feature Subset Selection in Software Defect Prediction

An Evidential approach on Feature Subset Selection in Software Defect Prediction

Conspiracy theories on the basis of the evidence

Conspiracy theories are often portrayed as unwarranted beliefs, typically supported by suspicious kinds of evidence. Yet contemporary work in Philosophy argues provisional belief in conspiracy theories is—at the very—least understandable (because conspiracies occur) and if we take an evidential approach—judging individual conspiracy theories on their particular merits—belief in such theories turns out to be warranted in a range of cases. Drawing on this work, I examine the kinds of evidence typically associated with conspiracy theories, showing that the evidential problems typically associated with conspiracy theories are not unique to such theories. As such, if there is a problem with the conspiracy theorist’s use of evidence, it is one of principle: is the principle which guides their use of evidence somehow in error? I argue that whatever we might think about conspiracy theories generally, there is no prima facie case for a scepticism of conspiracy theories based purely on their use of evidence.

CRISPR/Cas9-Mediated Genome Nano-Surgery: An Update

Recent advances in sequencing methods have prompted an upsurge in research into the modification of diseaseassociated genes or genes involved in drug resistance. In the early days of genome-editing, immunogenic and difficult to deliver tools with high off-target effects such as Zinc Finger Nucleases (ZFNs) and Transcription activatorlike effector nucleases (TALENs) proteins were used. This was followed by the discovery of the Clustered Regularly Interspaced Short Palindromic Repeat s, CRISPR/Cas9 system. This “self-non-self-discriminatory” natural defence mechanism in bacteria and archaea identifies and degrades extrachromosomal genomes or foreign genetic elements to prevent them from integrating into the prokaryotic genomes. Unlike traditional gene therapies that can merely insert a gene in a random pattern, the inexpensive and expedient CRISPR/ Cas9 system was harnessed by scientists to precisely cut, add or manipulate multiple DNA sequences at specific sites. This review will focus on the most recent studies in genome-editing by giving an overview of the past and modern methods in this field with an emphasis on the bacterial adaptive immune system called CRISPR/Cas9. This article will also analyze the applications of CRISPR/ Cas9 in rewriting the human genome in clinical and research settings and its potential future therapeutic applications. In addition, we shall consider the technical complexities which need to be overcome for the safe and effective delivery of this novel therapy and how the ethical concerns associated with this revolutionary genome engineering technique have constrained research in germ-line genome-editing. Furthermore, we shall highlight the role of scientific regulatory committees in evaluating and assessing safety issues such as potential complications before translating this proof-of-concept evidential approach to clinical reality. More research is required to explore the risk of hazardous genome edits and to fine-tune and improve this novel therapeutic system. Although the inexpensive and easy to use CRISPR/ Cas9 platform paves new ways for precise genome editing, clinical application is still at an early stage.

An evidential approach to SLAM, path planning, and active exploration

Probability theory has become the standard framework in the field of mobile robotics because of the inherent uncertainty associated with sensing and acting. In this paper, we show that the theory of belief functions with its ability to distinguish between different types of uncertainty is able to provide significant advantages over probabilistic approaches in the context of robotics. We do so by presenting solutions to the essential problems of simultaneous localization and mapping (SLAM) and planning based on belief functions. For SLAM, we show how the joint belief function over the map and the robot's poses can be factored and efficiently approximated using a Rao-Blackwellized particle filter, resulting in a generalization of the popular probabilistic FastSLAM algorithm. Our SLAM algorithm produces occupancy grid maps where belief functions explicitly represent additional information about missing and conflicting measurements compared to probabilistic grid maps. The basis for this SLAM algorithm are forward and inverse sensor models, and we present general evidential models for range sensors like sonar and laser scanners. Using the generated evidential grid maps, we show how optimal decisions can be made for path planning and active exploration. To demonstrate the effectiveness of our evidential approach, we apply it to two real-world datasets where a mobile robot has to explore unknown environments and solve different planning problems. Finally, we provide a quantitative evaluation and show that the evidential approach outperforms a probabilistic one both in terms of map quality and navigation performance.

Translating homosexuality into Chinese: a case study of Pan Guangdan’s translation of Havelock Ellis’ Psychology of Sex: A Manual for Students (1933)

Before the translation of modern Western works on sexology, China had created its own lexicon for sexuality, which was seen as either a temporary and changeable obsession or an expression of social status and taste, rather than an identity. This understanding was challenged when Western biologically based sexology was introduced. Centred on a case study of Pan Guangdan’s (1946) translation of Havelock Ellis’ Psychology of Sex: A Manual for Students (1933), in particular Chapter Five “Homosexuality” and Appendices, this paper investigates how Western sexological discourse was translated and deployed in Republican China’s quest for social and cultural modernity. It analyses the strategies that Pan adopted to translate terms and concepts related to homosexuality into Chinese and the evidential approach that he applied to trace and write a history of Chinese homosexual culture in the paratexts of his translation. In addition to shedding new light on global histories of sexuality, it also illustrates the role of translators in the development and interaction of different knowledge and knowledge systems across languages and cultures.

El delito de trata de personas como delito complejo y sus dificultades en la jurisprudencia peruana

The crime of human trafficking is a crime of complex nature and presents problems in its interpretation in the Peruvian law and jurisprudence. These problems require the author to study the legally protected goods behind this criminal prohibition, the consent of minors, analysis of the previous domain relationship above the victim or caused by the perpetrator, and the evidential approach that this reinterpretation of the crime of trafficking assumes. According to the previous legal framework, the author stands his proposal, which is characterized by criticism and being contrary to the Peruvian supreme jurisprudence.

An evidential fusion approach for gender profiling

CCTV (Closed-Circuit TeleVision) systems are broadly deployed in the present world. To ensure in-time reaction for intelligent surveillance, it is a fundamental task for real-world applications to determine the gender of people of interest. However, normal video algorithms for gender profiling (usually face profiling) have three drawbacks. First, the profiling result is always uncertain. Second, the profiling result is not stable. The degree of certainty usually varies over time, sometimes even to the extent that a male is classified as a female, and vice versa. Third, for a robust profiling result in cases that a person’s face is not visible, other features, such as body shape, are required. These algorithms may provide different recognition results - at the very least, they will provide different degrees of certainties. To overcome these problems, in this paper, we introduce an Dempster-Shafer (DS) evidential approach that makes use of profiling results from multiple algorithms over a period of time, in particular, Denoeux’s cautious rule is applied for fusing mass functions through time lines. Experiments show that this approach does provide better results than single profiling results and classic fusion results. Furthermore, it is found that if severe mis-classification has occurred at the beginning of the time line, the combination can yield undesirable results. To remedy this weakness, we further propose three extensions to the evidential approach proposed above incorporating notions of time-window, time-attenuation, and time-discounting, respectively. These extensions also applies Denoeux’s rule along with time lines and take the DS approach as a special case. Experiments show that these three extensions do provide better results than their predecessor when mis-classifications occur.

Corroborating evidence-based medicine.

Proponents of evidence-based medicine (EBM) have argued convincingly for applying this scientific method to medicine. However, the current methodological framework of the EBM movement has recently been called into question, especially in epidemiology and the philosophy of science. The debate has focused on whether the methodology of randomized controlled trials provides the best evidence available. This paper attempts to shift the focus of the debate by arguing that clinical reasoning involves a patchwork of evidential approaches and that the emphasis on evidence hierarchies of methodology fails to lend credence to the common practice of corroboration in medicine. I argue that the strength of evidence lies in the evidence itself, and not the methodology used to obtain that evidence. Ultimately, when it comes to evaluating the effectiveness of medical interventions, it is the evidence obtained from the methodology rather than the methodology that should establish the strength of the evidence.

An evidential approach to physical protection system design

A physical protection system (PPS) integrates people, procedures, and equipment for the protection of assets or facilities against theft, sabotage, or other malevolent intruder attacks. The physical protection components (detection, delay, and response) within a facility interact with each other and their locations significantly affects the effectiveness of PPS. This paper proposes a method based on an evidential approach to evaluate the risk level of PPS and optimally locate the physical protection components to balance cost and performance. Each individual component of the system is modeled in a simulated plane. Then, the risk level distribution of each component is determined based on its actual environment. The comprehensive risk level distribution is obtained by combining information from multiple sources within the framework of Dempster–Shafer evidence theory. Finally, optimization algorithms are used to find the optimal locations. A hypothetical example is discussed which demonstrates the usefulness of the developed methodology.

An evidential network approach to support uncertain multiviewpoint abductive reasoning

The paper proposes an approach to support human abductive reasoning in the diagnosis of a multiviewpoint system. The novelty of this work lies on the capability of the approach to treat the uncertainty held by the agent performing the diagnosis. To do so, we make use of evidential networks to represent and propagate the uncertain evidence gathered by the agent. Using forward and backward propagation of the information, the impact of the evidence over the different symptoms and causes of failure is quantified. The agent can then make use of this information as additional hints in an iterative diagnosis process until a desired degree of certainty is obtained. The model is compared with a deterministic one in which evidence is represented by binary states, that is, a symptom is either observed or not.

An evidential approach to non‐inferiority clinical trials

We present likelihood methods for defining the non-inferiority margin and measuring the strength of evidence in non-inferiority trials using the 'fixed-margin' framework. Likelihood methods are used to (1) evaluate and combine the evidence from historical trials to define the non-inferiority margin, (2) assess and report the smallest non-inferiority margin supported by the data, and (3) assess potential violations of the constancy assumption. Data from six aspirin-controlled trials for acute coronary syndrome and data from an active-controlled trial for acute coronary syndrome, Organisation to Assess Strategies for Ischemic Syndromes (OASIS-2) trial, are used for illustration. The likelihood framework offers important theoretical and practical advantages when measuring the strength of evidence in non-inferiority trials. Besides eliminating the influence of sample spaces and prior probabilities on the 'strength of evidence in the data', the likelihood approach maintains good frequentist properties. Violations of the constancy assumption can be assessed in the likelihood framework when it is appropriate to assume a unifying regression model for trial data and a constant control effect including a control rate parameter and a placebo rate parameter across historical placebo controlled trials and the non-inferiority trial. In situations where the statistical non-inferiority margin is data driven, lower likelihood support interval limits provide plausibly conservative candidate margins.

Classifying Personality Disorders: An Evolution-Based Alternative to an Evidence-Based Approach

The study of personality disorders, no less psychology as a wole, remains divorced from broader spheres of scientific knowledge. Development of a conceptual schema for classifying personality disorders should include the examination of research limitations and inductive inconsistences that undermine the likely achievements of the evidential approach. An alternative course of action is outlined here, one that looks to evolutionary theory rather than evidence-based methods for classification guidance.

An evidential approach for detection of abnormal behaviour in the presence of unreliable sensors

We address the problem of abnormal behaviour recognition of the inhabitant of a smart home in the presence of unreliable sensors. The corner stone of this work is a two-level architecture sensor fusion based on the Transferable Belief Model (TBM). The novelty of our work lies in the way we detect both unreliable sensors and abnormal behaviour within our architecture by using a temporal analysis of conflict resulting from the fusion of sensors. Detection of abnormal behaviour is based on a prediction/observation process and the influence of the faulty sources is discarded by discounting coefficients. Our architecture is tested in a real-life setting using three heterogeneous sensors enabling the detection of impossible transitions between three possible postures: Sitting, Standing and Lying. The impact of having a faulty sensor management is also tested in the real-life experiment for posture detection.

Using Parametric Multipoint Lods and Mods for Linkage Analysis Requires a Shift in Statistical Thinking

Multipoint (MP) linkage analysis represents a valuable tool for whole-genome studies but suffers from the disadvantage that its probability distribution is unknown and varies as a function of marker information and density, genetic model, number and structure of pedigrees, and the affection status distribution [Xing and Elston: Genet Epidemiol 2006;30:447–458; Hodge et al.: Genet Epidemiol 2008;32:800–815]. This implies that the MP significance criterion can differ for each marker and each dataset, and this fact makes planning and evaluation of MP linkage studies difficult. One way to circumvent this difficulty is to use simulations or permutation testing. Another approach is to use an alternative statistical paradigm to assess the statistical evidence for linkage, one that does not require computation of a p value. Here we show how to use the evidential statistical paradigm for planning, conducting, and interpreting MP linkage studies when the disease model is known (lod analysis) or unknown (mod analysis). As a key feature, the evidential paradigm decouples uncertainty (i.e. error probabilities) from statistical evidence. In the planning stage, the user calculates error probabilities, as functions of one’s design choices (sample size, choice of alternative hypothesis, choice of likelihood ratio (LR) criterion k) in order to ensure a reliable study design. In the data analysis stage one no longer pays attention to those error probabilities. In this stage, one calculates the LR for two simple hypotheses (i.e. trait locus is unlinked vs. trait locus is located at a particular position) as a function of the parameter of interest (position). The LR directly measures the strength of evidence for linkage in a given data set and remains completely divorced from the error probabilities calculated in the planning stage. An important consequence of this procedure is that one can use the same criterion k for all analyses. This contrasts with the situation described above, in which the value one uses to conclude significance may differ for each marker and each dataset in order to accommodate a fixed test size, α. In this study we accomplish two goals that lead to a general algorithm for conducting evidential MP linkage studies. (1) We provide two theoretical results that translate into guidelines for investigators conducting evidential MP linkage: (a) Comparing mods to lods, error rates (including probabilities of weak evidence) are generally higher for mods when the null hypothesis is true, but lower for mods in the presence of true linkage. Royall [J Am Stat Assoc 2000;95:760–780] has shown that errors based on lods are bounded and generally small. Therefore when the true disease model is unknown and one chooses to use mods, one needs to control misleading evidence rates only under the null hypothesis; (b) for any given pair of contiguous marker loci, error rates under the null are greatest at the midpoint between the markers spaced furthest apart, which provides an obvious simple alternative hypothesis to specify for planning MP linkage studies. (2) We demonstrate through extensive simulation that this evidential approach can yield low error rates under the null and alternative hypotheses for both lods and mods, despite the fact that mod scores are not true LRs. Using these results we provide a coherent approach to implement a MP linkage study using the evidential paradigm.