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This paper is about Fault detection over a wireless sensor network in a fully distributed manner. First, we proposed the Convex hull algorithm to calculate a set of extreme points with the neighbouring nodes and the duration of the message remains restricted as the number of nodes increases. Second, we proposed a Naïve Bayes classifier and convolution neural network (CNN) to improve the convergence performance and find the node faults. Finally, we analyze convex hull, Naïve bayes and CNN algorithms using real-world datasets to identify and organize the faults. Simulation and experimental outcomes retain feasibility and efficiency and show that the CNN algorithm has better-identified faults than the convex hull algorithm based on performance metrics. [ABSTRACT FROM AUTHOR]

It is generally agreed that for blame to be appropriate the wrongdoer must be blameworthy. However, blameworthiness is not sufficient for appropriate blame. It has been argued that for blame to be appropriate the blamer must have standing to blame. Philosophers writing on the topic have distinguished several considerations that might defeat someone's standing to blame. This paper examines the underexplored consideration of how personal relationships can influence who has the standing to express blame. We seem to assume that if we do not stand in the right relation to the wrongdoer, it is not our business to blame them. I identify three challenges to this view. First, we do not know what is wrong with meddling (whether it is morally or prudentially wrong). Second, there are cases where we have no close relation to the wrongdoer, but where we seem to have standing nonetheless - murder and other serious moral offences are examples of this. Third, we don't seem to have a clear conception of what 'standing' means, and this makes it hard to see how discussion on standing can help us determine the propriety of blame. This paper defends the notion of standing as a propriety condition on blame in cases of meddling. I argue that personal relationships influence who has the standing to blame through constitution of relationship-specific norms; and that the role these norms play in developing and regulating our relationships can explain why meddlesome blame is morally wrong. [ABSTRACT FROM AUTHOR]

A machine learning approach to perform automatic detection and diagnosis of faults of electrical submersible pump systems is presented. Several thousand vibration patterns were acquired from vertically distributed accelerometers along the string of motors, pumps and protectors. Intermediate features are extracted from the raw vibration signals originating from the set of accelerometers. Each pattern was labelled by a human expert to provide ground truth with respect to the different operation classes (normal, sensor fault, rubbing, unbalance or misalignment). A software framework is used to compare several classifier architectures (K-Nearest-Neighbor, Random Forest, Support Vector Machine, Naïve Bayes and Decision Trees) in a bias aware performance evaluation. In order to boost the classification performance, an ensemble of different versions of a classifier architecture is constructed using the Decision Templates fusion function. The robustness of the system with respect to the emergence of new faults (i.e., untreated faults so far) is corroborated by a systematic analysis methodology. [ABSTRACT FROM AUTHOR]

By using the six sets of interatomic potentials for face-centred cubic metals that differ in the stacking fault energy (SFE) while most of the other material parameters are kept almost identical, we conducted molecular dynamics simulations to evaluate the effects of SFE on the defect formation process through collision cascades. The simulations were performed at 100, 300 and 600 K, with a primary knock-on atom energy of 50 keV. The number of residual defects is not dependent on the SFE at all the temperatures. For clusters of self-interstitial atoms (SIAs), their clustering behaviour does not depend on the SFE, either. However, the ratio of glissile SIA clusters tends to decrease with increasing SFE. This is because perfect loops, the edges of which split into two partial dislocations with stacking fault structures between them in most cases, prefer to form at lower SFEs. The enhanced formation of glissile SIA clusters at lower SFEs can also be observed even at increased temperature. Because most large vacancy clusters have stacking fault structures, they preferentially form at lower SFE; however, it is observed only at the lowest temperature, where the mean size increases with decreasing SFE. At higher temperatures, because of their extremely low number density, the vacancy clustering behaviour does not depend on the SFEs. [ABSTRACT FROM AUTHOR]

In a mining operation, the structural model is considered as a first-order data required for planning. During the start-up and in-depth expansion of an operation, whether the case is open-pit or underground, the structural model must be systematically updated because most common failure mechanisms of a rock mass are generally controlled by geological discontinuities. This update represents one of the main responsibilities for structural geologists and mine engineers. For that purpose, our study presents a geochemically-developed tool based on the tridimensional (3-D) distribution of arsenic concentrations, which have been quantified with a very high-density of blast-holes sampling points throughout an open pit operation. Our results show that the arsenic spatial distribution clearly denotes alignments that match with faults that were previously recognized by classical direct mapping techniques. Consequently, the 3-D arsenic distribution can be used to endorse the existence and even more the real persistence of structures as well as the cross-cutting relationships between faults. In conclusion, by linking the arsenic fault-pathfinder tool to direct on field fault mapping, it is possible to improve structural models at mine scale, focusing on geotechnical design and management, with a direct impact in the generation of safety mining activities. [ABSTRACT FROM AUTHOR]

This study examined people’s willingness to falsely take the blame for a friend’s offense. We sought to identify whether friendship closeness and individual differences would predict false blame-taking. Participants were randomly assigned to think of either a close or casual friend engaging in driver negligence and indicated their willingness to falsely take responsibility. Although self-construal was unrelated to willingness, oneness mediated the relationship between friendship closeness and blame-taking willingness. Negative attitudes about reporting wrongdoing predicted a greater willingness, and men were more willing to take the blame than women. Results may help those in the legal system to better identify false confessions. [ABSTRACT FROM AUTHOR]

Nowadays, the data-driven diagnosis method, exploiting pattern recognition method to diagnose the fault patterns automatically, achieves much success for rotating machinery. Some popular classification algorithms such as artificial neural networks and support vector machine have been extensively studied and tested with many application cases, while the random forest, one of the present state-of-the-art classifiers based on ensemble learning strategy, is relatively unknown in this field. In this paper, the behavior of random forest for the intelligent diagnosis of rotating machinery is investigated with various features on two datasets. A framework for the comparison of different methods, that is, random forest, extreme learning machine, probabilistic neural network and support vector machine, is presented to find the most efficient one. Random forest has been proven to outperform the comparative classifiers in terms of recognition accuracy, stability and robustness to features, especially with a small training set. Additionally, compared with traditional methods, random forest is not easily influenced by environmental noise. Furthermore, the user-friendly parameters in random forest offer great convenience for practical engineering. These results suggest that random forest is a promising pattern recognition method for the intelligent diagnosis of rotating machinery. [ABSTRACT FROM AUTHOR]

Aiming at monitoring photovoltaic (PV) systems, evaluating the degree of fault and locating the fault automatically under different outdoor conditions, this paper discusses a new procedure of fault detection and evaluation of fault degree of the PV system. For the PV array connected by PV modules in series and parallel, each string shares the same voltage. The value of current can be used to identify the underperformed strings. In addition, considering the non-stationary stochastic characteristics of current of PV strings, the local outlier factor (LOF) is applied to detect the fault in PV system by evaluating the deviation between the observed data and the whole data. Nevertheless, the LOF method is more suitable for large samples and the LOF value varies with the value of string current. Hence, the conventional LOF method is not suitable for evaluating the fault degree. In order to apply this method to different scale PV systems to detect the fault accurately and evaluate the fault degree, a modified algorithm is proposed in this study. The simulations and experiments based on the model of PV array in MATLAB/Simulink and the 10 kWp PV power plant built on the campus of Hohai University are implemented. The results of experiments reveal that the modified LOF has good performance in fault detection and fault degree evaluation in different scales of the PV systems. [ABSTRACT FROM AUTHOR]

Power transformers are one of the most important components of the electrical power networks. A wide range of mechanical and electrical stresses in addition to the aging could cause failures in these apparatuses. As a result, evaluating the condition of the transformers during their lifetime is crucial to the power network reliability and service continuity. A large number of different fault diagnosis techniques are introduced for this purpose. Frequency Response Analysis (FRA) is sensitive to the great number of electrical or mechanical changes in the transformers that could occur during the manufacturing, transportation, installation, maintenance or operation of the device. Therefore, FRA is considered among the powerful methods of transformers’ condition assessment. This paper explains the frequency response analysis of transformers method, its application and test procedure as well as providing a comprehensive review of the researches and attempts that are done on different aspects of this field for enhancing quality and repeatability of the test and the interpretation of the results. [ABSTRACT FROM AUTHOR]

The paper begins with an attempt to distinguish the self from its internal objects in terms of the sense of otherness. It raises the issue of the level of contouring of the object and the link with early development. It discusses a type of semi-contoured object using Grotstein’s concept of the background object of primary identification. It concludes with a technical discussion concerning the repair of deficits or basic faults in internal objects. [ABSTRACT FROM AUTHOR]

In complex industrial systems, operating, regulating, maintenance activities and external incidents take place dynamically and multiple entities in same or different subsystems interact in a complex manner. Most of single faults have multiple propagation paths. Any local slight deviation is able to propagate, spread, accumulate and increase through system fault causal chains. It will finally result in system failure and unplanned outages or even catastrophic accidents. The key issues focus on both of how to reduce the probability of fault occurrence and decrease the loss of fault consequence. The implementation of such requirements can be studied in terms of the determination of the fault root causes, prediction of the possible consequence, and also estimation of the risk and timing of various maintenance activities, which are considered in a failure prognosis scheme. This study proposes a DBN based failure prognosis method for complex system. Not only the interaction between components, but also the influence of the layers of protection in the system is considered when the dynamic failure scenarios are analyzed. Therefore the proposed method considers multiple factors including degradation mechanism, parameter deviation, the response of the layers of protection and also the external environment. With this model, the dynamic influence diagram of the components' degradation trends can be calculated and be used to evaluate the different effects of the layers of protection quantitatively. Some key problems are also explained such as how to determine the new nodes in DBN representing the behavior of protective layers and how to update the CPT in the extended model. In the case study, the proposed method is tested on the flue gas energy recovery system (FGERS) which is widely used in the petrochemical industry to demonstrate its effectiveness. It makes a great help for early warning and optimization of the layers of protection in the complex industrial system. [ABSTRACT FROM AUTHOR]

Robustness, low running cost and reduced maintenance lead Induction Motors (IMs) to pioneerly penetrate the industrial drive system fields. Broken rotor bars (BRBs) can be considered as an important fault that needs to be early assessed to minimize the maintenance cost and labor time. The majority of recent BRBs’ fault diagnostic techniques focus on differentiating between healthy and faulty rotor cage. In this paper, a new technique is proposed for detecting the location of the broken bar in the rotor. The proposed technique relies on monitoring certain statistical parameters estimated from the analysis of the start-up stator current envelope. The envelope of the signal is obtained using Hilbert Transformation (HT). The proposed technique offers non-invasive, fast computational and accurate location diagnostic process. Various simulation scenarios are presented that validate the effectiveness of the proposed technique. [ABSTRACT FROM AUTHOR]

This research examines the use of financial mechanisms to impose controls while facilitating blame avoidance by public office-holders. A qualitative historical examination is used to examine legislation designed to prevent Radio Caroline, a pirate radio station, from broadcasting into Britain in the 1960s. Radio Caroline made a mockery of the British Government’s power to manage radio through a monopolist, the British Broadcasting Corporation. In addition, Radio Caroline played the type of rock music the British Government sought to suppress because it represented the undesirable side of youth culture. Hence, inter-generational conflict was connected to the British Government’s attitude towards Radio Caroline. This research examines the suppression of Radio Caroline through the Marine & Broadcasting (Offences) Act (UK) 1967 and the legislative scapegoating of Radio Caroline by targeting its revenue-earning potential. It demonstrates the use of financial control mechanisms to mask the strategies of governments. [ABSTRACT FROM AUTHOR]

In order to diagnose whether the photoelectric encoder of Roots flow meter is working well in assuring the wireless sensor networks (WSN) work properly, this paper discusses the features of Roots flow meter and proposes an on-line fault self-diagnosis method. First, a flexible fault sensing circuit is designed as a state detection module on WSN node. Second, a fault self-diagnosis method is proposed. The fault diagnosis method is based on the vibration frequency of Roots flow meter. The failure is diagnosed by whether the relationship between the measurement of instantaneous flow and the vibration frequency is correct. Experiment results demonstrate the fault self-diagnosis method is suit to the application in WSN nodes and the WSN nodes have been successfully applied to the oil tank trucks. [ABSTRACT FROM AUTHOR]

This paper proposes statistical feature extraction methods combined with artificial intelligence (AI) approaches for fault locations in non-intrusive single-line-to-ground fault (SLGF) detection of low voltage distribution systems. The input features of the AI algorithms are extracted using statistical moment transformation for reducing the dimensions of the power signature inputs measured by using non-intrusive fault monitoring (NIFM) techniques. The data required to develop the network are generated by simulating SLGF using the Electromagnetic Transient Program (EMTP) in a test system. To enhance the identification accuracy, these features after normalization are given to AI algorithms for presenting and evaluating in this paper. Different AI techniques are then utilized to compare which identification algorithms are suitable to diagnose the SLGF for various power signatures in a NIFM system. The simulation results show that the proposed method is effective and can identify the fault locations by using non-intrusive monitoring techniques for low voltage distribution systems. [ABSTRACT FROM AUTHOR]

The article offers a literary criticism of the book "The Limits of Critique" by Rita Felski. Topics discussed include the Felski's use of faultfinding as an attribute of literary criticism, the discussion on academic Eve Kosofsky Sedgwick and sociologist Bruno Latour in the book, and the discussion on humility in the book.

This paper considers the fault detection and isolation problem for nonlinear uncertain non-affine systems. The proposed approach is based on an output-feedback stabilisation strategy, which exploits a Luenberger-like nonlinear observer. As a main result, a residual-based fault detection and isolation approach is developed, which relies on the measurable output, some of its derivatives, which are provided exactly by a uniform high-order sliding-mode differentiator, and the observer’s state. The proposed methodology is able to detect some possiblecomponentsandactuatorsfaults, and to isolate, under some mild conditions, the actuator faults from those ones in components. Simulation results illustrate the feasibility of the proposed approach. [ABSTRACT FROM AUTHOR]

Series of earthquakes including three M > 6 earthquakes occurred in Kumamoto prefecture in the middle of the Kyushu island, Japan. In order to reveal the associated crustal deformation signals, we applied offset tracking technique to ALOS-2/PALSAR-2 data covering three M > 6 earthquakes and derived the 3D displacements around the epicenters. We could identify three NE-SW trending displacement discontinuities in the 3D displacements that were consistent with the surface location of Futagawa and Hinagu fault system. We set three-segment fault model whose positions matched the displacement discontinuities, and estimated the slip distributions on each segment from the observed pixel-offset data. Whereas right-lateral slip was dominant in the shallower depth of the larger segments, normal fault slip was more significant at a greater depth of the other segment. The inferred configuration and slip distribution of each segment suggest that slip partitioning under oblique extension stress regime took place during the 2016 Kumamoto earthquake sequence. Moreover, given the consistent focal mechanisms derived from both the slip distribution model and seismology, the significant non-double couple components in the focal mechanism of the main shock are due to simultaneous ruptures of both strike-slip and normal faulting at the distinct segments. [ABSTRACT FROM AUTHOR]

Tort scholars have long been obsessed with the dichotomy between strict liability and liability based on fault or wrongdoing. We argue that this is a false dichotomy. Torts such as battery, libel, negligence, and nuisance are wrongs, yet all are “strictly” defined in the sense of setting objective and thus quite demanding standards of conduct. We explain this basic insight under the heading of “the strict liability in fault.” We then turn to the special case of liability for abnormally dangerous activities, which at times really does involve liability without wrongdoing. Through an examination of this odd corner of tort law, we isolate “the fault in strict liability”—that is, the fault line between the wrongs-based form of strict liability that is frequently an aspect of tort liability and the wrongs-free form of strict liability that is found only within the very narrow domain of liability for abnormally dangerous activities. We conclude by defending these two features of the common law of tort: the strictness of the terms on which it defines wrongdoing and its begrudging willingness to recognize, in one special kind of case, liability without wrongdoing. [ABSTRACT FROM AUTHOR]

Several studies have shown that people are more likely to attribute intentionality and blame to agents who perform actions that have harmful consequences. This kind of bias has problematic implications for jury decisions because it predicts that judgment in juries will malfunction if an action has a blameworthy effect. Most of these studies include in their design a vignette in which it is clear that agents have foreknowledge of the effects of their actions. This kind of design fails to replicate trial situations where, in most cases, it is impossible to know with certainty whether agents have foreknowledge of the effects of their actions. In the present study, we adopt an alternative design that includes vignettes in which there is no direct evidence of foreknowledge to investigate the relationship between intentionality and blame in actions that have harmful and helpful effects. We find that people are still more likely to attribute intentionality to actions that produce harmful effects than actions that produce good effects. However, we find that people tend to attribute more blame when they have direct evidence of foreknowledge than when presented with an alternative design that does not include foreknowledge. Results indicate the relevant role that evidence of foreknowledge plays in experimental designs that study blame attribution. [ABSTRACT FROM AUTHOR]

Due to the advancements in data measurement and computer technology, automated data collection from multiple sensors has become common in recent years. However, very few papers have dealt with the cost-optimal early fault detection of gearboxes, condition based maintenance policy, and remaining useful life prediction when multiple sensors are used for data collection under varying load. The novel approach presented here is based on vector autoregressive vibration signal modeling and continuous time hidden Markov modeling using the optimal Bayesian control technique. System condition is modeled using a continuous time Markov chain with three states, namely, unobservable healthy state 0, unobservable warning state 1 and observable failure state 2. Model parameters are calculated using the expectation-maximization algorithm. The optimal control policy for the three-state model is represented by a Bayesian control chart for a multivariate observation process. The chart monitors the posterior probability that the system is in the warning state 1 and the system is stopped when this probability exceeds an optimal control limit. Prediction of mean residual life using a posterior probability is also developed in this paper. The validation of the proposed methodologies is carried out using actual gearbox vibration data obtained from multiple sensors. [ABSTRACT FROM AUTHOR]

The fault diagnosis and prognosis of low speed machines remains a difficult problem despite remarkable advances in the conditional monitoring domain. The Rolling-element bearing is a vital part of these machines and its failure is one of the main causes of machine breakdown. In order to have an efficient maintenance strategy, fault diagnosis of a bearing and time estimation of its remaining useful life is needed. However, conventional vibration analysis at very low speeds generally fails to detect vibrations issued from a faulty bearing due to its low energy, high and variable loading conditions and to the noisy environment generated by other mechanical components of low speed machines such as gearing systems. In this work, instantaneous angular speed (IAS)-based fault diagnosis is introduced in order to compensate for the shortcoming of conventional monitoring techniques since it is strictly synchronized to shaft rotation and much less dependent on the transfer path between the defect and the sensor contrary to vibration and acoustic emission analysis. At very low speeds and in the case of a seeded spall on the bearing’s race, the shaft IAS reveals the shaft dynamical behavior when the rolling element passes into the spall. It is proven that this behavior is different when entering the spall than when exiting. The determination of entrance and exit moments allows a precise fault size estimation which is a critical step for bearing prognosis. The proposed fault size estimation method is tested on different seeded spall widths at different low speeds. The results gave a satisfactory fault width estimation and show that IAS measurement is a promising tool for the health monitoring of very low speed machines. [ABSTRACT FROM AUTHOR]

Independent component analysis (ICA) has been widely used in non-Gaussian multivariate process monitoring. However, it assumes only one normal operation mode and omits the dynamic characteristic of process data. In order to overcome the shortcomings of traditional ICA based fault detection method, an improved ICA method, referred to as dynamic Bayesian independent component analysis (DBICA), is proposed to monitor the multimode non-Gaussian dynamic process. In this method, matrix dynamic augmentation is applied to extract dynamic information from original data. Then for analyzing multimode non-Gaussian data, Bayesian inference and ICA are combined to establish a probability mixture model. The ICA model parameters are obtained by the iterative optimization algorithm and the mode of each observation is determined by Bayesian inference simultaneously. Lastly case studies on one continuous stirring tank reactor (CSTR) simulation system and the Tennessee Eastman (TE) benchmark process are used to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

A central topic in experimental epistemology has been the ways that non-epistemic evaluations of an agent's actions can affect whether the agent is taken to have certain kinds of knowledge. Several scholars (e.g., Beebe and Buckwalter Mind Lang 25:474-98; 2010; Beebe and Jensen Philosophical Psychology 25:689-715, 2012; Schaffer and Knobe Noûs 46:675-708, 2012; Beebe and Shea Episteme 10:219-40, 2013; Buckwalter Philosophical Psychology 27:368-83, 2014; Turri Ergo 1:101-127, 2014) have found that the positive or negative valence of an action can influence attributions of knowledge to the agent. These evaluative effects on knowledge attributions are commonly seen as performance errors, failing to reflect individuals' genuine conceptual competence with knows. In the present article, I report the results of a series of studies designed to test the leading version of this view, which appeals to the allegedly distorting influence of individuals' motivation to blame. I argue that the data pose significant challenges to such a view. [ABSTRACT FROM AUTHOR]

Blame game is a term often used to describe a phenomenon that happens in groups of people when something goes wrong. The blame game hypothesis postulates that private investigators may be misled in their search for suspects and that suspected individuals do not necessarily become subject to a fair investigation by financial crime specialists and fraud examiners. The rotten apple hypothesis postulates that it is comforting to assume that one bad apple within an organisation is essentially responsible for the crime that is all too prevalent. The rotten apple view of white-collar crime is a comfortable perspective to apply to business and public organisations as it allows them to look no further than suspect a single individual. Based on a case study of the Norwegian company Hadeland and Ringerike Broadband, this paper discusses blame game and rotten apple issues in an internal investigation report written by an external financial crime specialist. The study finds support for both hypotheses, as blame is mainly isolated to the criminal and his superior, and both board and top management are protected from scrutiny. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Three preregistered studies investigated people's judgments of whether someone with implicit racial bias is obligated to change their bias and to avoid discrimination based on that bias. Two studies showed that hierarchy-legitimizing ideologies-Belief in a Just World, Social Dominance Orientation, and political conservatism-predict lower obligation judgments. One study showed that hierarchy-legitimizing ideologies predicted greater protection of a potential discriminator; in another, they also predicted lower protection of a person who may be discriminated against. Lastly, one study showed that greater obligation judgments predicted greater blame of a person who discriminated based on implicit bias. Taken together, these four studies address how people's ideologies relate to their obligation judgments for implicit racial bias and how those obligation judgments are related to blame for discrimination resulting from implicit racial bias. [ABSTRACT FROM AUTHOR]

Building on blame avoidance analysis, this article develops a method to assess the reactivity, sequencing and efficacy of defensive responses by officeholders facing a crisis of personal blame, analysing cases drawn from four advanced democracies. It tests the hypotheses that officeholders: react by positive action rather than non-engagement when blame levels are high; respond in a 'staged retreat' sequence; and can reduce the level of blame they face from one day to another through choice of presentational strategies. The article applies event history analysis to test the sequencing hypothesis and time series cross-sectional models to test the reactivity and efficacy hypotheses. The analysis shows that officeholders tend to respond actively when blame levels are high, that to some extent their responses tend to follow a staged retreat pattern, and their interventions have a systematic effect on the next day's media blame level only if they take the form of personal statements. [ABSTRACT FROM AUTHOR]

Following crises and fiascos, a framing contest takes place in which actors have to account for their actions and might get blamed for what went wrong. An inadequate response to blame can lead to resignation or losing a re-election. Currently, the literature on blame games focuses mainly on the policy, agency, and - especially - presentational strategies one can use to respond to blame. Based on our analysis of the blame games following two festival disasters in Germany and the Netherlands, we show that our current understanding of blame games and blame responses needs to be broadened to include context, rituals, and sub-blame games. [ABSTRACT FROM AUTHOR]

In this paper, integrated design of residual generation and evaluation is proposed to fault detection (FD) of networked control systems. Both the imperfect network transmissions and the sampling effects are considered under the assumption that no stochastic network model is available. By deriving a linear discrete time-varying system equivalent to the sampled plant, the continuous-time behaviors of disturbances and faults during sampling intervals are captured. Moreover, the effects of unknown but bounded packet delays and dropouts in the controller-to-actuator link are described by uncertain input delays with finite number of possibilities. A parity relation-based FD module with multiple residuals is constructed for the derived system model. For the constructed FD module, the set of undetectable faults is obtained from integrated analysis of residual generation and evaluation and then designed to achieve its worst-case minimal geometrical size while guaranteeing zero false alarms. Simulation results on a networked three-tank system are provided to show the merits of the proposed integrated design approach. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Introduction. Expert witness reports, prepared with the aim of quantifying fault rates among parties, play an important role in a court's final decision. However, conflicting fault rates assigned by different expert witness boards lead to iterative objections raised by the related parties. This unfavorable situation mainly originates due to the subjectivity of expert judgments and unavailability of objective information about the causes of accidents. As a solution to this shortcoming, an expert system based on a rule-based system was developed for the quantification of fault rates in construction fall accidents. The aim of developing DsSafe is decreasing the subjectivity inherent in expert witness reports. Methodology. Eighty-four inspection reports prepared by the official and authorized inspectors were examined and root causes of construction fall accidents in Turkey were identified. Using this information, an evaluation form was designed and submitted to the experts. Experts were asked to evaluate the importance level of the factors that govern fall accidents and determine the fault rates under different scenarios. Based on expert judgments, a rule-based expert system was developed. The accuracy and reliability of DsSafe were tested with real data as obtained from finalized court cases. Result. DsSafe gives satisfactory results. [ABSTRACT FROM AUTHOR]

How victims are portrayed in fictional crime dramas is an important way that individuals come to understand and interpret what it means to be a victim of crime. We examine how demographic variables (e.g., gender, race, age), incident variables (e.g., location of offense, relationship between victim and offender, type of crime), and behavioral variables (e.g., drug use/alcohol use, sexual promiscuity, negative personality traits, or concealing elements of personality) predict victim blame. Although some literature has analyzed victims in fictional crime dramas, such literature has been limited to a single year, a single show, a particular crime, or a particular factor. We extend this literature by focusing on multiple factors that predict victim blame using data collected from a systematic sample of 124 episodes from 4 fictional crime dramas (CSI, Law & Order: Special Victims Unit, Criminal Minds,andWithout a Trace) over 7 years (2003–2010). [ABSTRACT FROM AUTHOR]

The article discusses whether a liability insurers' duty to settle should be governed by a fault or no-fault liability standard in America as of 2015, and it mentions liability for breaching a duty to settle, as well as damage awards and a bad faith legal doctrine. According to the article, the adoption of no-fault liability would produce lower joint costs for insurers and the insured. A good faith legal doctrine is examined, as well as several U.S. insurance law-related legal cases.

The article discusses the state of parenting and personal responsibility in Canada. Topics mentioned the death of several children in the country which stirs people to blame the fire department and the federal government, the financial challenge of being a parent since the Great Depression, and the role of buying into the narrative of personal blame on justifying the need for the government to enact policies towards helping the poor or the middle class.

Conflicts and debates on wildlife issues often prove 'intractable' or resistant to resolution. This paper develops a three-layered methodological approach to identify the fault lines and dynamics, which perpetuate social division and conflict. This approach was applied to the analysis of six publicly debated events that followed the comeback of the red fox and wild boar in Flanders, Belgium. The integrated findings demonstrate that conflict was not merely a manifestation of incompatible goals and views, but was highly determined by the conduct of the debate itself. The debates evolved along a few main fault lines, most notably 'belonging/not belonging', 'opportunity/threat' and 'control by intervention/nature controls itself'. A number of dynamics were identified along these fault lines, including the convergence and alignment of arguments (in particular, dichotomisation), the linking and scaling up of issues and the stigmatisation of outgroups. These processes were largely driven by the parties' strategies to gain credibility and support with audiences. At the same time, however, they tended to magnify the problems, polarised positions along the fault lines, and thus hampered resolution. Furthermore, part of the debate served to confirm institutional roles and identities, which, in turn, contributed to the perpetuation of conflict. Contrasting views on 'nature' were hardly a topic of discussion. Rather they were locked into dichotomies and classifications expressed by the contending parties. Together, the findings from this paper provide useful clues for transforming the dynamics perpetuating the conflict to different dynamics that allow for more constructive relations between the parties involved. [ABSTRACT FROM AUTHOR]

In this study, we used chain store settings to confirm pseudorelationships (brand or branch relationship orientations) and to investigate customers’ attribution of blame. We devised 6 scenarios to measure customers’ attribution of blame: when customers are satisfied with transactions, when service personnel cause dissatisfactory transactions, and when products yield dissatisfactory transactions in industries with both branch-oriented relationships (i.e., hair salons) and brand-oriented relationships (i.e., supermarkets). The results showed that customers’ attribution of blame varies slightly with different relationship orientations and transaction scenarios. To whom customers attribute blame must be understood to effectively mitigate service failures. [ABSTRACT FROM AUTHOR]

The study of moral disengagement has greatly informed research on aggression and bullying. There has been some debate on whether cyberbullies and other cyber-aggressors show more or less of a tendency for moral disengagement than traditional aggressors and bullies. However, according to the triadic model of reciprocal determinism, an individual's behavior influences and is influenced by both personal factors and his/her social environment. This article reviews the literature to propose a new conceptual framework addressing how features of the online context may enable specific mechanisms that facilitate moral disengagement. Specific affordances for moral disengagement proposed here include the paucity of social-emotional cues, the ease of disseminating communication via social networks, and the media attention on cyberbullying, which may elicit moral justification, euphemistic labeling, palliative comparison, diffusion and displacement of responsibility, minimizing and disregarding the consequences for others, dehumanization, and attribution of blame. These ideas suggest that by providing affordances for these mechanisms of moral disengagement, online settings may facilitate cyber-aggression and cyberbullying. [ABSTRACT FROM AUTHOR]

Can judging that an agent blamelessly broke a rule lead us to claim, paradoxically, that no rule was broken at all? Surprisingly, it can. Across seven experiments, we document and explain the phenomenon of excuse validation. We found when an agent blamelessly breaks a rule, it significantly distorts people's description of the agent's conduct. Roughly half of people deny that a rule was broken. The results suggest that people engage in excuse validation in order to avoid indirectly blaming others for blameless transgressions. Excuse validation has implications for recent debates in normative ethics, epistemology and the philosophy of language. These debates have featured thought experiments perfectly designed to trigger excuse validation, inhibiting progress in these areas. [ABSTRACT FROM AUTHOR]

Are decades-long delays between sentencing and execution immune from Eighth Amendment violation because they are self-inflicted by prisoners, or is such prisoner fault for delays simply irrelevant to whether a state-imposed punishment is cruel and unusual? Typically finding delay to be the state's responsibility, Justices Breyer and Stevens argue that execution following upwards of forty years of death row incarceration is unconstitutional. Nearly every lower court disagrees, reasoning that prisoners have the choice of pursuing appellate and collateral review (with the delay that entails) or crafting the perfect remedy to any delay by submitting, as Justice Thomas has invited complaining prisoners to do, to execution. By choosing the former, any resulting delay is self-inflicted; delayed executions are prisoners' own fault. Despite this argument's commonsense appeal, left unexplained is how prisoner fault inoculates state-imposed punishment from Eighth Amendment violation. Lacking a rationale for the prisoner fault argument, this Article proposes the two most obvious candidates: (i) analogizing to fault attribution for delays in the Sixth Amendment speedy trial right context; and (ii) choosing post-conviction review rather than submitting to execution, prisoners waive Eighth Amendment challenge of the resulting delay. But neither is persuasive; moreover, each proposed rationale presupposes the existence of the very right that Justice Thomas and nearly every court vigorously deny: an Eighth Amendment right against excessively delayed execution. The absence of a persuasive rationale exposes prisoner fault as irrelevant and removes the primary obstacle to courts recognizing that execution following decades of death row incarceration constitutes cruel and unusual punishment. [ABSTRACT FROM AUTHOR]

The article discusses the role that fault plays in the division of premarital property in America in cases where marriage does not ensue, and it mentions ownership rights over engagement and wedding bands given in anticipation of marriage. U.S. property, contract, and family laws are addressed, along with the legal aspects of gifts given in contemplation of marriage. Breach-of-promise lawsuits and damages are examined, as well as American courts, fairness, and justice.