Journal articles on the topic 'Anomaly reasoning'

Relational reasoning plays an important role in helping students to understand mathematical concepts. The student's ability to distinguish patterns or objects is one of the understandings of mathematical concept indicators. The anomaly dimension is part of the relational reasoning that students need to be able to determine a pattern or object in mathematics. This study aims to reveal the student's relational reasoning ability of anomaly dimension in solving number pattern problems in terms of gender differences. The subjects of this study are 52 grade-8 students in one of Muhammadiyah Junior High Schools in Kartasura. We used two similar problems on number patterns to disclose the student's ability to identify the pattern deviation in solving problems. The two selected students had relatively similar in their mathematical abilities. The finding showed that female subject met the three anomaly dimension indicators: identification, interpretation, and adaptation. Conversely, male student cannot fulfill the anomaly indicators. He cannot recognize pattern deviation in the formed mathematical model. He also failed to identify a pattern different from the two problems. Although the subjects interviewed were limited, the finding provided the insightful into the differences in anomaly reasoning abilities in male and female students

Network anomaly traffic detection can discover network abnormal behavior and unknown network attacks. But anomaly detection system in current has the disadvantage of the high rate of false positives. Because the condition is not sufficient and high-order conditional reasoning cannot be computed, it leads inaccurate detection of abnormal behavior. In this paper, an analysis method for abnormal network traffic detection is presented. The method firstly applied conditional event algebra for abnormal network traffic detection of Denial-of-Service (DoS) attacks on the 10% trainset of KDD Cup 99 data set. Neptune attack, as an instance of DoS attacks, is used to illustrate this method. Firstly of all, introducing analyzes the attack process of neptune attack. Then, Selecting the most related features of neptune attack on KDD Cup 99 data set and summarizes the basic flow chart of neptune attack. Finally, applying this method for detection of Neptune attack, it can be found that this method can handle with high-order conditional reasoning under insufficient situation, and detect network abnormal behavior.

It is shown that the BRS (= Becchi–Rouet–Stora)-formulated two-dimensional BF theory in the light-cone gauge (coupled with chiral Dirac fields) is solved very easily in the Heisenberg picture. The structure of the exact solution is very similar to that of the BRS-formulated two-dimensional quantum gravity in the conformal gauge. In particular, the BRS Noether charge has anomaly. Based on this fact, a criticism is made on the reasoning of Kato and Ogawa, who derived the critical dimension D=26 of string theory on the basis of the anomaly of the BRS Noether charge. By adding the [Formula: see text] term to the BF-theory Lagrangian density, the exact solution to the two-dimensional Yang–Mills theory is also obtained.

The distinction between public and religious campuses often occurs in the community, the dividing barrier between the two has implications for the favorite attention of the nation's generation in choosing universities, and campuses based on religion are always superior. However, in the traces of developments at the State Islamic University KH. Achmad Siddiq has made significant progress every year, and the increasing interest of prospective students is forced to reject many applicants. It is the main attraction of this research for Then answer how the progress occurred. This research is a type of qualitative research, as a bridge so that the results are more in-depth the author will use integrative theory and approach the problem above with a psycho-sociological approach. The focuses that will be studied include; How is the pre-attention anomaly of new students in the Faculty of Tarbiyah and Teacher Training at UIN Jember? What is the process of reasoning? And the new paradigm of attention is developing? The results showed that the attention paradigm that emerged was the reasoning that was built after the anomaly and crisis in the selection of Islamic universities, there were three adjustment processes, namely economical commensurability, formal education commensurability, and moral commensurability. All three are carried out using a negotiation process of general expectations and the impact of anomalies which are believed to be a necessity of the era.

To facilitate the automated online monitoring of power plants, a systematic and qualitative strategy for anomaly detection is presented. This strategy is essential to provide credible reasoning on why and when an empirical versus hybrid (i.e., physics-supported) approach should be used and to determine the ideal mix of these two approaches for a defined anomaly detection scope. Empirical methods are usually based on pattern, statistical, and causal inference. Hybrid methods include the use of physics models to train and test data methods, reduce data dimensionality, reduce data-model complexity, augment data, and reduce empirical uncertainty; hybrid methods also include the use of data to tune physics models. The presented strategy is driven by key decision points related to data relevance, simple modeling feasibility, data inference, physics-modeling value, data dimensionality, physics knowledge, method of validation, performance, data availability, and suitability for training and testing, cause-effect, entropy inference, and model fitting. The strategy is demonstrated through a pilot use case for the application of anomaly detection to capture a valve packing leak at the high-pressure coolant injection system of a nuclear power plant.

For stability and reliability of real-world applications, the robustness of DNNs in unimodal tasks has been evaluated. However, few studies consider abnormal situations that a visual question answering (VQA) model might encounter at test time after deployment in the real-world. In this study, we evaluate the robustness of state-of-the-art VQA models to five different anomalies, including worst-case scenarios, the most frequent scenarios, and the current limitation of VQA models. Different from the results in unimodal tasks, the maximum confidence of answers in VQA models cannot detect anomalous inputs, and post-training of the outputs, such as outlier exposure, is ineffective for VQA models. Thus, we propose an attention-based method, which uses confidence of reasoning between input images and questions and shows much more promising results than the previous methods in unimodal tasks. In addition, we show that a maximum entropy regularization of attention networks can significantly improve the attention-based anomaly detection of the VQA models. Thanks to the simplicity, attention-based anomaly detection and the regularization are model-agnostic methods, which can be used for various cross-modal attentions in the state-of-the-art VQA models. The results imply that cross-modal attention in VQA is important to improve not only VQA accuracy, but also the robustness to various anomalies.

Security has been raised at major public buildings in the most famous and crowded cities all over the world following the terrorist attacks of the last years, the latest one at the Promenade des Anglais in Nice. For that reason, video surveillance systems have become more and more essential for detecting and hopefully even prevent dangerous events in public areas. In this work, we present an overview of the evolution of high-level surveillance event detection systems along with a prototype for anomaly detection in video surveillance context. The whole process is described, starting from the video frames captured by sensors/cameras till at the end some well-known reasoning algorithms for finding potentially dangerous activities are applied.

Streaming data processing is an exercise in taming disorder: from oftentimes huge torrents of information, we hope to extract powerful and timely analyses. But when dealing with streaming data, the unbounded and temporally disordered nature of real-world streams introduces a critical challenge: how does one reason about the completeness of a stream that never ends? In this paper, we present a comprehensive definition and analysis of watermarks , a key tool for reasoning about temporal completeness in infinite streams. First, we describe what watermarks are and why they are important, highlighting how they address a suite of stream processing needs that are poorly served by eventually-consistent approaches: • Computing a single correct answer, as in notifications. • Reasoning about a lack of data, as in dip detection. • Performing non-incremental processing over temporal subsets of an infinite stream, as in statistical anomaly detection with cubic spline models. • Safely and punctually garbage collecting obsolete inputs and intermediate state. • Surfacing a reliable signal of overall pipeline health . Second, we describe, evaluate, and compare the semantically equivalent, but starkly different, watermark implementations in two modern stream processing engines: Apache Flink and Google Cloud Dataflow.

Even in the 21st century, textbooks can play a significant role in fostering higher-order thinking skills (HOTs) for effective learning and understanding. Still, HOTs like analogies used in biology textbooks may miss their purpose in promoting in-depth understanding. Since most analogies are presented implicitly or partially explicitly, they lack an explicit mapping to explain the analogical pattern between the source and the target. This study examines the degree to which implicit and explicit expressions of four Relational Reasoning skills (RRs): Analogy, Antinomy, Anomaly, and Antithesis, appear in three biology textbooks taught in Israel's junior high school. Qualitative content analysis crosses four predetermined criteria (C1-C4): RRs' type, texts' type (T1, T2, T3), 'mapping process', and 'use-skill indication'. The quantification of the findings provided information on the RRs' distribution and prevalence. The study's findings indicate that only 14% of texts appear with explicit expressions for RRs, mainly in antinomies questions (T2). Although about 32% of the various texts in biology include instructions for learners to activate HOT by using RRs, they are presented at a partially explicit level. Moreover, less than 2% of activities (T3) explicitly enable HOT by using RRs to solve problems. This study expands the theoretical knowledge of analogies to all four RRs. Methodologically, the study presents explicit mapping processes developed for antinomies, anomalies, and antitheses. The implications of the RRs' degree of explicitness are discussed as an effective index of learners' scientific understanding

AbstractThe concept ofmanipulative abductionis devoted to capture the role of action in many interesting cognitive situations: action provides otherwise unavailable information that enables the agent to solve problems by starting and performing a suitable abductive process of generation or selection of hypotheses. We observe that many external things, usually inert from an epistemological point of view, can be transformed intoepistemic mediators. I will present some details derived from the history of the discovery of the non-Euclidean geometries that illustrate the relationships between strategies for anomaly resolution and visual thinking. Geometrical diagrams are external representations that play both amirrorrole (to externalize rough mental models) and anunveilingrole (as gateways to imaginary entities). I describe them as epistemic mediators able to perform various explanatory, non-explanatory, and instrumental abductive tasks (discovery of new properties or new propositions/hypotheses, provision of suitable sequences of models as able to convincingly verifying theorems, etc.). I am also convinced that they can be exploited and studied in everyday non-mathematical applications also to the aim of promoting new trends in artificial intelligence modeling of various aspects of hypothetical reasoning: finding routes, road signs, buildings maps, for example, in connection with various zooming effects of spatial reasoning. I also think that the cognitive activities of optical, mirror, and unveiling diagrams can be studied in other areas of manipulative and model-based reasoning, such as the ones involving creative, analogical, and spatial inferences, both in science and everyday situations so that this can extend the epistemological, computational, and the psychological theory.

Anomaly-based Intrusion Detection System (IDS) is a type of IDS that detects abnormal behaviors by analyzing system activity and network traffic. Anomaly-based IDS works by establishing a baseline of normal behavior for a system or a network. However, these types of systems are less used compared to signature-based IDS for one primary challenge: How to define this normal behavior baseline? The answer to this question is complicated, since it involves not only analyzing or learning from historical data, but requires and understanding of the business domain the system is implemented in. The present study proposes a novel approach to constructing an unsupervised data classifier that combines both Particle Swarm Optimization (PSO) and clustering techniques for anomaly detection. The primary objective of this methodology is to surmount the limitations that conventional clustering algorithms suffer from, such as their inability to identify non-linear patterns within the data, susceptibility to initial conditions, and difficulty in overcoming the problem of local optima. The concept of particle systems is discussed by examining their origins, search strategies, and convergence mechanisms. We use a variant of the Particle Swarm Optimization called Dynamic Inertia Weight-Particle Swarm optimization (DIW-PSO) for our clustering process, and we elaborate on the reasoning behind this decision. Subsequently, we describe the labeling algorithm used for the resulting clusters and we explain the process for identifying anomalous clusters. We have demonstrated the effectiveness of our method by applying it to an intelligent irrigation control system for cotton plants. The results show that our classifier was able to accurately detect abnormal patterns that deviated from the optimal water requirements and growth conditions of the plants.

With the recent increase in the use of sea transportation, the importance of maritime surveillance for detecting unusual vessel behavior related to several illegal activities has also risen. Unfortunately, the data collected by surveillance systems are often incomplete, creating a need for the data gaps to be filled using techniques such as interpolation methods. However, such approaches do not decrease the uncertainty of ship activities. Depending on the frequency of the data generated, they may even confuse operators, inducing errors when evaluating ship activities and tagging them as unusual. Using domain knowledge to classify activities as anomalous is essential in the maritime navigation environment since there is a well-known lack of labeled data in this domain. In an area where identifying anomalous trips is a challenging task using solely automatic approaches, we use visual analytics to bridge this gap by utilizing users’ reasoning and perception abilities. In this work, we propose a visual analytics tool that uses spatial segmentation to divide trips into subtrajectories and score them. These scores are displayed in a tabular visualization where users can rank trips by segment to find local anomalies. The amount of interpolation in subtrajectories is displayed together with scores so that users can use both their insight and the trip displayed on the map to determine if the score is reliable.

My research seeks to answer the question of how any agent that is tasked with making sense of its world, by finding explanations for evidence (e.g., sensor reports) using domain-general strategies, may accurately and efficiently handle incomplete evidence, noisy evidence, and an incomplete knowledge base. I propose the following answer to the question. The agent should employ an optimal abductive reasoning algorithm (developed piece-wise and shown to be best in a class of similar algorithms) that allows it to reason from evidence to causes. For the sake of efficiency and operational concerns, the agent should establish beliefs periodically rather than waiting until it has obtained all evidence it will ever be able to obtain. If the agent commits to beliefs on the basis of incomplete or noisy evidence or an incomplete knowledge base, these beliefs may be incorrect. Future evidence obtained by the agent may result in failed predictions or anomalies. The agent is then tasked with determining whether it should retain its beliefs and therefore discount the newly-obtained evidence, revise its prior beliefs, or expand its knowledge base (what can be described as anomaly-driven or explanation-based learning). I have developed an abductive metareasoning procedure that aims to appropriately reason about these situations. Preliminary experiments in two reasoning tasks indicate that the procedure is effective.

The United States resisted restrictionist immigration legislation in the late twentieth century, providing an anomaly for those who would expect restrictionism in times of economic recession. According to some expectations, labor unions would be part of a coalition that in such times would restrict migration to reduce job competition. This reasoning draws on a state-centric approach and assumes that effective barriers to entrance exist. If one alternatively assumes that states cannot fully regulate the socioeconomic forces driving migration flows, then one may expect labor unions to abandon their supposed preference for restrictionism and instead organize immigrant workers. In that case, unions would prefer migration law that accommodates the transnational migrants' interests. The data provide some support for this argument. The perspective of complex interdependence, which emphasizes transnational relations and the blurring of foreign and domestic politics, can enhance understanding of immigration policymaking.

Cloud computing has established a new horizon in the field of Information Technology. Due to the large number of users and extensive utilization, the Cloud computing paradigm attracts intruders who exploit its vulnerabilities. To secure the Cloud environment from such intruders an Intrusion Detection System (IDS) is required. In this paper the authors have proposed an anomaly based IDS which classifies an incoming connection by taking the deviation of it from the normal behaviors. The proposed method uses a novel Penalty Reward based Fuzzy C-Means (PRFCM) clustering algorithm to generate a rule set and the best rule set is extracted from it using a modified approach for KNN algorithm. This best rule set is used in evidential reasoning of Dempster Shafer Theory for classification. The IDS has been trained and tested with NSL-KDD dataset for performance evaluation. The results prove the proposed IDS to be highly efficient and reliable.

Cyber-Physical Systems (CPS) in heavy industry are a combination of closely integrated physical processes, networking, and scientific computing. The physical production process is monitored and controlled by the CPS in question, through advanced real-time networking systems, where high-precision feedback loops can be changed when the overgrid of cooperative computing and communication components that make up the industrial process is required. These CPS operate independently but integrate interaction capabilities as well as with the external environment, creating the connection of the physical with the digital world. The outline is that the most effective modeling and development of high-reliability CPS are directly related to the maximization of the production process, extroversion, and industrial competition. In this paper, considering the high importance of the operational status of CPS for heavy industry, an innovative autonomous anomaly detection system based on unsupervised disentangled representation learning is presented. It is a temporal disentangled variational autoencoder (TDVA) which, mimicking the process of rapid human intuition, using high- or low-dimensional reasoning, finds and models the useful information independently, regardless of the given problem. Specifically, taking samples from the real data distribution representation space, separating them appropriately, and encoding them as separate disentangling dimensions create new examples that the system has not yet dealt with. In this way, first, it utilizes information from potentially inconsistent sources to learn the right representations that can then be broken down into subspace subcategories for easier and simpler categorization, and second, utilizing the latent representation of the model, it performs high-precision estimates of how similar or dissimilar the inputs are to each other, thus recognizing, with great precision and in a fully automated way, the system anomalies.

The Monty Hall dilemma (MHD) presents an intriguing choice anomaly that offers insight into human reasoning. It presents a specific subclass of decision tasks that require the adequate use of Bayes theorem in order to make optimal decisions. In the MHD, participants are presented with three doors with only one door hiding the prize. After their initial choice of a door, they are offered additional information. A different door (one that does not hide the prize and one not chosen by the participant) is opened to reveal nothing behind it. Afterwards, the participants are offered to stay with their initial choice or to switch to the other remaining door. The better strategy is to always switch; a counterintuitive one for most people. We examine the notorious difficulty of the MHD from an affective perspective while relying on the dual processing approach to thinking. We varied participants? reliance on their affective reactions as opposed to a neutral condition and hypothesized that the affective reactions associated with the staying option contribute to worse performance on the task. Indeed, the participants in the affective condition chose the staying option more often than our control participants. Using the MHD as an appropriate paradigm of conditional probability reasoning we show that, for this type of task, an affective strategy is highly inefficient. We attribute these results to the affective reactions associated with the staying option, with regret avoidance associated with the switch option, and the conditional probability construction of the dilemma.

The term, Artificial Intelligence (AI), has changed since it was first coined by John MacCarthy in 1956. AI, believed to have been created with Kurt Gödel's unprovable computational statements in 1931, is now called deep learning or machine learning. AI is defined as a computer machine with the ability to make predictions about the future and solve complex tasks, using algorithms. The AI algorithms are enhanced and become effective with big data capturing the present and the past while still necessarily reflecting human biases into models and equations. AI is also capable of making choices like humans, mirroring human reasoning. AI can help robots to efficiently repeat the same labor intensive procedures in factories and can analyze historic and present data efficiently through deep learning, natural language processing, and anomaly detection. Thus, AI covers a spectrum of augmented intelligence relating to prediction, autonomous intelligence relating to decision making, automated intelligence for labor robots, and assisted intelligence for data analysis.

Abstract Objective Neuropsychological profiles of patients with pediatric movement disorders are not fully understood, though research suggests greater impairments in cognitive processes reliant on white matter functional integrity. Interpretation of neuropsychological data in these patients is often informed by imaging data that suggests specific areas of brain abnormality. The purpose of this presentation is to discuss the neurocognitive profile of a patient with an unspecified, progressive movement disorder with onset in middle childhood with no observable brain abnormality. Method The patient is an 11-year-old, right-handed male with a history of spastic diplegia and ataxia, onset at seven years of age, in the context of a normal brain MRI and genetic anomaly of unclear clinical significance. Patient has since experienced progressive weakness and spasticity of his bilateral lower limbs, and increasing inflammation in the upper thoracic region. He also has a history of auditory hallucinations. Results His neuropsychological profile was indicative of white matter and right hemispheric dysfunction in the brain with well-preserved left hemisphere functions. He demonstrated stronger verbal reasoning and verbally-based executive functioning abilities compared to visual-spatial reasoning and visual perception. Deficits in sustained attention, vigilance, working memory, and processing speed were also noted. Psychomotor coordination and planning was impaired bilaterally, with more pronounced left-hand deficits. He also demonstrated significant speech dysarthria and dyspraxia. He denied experiencing auditory hallucinations in the past six months. Conclusions This patient’s neurocognitive profile is largely consistent with literature on neuropsychological functioning in pediatric movement disorders despite the absence of an identifiable region of brain abnormality.

Abstract Objective Individuals with deletions of the long arm of chromosome 6 have been known since 1975 with just over 100 cases reported as of 2015. Individuals with deletions involving band 6q25 have a high incidence of intrauterine growth retardation, intellectual disability, dysmorphic features, growth failure, and medical complications (Stagi et al, 2015). Findings will add to the literature base on this genetic anomaly. Methods A 21-year-old male was assessed to differentiate between obsessive vs. psychotic thinking. His history was notable for being born weighing 2300 grams at term, and having feeding, learning and social/emotional difficulties which progressed to OCD in later childhood. At age 15, he was determined to have a de novo 3.7 Mb microdeletion at 6q24.3. Results Neuropsychological assessment of attention, motor and executive functions reveal a variable profile with pockets of strengths relative to his own performance as well as significant normative impairment. Findings represented a significant decline from prior testing at age 10. His verbal memory was below average and his overall attention capacity was impaired. JT’s executive functioning, visual-motor integration, motor speed, and his verbal abstract reasoning were all below average. His non-verbal abstract reasoning and visual perception were intact. On results of objective, projective and neurocognitive testing, JT met criteria for diagnoses of Autism, Obsessive Compulsive Disorder, and Schizoaffective Disorder. Conclusions JT’s developmental history and symptom presentation are complex, revealing significant comorbidity; this case study describes the progression of JT’s difficulties over his lifespan, beginning with feeding difficulties, diagnoses of autism and OCD and progressing to a psychotic disorder.

In nulear emergency condition, after determining the initiating event and the type of the anomaly, operators should take counteractions to control the reactor to mitigate the accident and to bring back the plant to the safe condition. The actions should based on emergency operating procedures. In order to minimize the human error related to the actions, some necessary information is needed. Such kind of information is the consequence of the actions, which can be derived by modeling the counteractions. Multilevel flow modeling (MFM), a functional modeling, is chosen to model the counteraction with the consideration that it is based on cause-effect relations and consequence reasoning, it provides realization relationship which corresponds physical components with their functions, and it provides comprehensive diagnosis based on human perspective of the system objectives. The counteractions are represented by the control functions in the MFM. This paper discusses how to model the counteractions and the consequences of the actions to the system components, which are necessary to enhance situation awareness and to reduce human errors.Keywords: Operator actions, emergency operating procedures, multilevel flow modeling, control function, nuclear safety, human error

Summary Objective: To introduce the special topic of Methods of Information in Medicine on data mining in biomedicine, with selected papers from two workshops on Intelligent Data Analysis in bioMedicine (IDAMAP) held in Verona (2006) and Amsterdam (2007). Methods: Defining the field of biomedical data mining. Characterizing current developments and challenges for researchers in the field. Reporting on current and future activities of IMIA’s working group on Intelligent Data Analysis and Data Mining. Describing the content of the selected papers in this special topic. Results and Conclusions: In the biomedical field, data mining methods are used to develop clinical diagnostic and prognostic systems, to interpret biomedical signal and image data, to discover knowledge from biological and clinical databases, and in biosurveillance and anomaly detection applications. The main challenges for the field are i) dealing with very large search spaces in a both computationally efficient and statistically valid manner, ii) incorporating and utilizing medical and biological background knowledge in the data analysis process, iii) reasoning with time-oriented data and temporal abstraction, and iv) developing end-user tools for interactive presentation, interpretation, and analysis of large datasets.

Background: The development of cloud-based, service-focused and intelligent networks has increased the demand for highly reliable, error-tolerant and computationally efficient means of reducing the costs associated with network operation, maintenance, testing and innovations. Methods: We present a fault self-recovery method for fifth-generation core (5GC) networks. Data models are built according to the data governance approach to include the equipment, links and services of the physical network in the digital twin. Visual topology technology is used to extract knowledge-as-a-service (KaaS) capabilities such as call quality tests, fault-propagation chain reasoning and disaster recovery analysis. Results: The proposed method realises 5GC closed-loop self-recovery through four processes: perception, analysis, decision-making and execution. In tests, it achieved 5GC network fault detection in 1 min, delimitation in 20 min, and recovery in 5 min. Conclusions: Through the network digital twin technology, based on the model and state data, the twinning capabilities such as simulation and event topology can be used to realize the network anomaly perception, fault rapid confinement and service survival decision, thus effectively improving the fault processing efficiency and reducing the fault impact.

A major archetype of artificial intelligence is developing algorithms facilitating temporal efficiency and accuracy while boosting the generalization performance. Even with the latest developments in machine learning, a key limitation has been the inefficient feature extraction from the initial data, which is essential in performance optimization. Here, we introduce a feature extraction method inspired by energy–entropy relations of sensory cortical networks in the brain. Dubbed the brain-inspired cortex, the algorithm provides convergence to orthogonal features from streaming signals with superior computational efficiency while processing data in a compressed form. We demonstrate the performance of the new algorithm using artificially created complex data by comparing it with the commonly used traditional clustering algorithms, such as Birch, GMM, and K-means. While the data processing time is significantly reduced—seconds versus hours—encoding distortions remain essentially the same in the new algorithm, providing a basis for better generalization. Although we show herein the superior performance of the cortical coding model in clustering and vector quantization, it also provides potent implementation opportunities for machine learning fundamental components, such as reasoning, anomaly detection and classification in large scope applications, e.g., finance, cybersecurity, and healthcare.

Poor chip solder joints can severely affect the quality of the finished printed circuit boards (PCBs). Due to the diversity of solder joint defects and the scarcity of anomaly data, it is a challenging task to automatically and accurately detect all types of solder joint defects in the production process in real time. To address this issue, we propose a flexible framework based on contrastive self-supervised learning (CSSL). In this framework, we first design several special data augmentation approaches to generate abundant synthetic, not good (sNG) data from the normal solder joint data. Then, we develop a data filter network to distill the highest quality data from sNG data. Based on the proposed CSSL framework, a high-accuracy classifier can be obtained even when the available training data are very limited. Ablation experiments verify that the proposed method can effectively improve the ability of the classifier to learn normal solder joint (OK) features. Through comparative experiments, the classifier trained with the help of the proposed method can achieve an accuracy of 99.14% on the test set, which is better than other competitive methods. In addition, its reasoning time is less than 6 ms per chip image, which is in favor of the real-time defect detection of chip solder joints.

Purpose The purpose of this paper is to explore the “race report” as a document genre in the serious-leisure pursuit of ultrarunning. Despite the sport’s largely non-documental nature, race reports stand as an anomaly in their importance. This exploration serves as a springboard to investigate the informativeness of story in human life generally. Design/methodology/approach A qualitative survey of the information behavior of ultrarunners was conducted. The 46 participants were runners in a 100-mile footrace in 2016. Responses were first analyzed through phenomenological theme analysis and then were subjected to a deductive audit using a framework of information activities validated for use in serious-leisure pursuits. Findings Race reports are bound up in information activities across the information-communication chain. Race reports help athletes choose races, prepare for races, pre-experience races, communicate their race experiences, gather new ideas, extend their training and, finally, find entertainment. Research limitations/implications This discussion of genre is synchronic, largely limited to one moment in time, and its findings were limited in depth by the survey method. Further research should investigate race reports historically (diachronically) and infrastructurally. Originality/value This work points to symbiosis between genre theory and information behavior theory. It also legitimizes narrative reasoning as a way of knowing, which has been largely unrecognized in information behavior. Some implications of this for information science and technology are discussed.

This article provides a two-dimensional approach to webshops. Building a webshop was getting more and more popular during Covid-19. With the technological extension of 5G, e-commerce might gain market share. This study aims to determine if there is a huge gap between the user's exceptions and the developer’s experience. Based on the developer’s experience, marketers prefer price-effective, fast, and cliche-based solutions to enter the online market. In contrast, users want to use comfortable, reliable, and userfriendly platforms. The hypotheses are based on this anomaly, and the research seeks to reveal this by providing useful and practical solutions. The House of Quality (HoQ) model was used to gather, compare, and analyse the expectations of multiple stakeholders. The main goal was to identify the main features driving engagement and trust from the consumer’s point of view. The experts’ roles and the idea were also analysed as an essential pillar of the multiple stakeholders. The main variables were presented in the House of Quality (HoQ) model presented the main variables. The study begins with statistical reasoning of the topic’s relevance and continues with defining critical terms. After analysing focus groups and interview results, the data was entered into the HoQ model, and the dimensions were compared. Conclusions and business recommendations were drawn, such as the possible further directions of the research.

In the recent past deep learning approaches have achieved some remarkable results in the area of fault diagnostics and anomaly detection. Nevertheless, these algorithms rely on large amounts of data, which is often not available, and produce outputs, which are hard to interpret. These deficiencies make real life applications difficult. Before the broad success of deep learning machine faults were often classified using domain expert knowledge based on experience and physical models. In comparison, these approaches only require small amounts of data and produce highly interpretable results. On the downside, however, they struggle to predict unexpected patterns hidden in data. Merging these two concepts promises to increase accuracy, robustness and interpretability of models. In this paper we present a hybrid approach to combine expert knowledge with deep learning and evaluate it on rolling element bearing fault detection. First, we create a knowledge base for fault classification derived from the expected physical attributes of different faults in the envelope spectrum of vibration signals. This knowledge is used to derive a similarity function for comparing input signals to expected faulty signals. Afterwards, the similarity measure is incorporated into different neural networks using a Logic Tensor Network (LTN). This enables logical reasoning in the loss function, in which we aim to mimic the decision process of an expert analyzing the input data. Further, we extend LTNs by weight schedules for axiom groups. We show that our approach outperforms the baseline models on two bearing fault data sets with different attributes and directly gives a better understanding of whether or not fault signals are influenced by other effects or behave as expected.

Covid-19 pandemic, which struck the world globally and rapidly, has caused significant fatalities. The government has implemented strict health protocols to suppress the spread of coronavirus. The reckless attitude of Tablighi Jamaat to hold “ijtima” amidst the massive spread of the virus is considered as an anomaly in preventing the Covid-19 pandemic and contradicts with the Fatwa of MUI (Indonesian Ulama Council) No. 14 of 2020 regarding the Implementation of Worship during Covid-19 Condition. This paper aims to find out the attitude of Tablighi Jamaat toward pandemic from the perspective of ḍarūrah (Naẓariyyat al-Ḍarūrah) theory by Wahbah al-Zuḥaylī. The writer gives a critical note of the arguments expressed by the Tablighi Jamaat and trying to show a more enlightening reconstruction of the fiqh (Islamic law) paradigm. The results of the study show that Tablighi Jamaat is a religious group that does not care about Covid-19. This attitude was triggered by the assumption that the existence of coronavirus is still in doubt. The doubt generates the understanding of fiqh that has not considered the corona issues as the ‘udhr category, which allows rukhṣah and abort the original law (‘aẓīmah), either in mashaqqah or ḍarūrah. The article assumes that the religious group’s narration that ignored the Covid-19 gives its members the feeling of peace and comfort, but it is counter-productive with the attempt to prevent the spread of Covid-19. It is necessary to reconstruct the fiqh paradigm to bring together science and religion, which is marked by the application of religious reasoning and sciences at the same time.

The network attacks are discovered using the Intrusion Detection Systems (IDS). Anomaly, signature and compound attack detection schemes are employed to fetch malicious data traffic activities. The attack impact analysis operations are carried out to discover the malicious objects in the network. The system objects are contaminated with process injection or hijacking. The attack ramification model discovers the contaminated objects. The dependency networks are built to model the information flow over the objects in the network. The dependency network is a directed graph built to indicate the data communication over the objects. The attack ramification models are designed with intrusion root information. The attack ramifications are applied to identify the malicious objects and contaminated objects. The attack ramifications are discovered with the information flows from the attack sources. The Attack Ramification with Bayesian Network (ARBN) scheme discovers the attack impact without the knowledge of the intrusion root. The probabilistic reasoning approach is employed to analyze the object state for ramification process. The objects lifetime is divided into temporal slices to verify the object state changes. The system call traces and object slices are correlated to construct the Temporal Dependency Network (TDN). The Bayesian Network (BN) is constructed with the uncertain data communication activities extracted from the TDN. The attack impact is fetched with loopy belief propagation on the BN model. The network security system is built with attack impact analysis and recovery operations. Live traffic data analysis process is carried out with improved temporal slicing concepts. Attack Ramification and Recovery with Dynamic Bayesian Network (ARRDBN) is built to support attack impact analysis and recovery tasks. The unsupervised attack handling mechanism automatically discovers the feasible solution for the associated attacks.

Advances in the trusted autonomy of air-traffic management (ATM) systems are currently being pursued to cope with the predicted growth in air-traffic densities in all classes of airspace. Highly automated ATM systems relying on artificial intelligence (AI) algorithms for anomaly detection, pattern identification, accurate inference, and optimal conflict resolution are technically feasible and demonstrably able to take on a wide variety of tasks currently accomplished by humans. However, the opaqueness and inexplicability of most intelligent algorithms restrict the usability of such technology. Consequently, AI-based ATM decision-support systems (DSS) are foreseen to integrate eXplainable AI (XAI) in order to increase interpretability and transparency of the system reasoning and, consequently, build the human operators’ trust in these systems. This research presents a viable solution to implement XAI in ATM DSS, providing explanations that can be appraised and analysed by the human air-traffic control operator (ATCO). The maturity of XAI approaches and their application in ATM operational risk prediction is investigated in this paper, which can support both existing ATM advisory services in uncontrolled airspace (Classes E and F) and also drive the inflation of avoidance volumes in emerging performance-driven autonomy concepts. In particular, aviation occurrences and meteorological databases are exploited to train a machine learning (ML)-based risk-prediction tool capable of real-time situation analysis and operational risk monitoring. The proposed approach is based on the XGBoost library, which is a gradient-boost decision tree algorithm for which post-hoc explanations are produced by SHapley Additive exPlanations (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME). Results are presented and discussed, and considerations are made on the most promising strategies for evolving the human–machine interactions (HMI) to strengthen the mutual trust between ATCO and systems. The presented approach is not limited only to conventional applications but also suitable for UAS-traffic management (UTM) and other emerging applications.

This special issue features the selected papers from i-SAIRAS 2010 (The 10th International Symposium on Artificial Intelligence, Robotics and Automation in Space) at Sapporo, Japan on August 29 - September 1, 2010), which explores the technology of Artificial Intelligence (AI), Automation and Robotics, and its application in space. In the AI domain, in particular, i-SAIRAS focuses on the following issues: (1) spacecraft autonomy (e.g., inboard software for mission planning and execution, resource management, fault protection, science data analysis, guidance, navigation and control, smart sensors, testing and validation, architectures); (2) mission operations automation (e.g., decision support tools for mission planning and scheduling, anomaly detection and fault analysis, innovative operations concepts, data visualization, secure commanding and networking); (3) design tools and optimization methods, electronic documentation; and (4) AI methods (e.g., automated planning and scheduling, agents model-based reasoning, machine learning and data mining). In the selection process for JACIII (Journal of Advanced Computational Intelligence and Intelligent Informatics), 13 papers were firstly nominated from 133 oral presentation papers as outstanding AI-related papers by i-SAIRAS International Committee, and 6 papers were finally accepted through the two-stages of pear-reviews. All papers were reviewed by three reviewers. As the brief introduction of these papers, the paper by Mark Johnston and Mark Giuliano presents an architecture called MUSE (Multi-User Scheduling Environment) to integrate multi-objective evolutionary algorithms with existing domain planning and scheduling tools. The second paper by Amdeo Cesta et al. discusses general lessons learned from a series of deployed planning and scheduling systems. The third paper by Alessandro Donati et al. spotlights specific achievements and trends in the area of spacecraft diagnosis and mission planning and scheduling. The fourth paper by Cedric Cocaud and Takashi Kubota proposes the system that provides position and attitude information to a spacecraft during its approach descent and landing phase toward the surface of an asteroid. The firth paper by Tomohiro Harada et al. studies On-Board Computer which evolves computer programs through the bit inversion and analyzes its robustness to the bit inversion. Finally, the last paper by Masayuki Otani et al. explores the distributed control of the multiple robots which may be broken in the assembly of space solar power satellite. The editor hopes that these papers would help for readers to capture the state-of-art of AI technology in space.

Background: The occurrence of congenital defects in the sheep is estimated to be between 0.2% and 2%. For congenital anatomical alterations, diagnostic imaging allows objective understanding and evaluation, and is a great aid in the formulation of clinical decisions. Most of these anomalies are diagnosed by radiography; but computed tomography (CT) can provide important additional information. In the current literature there are no descriptions of the use of radiography andCT for a more detailed evaluation of the anatomical structures in cases of congenital cervical malformations in lambs. The objective of this study is to report the clinical, radiographic and tomographic findings in two cases of congenital cervical vertebral malformation in lambs.Cases: Two lambs with cervical morphological alterations since birth were attended. A 4-month-old mixed-breed lamb, weighing 11 kg, with lateroventrocaudal deviation of the neck was observed to the right side, not yielding to the attempt of repositioning. The owner reported that these changes were identified since birth, leading to difficulties in suckling colostrum, necessitating artificial feeding. With the growth of the animal, worsening of the cervical deviation resulted in the impossibility of grazing. The radiographs of the cervical spine identified marked scoliosis, and the axis presented small dimensions and morphological changes with a slight loss of atlantoaxial articular relationship. Spondylopathies were detectedalong the cervical spine. Other lamb of the Lacaune breed, weighing 4.2 kg, was presented shortly after birth with changes in the shape and posture of the neck, difficult locomotion and in sternal decubitus. The owner reported that the lamb came from a twin eutocic birth, with the other lamb being apparently normal. The animal was unable to ingest the colostrum, in which the sheep was milked and colostrum was offered through a bottle. Lateroventrocaudal deviation of the neck to the left side did not yield to the repositioning attempt, the mandible also presented left lateral deviation. The radiographs of the cervical spine showed morphological changes in atlas, and it was not possible to delimit its wings; itwas also observed that the dorsal blade was parallel to the spinal process of the axis. The presence of a hypoattenuating linear left lateral image of the dorsal arch and a right ventro-lateral aspect of the atlas body was identified with slightly irregular and sclerotic margins, suggesting fracture lines. The body of the axis presented a conformational alteration withirregular contours and a large free fragment in the cranial aspect, suggestive of being the odontoid process, with rotation and deviation to the left in relation to the atlas. The right lateral cranial articular process of the third cervical vertebra (C3) presented a conformational change and important lateral rotation of the axis. Mild stenosis of the medullary canal was observed in the segment adjacent to C3. The euthanasia was recommended.Discussion: Congenital cervical malformations in sheep are rare in the literature and may lead to serious decrease in the quality of life of the animals. Computed tomography was superior to radiography in morphological evaluation in cases of congenital cervical malformations in sheep. However, both diagnostic methods were important to establish the best clinical behavior. The etiology of most congenital malformations is unknown, simply because of the complexity of the mechanismsthat lead to the formation of an abnormality. The isolated episodes of this anomaly, in the herd without previous alterations, suggest a non-infectious cause, probably similar among the cases, but not established. The information presented can be used to validate clinical reasoning in future cases similar to those described, where imaging features are not available.Keywords: anomalies, fetus, radiography, computed tomography.

In order to reduce unnecessary stops and expensive downtime originating from clutch failure of construction equipment machines; adequate real time sensor data measured on the machine in combination with feature extraction and classification methods may be utilized.This paper presents a framework with feature extraction methods and an anomaly detection module combined with Case-Based Reasoning (CBR) for on-board clutch slippage detection and diagnosis in heavy duty equipment. The feature extraction methods used are Moving Average Square Value Filtering (MASVF) and a measure of the fourth order statistical properties of the signals implemented as continuous queries over data streams. The anomaly detection module has two components, the Gaussian Mixture Model (GMM) and the Logistics Regression classifier. CBR is a learning approach that classifies faults by creating a new solution for a new fault case from the solution of the previous fault cases. Through use of a data stream management system and continuous queries (CQs), the anomaly detection module continuously waits for a clutch slippage event detected by the feature extraction methods, the query returns a set of features, which activates the anomaly detection module. The first component of the anomaly detection module trains a GMM to extracted features while the second component uses a Logistic Regression classifier for classifying normal and anomalous data. When an anomaly is detected, the Case-Based diagnosis module is activated for fault severity estimation.

Network protocol analyzers such asWireshark are valuable for analyzing network traffic but pose a challenge in that it can be difficult to determine which behaviors are out of the ordinary due to the volume of data that must be analyzed. Network anomaly detection systems can provide vital insights to security analysts to supplement protocol analyzers, but this feedback can be difficult to interpret due to the complexity of the algorithms used and the lack of context to determine the reasoning for which an event was labeled as anomalous. We present an approach for visualizing anomalies using a graph-based anomaly detection methodology that aims to provide visual context to network traffic. We demonstrate the approach using network traffic flows as an approach for aiding in the investigation and triage of anomalous network events. The simplicity of a visual representation supports fast analysis of anomalous traffic to identify true positives from false positives and prevent further potential damage.

‘Bitzer,’ said Thomas Gradgrind. ‘Your definition of a horse.’‘Quadruped. Graminivorous. Forty teeth, namely twenty-four grinders, four eye-teeth, and twelve incisive. Sheds coat in the spring; in marshy countries, sheds hoofs, too. Hoofs hard, but requiring to be shod with iron. Age known by marks in mouth.’ Thus (and much more) Bitzer.‘Now girl number twenty,’ said Mr. Gradgrind. ‘You know what a horse is.’— Charles Dickens, Hard Times (1854)Dickens’s famous pedant, Thomas Gradgrind, was not an anomaly. He is the pedagogical manifestation of the rise of quantification in modernism that was the necessary adjunct to massive urbanisation and industrialisation. His classroom caricatures the dominant epistemic modality of modern global democracies, our unwavering trust in numbers, “data”, and reproductive predictability. This brief quotation from Hard Times both presents and parodies the 19th century’s displacement of what were previously more commonly living and heterogeneous existential encounters with events and things. The world had not yet been made predictably repetitive through industrialisation, standardisation, law, and ubiquitous codes of construction. Theirs was much more a world of unique events and not the homogenised and orthodox iteration of standardised knowledge. Horses and, by extension, all entities and events gradually were displaced by their rote definitions: individuals of a so-called natural kind were reduced to identicals. Further, these mechanical standardisations were and still are underwritten by mapping them into a numerical and extensive characterisation. On top of standardised objects and procedures appeared assigned numerical equivalents which lent standardisation the seemingly apodictic certainty of deductive demonstrations. The algebraic becomes the socially enforced criterion for the previously more sensory, qualitative, and experiential encounters with becoming that were more likely in pre-industrial life. Here too, we see that the function of this reproductive protocol is not just notational but is the sine qua non for, in Althusser’s famous phrase, the manufacture of citizens as “subject subjects”, those concrete individuals who are educated to understand themselves ideologically in an imaginary relation with their real position in any society’s self-reproduction. Here, however, ideology performs that operation through that nominally least political of cognitive modes, the supposed friend of classical Marxism’s social science, the mathematical. The historical onset of this social and political reproductive hegemony, this uniform supplanting of time’s ineluctable differencing with the parasite of its associated model, can partial be found in the formation of metrics. Before the 19th century, the measures of space and time were local. Units of length and weight varied not just between nations but often by municipality. These parochial standards reflected indigenous traditions, actualities, personalities, and needs. This variation in measurement standards suggested that every exchange or judgment of kind and value relied upon the specificity of that instance. Every evaluation of an instance required perceptual acuity and not the banality of enumeration constituted by commodification and the accounting practices intrinsic to centralised governance. This variability in measure was complicated by similar variability in the currencies of the day. Thus, barter presented the participants with complexities and engagements of skills and discrete observation completely alien to the modern purchase of duplicate consumer objects with stable currencies. Almost nothing of life was iterative: every exchange was, more or less, an anomaly. However, in 1790, immediately following the French Revolution and as a central manifestation of its movement to rational democratisation, Charles Maurice de Talleyrand proposed a metrical system to the French National Assembly. The units of this metric system, based originally on observable features of nature, are now formally codified in all scientific practice by seven physical constants. Further, they are ubiquitous now in almost all public exchanges between individuals, corporations, and states. These units form a coherent and extensible structure whose elements and rules are subject to seemingly lossless symbolic exchange in a mathematic coherence aided by their conformity to decimal representation. From 1960, their basic contemporary form was established as the International System of Units (SI). Since then, all but three of the countries of the world (Myanmar, Liberia, and the United States), regardless of political organisation and individual history, have adopted these standards for commerce and general measurement. The uniformity and rational advantage of this system is easily demonstrable in just the absurd variation in the numeric bases of the Imperial / British system which uses base 16 for ounces/pounds, base 12 for inches/feet, base three for feet/yards, base 180 for degrees between freezing and cooling, 43,560 square feet per acre, eights for division of inches, etc. Even with its abiding antagonism to the French, Britain officially adopted the metric system as was required by its admission to the EU in 1973. The United States is the last great holdout in the public use of the metric system even though SI has long been the standard wanted by the federal government. At first, the move toward U.S. adoption was promising. Following France and rejecting England’s practice, America was founded on a decimal currency system in 1792. In 1793, Jefferson requested a copy of the standard kilogram from France in a first attempt to move to the metric system: however, the ship carrying the copy was captured by pirates. Indeed, The Metric Conversion Act of 1975 expressed a more serious national intention to adopt SI, but after some abortive efforts, the nation fell back into the more archaic measurements dominant since before its revolution. However, the central point remains that while the U.S. is unique in its public measurement standard among dominant powers, it is equally committed to the hegemonic application of a numerical rendition of events.The massive importance of this underlying uniformity is that it supplies the central global mechanism whereby the world’s chaotic variation is continuously parsed and supplanted into comparable, intelligible, and predictable units that understand individuating difference as anomaly. Difference, then, is understood in this method not as qualitative and intensive, which it necessarily is, but quantitative and extensive. Like Gradgrind’s “horse”, the living and unique thing is rendered through the Apollonian dream of standardisation and enumeration. While differencing is the only inherent quality of time’s chaotic flow, accounting and management requite iteration. To order the reproduction of modern society, the unique individuating differences that render an object as “this one”, what the Medieval logicians called haecceities, are only seen as “accidental” and “non-essential” deviations. This is not just odd but illogical since these very differences allow events to be individuated items so to appear as countable at all. As Leibniz’s principle, the indiscernibility of identicals, suggests, the application of the metrical same to different occasions is inherently paradoxical: if each unit were truly the same, there could only be one. As the etymology of “anomaly” suggests, it is that which is unexpected, irregular, out of line, or, going back to the Greek, nomos, at variance with the law. However, as the only “law” that always is at hand is the so-called “Second Law of Thermodynamics”, the inconsistently consistent roiling of entropy, the evident theoretical question might be, “how is anomaly possible when regularity itself is impossible?” The answer lies not in events “themselves” but exactly in the deductive valorisations projected by that most durable invention of the French Revolution adumbrated above, the metric system. This seemingly innocuous system has formed the reproductive and iterative bias of modern post-industrial perceptual homogenisation. Metrical modeling allows – indeed, requires – that one mistake the metrical changeling for the experiential event it replaces. Gilles Deleuze, that most powerful French metaphysician (1925-1995) offers some theories to understand the seminal production (not reproduction) of disparity that is intrinsic to time and to distinguish it from its homogenised representation. For him, and his sometime co-author, Felix Guattari, time’s “chaosmosis” is the host constantly parasitised by its symbolic model. This problem, however, of standardisation in the face of time’s originality, is obscured by its very ubiquity; we must first denaturalise the seemingly self-evident metrical concept of countable and uniform units.A central disagreement in ancient Greece was between the proponents of physis (often translated as “nature” but etymologically indicative of growth and becoming, process and not fixed form) and nomos (law or custom). This is one of the first ethical and so political debates in Western philosophy. For Heraclitus and other pre-Socratics, the emphatic character of nature was change, its differencing dynamism, its processual but not iterative character. In anticipation of Hume, Sophists disparaged nomos (νόμος) as simply the habituated application of synthetic law and custom to the fluidity of natural phenomena. The historical winners of this debate, Plato and the scientific attitudes of regularity and taxonomy characteristic of his best pupil, Aristotle, have dominated ever since, but not without opponents.In the modern era, anti-enlightenment figures such as Hamann, Herder, and the Schlegel brothers gave theoretical voice to romanticism’s repudiation of the paradoxical impulses of the democratic state for regulation and uniformity that Talleyrand’s “revolutionary” metrical proposal personified. They saw the correlationalism (as adumbrated by Meillassoux) between thought and thing based upon their hypothetical equitability as a betrayal of the dynamic physis that experience presented. Variable infinity might come either from the character of God or nature or, as famously in Spinoza’s Ethics, both (“deus sive natura”). In any case, the plenum of nature was never iterative. This rejection of metrical regularity finds its synoptic expression in Nietzsche. As a classicist, Nietzsche supplies the bridge between the pre-Socratics and the “post-structuralists”. His early mobilisation of the Apollonian, the dream of regularity embodied in the sun god, and the Dionysian, the drunken but inarticulate inexpression of the universe’s changing manifold, gives voice to a new resistance to the already dominate metrical system. His is a new spin of the mythic representatives of Nomos and physis. For him, this pair, however, are not – as they are often mischaracterised – in dialectical dialogue. To place them into the thesis / antithesis formulation would be to give them the very binary character that they cannot share and to, tacitly, place both under Apollo’s procedure of analysis. Their modalities are not antithetical but mutually exclusive. To represent the chaotic and non-iterative processes of becoming, of physis, under the rubric of a common metrics, nomos, is to mistake the parasite for the host. In its structural hubris, the ideological placebo of metrical knowing thinks it non-reductively captures the multiplicity it only interpellates. In short, the polyvalent, fluid, and inductive phenomena that empiricists try to render are, in their intrinsic character, unavailable to deductive method except, first, under the reductive equivalence (the Gradgrind pedagogy) of metrical modeling. This incompatibility of physis and nomos was made manifest by David Hume in A Treatise of Human Nature (1739-40) just before the cooptation of the 18th century’s democratic revolutions by “representative” governments. There, Hume displays the Apollonian dream’s inability to accurately and non-reductively capture a phenomenon in the wild, free from the stringent requirements of synthetic reproduction. His argument in Book I is succinct.Now as we call every thing custom, which proceeds from a past repetition, without any new reasoning or conclusion, we may establish it as a certain truth, that all the belief, which follows upon any present impression, is deriv'd solely from that origin. (Part 3, Section 8)There is nothing in any object, consider'd in itself, which can afford us a reason for drawing a conclusion beyond it; ... even after the observation of the frequent or constant conjunction of objects, we have no reason to draw any inference concerning any object beyond those of which we have had experience. (Part 3, Section 12)The rest of mankind ... are nothing but a bundle or collection of different perceptions, which succeed each other with an inconceivable rapidity, and are in a perpetual flux and movement. (Part 4, Section 6)In sum, then, nomos is nothing but habit, a Pavlovian response codified into a symbolic representation and, pragmatically, into a reproductive protocol specifically ordered to exclude anomaly, the inherent chaotic variation that is the hallmark of physis. The Apollonian dream that there can be an adequate metric of unrestricted natural phenomena in their full, open, turbulent, and manifold becoming is just that, a dream. Order, not chaos, is the anomaly. Of course, Kant felt he had overcome this unacceptable challenge to rational application to induction after Hume woke him from his “dogmatic slumber”. But what is perhaps one of the most important assertions of the critiques may be only an evasion of Hume’s radical empiricism: “there are only two ways we can account for the necessary agreement of experience with the concepts of its objects: either experience makes these concepts possible or these concepts make experience possible. The former supposition does not hold of the categories (nor of pure sensible intuition) ... . There remains ... only the second—a system ... of the epigenesis of pure reason” (B167). Unless “necessary agreement” means the dictatorial and unrelenting insistence in a symbolic model of perception of the equivalence of concept and appearance, this assertion appears circular. This “reading” of Kant’s evasion of the very Humean crux, the necessary inequivalence of a metric or concept to the metered or defined, is manifest in Nietzsche.In his early “On Truth and Lies in a Nonmoral Sense” (1873), Nietzsche suggests that there is no possible equivalence between a concept and its objects, or, to use Frege’s vocabulary, between sense or reference. We speak of a "snake" [see “horse” in Dickens]: this designation touches only upon its ability to twist itself and could therefore also fit a worm. What arbitrary differentiations! What one-sided preferences, first for this, then for that property of a thing! The various languages placed side by side show that with words it is never a question of truth, never a question of adequate expression; otherwise, there would not be so many languages. The "thing in itself" (which is precisely what the pure truth, apart from any of its consequences, would be) is likewise something quite incomprehensible to the creator of language and something not in the least worth striving for. This creator only designates the relations of things to men, and for expressing these relations he lays hold of the boldest metaphors.The literal is always already a reductive—as opposed to literature’s sometimes expansive agency—metaphorisation of events as “one of those” (a token of “its” type). The “necessary” equivalence in nomos is uncovered but demanded. The same is reproduced by the habitual projection of certain “essential qualities” at the expense of all those others residing in every experiential multiplicity. Only in this prison of nomos can anomaly appear: otherwise all experience would appear as it is, anomalous. With this paradoxical metaphor of the straight and equal, Nietzsche inverts the paradigm of scientific expression. He reveals as a repressive social and political obligation the symbolic assertion homology where actually none can be. Supposed equality and measurement all transpire within an Apollonian “dream within a dream”. The concept captures not the manifold of chaotic experience but supplies its placebo instead by an analytic tautology worthy of Gradgrind. The equivalence of event and definition is always nothing but a symbolic iteration. Such nominal equivalence is nothing more than shifting events into a symbolic frame where they can be commodified, owned, and controlled in pursuit of that tertiary equivalence which has become the primary repressive modality of modern societies: money. This article has attempted, with absurd rapidity, to hint why some ubiquitous concepts, which are generally considered self-evident and philosophically unassailable, are open not only to metaphysical, political, and ethical challenge, but are existentially unjustified. All this was done to defend the smaller thesis that the concept of anomaly is itself a reflection of a global misrepresentation of the chaos of becoming. This global substitution expresses a conservative model and measure of the world in the place of the world’s intrinsic heterogenesis, a misrepresentation convenient for those who control the representational powers of governance. In conclusion, let us look, again too briefly, at a philosopher who neither accepts this normative world picture of regularity nor surrenders to Nietzschean irony, Gilles Deleuze.Throughout his career, Deleuze uses the word “pure” with senses antithetical to so-called common sense and, even more, Kant. In its traditional concept, pure means an entity or substance whose essence is not mixed or adulterated with any other substance or material, uncontaminated by physical pollution, clean and immaculate. The pure is that which is itself itself. To insure intelligibility, that which is elemental, alphabetic, must be what it is itself and no other. This discrete character forms the necessary, if often tacit, precondition to any analysis and decomposition of beings into their delimited “parts” that are subject to measurement and measured disaggregation. Any entity available for structural decomposition, then, must be pictured as constituted exhaustively by extensive ones, measurable units, its metrically available components. Dualism having established as its primary axiomatic hypothesis the separability of extension and thought must now overcome that very separation with an adequacy, a one to one correspondence, between a supposedly neatly measurable world and ideological hegemony that presents itself as rational governance. Thus, what is needed is not only a purity of substance but a matching purity of reason, and it is this clarification of thought, then, which, as indicated above, is the central concern of Kant’s influential and grand opus, The Critique of Pure Reason.Deleuze heard a repressed alternative to the purity of the measured self-same and equivalent that, as he said about Plato, “rumbled” under the metaphysics of analysis. This was the dark tradition he teased out of the Stoics, Ockham, Gregory of Rimini, Nicholas d’Autrecourt, Spinoza, Meinong, Bergson, Nietzsche, and McLuhan. This is not the purity of identity, A = A, of metrical uniformity and its shadow, anomaly. Rather than repressing, Deleuze revels in the perverse purity of differencing, difference constituted by becoming without the Apollonian imposition of normalcy or definitional identity. One cannot say “difference in itself” because its ontology, its genesis, is not that of anything itself but exactly the impossibility of such a manner of constitution: universal anomaly. No thing or idea can be iterative, separate, or discrete.In his Difference and Repetition, the idea of the purely same is undone: the Ding an sich is a paradox. While the dogmatic image of thought portrays the possibility of the purely self-same, Deleuze never does. His notions of individuation without individuals, of modulation without models, of simulacra without originals, always finds a reflection in his attitudes toward, not language as logical structure, but what necessarily forms the differential making of events, the heterogenesis of ontological symptoms. His theory has none of the categories of Pierce’s triadic construction: not the arbitrary of symbols, the “self-representation” of icons, or even the causal relation of indices. His “signs” are symptoms: the non-representational consequences of the forces that are concurrently producing them. Events, then, are the symptoms of the heterogenetic forces that produce, not reproduce them. To measure them is to export them into a representational modality that is ontologically inapplicable as they are not themselves themselves but the consequences of the ongoing differences of their genesis. Thus, the temperature associated with a fever is neither the body nor the disease.Every event, then, is a diaphora, the pure consequent of the multiplicity of the forces it cannot resemble, an original dynamic anomaly without standard. This term, diaphora, appears at the conclusion of that dialogue some consider Plato’s best, the Theaetetus. There we find perhaps the most important discussion of knowledge in Western metaphysics, which in its final moments attempts to understand how knowledge can be “True Judgement with an Account” (201d-210a). Following this idea leads to a theory, usually known as the “Dream of Socrates”, which posits two kinds of existents, complexes and simples, and proposes that “an account” means “an account of the complexes that analyses them into their simple components … the primary elements (prôta stoikheia)” of which we and everything else are composed (201e2). This—it will be noticed—suggests the ancient heritage of Kant’s own attempted purification of mereological (part/whole relations) nested elementals. He attempts the coordination of pure speculative reason to pure practical reason and, thus, attempts to supply the root of measurement and scientific regularity. However, as adumbrated by the Platonic dialogue, the attempted decompositions, speculative and pragmatic, lead to an impasse, an aporia, as the rational is based upon a correspondence and not the self-synthesis of the diaphorae by their own dynamic disequilibrium. Thus the dialogue ends inconclusively; Socrates rejects the solution, which is the problem itself, and leaves to meet his accusers and quaff his hemlock. The proposal in this article is that the diaphorae are all that exists in Deleuze’s world and indeed any world, including ours. Nor is this production decomposable into pure measured and defined elementals, as such decomposition is indeed exactly opposite what differential production is doing. For Deleuze, what exists is disparate conjunction. But in intensive conjunction the same cannot be the same except in so far as it differs. The diaphorae of events are irremediably asymmetric to their inputs: the actual does not resemble the virtual matrix that is its cause. Indeed, any recourse to those supposedly disaggregate inputs, the supposedly intelligible constituents of the measured image, will always but repeat the problematic of metrical representation at another remove. This is not, however, the traditional postmodern trap of infinite meta-shifting, as the diaphoric always is in each instance the very presentation that is sought. Heterogenesis can never be undone, but it can be affirmed. In a heterogenetic monism, what was the insoluble problem of correspondence in dualism is now its paradoxical solution: the problematic per se. What manifests in becoming is not, nor can be, an object or thought as separate or even separable, measured in units of the self-same. Dogmatic thought habitually translates intensity, the differential medium of chaosmosis, into the nominally same or similar so as to suit the Apollonian illusions of “correlational adequacy”. However, as the measured cannot be other than a calculation’s placebo, the correlation is but the shadow of a shadow. Every diaphora is an event born of an active conjunction of differential forces that give rise to this, their product, an interference pattern. Whatever we know and are is not the correlation of pure entities and thoughts subject to measured analysis but the confused and chaotic confluence of the specific, material, aleatory, differential, and unrepresentable forces under which we subsist not as ourselves but as the always changing product of our milieu. In short, only anomaly without a nominal becomes, and we should view any assertion that maps experience into the “objective” modality of the same, self-evident, and normal as a political prestidigitation motivated, not by “truth”, but by established political interest. ReferencesDella Volpe, Galvano. Logic as a Positive Science. London: NLB, 1980.Deleuze, Gilles. Difference and Repetition. Trans. Paul Patton. New York: Columbia UP, 1994.———. The Logic of Sense. Trans. Mark Lester. New York: Columbia UP, 1990.Guenon, René. The Reign of Quantity. New York: Penguin, 1972.Hawley, K. "Identity and Indiscernibility." Mind 118 (2009): 101-9.Hume, David. A Treatise of Human Nature. Oxford: Clarendon, 2014.Kant, Immanuel. Critique of Pure Reason. Trans. Norman Kemp Smith. London: Palgrave Macmillan, 1929.Meillassoux, Quentin. After Finitude: An Essay on the Necessity of Contingency. Trans. Ray Brassier. New York: Continuum, 2008.Naddaf, Gerard. The Greek Concept of Nature. Albany: SUNY, 2005. Nietzsche, Friedrich. The Birth of Tragedy. Trans. Douglas Smith. Oxford: Oxford UP, 2008.———. “On Truth and Lies in a Nonmoral Sense.” Trans. Walter Kaufmann. The Portable Nietzsche. New York: Viking, 1976.Welch, Kathleen Ethel. "Keywords from Classical Rhetoric: The Example of Physis." Rhetoric Society Quarterly 17.2 (1987): 193–204.

Relational reasoning is a higher-order executive function that involves the ability to perceive meaningful patterns within a body of seemingly unrelated information. In this study, the ability of 749 fourth (Mage = 10), sixth (Mage = 12), eighth (Mage = 14), and tenth graders (Mage = 16) to identify meaningful relational patterns was investigated. This general cognitive ability was assessed by means of the Test of Relational Reasoning-Junior (TORRjr), a 32-item measure organized into four 8-item scales that assess analogical, anomalous, antinomous, and antithetical reasoning. Students’ performance on the TORRjr was analyzed using confirmatory factor analysis, measurement invariance test, and non-parametric median-based analyses. The confirmatory factor analysis supported that the higher-order factor model was the best fit for the TORRjr data for the Korean students. The measurement was determined to be invariant by gender but variant across grade levels. The non-parametric analysis resulted in an asymptotic (a constant increasing up to grade 6 and then a level off witnessed from grades 8 to 10) development pattern in overall relational reasoning across the grades. In comparison to analogy and anomaly, antinomy and antithesis scores were more fully developed by grade 8 and that level of performance was maintained at grade 10. The TORRjr appeared to be a viable measure for the Korean samples up to approximately 15 years of age. The significance of these findings for research and instructional practice are discussed.

An engine health management (EHM) system typically consists of automated logic for data acquisition, parameter calculation, anomaly detection and eventually, fault identification (or isolation). Accurate fault isolation is pivotal to timely and cost-effective maintenance but is often challenging due to limited fault symptom observability and the intricacy of reasoning with heterogeneous parameters. Traditional fault isolation methods often utilize a single fault isolator (SFI) that primarily relies on gas path performance parameters. While effective for many performance-related faults, such approaches often suffer from ambiguity when two or more faults have signatures that are very similar when monitored by a rather limited number of gas path sensors. In these cases, the ambiguity often has to be resolved by experienced analysts using additional information that takes many different forms, such as various nongas path symptoms, full authority digital engine control fault codes, comparisons with the companion engine, maintenance records, and quite often, the analyst's gas turbine domain knowledge. This paper introduces an intelligent reasoner that combines the strength of an optimal, physics-based SFI and a fuzzy expert system that mimics the analytical process of human experts for ambiguity resolution. A prototype diagnostic reasoner software has been developed and evaluated using existing flight data. Significant performance improvements were observed as compared with traditional SFI results. As a generic reasoning framework, this approach can be applied not only to traditional snapshot data, but to full flight data analytics as well.

fault management systems that observe the state of the system, decide if there is an anomaly and then take automated actions to isolate faults. For example, in electrical networks relays and breaks isolate faults in order to arrest failure propagation and protect the healthy parts of the system. However, due to the limited situational awareness and hidden failures the protection devices themselves, through their operation (or mis-operation) may cause overloading and the disconnection of parts of an otherwise healthy system. Additionally, often there can be faults in the management system itself leading to situations where it is difficult to isolate failures. Our work presented in this paper is geared towards solution of this problem by describing the formalism of Temporal Causal Diagrams (TCD-s) that augment the failure models for the physical systems with discrete time models of protection elements, accounting for the complex interactions between the protection devices and the physical plants. We use the case study of the standard Western System Coordinating Council (WSCC) 9 bus system to describe four different fault scenarios and illustrate how our approach can help isolate these failures. Though, we use power networks as exemplars in this paper our approach can be applied to other distributed cyberphysical systems, for example water networks.

Abstract We revisit the covariant phase space formalism applied to gravitational theories with null boundaries, utilizing the most general boundary conditions consistent with a fixed null normal. To fix the ambiguity inherent in the Wald-Zoupas definition of quasilocal charges, we propose a new principle, based on holographic reasoning, that the flux be of Dirichlet form. This also produces an expression for the analog of the Brown-York stress tensor on the null surface. Defining the algebra of charges using the Barnich-Troessaert bracket for open subsystems, we give a general formula for the central — or more generally, abelian — extensions that appear in terms of the anomalous transformation of the boundary term in the gravitational action. This anomaly arises from having fixed a frame for the null normal, and we draw parallels between it and the holographic Weyl anomaly that occurs in AdS/CFT. As an application of this formalism, we analyze the near-horizon Virasoro symmetry considered by Haco, Hawking, Perry, and Strominger, and perform a systematic derivation of the fluxes and central charges. Applying the Cardy formula to the result yields an entropy that is twice the Bekenstein-Hawking entropy of the horizon. Motivated by the extended Hilbert space construction, we interpret this in terms of a pair of entangled CFTs associated with edge modes on either side of the bifurcation surface.

AbstractAnatomy is a vital basic science for safe and effective medical practice and its significance increases several folds when it is taught in a clinically relevant manner. In today's time-compressed modern medical curricula, the importance of dissection-based anatomy programs is integral to teaching–learning outcome. Sound anatomical knowledge is critical to safe clinical and surgical practice as it is fundamental to the career of future doctors. In this pictorial essay, we present a case of a left ectopic pelvic kidney during one of the faculty-guided dissection sessions at the Alfaisal University. Such an anomaly motivated students to perform further meticulous dissection and to engage in detailed discussions after identifying associated abnormal findings. It is believed that these practices at the very start of the medical journey of students will effectively enhance their clinical reasoning skills by integrating basic and clinical anatomy.