Should offenders with psychopathy or those exhibiting extreme forms of antisocial behav- iour be considered criminally responsible? The current debate seems to have reached a stalemate. Several scholars have argued that neuropsychologi- cal data on individuals with psychopathy might be relevant for determining their criminal responsibil- ity. However, relying on such data has not produced a consensus among legal scholars and philosophers on whether individuals with psychopathy should be excused from responsibility. We offer a diagnosis about why this debate has (...) reached a standoff. We argue that part of the problem is that psychopathy, being a syndrome-based category, is too heterogeneous and thus offers low prospects for being integrated with neuropsychological data that might support significant conclusions about the criminal responsibility of individuals with psychopathy. Moreover, the construct of psychopathy was not originally devised to discriminate criminally accountable from unac- countable antisocial individuals. To overcome these difficulties and advance the debate, we extend a currently less discussed theoretical framework for bridging biopsychology and the law that focuses on neuropsychological constructs, domains, and processes that directly measure capacities of offenders that are relevant for criminal responsibility, without necessarily relying on mediating syndrome-based constructs. The novelty of our contribution is that the biopsy- chological bases of exculpation can be further devel- oped and used for determining more fine-grained cat- egorisations of antisocial personality types. We show how this framework provides guidelines for inter- disciplinary research that can significantly advance our understanding of the preconditions for criminal responsibility and help the legal practice of ascribing or withholding it. (shrink)

Abstract : Background: Vegetable agriculture is very important to human continued existence and remains a key driver of many economies worldwide, especially in underdeveloped and developing economies. Objectives: There is an increasing demand for food and cash crops, due to the increasing in world population and the challenges enforced by climate modifications, there is an urgent need to increase plant production while reducing costs. Methods: In this paper, Lemon classification approach is presented with a dataset that contains approximately 2,000 (...) images belong to 3 species at a few developing phases. Convolutional Neural Network (CNN) algorithms, a deep learning technique extensively applied to image recognition was used, for this task. The results: found that CNN-driven lemon classification applications when used in farming automation have the latent to enhance crop harvest and improve output and productivity when designed properly. The trained model achieved an accuracy of 99.48% on a held-out test set, demonstrating the feasibility of this approach. (shrink)

What is the biological function of daily mood variations? What is the relationship between mood and such factors as exercise, time of day, nutrition, stress, and illness? Drawing on his own wide-ranging research concerning subjective assessments of mood and on extensive research by others, Dr. Thayer presents a comprehensive theory of normal mood states, viewing them as subjective components of two biological arousal systems, one which people find energizing, and the other which people describe as producing tension. The author explains (...) these two mood effects in relation to a complex relationship between energy and tension. Relevant research is systematically reviewed, and moods are analyzed in relation to circadian rhythms, exercise, nutrition, sleep, stress, and cognition. Perceptual and motivational effects of mood are also discussed, as are measurement and research design issues. Unique in its depth and comprehensiveness, this book will be of interest not only to researchers in psychology, biology, and medicine, but its clear style of presentation and the practical activities suggested for mood regulation will make it interesting to general readers as well. (shrink)

Abstract: Potatoes are edible tubers, available worldwide and all year long. They are relatively cheap to grow, rich in nutrients, and they can make a delicious treat. The humble potato has fallen in popularity in recent years, due to the interest in low-carb foods. However, the fiber, vitamins, minerals, and phytochemicals it provides can help ward off disease and benefit human health. They are an important staple food in many countries around the world. There are an estimated 200 varieties of (...) potatoes, which can be classified into a number of categories based on the cooked texture and ingredient functionality. Using a public dataset of 2400 images of potatoes, we trained a deep convolutional neural network to identify 4 types (Red, Red Washed, Sweet, and White).The trained model achieved an accuracy of 99.5% of test set, demonstrating the feasibility of this approach. (shrink)

A. W. F. Edwards famously named “Lewontin’s fallacy” after Richard Lewontin, the geneticist who showed that most human genetic diversity can be found within any given racialized group. “Lewontin’s fallacy” is the assumption that uncorrelated genetic data would be sufficient to classify genotypes into conventional “racial” groups. In this chapter, I argue that Lewontin does not commit the fallacy named after him, and that it is not a genuine fallacy. Furthermore, I argue that when Edwards assumes that stable classification (...) is all it takes to vindicate racial naturalism, he commits a fallacy of his own: Edwards’ fallacy. The ability to create a classificatory system, and then reliably sort things within that system, is not enough to make that system scientifically respectable. I show that Edwards’ fallacy is rife in debates about the existence of human biological races. (shrink)

In a world of ever growing specialization, the idea of a unity of science is commonly discarded, but cooperative work involving cross-disciplinary points of view is encouraged. The aim of this paper is to show with some textual support that Charles S. Peirce not only identified this paradoxical situation a century ago, but he also mapped out some paths for reaching a successful solution. A particular attention is paid to Peirce's classification of the sciences and to his conception of (...) science as a collective and cooperative activity of all those whose lives are animated by the desire to discover the truth. -/- . (shrink)

How Classification Works attempts to bridge the gap between philosophy and the social sciences using as a focus some of the work of Nelson Goodman. Throughout his long career Goodman has addressed the question: are some ways of conceptualizing more natural than others? This book looks at the rightness of categories, assessing Goodman's role in modern philosophy and explaining some of his ideas on the relation between aesthetics and cognitive theory. Two papers by Nelson Goodman are included in the (...) collection and there are analyses of his work by seven leading academics in anthropology, philosophy, sociology and musicology. (shrink)

A classification of the global catastrophic risks of AI is presented, along with a comprehensive list of previously identified risks. This classification allows the identification of several new risks. We show that at each level of AI’s intelligence power, separate types of possible catastrophes dominate. Our classification demonstrates that the field of AI risks is diverse, and includes many scenarios beyond the commonly discussed cases of a paperclip maximizer or robot-caused unemployment. Global catastrophic failure could happen at (...) various levels of AI development, namely, before it starts self-improvement, during its takeoff, when it uses various instruments to escape its initial confinement, or after it successfully takes over the world and starts to implement its goal system, which could be plainly unaligned, or feature-flawed friendliness. AI could also halt at later stages of its development either due to technical glitches or ontological problems. Overall, we identified around several dozen scenarios of AI-driven global catastrophe. The extent of this list illustrates that there is no one simple solution to the problem of AI safety, and that AI safety theory is complex and must be customized for each AI development level. (shrink)

In psychiatry some disorders of cognition are distinguished from instances of normal cognitive functioning and from other disorders in virtue of their surface features rather than in virtue of the underlying mechanisms responsible for their occurrence. Aetiological considerations often cannot play a significant classificatory and diagnostic role, because there is no sufficient knowledge or consensus about the causal history of many psychiatric disorders. Moreover, it is not always possible to uniquely identify a pathological behaviour as the symptom of a certain (...) disorder, as disorders that are likely to differ both in their causal histories and in their overall manifestations may give rise to very similar patterns of behaviour. -/- Consider delusions as an example. It wouldn’t be correct to define delusions as those beliefs people form as a result of a neurobiological deficit and a hypothesis-evaluation deficit (as some versions of the two-factor theory of delusions suggest), because for some delusions no neurobiological deficit may be found, and reasoning biases and motivational factors may be contributors to the formation of the delusion (e.g. McKay et al., 2005). Moreover, it would be a mistake to define delusions as symptoms of schizophrenia alone, because they occur also in other disorders, including dementia, amnesia, and delusional disorders. Thus, aetiological considerations may appear in the description and analysis of delusions, but do not feature prominently in their definition. -/- In this paper I argue that the surface features used as criteria for the classification and diagnosis of disorders of cognition are often epistemic in character. I shall offer two examples: confabulations and delusions are defined as beliefs or narratives that fail to meet standards of accuracy and justification. Although classifications and diagnoses based on features of people’s observable behaviour are necessary at these early stages of neuropsychiatric research, given the variety of conditions in which certain phenomena appear, I shall attempt to show that current epistemic accounts of confabulations and delusions have limitations. Epistemic criteria can guide both research and clinical practice, but fail to provide sufficient conditions for the identification of delusions and confabulations, and fail to demarcate pathological from non-pathological narratives or beliefs. -/- Another limitation of current epistemic accounts – which I shall not address here – is the excessive focus on epistemic faults of confabulations and delusions at the expense of their epistemically neutral or advantageous features (see Bortolotti and Cox, 2009). This may lead to a misconception of delusions and confabulations, and to an oversimplification in the assessment of the needs of people who require clinical treatment for their psychotic symptoms. (shrink)

Aristotle, in the Historia Animalium, follows the explanation‐involving approach to classification that he developed in the pattern of the Posterior Analytics. Thus, he draws in his theory of animal classification on his explanatory account of soul functions developed in De Anima. However, his project encounters a severe problem: he failed to uncover in his study of biological phenomena the unified, causally basic essences that his theory of definition required. I consider whether Aristotle can resolve this crisis while remaining (...) true to the basic features of his Analytics paradigm. (shrink)

As a type of evidence glass can be very useful contact trace material in a wide range of offences including burglaries and robberies, hit-and-run accidents, murders, assaults, ram-raids, criminal damage and thefts of and from motor vehicles. All of that offer the potential for glass fragments to be transferred from anything made of glass which breaks, to whoever or whatever was responsible. Variation in manufacture of glass allows considerable discrimination even with tiny fragments. In this study, we worked glass (...) class='Hi'>classification and testing of artificial neural network model created by the JustNN. The aim of the study is help investigator in identifying the type of glass found in arena of the crime. The Neural Network model was trained and validated using the type of glass dataset. The accuracy of model in predicting the type of glass reached 96.7%. Thus neural network is suitable for predicating type of glasses. (shrink)

A great deal of interest in codes of ethics exists in both the business community and the academic community. Within the academic community, this interest has given rise to a number of studies of codes of ethics. Many of these studies have focused on the content of various codes.One important way the study of codes of ethics can be advanced is by applying formal tools of analysis to codes of ethics. An understanding of important dimensions that may differ across codes (...) of ethics, a common terminology to describe these dimensions, and a means to measure these dimensions will facilitate applying such tools. They will also facilitate discussion, enable comparisons, and advance our understanding of codes of ethics. The present paper describes a classification scheme to use in studying codes of ethics. This scheme uses six important dimensions to distinguish among codes of ethics: length, focus, level of detail, shape, thematic content, and tone. The paper also introduces metrics that can be used to measure the dimensions. (shrink)

Modern biological classification is based on the system developed by Linnaeus, and interpreted by Darwin as representing the tree of life. But despite its widespread acceptance, the evolutionary interpretation has some problems and limitations. This comprehensive book provides a single resource for understanding all the main philosophical issues and controversies about biological classification. It surveys the history of biological classification from Aristotle to contemporary phylogenetics and shows how modern biological classification has developed and changed over time. (...) Readers will also be able to see how biological classification is in part a consequence of human psychology, language development and culture. The book will be valuable for student readers and others interested in a range of topics in philosophy and biology. (shrink)

Effective and specifically targeted social and therapeutic responses for antisocial personality disorders and psychopathy are scarce. Some authors maintain that this scarcity should be overcome by revising current syndrome - based classifications of these conditions and devising better biocognitive classifications of antisocial individuals. The inspiration for the latter classifications has been embedded in the Research domain criteria approach (RDoC). RDoC - type approaches to psychiatric research aim at transforming diagnosis, provide valid measures of disorders, aid clinical practice, and improve health (...) outcomes by integrating the data on the genetic, neural, cognitive, and affective systems underlying psychiatric conditions. In the first part of the paper, we discuss the benefits of such approaches in comparison to the dominant syndrome-based ones and review recent attempts at building biocognitive classifications of antisocial individuals. Other researchers, how ever, have objected that biocognitive approaches in psychiatry are committed to an untenable form of explanatory. (shrink)

This chapter proceeds in five steps. First, we will describe and justify the structure of the traditional system of species classification. Second, we will discuss three formal principles governing the development of taxonomies in general. It will emerge that, in addition to these formal principles, a division of living beings must meet certain empirical constraints. In the third section, we will show that the traditional division of living beings into species best meets these constraints. Fourth, we will argue that (...) a taxonomic system based on this notion of species provides a more natural alternative to the many arbitrary classifications that are possible. Hence, the traditional classificatory system is also the most natural one. Finally, we will discuss and reject an alternative account that suggests defining species solely with a view to their evolutionary history. We will argue that taxonomic trees do not depict hereditary connections but, rather, something else. (shrink)

We contend that it is possible to argue reasonably for and against arguments from classifications and definitions, provided they are seen as defeasible (subject to exceptions and critical questioning). Arguments from classification of the most common sorts are shown to be based on defeasible reasoning of various kinds represented by patterns of logical reasoning called defeasible argumentation schemes. We show how such schemes can be identified with heuristics, or short-cut solutions to a problem. We examine a variety of arguments (...) of this sort, including argument from abductive classification, argument from causal classification, argument from analogy-based classification and arguments from classification based on generalizations. (shrink)

Comparative cognitive science often involves asking questions like ‘Do nonhumans have C?’ where C is a capacity we take humans to have. These questions frequently generate unproductive disagreements, in which one party affirms and the other denies that nonhumans have the relevant capacity on the basis of the same evidence. I argue that these questions can be productively understood as questions about natural kinds: do nonhuman capacities fall into the same natural kinds as our own? Understanding such questions in this (...) way has several advantages: it preserves the intuition that these are substantive empirical questions worth asking; it helps us to understand why they so frequently give rise to disagreements of the kind described; and it provides clues about how to diagnose and resolve them. (shrink)

This chapter examines philosophical issues surrounding the classification of mental disorders by the Diagnostic and Statistical Manual of Mental Disorders (DSM). In particular, the chapter focuses on issues concerning the relative merits of descriptive versus theoretical approaches to psychiatric classification and whether the DSM should classify natural kinds. These issues are presented with reference to the history of the DSM, which has been published regularly by the American Psychiatric Association since 1952 and is currently in its fifth edition. (...) While the first two editions of the DSM adopted a theoretical (psychoanalytic) and etiological approach to classification, subsequent editions of the DSM have adopted an atheoretical and purely descriptive (“neo-Kraepelinian”) approach. It is argued that largest problem with the DSM at present—viz., its failure to provide valid diagnostic categories—is directly related to the purely descriptive methodology championed by the DSM since the third edition of the DSM. In light of this problem, the chapter discusses the prospects of a theoretical and causal approach to psychiatric classification and critically examines the assumption that the DSM should classify natural kinds. (shrink)

„Errors are the greatest obstacles to the progress of science; to correct such errors is of more practical value than to achieve new knowledge,“ asserted Eugen Bleuler. Basic error of several prevailing classification schemes of pathological conditions, as for example ICD-10, lies in confusing and mixing symptoms with diseases, what makes them unscientific. Considering the need to bring order into the chaos and light into terminological obscureness, I introduce the Causal classification of diseases originating from the notion of (...) bodily wholeness and causality of its loss. (shrink)

Classifications of animals and plants have long been represented by hierarchical lists of taxa, but occasional authors have drawn diagrammatic versions of their classifications in an attempt to better depict the "natural relationships" of their organisms. Ornithologists in 19th-century Britain produced and pioneered many types of classificatory diagrams, and these fall into three groups: (a) the quinarian systems of Vigors and Swainson (1820s and 1830s); (b) the "maps" of Strickland and Wallace (1840s and 1850s); and (c) the evolutionary diagrams of (...) the post-Darwin authors (1860 on). The quinarians distinguished between affinity and analogy and used both in their classifications, whereas Strickland rejected the quinarians' belief in numerical regularity and their use of analogy. Wallace's "maps" are easily given an evolutionary interpretation, and his approach was taken up and modified by later evolutionary anatomists. Sharpe returned to Strickland's methods and merely appended a superficial evolutionary interpretation. Contrary to common belief systematics has a rich conceptual history, and many of the conceptual developments in 19th-century systematics were made by ornithologists. (shrink)

We study the complexity of the classification problem of conjugacy on dynamical systems on some compact metrizable spaces. Especially we prove that the conjugacy equivalence relation of interval dynamical systems is Borel bireducible to isomorphism equivalence relation of countable graphs. This solves a special case of Hjorth’s conjecture which states that every orbit equivalence relation induced by a continuous action of the group of all homeomorphisms of the closed unit interval is classifiable by countable structures. We also prove that (...) conjugacy equivalence relation of Hilbert cube homeomorphisms is Borel bireducible to the universal orbit equivalence relation. (shrink)

This paper investigates the case of enzyme classification to evaluate different ideals for regulating values in science. I show that epistemic and non-epistemic considerations are inevitably and untraceably entangled in enzyme classification, and argue that this has significant implications for the two main kinds of views on values in science, namely, Epistemic Priority Views and Joint Satisfaction Views. More precisely, I argue that the case of enzyme classification poses a problem for the usability and descriptive accuracy of (...) these two views. The paper ends by suggesting that these two views provide different but complementary perspectives, and that both are useful for evaluating values in science. (shrink)

Scientists represent their world, grouping and organizing phenomena into classes by means of concepts. Philosophers of science have historically been interested in the nature of these concepts, the criteria that inform their application and the nature of the kinds that the concepts individuate. They also have sought to understand whether and how different systems of classification are related and more recently, how investigative practices shape conceptual development and change. Our aim in this paper is to provide a critical overview (...) of some of the key developments in this philosophical literature and identify some interesting issues it raises about the prospects of the so-called “special sciences”, including psychiatry, psychology, and the mind-brain sciences more generally, to discover natural kinds. (shrink)

This volume launches a new series of contemporary conversations about scientific classification. Most philosophical conversations about kinds have focused centrally or solely on natural kinds, that is, kinds whose existence is not dependent on the scientific process of synthesis. This volume refocuses conversations about classification on unnatural, or synthetic, kinds via extensive study of three paradigm cases of unnatural kinds: nanomaterials, stem cells, and synthetic biology.

The large number of sensors and actuators that make up the Internet of Things obliges these systems to use diverse technologies and protocols. This means that IoT networks are more heterogeneous than traditional networks. This gives rise to new challenges in cybersecurity to protect these systems and devices which are characterized by being connected continuously to the Internet. Intrusion detection systems are used to protect IoT systems from the various anomalies and attacks at the network level. Intrusion Detection Systems can (...) be improved through machine learning techniques. Our work focuses on creating classification models that can feed an IDS using a dataset containing frames under attacks of an IoT system that uses the MQTT protocol. We have addressed two types of method for classifying the attacks, ensemble methods and deep learning models, more specifically recurrent networks with very satisfactory results. (shrink)

Classification One of the main topics of scientific research is classification. Classification is the operation of distributing objects into classes or groups—which are, in general, less numerous than them. It has a long history that has developed during four periods: Antiquity, where its lineaments may be found in the writings of Plato and Aristotle; … Continue reading Classification →.

First thoughts about classification inevitably turn to the simultaneously mundane and extraordinary ambition to capture the universe of all that there is and has been. This dream of the universal has two basic modes (and so the process begins!). First, I will follow the spirit of theos and logos as represented by the Platonic embrace of totality enshrined in Socrates’ scrupulous rejection of rhetorical dishonesty. Second, I will address the later part of the march to subjectivity as expressed by (...) the mechanics of atomism and Cartesian reduction. Following this move from theology to ontology, from in other words the post-synthetic to the post-analytic, I will connect with the sociological destruction of such pretensions to absolute classificatory veracity – a necessary pre-requisite for the engagement of reflexivity and classification to be found in the work of Georges Perec. (shrink)

This paper examines the ways in which social scientific discourse and classification interact with the objects of social scientific investigation. I examine this interaction in the context of the traditional philosophical project of demarcating the social sciences from the natural sciences. I begin by reviewing Ian Hacking’s work on interactive classification and argue that there are additional forms of interaction that must be treated.

In this influential work, first published in English in 1963, Durkheim and Mauss claim that the individual mind is capable of classification and they seek the origin of the ‘classificatory function’ in society. On the basis of an intensive examination of forms and principles of symbolic classification reported from the Australian aborigines, the Zuñi and traditional China, they try to establish a formal correspondence between social and symbolic classification. From this they argue that the mode of (...) class='Hi'>classification is determined by the form of society and that the notions of space, time, hierarchy, number, class and other such cognitive categories are products of society. Dr Needham’s introduction assesses the validity of Durkhiem and Mauss’s argument, traces its continued influence in various disciplines, and indicates its analytical value for future researches in social anthropology. (shrink)

The scientific study of emotion has been characterized by classification schemes that propose to 'carve nature at the joints.' This article examines several of these classifications, drawn from both the categorical and dimensional perspectives. Each classification is given credit for what it contributes to our understanding, but the dream of a single, all purpose taxonomy of emotional phenomena is called into question. Such hopes are often associated with the carving at the joints metaphor, which is here argued to (...) be harmful to scientific realism, and better rejected in favor of a pragmatic approach. Questioning the mere discovery theory of scientific progress, I argue that psychologists discover facts about their domain of study, but have to decide how to classify them. 2012 APA, all rights reserved). (shrink)

This paper explains the importance of classifying argumentation schemes, and outlines how schemes are being used in current research in artificial intelligence and computational linguistics on argument mining. It provides a survey of the literature on scheme classification. What are so far generally taken to represent a set of the most widely useful defeasible argumentation schemes are surveyed and explained systematically, including some that are difficult to classify. A new classification system covering these centrally important schemes is built.

This work has been selected by scholars as being culturally important and is part of the knowledge base of civilization as we know it. This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work. Scholars believe, and we concur, that this work is important enough to be (...) preserved, reproduced, and made generally available to the public. To ensure a quality reading experience, this work has been proofread and republished using a format that seamlessly blends the original graphical elements with text in an easy-to-read typeface. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant. (shrink)

Classification is an important goal in many branches of mathematics. The idea is to describe the members of some class of mathematical objects, up to isomorphism or other important equivalence, in terms of relatively simple invariants. Where this is impossible, it is useful to have concrete results saying so. In model theory and descriptive set theory, there is a large body of work showing that certain classes of mathematical structures admit classification while others do not. In the present (...) paper, we describe some recent work on classification in computable structure theory.Section 1 gives some background from model theory and descriptive set theory. From model theory, we give sample structure and non-structure theorems for classes that include structures of arbitrary cardinality. We also describe the notion of Scott rank, which is useful in the more restricted setting of countable structures. From descriptive set theory, we describe the basic Polish space of structures for a fixed countable language with fixed countable universe. We give sample structure and non-structure theorems based on the complexity of the isomorphism relation, and on Borel embeddings.Section 2 gives some background on computable structures. We describe three approaches to classification for these structures. The approaches are all equivalent. However, one approach, which involves calculating the complexity of the isomorphism relation, has turned out to be more productive than the others. Section 3 describes results on the isomorphism relation for a number of mathematically interesting classes—various kinds of groups and fields. In Section 4, we consider a setting similar to that in descriptive set theory. We describe an effective analogue of Borel embedding which allows us to make distinctions even among classes of finite structures. Section 5 gives results on computable structures of high Scott rank. Some of these results make use of computable embeddings. Finally, in Section 6, we mention some open problems and possible directions for future work. (shrink)