We offer a preliminary account of the information-based aspects of punctuation marks. We give our initial treatment within the Discourse Representation Theory and its segmented version. We hypothesize that this work will be useful in classifying the informational contributions of punctuation marks and bringing them to bear on the semantic characterization of written discourse.

The causal and simulation theories are often presented as very distinct views about declarative memory, their major difference lying on the causal condition. The causal theory states that remembering involves an accurate representation causally connected to an earlier experience. In the simulation theory, remembering involves an accurate representation generated by a reliable memory process. I investigate how to construe detailed versions of these theories that correctly classify memory errors as misremembering or confabulation. Neither causalists nor simulationists have paid attention to (...) memory-conjunction errors, which is unfortunate because both theories have problems with these cases. The source of the difficulty is the background assumption that an act of remembering has one target. I fix these theories for those cases. The resulting versions are closely related when implemented using tools of information theory, differing only on how memory transmits information about the past. The implementation provides us with insights about the distinction between confabulatory and non-confabulatory memory, where memory-conjunction errors have a privileged position. (shrink)

There are (at least) three approaches to quantifying information. The first, algorithmic information or Kolmogorov complexity, takes events as strings and, given a universal Turing machine, quantifies the information content of a string as the length of the shortest program producing it [1]. The second, Shannon information, takes events as belonging to ensembles and quantifies the information resulting from observing the given event in terms of the number of alternate events that have been ruled out (...) [2]. The third, statistical learning theory, has introduced measures of capacity that control (in part) the expected risk of classifiers [3]. These capacities quantify the expectations regarding future data that learning algorithms embed into classifiers. Solomonoff and Hutter have applied algorithmic information to prove remarkable results on universal induction. Shannon information provides the mathematical foundation for communication and coding theory. However, both approaches have shortcomings. Algorithmic information is not computable, severely limiting its practical usefulness. Shannon information refers to ensembles rather than actual events: it makes no sense to compute the Shannon information of a single string – or rather, there are many answers to this question depending on how a related ensemble is constructed. Although there are asymptotic results linking algorithmic and Shannon information, it is unsatisfying that there is such a large gap – a difference in kind – between the two measures. This note describes a new method of quantifying information, effective information, that links algorithmic information to Shannon information, and also links both to capacities arising in statistical learning theory [4, 5]. After introducing the measure, we show that it provides a non-universal analog of Kolmogorov complexity. We then apply it to derive basic capacities in statistical learning theory: empirical VC-entropy and empirical Rademacher complexity. A nice byproduct of our approach is an interpretation of the explanatory power of a learning algorithm in terms of the number of hypotheses it falsifies [6], counted in two different ways for the two capacities. We also discuss how effective information relates to information gain, Shannon and mutual information. (shrink)

I leave the work I’ve done to classify all UKLO questions below, with the latest appendices for historical record. From my recollection, this was the first complete system to classify all UKLO questions. Attempts at classifying UKLO questions before accounted for some questions but not others, leaving some questions unclassified. The classifications then were more labelling rather than a systemic approach that applied to all questions. As a result, this made it difficult for competitors and test development to find the (...) questions they were looking for by subject area, and to find related questions. There was a need to provide an organised and clean system to classify not just some but all the questions in order to establish fundamental classification data, basic statistics, and enhanced usability for test development and competitors. The system is provided below and was displayed on the website under technical information. I’ve decided to leave the system unedited with further commentary and general thoughts about mistakes made, analysis of the scope of UKLO questions, and future projections. Further improvements are being made to the classification system for a greater user experience, but so far the system has been a huge success and is fully working and operational. (shrink)

Abstract— In this study, a proposed faces recognition methodology based on the neural micro-classifier network. The proposed methodology uses simple well known feature extraction methodology. The feature extraction used is the discrete cosine transformation low frequencies coefficients. The micro-classifier network is a deterministic four layers neural network, the four layers are: input, micro-classifier, counter, and output. The network provide confidence factor, and proper generalization is guaranteed. Also, the network allows incremental learning, and more natural than others. The proposed face recognition (...) methodology was tested using the standard ORL data set. The experimental results of the methodology showed comparative performance. (shrink)

We undeniably live in an information age—as, indeed, did those who lived before us. After all, as the cultural historian Robert Darnton pointed out: ‘every age was an age of information, each in its own way’ (Darnton 2000: 1). Darnton was referring to the news media, but his insight surely also applies to the sciences. The practices of acquiring, storing, labeling, organizing, retrieving, mobilizing, and integrating data about the natural world has always been an enabling aspect of scientific (...) work. Natural history and its descendant discipline of biological taxonomy are prime examples of sciences dedicated to creating and managing systems of ordering data. In some sense, the idea of biological taxonomy as an information science is commonplace. Perhaps it is because of its self-evidence that the information science perspective on taxonomy has not been a major theme in the history and philosophy of science. The botanist Vernon Heywood once pointed out that historians of biology, in their ‘preoccupation with the development of the sciences of botany and zoology… [have] diverted attention from the role of taxonomy as an information science’ (Heywood 1985: 11). More specifically, he argued that historians had failed to appreciate how principles and practices that can be traced to Linnaeus constituted ‘a change in the nature of taxonomy from a local or limited folk communication system and later a codified folk taxonomy to a formal system of information science [that] marked a watershed in the history of biology’ (ibid.). A similar observation could be made about twentieth-century philosophy of biology, which mostly skipped over practical and epistemic questions about information management in taxonomy. The taxonomic themes that featured in the emerging philosophy of biology literature in the second half of the twentieth century were predominantly metaphysical in orientation. This is illustrated by what has become known as the ‘essentialism story’: an account about the essentialist nature of pre- Darwinian taxonomy that used to be accepted by many historians and philosophers, and which stimulated efforts to document and interpret shifts in the metaphysical understanding of species and (natural) classification (Richards 2010; Winsor 2003; Wilkins 2009). Although contemporary debates in the philosophy of taxonomy have moved on, much discussion continues to focus on conceptual and metaphysical issues surrounding the nature of species and the principles of classification. Discussions centring on whether species are individuals, classes, or kinds have sprung up as predictably as perennials. Raucous debates have arisen even with the aim of accommodating the diversity of views: is monism, pluralism, or eliminativism about the species category the best position to take? In addition to these, our disciplines continue to interrogate what is the nature of these different approaches to classification: are they representational or inferential roles of different approaches to classification (evolutionary taxonomy, phenetics, phylogenetic systematics)? While there is still much to learn from these discussions—in which we both actively participate—our aim with this topical collection has been to seek different entrypoints and address underexposed themes in the history and philosophy of taxonomy. We believe that approaching taxonomy as an information science prompts new questions and can open up new philosophical vistas worth exploring. A twenty-first century information science turn in the history and philosophy of taxonomy is already underway. In scientific practice and in daily life it is hard to escape the imaginaries of Big Data and the constant threats of being ‘flooded with data’. In the life sciences, these developments are often associated with the socalled bioinformatics crisis that can hopefully be contained by a new, interdisciplinary breed of bioinformaticians. These new concepts, narratives, and developments surrounding the centrality of data and information systems in the biological and biomedical sciences have raised important philosophical questions about their challenges and implications. But historical perspectives are just as necessary to judge what makes our information age different from those that preceded us. Indeed, as the British zoologist Charles Godfray has often pointed out, the piles of data that are being generated in contemporary systematic biology have led to a second bioinformatics crisis, the first being the one that confronted Linnaeus in the mid-18th century (Godfray 2007). Although our aim is to clear a path for new discussions of taxonomy from an information science-informed point of view, we continue where others in the history, philosophy, and sociology of science have already trod. We believe that an appreciation of biological taxonomy as an information science raises many questions about the philosophical, theoretical, material, and practical aspects of the use and revision of biological nomenclatures in different local and global communities of scientists and citizen scientists. In particular, conceiving of taxonomy as an information science directs attention to the temporalities of managing an accumulating data about classified entities that are themselves subject to revision, to the means by which revision is accomplished, and to the semantic, material, and collaborative contexts that mediate the execution of revisions. (shrink)

Let f(1)=2, f(2)=4, and let f(n+1)=f(n)! for every integer n≥2. Edmund Landau's conjecture states that the set P(n^2+1) of primes of the form n^2+1 is infinite. Landau's conjecture implies the following unproven statement Φ: card(P(n^2+1))<ω ⇒ P(n^2+1)⊆[2,f(7)]. Let B denote the system of equations: {x_j!=x_k: i,k∈{1,...,9}}∪{x_i⋅x_j=x_k: i,j,k∈{1,...,9}}. The system of equations {x_1!=x_1, x_1 \cdot x_1=x_2, x_2!=x_3, x_3!=x_4, x_4!=x_5, x_5!=x_6, x_6!=x_7, x_7!=x_8, x_8!=x_9} has exactly two solutions in positive integers x_1,...,x_9, namely (1,...,1) and (f(1),...,f(9)). No known system S⊆B with a finite (...) number of solutions in positive integers x_1,...,x_9 has a solution (x_1,...,x_9)∈(N\{0})^9 satisfying max(x_1,...,x_9)>f(9). For every known system S⊆B, if the finiteness/infiniteness of the set {(x_1,...,x_9)∈(N\{0})^9: (x_1,...,x_9) solves S} is unknown, then the statement ∃ x_1,...,x_9∈N\{0} ((x_1,...,x_9) solves S)∧(max(x_1,...,x_9)>f(9)) remains unproven. Let Λ denote the statement: if the system of equations {x_2!=x_3, x_3!=x_4, x_5!=x_6, x_8!=x_9, x_1 \cdot x_1=x_2, x_3 \cdot x_5=x_6, x_4 \cdot x_8=x_9, x_5 \cdot x_7=x_8} has at most finitely many solutions in positive integers x_1,...,x_9, then each such solution (x_1,...,x_9) satisfies x_1,...,x_9≤f(9). The statement Λ is equivalent to the statement Φ. It heuristically justifies the statement Φ . This justification does not yield the finiteness/infiniteness of P(n^2+1). We present a new heuristic argument for the infiniteness of P(n^2+1), which is not based on the statement Φ. Algorithms always terminate. We explain the distinction between existing algorithms (i.e. algorithms whose existence is provable in ZFC) and known algorithms (i.e. algorithms whose definition is constructive and currently known). Assuming that the infiniteness of a set X⊆N is false or unproven, we define which elements of X are classified as known. No known set X⊆N satisfies Conditions (1)-(4) and is widely known in number theory or naturally defined, where this term has only informal meaning. *** (1) A known algorithm with no input returns an integer n satisfying card(X)<ω ⇒ X⊆(-∞,n]. (2) A known algorithm for every k∈N decides whether or not k∈X. (3) No known algorithm with no input returns the logical value of the statement card(X)=ω. (4) There are many elements of X and it is conjectured, though so far unproven, that X is infinite. (5) X is naturally defined. The infiniteness of X is false or unproven. X has the simplest definition among known sets Y⊆N with the same set of known elements. *** Conditions (2)-(5) hold for X=P(n^2+1). The statement Φ implies Condition (1) for X=P(n^2+1). The set X={n∈N: the interval [-1,n] contains more than 29.5+\frac{11!}{3n+1}⋅sin(n) primes of the form k!+1} satisfies Conditions (1)-(5) except the requirement that X is naturally defined. 501893∈X. Condition (1) holds with n=501893. card(X∩[0,501893])=159827. X∩[501894,∞)= {n∈N: the interval [-1,n] contains at least 30 primes of the form k!+1}. We present a table that shows satisfiable conjunctions of the form #(Condition 1) ∧ (Condition 2) ∧ #(Condition 3) ∧ (Condition 4) ∧ #(Condition 5), where # denotes the negation ¬ or the absence of any symbol. No set X⊆N will satisfy Conditions (1)-(4) forever, if for every algorithm with no input, at some future day, a computer will be able to execute this algorithm in 1 second or less. The physical limits of computation disprove this assumption. (shrink)

What is wrong with government whistleblowing and when can it be justified? In my view, ‘government whistleblowing’, i.e., the unauthorized acquisition and disclosure of classified information about the state or government, is a form of ‘political vigilantism’, which involves transgressing the boundaries around state secrets, for the purpose of challenging the allocation or use of power. It may nonetheless be justified when it is suitably constrained and exposes some information that the public ought to know and deliberate (...) about. Government whistleblowing should then be viewed, along the lines of civil disobedience, as a collective cognition- and legitimacy-enhancing device. (shrink)

Vietnamese scientists on the list of "100.000 influential scientists" this year increased sharply in number and rank. -/- The ranking was selected by a group of scientists led by Professor John PA Ioannidis and colleagues from Stanford University (USA) on the Scopus database and published by Elsevier Publishing House.

We information-theoretically reformulate two measures of capacity from statistical learning theory: empirical VC-entropy and empirical Rademacher complexity. We show these capacity measures count the number of hypotheses about a dataset that a learning algorithm falsifies when it finds the classifier in its repertoire minimizing empirical risk. It then follows from that the future performance of predictors on unseen data is controlled in part by how many hypotheses the learner falsifies. As a corollary we show that empirical VC-entropy quantifies the (...) message length of the true hypothesis in the optimal code of a particular probability distribution, the so-called actual repertoire. (shrink)

On April 20, 1999, Eric Harris and Dylan Klebold shot and killed fifteen people at their high school in Columbine, Colorado. National media dubbed the event a “school shooting.” The term grimly expanded over the next several years to include similar events at army bases, movie theaters, churches, and nightclubs. Today, we commonly use the categories “mass shooter” and “mass shooting” to organize and classify information about gun violence. I will argue that neither category is an effective tool for (...) reducing gun violence and use empirical data to show how these categories perpetuate a moral panic that harms already vulnerable demographics. I conclude that we should instead favor a narrower description of individuals and events, (e.g., “X shot Y people at Z”) because we can talk about all of the relevant cases without contributing the undue harms. (shrink)

Geographic Information Science (GIS) is an interdisciplinary science aiming to detect and visually represent patterns in spatial data. GIS is used by businesses to determine where to open new stores and by conservation biologists to identify field study locations with relatively little anthropogenic influence. Products of GIS include topographic and thematic maps of the Earth’s surface, climate maps, and spatially referenced demographic graphs and charts. In addition to its social, political, and economic importance, GIS is of intrinsic philosophical interest (...) due to its methodological richness and because it is an instructive analogue to other sciences. This chapter works towards a philosophy of GIS and cartography, or PGISC. In particular, it examines practices of classifying geographic space, objects, and relations. By focusing on the use of natural kinds in data modeling and map generalization practices, I show how the making and using of kinds is contextual, fallible, plural, and purposive. (shrink)

In this paper I will use sex by deception as a case study for highlighting some of the most tricky concepts around sexuality and moral psychology, including rape, consensual sex, sexual rights, sexual autonomy, sexual individuality, and disrespectful sex. I begin with a discussion of morally wrong sex as rooted in the breach of five sexual liberty rights that are derived from our fundamental human liberty rights: sexual self-possession, sexual autonomy, sexual individuality, sexual dignity and sexual privacy. I then argue (...) (against the standard interpretation) that experimental findings in moral psychology show that the principle of respect for persons—a principle that grounds our human liberty rights—drives our intuitive moral judgments. In light of this discussion, I examine a puzzle about sex by deception—a puzzle which at first may seem to compel us to define 'rape' strictly in terms of force rather than sexual autonomy. I proceed by presenting an argument against the view that, as a rule, sex by deception undermines consent—a position held by prominent thinkers such as Philippe Patry (2001), Onora O’Neill (2003), Rubenfeld (2012), Tom Dougherty (2013a, 2013b), Joyce M. Short (2013), and Danielle Bromwich and Joseph Millum (2013, 2018). As we will see, sex following deception to increase your chances does not always constitute rape. Lying about your age, education, job, family background, marital status, or interest in a relationship, for example, does not make your sex partner incapable of consenting, which is to say that sex by deception need not be rape. I even go so far as to say that sex with another person that is facilitated by withholding information about having a venereal disease shouldn't be classified as rape. Although sex by deception doesn't compromise consent, it nonetheless violates the principle of respect for persons, not by vitiating sexual autonomy and compromising consent, but by failing to respect other sexual rights, such as our rights to sexual dignity, individuality, and privacy. (shrink)

This paper explores the hypothesis that proper names serve as anchors identifying the individuals in the possible or real world. This hypothesis is tested on Old Icelandic narratives. A prominent feature of Old Icelandic sagas is that the narrative matter is not quite new. A Saga is reliable iff it refers to the events relevant for its audience and accepted as true by the whole community. I argue that proper names must be regarded as references to the background knowledge of (...) the medieval audience. I follow two contemporary Sagas based on the fresh events and show that proper names in a Saga mind were arranged in form of a database, each type of a personal designation having its charachteristic text-building profile. The form of the name and its frequency in the Saga are linked with the rank of the character. The high number of people mentioned in the Sagas is explained by the fact that the Sagas aimed at describing the real world, where the names of the individuals and the events they were involved cross-identified each other. Every character had its rigid identifiers. The total amount of propria is always higher than the number of active figures. I classify the Saga characters into five ranks and discuss their information-structural profiles. (shrink)

Since the outbreak of the Coronavirus disease 2019 (Covid-19), tremendous efforts have been made by scientists, health professionals, business people, politicians, and laypeople around the world. Covid-19 vaccines are one of the most crucial innovations that help fight against the virus. This paper attempts to revisit the Covid-19 vaccines production process by employing the serendipity-mindsponge-3D creativity management theory. Vaccine production can be considered an information process and classified into three main stages. The first stage involved the processes of (...) absorbing information (e.g., digital data and open science) and rejecting unhelpful information (e.g., misinformation and fake news) for effectively acquiring useful insights. Useful insights were later employed by experts, enterprises, governments, and international organizations through interdisciplinary coordinated efforts for developing vaccines within a short period. Finally, the appearance of multiple types of vaccines enabled more strategic options for vaccine distribution and administration. Findings from this vaccine creativity management process could be used as critical lessons for further improvements of vaccination programs. (shrink)

Despite its centrality in the philosophy of cognitive science, there has been little prior philosophical work engaging with the notion of representation in contemporary NLP practice. This paper attempts to fill that lacuna: drawing on ideas from cognitive science, I introduce a framework for evaluating the representational claims made about components of neural NLP models, proposing three criteria with which to evaluate whether a component of a model represents a property and operationalising these criteria using probing classifiers, a popular analysis (...) technique in NLP (and deep learning more broadly). The project of operationalising a philosophically-informed notion of representation should be of interest to both philosophers of science and NLP practitioners. It affords philosophers a novel testing-ground for claims about the nature of representation, and helps NLPers organise the large literature on probing experiments, suggesting novel avenues for empirical research. (shrink)

Memory technologies are cultural artifacts that scaffold, transform, and are interwoven with human biological memory systems. The goal of this article is to provide a systematic and integrative survey of their philosophical dimensions, including their metaphysical, epistemological and ethical dimensions, drawing together debates across the humanities, cognitive sciences, and social sciences. Metaphysical dimensions of memory technologies include their function, the nature of their informational properties, ways of classifying them, and their ontological status. Epistemological dimensions include the truth-conduciveness of external memory, (...) the conditions under which external memory counts as knowledge, and the metacognitive monitoring of external memory processes. And lastly, ethical and normative dimensions include the desirability of the effects memory technologies have on biological memory, their effects on self and culture, and their moral status. Whilst the focus in the article is largely philosophical and conceptual, empirical issues such as the way we interact with memory technologies in various contexts are also discussed. We thus take a naturalistic approach in which philosophical and empirical concepts and approaches are seen as continuous. (shrink)

Bayesian classifiers perform well when each of the features is completely independent of the other which is not always valid in real world applications. The aim of this study is to implement and compare the performances of each variant of the Bayesian classifier (Multinomial, Bernoulli, and Gaussian) on anomaly detection in network intrusion, and to investigate whether there is any association between each variant’s assumption and their performance. Our investigation showed that each variant of the Bayesian algorithm blindly follows its (...) assumption regardless of feature property, and that the assumption is the single most important factor that influences their accuracy. Experimental results show that Bernoulli has accuracy of 69.9% test (71% train), Multinomial has accuracy of 31.2% test (31.2% train), while Gaussian has an accuracy of 81.69% test (82.84% train). Going deeper, we investigated and found that each Naïve Bayes variants performances and accuracy is largely due to each classifier assumption, Gaussian classifier performed best on anomaly detection due to its assumption that features follow normal distributions which are continuous, while multinomial classifier have a dismal performance as it simply assumes discreet and multinomial distribution. (shrink)

K denotes both the knowledge predicate satisfied by every currently known theorem and the finite set of all currently known theorems. The set K is time-dependent, publicly available, and contains theorems both from formal and constructive mathematics. Any theorem of any mathematician from past or present forever belongs to K. Mathematical statements with known constructive proofs exist in K separately and form the set K_c⊆K. We assume that mathematical sets are atemporal entities. They exist formally in ZFC theory although their (...) properties can be time-dependent (when they depend on K) or informal. The true statement "K is non-empty" is outside K forever because K is not a formal set. Paul Cohen proved in 1963 that the equality 2^{\aleph_0}=\aleph_1 is independent of ZFC. Before 1963, the statement "There is a known constructively defined integer n⩾1 such that 2^{\aleph_0}=\aleph_n" was outside K. Since 1963, this statement is outside K forever. The true statement "There exists a set X⊆{1,...,49} such that card(X)=6 and X never occurred as the winning six numbers in the Polish Lotto lottery" refers to the current non-mathematical knowledge and is outside K forever. In Martin-Löf's terminology, every currently known theorem is actually true whereas every theorem (known or unknown) is potentially true. Actual truth is knowledge dependent and tensed. Potential truth is knowledge independent and tenseless. Algorithms always terminate. We explain the distinction between algorithms whose existence is provable in ZFC and constructively defined algorithms which are currently known. By using this distinction, we obtain non-trivially true statements on decidable sets X⊆N that belong to constructive and informal mathematics and refer to the current mathematical knowledge on X. For every such statement, its truth concerning the current mathematical knowledge is implied by a true statement of the form: (the conjunction of i conditions of the form α∈K)∧(the conjunction of j conditions of the form β∉K)∧(the conjunction of k conditions of the form γ∈K_c)∧(the conjunction of l conditions of the form δ∉K_c), where i,j,k,l∈N and α,β,γ,δ are mathematical statements. In constructive mathematics and the traditional Brouwerian intuitionism, the truth of a mathematical statement means that we know a constructive proof. Therefore, the truth of a mathematical statement depends on time, where the statement is formally stated in the classical mathematics without the predicate K. In this article, mathematical statements on decidable sets X⊆N refer to time because they refer to the current mathematical knowledge on X. They cannot be formally stated in the classical mathematics without the predicate K and their logical values may change in time. For a set X⊆N whose infiniteness is false or unproven, we define which elements of X are classified as known. No known set X⊆N satisfies Conditions (1)-(4) and is widely known in number theory or naturally defined, where this term has only informal meaning. (1) A known algorithm with no input returns an integer n satisfying card(X)<ω ⇒ X⊆(-∞,n]. (2) A known algorithm for every k∈N decides whether or not k∈X. (3) For every known algorithm A with no input, the statement "A returns the logical value of the statement card(X)=ω" is outside K. (4) There are many elements of X and it is conjectured, though so far unproven, that X is infinite. (5) X is naturally defined. The infiniteness of X is false or unproven. X has the simplest definition among known sets Y⊆N with the same set of known elements. No set X⊆N will satisfy Conditions (1)-(4) forever, if for every algorithm with no input, at some future day, a computer will be able to execute this algorithm in 1 second or less. The physical limits of computation disprove the assumption of the above statement. We prove that the set X={n∈N: the interval [-1,n] contains more than 29.5+(11!/(3n+1))∙sin(n) primes of the form k!+1} satisfies Conditions (1)-(5) except the requirement that X is naturally defined. We present a table that shows satisfiable conjunctions of the form #(Condition1)∧(Condition 2)∧#(Condition 3)∧(Condition 4)∧#(Condition 5), where # denotes the negation ¬ or the absence of any symbol. We prove that there exists a naturally defined set C⊆N which satisfies the following conditions (6)-(11). (6) A known and simple algorithm for every k∈N decides whether or not k∈C. (7) For every known algorithm A with no input, the statement "A returns the logical value of the statement card(C)=ω" is outside K. (8) For every known algorithm A with no input, the statement "A returns the logical value of the statement card(N\C)=ω" is outside K. (9) It is conjectured, though so far unproven, that C is infinite. (10) For every known algorithm A with no input, the statement "A returns an integer n satisfying card(C)<ω ⇒ C⊆(-∞,n]" is outside K. (11) For every known algorithm A with no input, the statement "A returns an integer m satisfying card(N\C)<ω ⇒ N\C⊆(-∞,m]" is outside K. The set C={k∈N: 2^{2^k}+1 is composite} is naturally defined and satisfies conditions (6)-(11). (shrink)

A large part of the controversy surrounding the publication of DSM-5 stems from the possibility of replacing the purely descriptive approach to classification favored by the DSM since 1980. This paper examines the question of how mental disorders should be classified, focusing on the issue of whether the DSM should adopt a purely descriptive or theoretical approach. I argue that the DSM should replace its purely descriptive approach with a theoretical approach that integrates causal information into the DSM’s (...) descriptive diagnostic categories. The paper proceeds in three sections. In the first section, I examine the goals (viz., guiding treatment, facilitating research, and improving communication) associated with the DSM’s purely descriptive approach. In the second section, I suggest that the DSM’s purely descriptive approach is best suited for improving communication among mental health professionals; however, theoretical approaches would be superior for purposes of treatment and research. In the third section, I outline steps required to move the DSM towards a hybrid system of classification that can accommodate the benefits of descriptive and theoretical approaches, and I discuss how the DSM’s descriptive categories could be revised to incorporate theoretical information regarding the causes of disorders. I argue that the DSM should reconceive of its goals more narrowly such that it functions primarily as an epistemic hub that mediates among various contexts of use in which definitions of mental disorders appear. My analysis emphasizes the importance of pluralism as a methodological means for avoiding theoretical dogmatism and ensuring that the DSM is a reflexive and self-correcting manual. (shrink)

It is widely understood that protein functions can be exhaustively described in terms of no single parameter, whether this be amino acid sequence or the three-dimensional structure of the underlying protein molecule. This means that a number of different attributes must be used to create an ontology of protein functions. Certainly much of the required information is already stored in databases such as Swiss-Prot, Protein Data Bank, SCOP and MIPS. But the latter have been developed for different purposes and (...) the separate data-structures which they employ are not conducive to the needed data integration. When we attempt to classify the entities in the domain of proteins, we find ourselves faced with a number of cross-cutting principles of classification. Our question here is: how can we bring together these separate taxonomies in order to describe protein functions? Our proposed answer is: via a careful top-level ontological analysis of the relevant principles of classification, combined with a new framework for the simultaneous manipulation of classifications constructed for different purposes. (shrink)

We have a variety of different ways of dividing up, classifying, mapping, sorting and listing the objects in reality. The theory of granular partitions presented here seeks to provide a general and unified basis for understanding such phenomena in formal terms that is more realistic than existing alternatives. Our theory has two orthogonal parts: the first is a theory of classification; it provides an account of partitions as cells and subcells; the second is a theory of reference or intentionality; it (...) provides an account of how cells and subcells relate to objects in reality. We define a notion of well-formedness for partitions, and we give an account of what it means for a partition to project onto objects in reality. We continue by classifying partitions along three axes: (a) in terms of the degree of correspondence between partition cells and objects in reality; (b) in terms of the degree to which a partition represents the mereological structure of the domain it is projected onto; and (c) in terms of the degree of completeness with which a partition represents this domain. (shrink)

The aim of this study is to justify the belief that there are biological normative mechanisms that fulfill non-trivial causal roles in the explanations (as formulated by researchers) of actions and behaviors present in specific systems. One example of such mechanisms is the predictive mechanisms described and explained by predictive processing (hereinafter PP), which (1) guide actions and (2) shape causal transitions between states that have specific content and fulfillment conditions (e.g. mental states). Therefore, I am guided by a specific (...) theoretical goal associated with the need to indicate those conditions that should be met by the non-trivial theory of normative mechanisms and the specific models proposed by PP supporters. In this work, I use classical philosophical methods, such as conceptual analysis and critical reflection. I also analyze selected studies in the field of cognitive science, cognitive psychology, neurology, information theory and biology in terms of the methodology, argumentation and language used, in accordance with their theoretical importance for the issues discussed in this study. In this sense, the research presented here is interdisciplinary. My research framework is informed by the mechanistic model of explanation, which defines the necessary and sufficient conditions for explaining a given phenomenon. The research methods I chose are therefore related to the problems that I intend to solve. In the introductory chapter, “The concept of predictive processing”, I discuss the nature of PP as well as its main assumptions and theses. I also highlight the key concepts and distinctions for this research framework. Many authors argue that PP is a contemporary version of Kantianism and is exposed to objections similar to those made against the approach of Immanuel Kant. I discuss this thesis and show that it is only in a very general sense that the PP framework is neo-Kantian. Here we are not dealing with transcendental deduction nor with the application of transcendental arguments. I argue that PP is based on reverse engineering and abduction inferences. In the second part of this chapter, I respond to the objection formulated by Dan Zahavi, who directly accuses this research framework of anti-realistic consequences. I demonstrate that the position of internalism, present in the so-called conservative PP, does not imply anti-realism, and that, due to the explanatory role played in it by structural representations directed at real patterns, it is justified to claim that PP is realistic. In this way, I show that PP is a non-trivial research framework, having its subject, specific methods and its own epistemic status. Finally, I discuss positions classified as the socalled radical PP. In the chapter “Predictive processing as a Bayesian explanatory model” I justify the thesis according to which PP offers Bayesian modeling. Many researchers claim that the brain is an implemented statistical probabilistic network that is an approximation of the Bayesian 7 rule. In practice, this means that all cognitive processes are to apply Bayes' rule and can be described in terms of probability distributions. Such a solution arouses objections among many researchers and is the subject of wide criticism. The purpose of this chapter is to justify the thesis that Bayesian PP is a non-trivial research framework. For this purpose, I argue that it explains certain phenomena not only at the computational level described by David Marr, but also at the level of algorithms and implementation. Later in this chapter I demonstrate that PP is normative modeling. Proponents of the use of Bayesian models in psychology or decision theory argue that they are normative because they allow the formulation of formal rules of action that show what needs to be done to make a given action optimal. Critics of this approach emphasize that such thinking about the normativity of Bayesian modeling is unjustified and that science should shift from prescriptive to descriptive positions. In a polemic with Shira Elqayam and Jonathan Evans (2011), I show that the division they propose into prescriptivism and Bayesian descriptivism is apparent, because, as I argue, there are two forms of prescriptivism, i.e. the weak and the strong. I argue that the weak version is epistemic and can lead to anti-realism, while the strong version is ontic and allows one to justify realism in relation to Bayesian models. I argue that a weak version of prescriptivism is valid for PP. It allows us to adopt anti-realism in relation to PP. In practice, this means that you can explain phenomena using Bayes' rule. This does not, however, imply that they are Bayesian in nature. However, the full justification of realism in relation to the Bayesian PP presupposes the adoption of strong prescriptivism. This position assumes that phenomena are explained by Bayesian rule because they are Bayesian as such. If they are Bayesian in nature, then they should be explained using Bayesian modeling. This thesis will be substantiated in the chapters “Normative functions and mechanisms in the context of predictive processing” and “Normative mechanisms and actions in predictive processing”. In the chapter “The Free Energy Principle in predictive processing”, I discuss the Free Energy Principle (hereinafter FEP) formulated by Karl Friston and some of its implications. According to this principle, all biological systems (defined in terms of Markov blankets) minimize the free energy of their internal states in order to maintain homeostasis. Some researchers believe that PP is a special case of applying this principle to cognition, and that predictive mechanisms are homeostatic mechanisms that minimize free energy. The discussion of FEP is important due to the fact that some authors consider it to be important for explanatory purposes and normative. If this is the case, then FEP turns out to be crucial in explaining normative predictive mechanisms and, in general, any normative biological mechanisms. To define the explanatory possibilities of this principle, I refer to the discussion of its supporters on the issue they define as the problem of continuity and discontinuity between life and mind. A critical analysis of this discussion and the additional arguments I have formulated have allowed me to revise the explanatory ambitions of FEP. I also reject the belief that this principle is necessary to explain the nature of predictive mechanisms. I argue that the principle formulated and defended by Friston is an important research heuristic for PP analysis. 8 In the chapter “Normative functions and mechanisms in predictive processing”, I start my analyzes by formulating an answer to the question about the normative nature of homeostatic mechanisms. I demonstrate that predictive mechanisms are not homeostatic. I defend the view that a full explanation of normative mechanisms presupposes an explanation of normative functions. I discuss the most important proposals for understanding the normativity of a function, both from a systemic and teleosemantic perspective. I conclude that the non-trivial concept of a function must meet two requirements which I define as explanatory and normative. I show that none of the theories I have invoked satisfactorily meets both of these requirements. Instead, I propose a model of normativity based on Bickhard's account, but supplemented by a mechanistic perspective. I argue that a function is normative when: (1) it allows one to explain the dysfunction of a given mechanism; (2) it contributes to the maintenance of the organism's stability by shaping and limiting possible relations, processes and behaviors of a given system; and when (3) (according to the representational and predictive functions) it enables explaining the attribution of logical values of certain representations / predictions. In such an approach, a mechanism is normative when it performs certain normative functions and when it is constitutive for a specific action or behavior, despite the fact that for some reason it cannot realize it either currently or in the long-term. Such an understanding of the normativity of mechanisms presupposes the acceptance of the epistemic hypothesis. I argue that this hypothesis is not cognitively satisfactory, and therefore the ontic hypothesis should be justified, which is directly related to adopting the position of ontic prescriptivism. For this reason, referring to the mechanistic theory of scientific explanations, I formulate an ontical interpretation of the concept of a normative mechanism. According to this approach, a mechanism or a function is normative when they perform such and such causal roles in explaining certain actions and behaviors. With regard to the normative properties of predictive mechanisms and functions, this means that they are the causes of specific actions an organism carries out in the environment. In this way, I justify the necessity of accepting the ontic hypothesis and rejecting the epistemic hypothesis. The fifth chapter, “Normative mechanisms and actions in predictive processing”, is devoted to the dark room problem and the related exploration-exploitation trade-off. A dark room is the state that an agent could be in if it minimized the sum of all potential prediction errors. I demonstrate that, in accordance with the basic assumption of PP about the need for continuous and long-term minimization of prediction errors, such a state should be desirable for the agent. Is it really so? Many authors believe it is not. I argue that the test of the value of PP is the possibility of a non-trivial solution of this problem, which can be reduced to the choice between active and uncertainty-increasing exploration and safe and easily predictable exploitation. I show that the solution proposed by PP supporters present in the literature does not enable a fully satisfactory explanation of this dilemma. Then I defend the position according to which the full explanation of the normative mechanisms, and, subsequently, the solution to the dilemma of exploration and exploitation, involves reference to the existence of constraints present in the environment. The constraints 9 include elements of the environment that make a given mechanism not only causal but also normative. They are therefore key to explaining the predictive mechanisms. They do not only play the role of the context in which the mechanism is implemented, but, above all, are its constitutive component. I argue that the full explanation of the role of constraints in normative predictive mechanisms presupposes the integration of individual models of specific cognitive phenomena, because only the mechanistic integration of PP with other models allows for a non-trivial explanation of the nature of normative predictive mechanisms that would have a strong explanatory value. The explanatory monism present in many approaches to PP makes it impossible to solve the problem of the dark room. Later in this chapter, I argue that the Bayesian PP is normative not because it enables the formulation of such and such rules of action, but because the predictive mechanisms themselves are normative. They are normative because they condition the choice of such and such actions by agents. In this way, I justify the hypothesis that normative mechanisms make it possible to explain the phenomenon of agent motivation, which is crucial for solving the dark room problem. In the last part of the chapter, I formulate the hypothesis of distributed normativity, which assumes that the normative nature of certain mechanisms, functions or objects is determined by the relations into which these mechanisms, functions or objects enter. This means that what is normative (in the primary sense) is the relational structure that constitutes the normativity of specific items included in it. I suggest that this hypothesis opens up many areas of research and makes it possible to rethink many problems. In the “Conclusion”, I summarize the results of my research and indicate further research perspectives. (shrink)

The rediscovery of the silver-backed chevrotain, an endemic species to Vietnam, in 2019, after almost 30 years of being lost to science, is a remarkable outcome for the global conservation agenda. However, along with the happiness, there is a tremendous concern for the conservation of the species as eating wildmeat, including chevrotain, is deeply rooted in the socio-cultural values of Vietnamese. Meanwhile, conservation plans face multiple obstacles since the species has not been listed in the list of endangered, precious, and (...) rare wildlife prioritized for protection and is still classified by the IUCN as lacking data. Given the limited effectiveness of conservation measures, this essay discusses the determining roles of local actions, community cooperation, and humanistic values oriented toward eco-surplus culture in addressing the global biodiversity conservation agenda, specifically the conservation of the silver-backed chevrotain. Local actions and community cooperation for conservation can be actualized to achieve conservation goals through citizen and community sciences, integration of modern technologies (e.g., Internet, crowdfunding platforms, social media, AI, etc.), and the bonding capability of humanistic values that prioritize environmental healing. Communicating conservation information to the community, especially the children, has to stimulate their thinking and imagination about nature, develop their curiosity and desire to protect wildlife, and eventually build eco-surplus core values in their mindsets. To successfully awaken the humanistic values within the community and incorporate them into conservation endeavors, the conservation message with the name “mouse-deer”, “chevrotain”, or scientific name (Tragulus versicolor) is largely insufficient as they show an unfamiliar feeling. Therefore, we suggest calling the mouse-deer “cheo cheo”, a local name that can create familiarity and closeness, awaken the environmental conscience and humanistic values, and stimulate thinking and imagination. All these factors are essential for conservationists, scientists, and the government to support the community in building the eco-surplus culture. (shrink)

Brain-related diseases are among the most difficult diseases due to their sensitivity, the difficulty of performing operations, and their high costs. In contrast, the operation is not necessary to succeed, as the results of the operation may be unsuccessful. One of the most common diseases that affect the brain is Alzheimer’s disease, which affects adults, a disease that leads to memory loss and forgetting information in varying degrees. According to the condition of each patient. For these reasons, it is (...) important to classify memory loss and to know the patient at what level and his assessment of Alzheimer's disease through CT scans of the brain. In this thesis, we review ways and techniques to use deep learning classification to classifying the Alzheimer's Disease The proposed method used to improve patient care, reduce costs, and allow fast and reliable analysis in large studies. The model will be designed using Python language for implementing the system, which is very useful for doctors, classifying the Alzheimer's Disease, was used. The model used 70% from image for training and 30% from image for validation, our trained model achieved an accuracy of 100% on a held-out test set. (shrink)

Analyzing geometric properties of high-dimensional loss functions, such as local curvature and the existence of other optima around a certain point in loss space, can help provide a better understanding of the interplay between neural network structure, implementation attributes, and learning performance. In this work, we combine concepts from high-dimensional probability and differential geometry to study how curvature properties in lower-dimensional loss representations depend on those in the original loss space. We show that saddle points in the original space are (...) rarely correctly identified as such in expected lower-dimensional representations if random projections are used. The principal curvature in the expected lower-dimensional representation is proportional to the mean curvature in the original loss space. Hence, the mean curvature in the original loss space determines if saddle points appear, on average, as either minima, maxima, or almost flat regions. We use the connection between expected curvature in random projections and mean curvature in the original space (i.e., the normalized Hessian trace) to compute Hutchinson-type trace estimates without calculating Hessian-vector products as in the original Hutchinson method. Because random projections are not suitable to correctly identify saddle information, we propose to study projections along dominant Hessian directions that are associated with the largest and smallest principal curvatures. We connect our findings to the ongoing debate on loss landscape flatness and generalizability. Finally, for different common image classifiers and a function approximator, we show and compare random and Hessian projections of loss landscapes with up to about 7×10^6 parameters. (shrink)

There are at least twelve major virtues of good theories: evidential accuracy, causal adequacy, explanatory depth, internal consistency, internal coherence, universal coherence, beauty, simplicity, unification, durability, fruitfulness, and applicability. These virtues are best classified into four classes: evidential, coherential, aesthetic, and diachronic. Each virtue class contains at least three virtues that sequentially follow a repeating pattern of progressive disclosure and expansion. Systematizing the theoretical virtues in this manner clarifies each virtue and suggests how they might have a coordinated and (...) cumulative role in theory formation and evaluation across the disciplines—with allowance for discipline specific modification. An informal and flexible logic of theory choice is in the making here. Evidential accuracy, according to my systematization, is not a largely isolated trait of good theories, as some have made it out to be. Rather, it bears multifaceted relationships, constituting significant epistemic entanglements, with other theoretical virtues. (shrink)

Abstract: This research employs a Random Forest classification model to predict and assess obesity and cardiovascular disease (CVD) risk based on a comprehensive dataset collected from individuals in Mexico, Peru, and Colombia. The dataset comprises 17 attributes, including information on eating habits, physical condition, gender, age, height, and weight. The study focuses on classifying individuals into different health risk categories using machine learning algorithms. Our Random Forest model achieved remarkable performance with an accuracy, F1-score, recall, and precision all reaching (...) 97.23%. The model's success is attributed to its ability to effectively leverage attributes related to eating habits, physical condition, and demographic factors. Feature importance analysis reveals key factors contributing to accurate predictions. This paper contributes to the field of health analytics by demonstrating the effectiveness of Random Forest in predicting and categorizing health risks. The insights gained from this research have the potential to inform personalized health interventions and contribute to the advancement of precision health strategies. Furthermore, the study highlights the importance of leveraging machine learning techniques for health risk assessment in diverse populations. (shrink)

Husserl’s Logical Grammar is intended to explain how complex expressions can be constructed out of simple ones so that their meaning turns out to be determined by the meanings of their constituent parts and the way they are put together. Meanings are thus understood as structured contents and classified into formal categories to the effect that the logical properties of expressions reflect their grammatical properties. As long as linguistic meaning reduces to the intentional content of pre-linguistic representations, however, it (...) is not trivial to account for how semantics relates to syntax in this context. In this paper, I analyze Husserl’s Logical Grammar as a system of recursive rules operating on representations and suggest that the syntactic form of representations contributes to their semantics because it carries information about semantic role. I further discuss Husserl’s syntactic account of the unity of propositions and argue that, on this account, logical form supervenes on syntactic form. In the last section I draw some implications for the phenomenology of thought and conjecture that the structural features it displays are likely to convey the syntactic structures of an underlying language-like representational system. (shrink)

Notions of fitting seem to be attractive in explaining language understanding. This paper tries to interpret "fitting" in terms of holistic (cheng, 誠) intentionality rather than the dualistic one. I propose to interpret “cheng” as a notion of integration: The cheng of an entity is the power to realize the embedded objective of it in the context where it interacts with all others; "Mind" refers to the ability of not a single kind of entity but to that of all entities (...) of complex degrees in processing informations and to any agent that integrates. I would like to discuss some cases where this notion of fitting is working. First, building of a primitive language could have been done by fittings of primitive expressions which came out of people's basic needs and desires, their forms of life. Second, we do not identify an object on the basis of a criterion of similarity, but by asking questions like whether it would be more fitting to identify two objects in the present context than not to.Third, what is involved in our recognition of a fact is a context. A context does not dictate one single description but does allow any number of descriptions, some of which are more or less fitting and others of which are more or less unfitting. It may take time for the community of language involved to come to a more fitting description. For the sake of convenience, this description may come to have a grammar for the community where it can be classified as true and others as false. (shrink)

This paper deals with Gärdenfors’ theory of conceptual spaces. Let \({\mathcal {S}}\) be a conceptual space consisting of 2-type fuzzy sets equipped with several kinds of metrics. Let a finite set of prototypes \(\tilde{P}_1,\ldots,\tilde{P}_n\in \mathcal {S}\) be given. Our main result is the construction of a classification algorithm. That is, given an element \({\tilde{A}}\in \mathcal {S},\) our algorithm classifies it into the conceptual field determined by one of the given prototypes \(\tilde{P}_i.\) The construction of our algorithm uses some physical analogies (...) and the Newton potential plays a significant role here. Importantly, the resulting conceptual fields are not convex in the Euclidean sense, which we believe is a reasonable departure from the assumptions of Gardenfors’ original definition of the conceptual space. A partitioning algorithm of the space \(\mathcal {S}\) is also considered in the paper. In the application section, we test our classification algorithm on real data and obtain very satisfactory results. Moreover, the example we consider is another argument against requiring convexity of conceptual fields. (shrink)

Concurring to information from the Centresfor Illness Control and Anticipation, instruction and religion are both capable indicators of lasting or dissolving unions. The chance of a marriage finishing in separate was lower for individuals with more knowledge, with over half of relational unions of those who did not complete high school having finished in separate compared with roughly 30 percent of relational unions of college graduates. With this overview, the divorce rate dataset from UCI dataset repository is used for (...) predicting the divorce class target with the following contributions. Firstly, the Divorce rate dataset is subjected with the data cleaning and exploratory data analysis. Secondly, the data set is settled with different classifiers to look at the classification before and after feature scaling. Thirdly, the dataset is processed with various cross validation of training and testing dataset i.e 80:20, 30:70, 40:60, 50:50 to improve the accuracy of all the classifiers. Fourth, the dataset is processed with 15, 20 and 30 components of principal component analysis and then applied with all classifier algorithm to analyze the accuracy of divorce rate prediction. Fifth, the performance analysis is done with precision, recall, accuracy, fscore and running time to infer the classification before and after feature scaling. Experimental results show that the Random Forest classifier is found to have the accuracy of 98% for all PCA reduced dataset with 15, 20 and 30 components. The result showsthat Random Forest classifier is found to have the accuracy of 98% for 40:60, 50:50 of training and testing dataset. (shrink)

This paper introduces the concept of Adaptive Rooms, which are virtual environments able to dynamically adapt to users’ needs, including ‘physical’ and cognitive workflow requirements, number of users, differing cognitive abilities and skills. Adaptive rooms are collections of virtual objects, many of them self-transforming objects, housed in an architecturally active room with information spaces and tools. An ontology of objects used in adap- tive rooms is presented. Virtual entities are classified as passive, reactive, ac- tive, and information (...) entities, and their sub-categories. Only active objects can be self-transforming. Adaptive Rooms are meant to combine the insights of ubiquitous computing -- that computerization should be everywhere, transpar- ently incorporated -- with the insights of augmented reality -- that everyday ob- jects can be digitally enhanced to carry more information about their use. To display the special potential of adaptive rooms, concrete examples are given to show how the demands of cognitive workflow can be reduced. (shrink)

In this study, we extracted facial action units (AUs) data during a Hearthstone tournament to investigate behavioural differences between expert, intermediate, and novice players. Our aim was to obtain insights into the nature of expertise and how it may be tracked using non-invasive methods such as AUs. These insights may shed light on the endogenous responses in the player and at the same time may provide information to the opponents during a competition. Our results show that player expertise may (...) be characterised by specific patterns in facial expressions. More specifically, AU17 (chin raiser), AU25 (lips apart), and AU26 (jaws drop) intensity responses during gameplay may vary according to players' expertise. Such results were obtained by training a random forest classifier to test whether we can use these three AUs alone to accurately detect players' expertise. The classifier reached 0.75 accuracy on 5-fold cross-validation, after balancing the class weights, and 0.85 after having applied the Synthetic Minority Over-sampling Technique (SMOTE) function. These results suggest that AUs can be effectively used to discriminate different levels of expertise in competitive video game players. (shrink)

In Fallibilism: Evidence and Knowledge, Jessica Brown identifies a number of problems for the so-called knowledge view of justification. According to this view, we cannot justifiably believe what we do not know. Most epistemologists reject this view on the grounds that false beliefs can be justified if, say, supported by the evidence or produced by reliable processes. We think this is a mistake and that many epistemologists are classifying beliefs as justified because they have properties that indicate that something should (...) be excused. Brown thinks that previous attempts to make this case have been unsuccessful. While the difficulties Brown points to are genuine, I think they show that attempts to explain a classificatory judgment haven't been successful. Still, I would argue that the classification is correct. We need a better explanation of this classificatory judgment. I will try to clarify the justification-excuse distinction and explain why it's a mistake to insist that beliefs that violate epistemic norms might be justified. Just as it's possible for a rational agent to act without justification in spite of her best intentions, it's possible that a rational thinker who follows the evidence and meets our expectations might nevertheless believe without sufficient justification. If our justified beliefs are supposed to guide us in deciding what to do, we probably should draw on discussions from morality and the law about the justification/excuse distinction to inform our understanding of the epistemic case. (shrink)

A reality for many information technology (IT) organizations is the need to hire IT talent from other cities or countries to supplement their employee staff. As organizations extend their software development work to remote locations, however, a distinct productivity gap can emerge between co-located and distributed teams. The problem this study addresses is the reduced productivity levels for teams practicing the Agile methodology when team members are distributed by location or time zone. Specifically, it was unknown if there are (...) organizational factors which can improve the productivity of these distributed development teams. The purpose of this study was to determine whether any amount of separation of team members impacts productivity, or if various degrees of time zone overlap allows for sufficient synchronous communication to overcome the communication lag inherit with having distributed teams. Productivity was measured by the number of story points per cycle day completed by the team. Two additional variables were collected to study the impact of sourcing and task complexity on distributed team productivity. A quantitative data analysis was conducted on a large, globally distributed technology organization practicing the Agile methodology across the Americas, Europe, Africa, Asia, and Australia. Teams were classified in the study based on the amount of time zone overlap of the team members. The results of the study found that teams which were co-located or had any amount of time zone overlap performed at similar levels of productivity, while teams with no overlapping business day experienced significantly lower levels of productivity (p < .05). Conversely, sourcing of the resources either as contractors or employees did not demonstrate a significant difference in team productivity. The data analysis on task complexity showed mixed results; there was a different level of productivity when some teams were working tasks of different complexity, but the data was further nuanced by team member location. This study indicates the importance of resource location as a key factor in team productivity. Further study on organizational design could be beneficial to better understand how organizations should select locations to optimize productivity. (shrink)

People are increasingly exposed to conflicting health information and must navigate this information to make numerous decisions, such as which foods to consume, a process many find difficult. Although some consumers attribute these disagreements to aspects related to uncertainty and complexity of research, many use a narrower set of credibility-based explanations. Experts’ views on disagreements are underinvestigated and lack explicit identification and classification of the differences in causes for disagreement. Consequently, there is a gap in existing literature to (...) understand the range of reasons for these contradictions. Combining the findings from a literature study and expert interviews, a taxonomy of disagreements was developed. It identifies 10 types of disagreement classified under three dimensions: informant-, information- and uncertainty-related causes for disagreement. The taxonomy may assist with adoption of more effective strategies to deal with conflicting information and contributes to research and practice of science communication in the context of disagreement. (shrink)

Talk of different types of cells is commonplace in the biological sciences. We know a great deal, for example, about human muscle cells by studying the same type of cells in mice. Information about cell type is apparently largely projectible across species boundaries. But what defines cell type? Do cells come pre-packaged into different natural kinds? Philosophical attention to these questions has been extremely limited [see e.g., Wilson (Species: New Interdisciplinary Essays, pp 187–207, 1999; Genes and the Agents of (...) Life, 2005; Wilson et al. Philos Top 35(1/2):189–215, 2007)]. On the face of it, the problems we face in individuating cellular kinds resemble those biologists and philosophers of biology encountered in thinking about species: there are apparently many different (and interconnected) bases on which we might legitimately classify cells. We could, for example, focus on their developmental history (a sort of analogue to a species’ evolutionary history); or we might divide on the basis of certain structural features, functional role, location within larger systems, and so on. In this paper, I sketch an approach to cellular kinds inspired by Boyd’s Homeostatic Property Cluster Theory, applying some lessons from this application back to general questions about the nature of natural kinds. (shrink)

Working memory, an important posit in cognitive science, allows one to temporarily store and manipulate information in the service of ongoing tasks. Working memory has been traditionally classified as an explicit memory system – that is, as operating on and maintaining only consciously perceived information. Recently, however, several studies have questioned this assumption, purporting to provide evidence for unconscious working memory. In this paper, we focus on visual working memory and critically examine these studies as well as (...) studies of unconscious perception that seem to provide indirect evidence for unconscious working memory. Our analysis indicates that current evidence does not support an unconscious working memory store, though we offer independent reasons to think that working memory may operate on unconsciously perceived information. (shrink)

Ethnobotanical research provides ample justification for comparing diverse biological nomenclatures and exploring ways that retain alternative naming practices. However, how (and whether) comparison of nomenclatures is possible remains a subject of discussion. The comparison of diverse nomenclatural practices introduces a suite of epistemic and ontological difficulties and considerations. Different nomenclatures may depend on whether the communities using them rely on formalized naming conventions; cultural or spiritual valuations; or worldviews. Because of this, some argue that the different naming practices may not (...) be comparable if the ontological commitments employed differ. Comparisons between different nomenclatures cannot assume that either the naming practices or the object to which these names are intended to apply identifies some universally agreed upon object of interest. Investigating this suite of philosophical problems, I explore the role grey nomenclatures play in classification. ‘Grey nomenclatures’ are defined as those that employ names that are either intentionally or accidentally non-Linnaean. The classification of the lichen thallus (a symbiont) has been classified outside the Linnaean system by botanists relying on the International Code of Nomenclature for algae, fungi, and plants (ICN). But, I argue, the use of grey names is not isolated and does not occur exclusively within institutionalized naming practices. I suggest, ‘grey names’ also aptly describe nomenclatures employed by indigenous communities such as the Samí of Northern Finmark, the Sherpa of Nepal, and the Okanagan First Nations. I pay particular attention to how naming practices are employed in these communities; what ontological commitments they hold; for what purposes are these names used; and what anchors the community’s nomenclatural practices. Exploring the history of lichen naming and early ethnolichenological research, I then investigate the stakes that must be considered for any attempt to preserve, retain, integrate, or compare the knowledge contained in both academically formalized grey names and indigenous nomenclatures in a way that preserves their source-specific informational content. (shrink)

This article is a preliminary draft for initiating and commencing a new pioneer dimension of expression. To deal with higher-dimensional data or information flowing in this modern era of information technology and artificial intelligence, some innovative super algebraic structures are essential to be formulated. In this paper, we have introduced such matrices that have multiple layers and clusters of layers to portray multi-dimensional data or massively dispersed information of the plithogenic universe made up of numerous subjects their (...) attributes, and sub-attributes. For grasping that field of parallel information, events, and realities flowing from the micro to the macro level of universes, we have constructed hypersoft and hyper-super-soft matrices in a Plithogenic Fuzzy environment. These Matrices classify the non-physical attributes by accumulating the physical subjects and further sort the physical subjects by accumulating their non-physical attributes. We presented themasPlithogenicAttributiveSubjectivelyWholeHyper-Super-Soft-Matrix(PASWHSS-Matrix)andPlithogenic Subjective Attributively Whole-Hyper-Super-Soft-Matrix (PSAWHSS-Matrix). Several types of views and level-layers of these matrices are described. In addition, some local aggregation operators for Plithogenic Fuzzy Hypersoft Set (PPFHS-Set) are developed. Finally, few applications of these matrices and operators are used as numerical examples of COVID-19 data structures. (shrink)

In this paper we propose a formal theory of partitions (ways of dividing up or sorting or mapping reality) and we show how the theory can be applied in the geospatial domain. We characterize partitions at two levels: as systems of cells (theory A), and in terms of their projective relation to reality (theory B). We lay down conditions of well-formedness for partitions and we define what it means for partitions to project truly onto reality. We continue by classifying well-formed (...) partitions along three axes: (a) degree of correspondence between partition cells and objects in reality; (b) degree to which a partition represents the mereological structure of the domain it is projected onto; and (c) degree of completeness and exhaustiveness with which a partition represents reality. This classification is used to characterize three types of partitions that play an important role in spatial information science: cadastral partitions, categorical coverages, and the partitions involved in folk categorizations of the geospatial domain. (shrink)

This essay is part of larger project in which I attempt to show that Western formal logic, from its inception in Aristotle onward, has both been partially constituted by, and partially constitutive of, what has become known as racism. More specifically, (a) racist/quasi-racist/proto-racist political forces were part of the impetus for logic’s attempt to classify the world into mutually exclusive, hierarchically-valued categories in the first place; and (b) these classifications, in turn, have been deployed throughout history to justify and empower (...) racism/quasi-racism/proto-racism. In other words, (a) an important part of the chaos and messiness that so troubles logic has been the natural bio-cultural diversity of human beings as described by concepts such as race and ethnicity; and (b) once these concepts were historically in place, taken for granted, buttressed with pseudo-science, and had their origins forgotten, they became tools for the oppression of diverse human groups. The central thesis of this essay is that close readings of a variety of Leibniz’s writings (including several essays and one letter) will reveal a pattern of mutual dependency and creation in regard to logic and racism in Leibniz. My conclusion will be that there is a meaningful connection between logic and racism (or at least between logic and politics in general) in Leibniz such that one should be skeptical of his logic’s claim to offer transparent and neutral descriptions of the world as well as imperatives for action. Put differently, I want to ask the following specific question: how do Leibniz’s own racially-informed political goals, along with the emergence of race-centric European colonialism, both invest and disguise themselves within Leibniz’s mathematizing of logic? (shrink)

Aim: The aim of this study is to reveal the convergence of public health ethics, institutional, collective, and individual ethics obligation during the COVID-19 pandemic and give some explanations with online media reports. Method: The study method is qualitative content analysis; this method was chosen as it would suit best the purpose of the study. The Turkish Medical Association, Turkish Public Health Association, and online newspaper articles and videos have been scanned using keywords. After that, related online reports and interviews (...) have been classified and analyzed according to the context in between May 22, 2020 and November 16, 2020. No official ethical permission was obtained as the study was conducted through open access internet news sites. Results: The COVID-19 scientific committee and the Ministry of Health has suggested a new way of normal life called controlled social life for all places in Turkey. In the frame of these recommendations, with the Google research engine, many articles of online media including some announcements of medical and legal associations, interviews, and calls made by the authorities were selected and analyzed. These articles and interviews containing each problem and pieces of information provided for the common understandings of the society were selected and evaluated at three topics individual, collective and state and institutional responsibility and obligations. Conclusion: Although the warnings of associations, health authorities, and scientists are mostly about personal-civil responsibility, some occurring practices have caused violations. In addition, the level of education, perception capacity, and habits that include existing social-cultural and religious rituals have prevented people from adapting to this new style of life, in other words, controlled social life. Therefore, besides the original national culture and customs, universal ethical responsibilities and obligations should teach starting from primary school and should consist of whole life understanding as a higher perspective. (shrink)

Delicate Tissue Tumors (STT) are a type of sarcoma found in tissues that interface, backing, and encompass body structures. Due to their shallow recurrence in the body and their extraordinary variety, they seem, by all accounts, to be heterogeneous when seen through Magnetic Resonance Imaging (MRI). They are effortlessly mistaken for different infections, for example, fibro adenoma mammae, lymphadenopathy, and struma nodosa, and these indicative blunders have an extensive unfavorable impact on the clinical treatment cycle of patients. Analysts have proposed (...) a few AI models to characterize cancers, however none have sufficiently tended to this misdiagnosis issue. Likewise, comparative investigations that have proposed models for assessment of such cancers generally don't think about the heterogeneity and the size of the information. Thusly, we propose an AI based approach which joins another strategy of pre handling the information for highlights change, resampling methods to dispense with the predisposition and the deviation of precariousness and performing classifier tests in light of the and Deep learning Algorithm as Artificial brain organization. -/- Tumors (STT). (shrink)

There is a common misconception across the lntelligence Community (IC) to the effect that information trapped within multiple heterogeneous data silos can be semantically integrated by the sorts of meaning-blind statistical methods employed in much of artificial intelligence (Al) and natural language processlng (NLP). This leads to the misconception that incoming data can be analysed coherently by relying exclusively on the use of statistical algorithms and thus without any shared framework for classifying what the data are about. Unfortunately, such (...) approaches do not yield sustainable results where we are dealing with widely distributed, highly heterogeneous and often changing bodies of data. We argue here that the needed integration requires the use of what we call an lntegrating Semantic Framework (ISF), which provldes a consistent set of categories and relationships that can be reused over and over again to tag successive bodies of data in ways which foster more coherent representation and reasoning. (shrink)

The Internet of Things (IoT) connects schemes, programs, data management, and operations, and as they continuously assist in the corporation, they may be a fresh entryway for cyber-attacks. Presently, illegal downloading and virus attacks pose significant threats to IoT security. These risks may acquire confidential material, causing reputational and financial harm. In this paper hybrid optimization mechanism and deep learning,a frame is used to detect the attack prevention in IoT. To develop a cybersecurity warning system in a huge data set, (...) the cybersecurity warning systems index system is first constructed, then the index factors are picked and measured, and finally, the situation evaluation is done.Numerous bio-inspired techniques were used to enhance the productivity of an IDS by lowering the data dimensionality and deleting unnecessary and noisy input. The Grey Wolf Optimization algorithm (GWO) is a developed bio-inspired algorithm that improves the efficacy of the IDS in detecting both regular and abnormal congestion in the network. The smart initialization step integrates the different pre-processing strategies to make sure that informative features are incorporated in the early development stages, has been improved. Researchers pick multi-source material in a big data environment for the identification and verification of index components and present a parallel reduction approach based on the classification significance matrix to decrease data underlying data characteristics. For the simulation of this situation, grey wolf optimization and whale optimization were combined to detect the attack prevention and the deep learning approach was presented. Utilizing system software plagiarism, the TensorFlow deep neural network is intended to classify stolen software. To reduce the noise from the signal and to zoom the significance of each word in the perspective of open-source plagiarism, the tokenization and weighting feature approaches are utilized. Malware specimens have been collected from the Mailing database for testing purposes. The experimental findings show that the suggested technique for measuring cyber security hazards in IoT has superior classification results to existing methods. Hence to detect the attack prevention in IoT process Whale with Grey wolf optimization (WGWO) and deep convolution network is used. (shrink)

Disputes at the intersection of national security, surveillance, civil liberties, and transparency are nothing new, but they have become a particularly prominent part of public discourse in the years since the attacks on the World Trade Center in September 2001. This is in part due to the dramatic nature of those attacks, in part based on significant legal developments after the attacks (classifying persons as “enemy combatants” outside the scope of traditional Geneva protections, legal memos by White House counsel providing (...) rationale for torture, the USA Patriot Act), and in part because of the rapid development of communications and computing technologies that enable both greater connectivity among people and the greater ability to collect information about those connections. -/- One important way in which these questions intersect is in the controversy surrounding bulk collection of telephone metadata by the U.S. National Security Agency. The bulk metadata program (the “metadata program” or “program”) involved court orders under section 215 of the USA Patriot Act requiring telecommunications companies to provide records about all calls the companies handled and the creation of database that the NSA could search. The program was revealed to the general public in June 2013 as part of the large document leak by Edward Snowden, a former contractor for the NSA. -/- A fair amount has been written about section 215 and the bulk metadata program. Much of the commentary has focused on three discrete issues. First is whether the program is legal; that is, does the program comport with the language of the statute and is it consistent with Fourth Amendment protections against unreasonable searches and seizures? Second is whether the program infringes privacy rights; that is, does bulk metadata collection diminish individual privacy in a way that rises to the level that it infringes persons’ rights to privacy? Third is whether the secrecy of the program is inconsistent with democratic accountability. After all, people in the general public only became aware of the metadata program via the Snowden leaks; absent those leaks, there would have not likely been the sort of political backlash and investigation necessary to provide some kind of accountability. -/- In this chapter I argue that we need to look at these not as discrete questions, but as intersecting ones. The metadata program is not simply a legal problem (though it is one); it is not simply a privacy problem (though it is one); and it is not simply a secrecy problem (though it is one). Instead, the importance of the metadata program is the way in which these problems intersect and reinforce one another. Specifically, I will argue that the intersection of the questions undermines the value of rights, and that this is a deeper and more far-reaching moral problem than each of the component questions. (shrink)

Free will is difficult to classify with respect to determinism or indeterminism, and its phenomenology in consciousness often shows both aspects. Initially, it is felt as unlimited and indeterminate will power, with the potentiality of multiple choices. Thereafter, reductive deliberation is led by determinism to the final decision, which realises only one of the potential choices. The reductive deliberation phase tries to find out the best alternative and simultaneously satisfying vague motivations, contextual conditions and personal preferences. The essential sense of (...) free will is the introduction of personal preferences, which allows a higher diversity of reactions to vague motivations. With an oversimplified model of determinism as a chain of events, incompatibilists define “free” as “undetermined” so that determinism becomes incompatible with any free choice between alternatives. In consciousness, free will requires a more complex model of network determinism as well as the consideration of unconsciousness as a causal factor. When “free” defined as “undetermined” is applied to the context of consciousness, it should be reinterpreted as “unconscious of being determined” or not aware of underlying determinism. Lacking information on determinism generates a feeling of “free” in consciousness and, therefore, gives the impression of indeterminism. Lacking information may be induced by an uncertain future without determined events—an unconscious past with biological reactions suddenly emerging from the unconsciousness or an unknown present unable to distinguish determinism of complex events. Therefore, at the level of human consciousness, the experience of free will is associated with apparent indeterminism although it is based on unconscious determinism. The concepts of compatibilism and incompatibilism are only two different aspects of the same phenomenon and correspond to consciousness and unconsciousness. Nevertheless, they can be considered together with a free will concept based on relativity depending on two different reference frames—the first person’s experience frame or the Laplace’s demon frame with knowledge on every molecule of the universe. Only relativity of the free will concept avoids the contradiction between “free” and “unfree” for the same phenomenon and could be a compromise for considering compatibilism and incompatibilism equally. (shrink)

The scientificity of the research should be evaluated according to the methodology used in the study. However, these are usually the research areas or the institutions that are classified as scientific or non-scientific. Because of various reasons, it may turn out that the scientific institutions are not producing science, while the “non-scientists” are doing real science. In the extreme case, the official science system is entirely corrupt, consisting of fraudsters, while the real scientists have been expelled from academic institutions. (...) Since 2016-2017, there has been much talk about the “post-truth era” and the politicians who are “denying science”. However, simultaneously, many complaints about the corruption of science appeared. The outsider cannot tell who is telling the truth as it may be the case that the science fraudsters are defending themselves and these politicians are aware of the corruption. It is also untrue that the censoring or suppression of science started from 2016-2017. Suppression of science because of political and ideological reasons was present already long ago, and during the last few years, it has been increasing. The picture is highly complicated as there are many pretenders, false accusations, etc. For example, because of political reasons, someone may be set up as a pseudoscientist, the real scientist may be expelled using political accusations, justified criticism may be labelled as political pressure, etc. There is something like an inner information war ongoing in and around science. The classical philosophy of science seems unable to handle it because every formal rule can be misapplied. Science, as a whole, may be unable to persist. (shrink)