Convolutional neural networks (CNNs) are increasingly widely used in psychology and neuroscience to predict how human minds and brains respond to visual images. Typically, CNNs represent these images using thousands of features that are learned through extensive training on image datasets. This raises a question: How many of these features are really needed to model human behavior? Here, we attempt to estimate the number of dimensions in CNN representations that are required to capture human psychological representations in two ways: (1) (...) directly, using human similarity judgments and (2) indirectly, in the context of categorization. In both cases, we find that low-dimensional projections of CNN representations are sufficient to predict human behavior. We show that these low-dimensional representations can be easily interpreted, providing further insight into how people represent visual information. A series of control studies indicate that these findings are not due to the size of the dataset we used and may be due to a high level of redundancy in the features appearing in CNN representations. (shrink)

A four dimensional approach to Newtonian physics is used to distinguish between a number of different structures for Newtonian space-time and a number of different formulations of Newtonian gravitational theory. This in turn makes possible an in-depth study of the meaning and status of Newton's Law of Inertia and a detailed comparison of the Newtonian and Einsteinian versions of the Law of Inertia and the Newtonian and Einsteinian treatments of gravitational forces. Various claims about the status of Newton's Law (...) of Inertia are critically examined including these: the Law of Inertia is not an empirical law but a definition; it is not a law simpliciter but a family of schemata; it is a convention and gravitational forces exist only by convention; it is (or is not) redundant; the concepts it embodies can be dispensed with in favor of operationally defined entities; it is unique for a given theory. More generally, the paper demonstrates the importance of space-time structure for the philosophy of space and time and provides support for a realist interpretation of space-time theories. (shrink)

We abandon as redundant the assumption that there exists something more in the physical world than action quanta, which constitute the atoms of the events of which the four-dimensional world consists. We derive metric, energy, matter, etc., from action and the structure formed by the quanta. In the microworld thequantization of space so introduced implies deviations from conventional metrics that make it possible in particular to explain nonlocality. The uncertainty relations, then, in conjunction with the action-based metric, appear to (...) play an essential role in making direct physical contact between emission and absorption events (i.e., retroactivity) possible, which concretely answers Bohr's conjecture that microprocesses constitute “wholes.” All of this appears to afford a realistic explanation of wave-particle “duality,” the EPR and other quantum paradoxes, the hidden variable problem, the “collapse” of wave packets, and the wave interference mechanism with the ¦ ϕ ¦2 rule. (shrink)

The article deals with the algorithm of encrypting graphic information using transformation matrixes. It presents the actions that can be done with the image. The article also gives algorithms for forming matrixes that are created with the use of random processes. Examples of matrixes and encryption results are shown. Calculations of the analysis of combinations and conclusions to them are carried out. The article shows the possibilities and advantages of this image encryption algorithm. The proposed algorithm will allow to transmit (...) encrypted information through open communication channels. The algorithm uses all possible actions that can be done with the image, namely: image resizing, adding redundant elements to the image, changing the location of the pixels, changing the brightness of the image pixels, inverting the image pixels, changing the colours of the images pixels. A randomized approach to matrix formation will make it impossible to use neural systems. The algorithm of the implementation of writing encryption code is rather simple. It is not possible to decrypt the image without a key as the number of possible combinations is extremely large. This algorithm can be used in the military, intelligence, information security. Encryption does not require significant computing or RAM resources. This algorithm can be implemented in WEB-technology and in mobile applications, it has no recursive functions and loop in loop. The algorithm hides the image size, which in turn adds extra protection. Redundant elements will not allow neural networks to compare pixels. Changing colors, changing brightness, inversion by random processes will not allow neural networks to find the decryption function. The article considers an image encryption algorithm that will give a possibility to generate a key. The key will be a set of two-dimensional arrays formed in a randomized manner. A randomized approach to matrix formation will make it impossible to use neural systems. The algorithm uses all possible actions that can be done with the image, namely: Image resizing. Adding redundant elements to the image. Changing the location of the pixels. Changing the brightness of the image pixels. Inverting the image pixels. Changing the colours of the images pixels. The pixel positioning matrix gives us! combinations. The pixel brightness change matrix gives us 8 *! combinations. The pixel inversion matrix gives us 8 *! combinations. The pixel colour change matrix gives us 6 *! Combinations. The total number of combinations N is equal to: It is not possible to decrypt the image without a key as the number of possible combinations is extremely large. The algorithm of the implementation of writing encryption code is rather simple. This algorithm can be used in the military, intelligence, information security. The advantage of this algorithm is the fact that the encrypted image can be transmitted through open chann. (shrink)

In the mid-twentieth century when One-Dimensional Man was first published, the rapid advance of technology was already beginning to render “labor”—that is, what is known as “work”—superfluous. In 2016, half a century later, the process of “work” is being made largely redundant, if not “unnecessary”: the material truth of capitalist society that can never be uttered since as “work” disappears, so does what was one of its functional cornerstones. This article seeks to contribute to identifying some of the trends (...) in the early twenty-first century first outlined by Marcuse in One-Dimensional Man fifty years ago, in critically defining One-Dimensional Society in 2016. (shrink)

Manifold learning and effective model building are generally viewed as fundamentally different types of procedure. After all, in one we build a simplified model of the data, in the other, we construct a simplified model of the another model. Nonetheless, I argue that certain kinds of high-dimensional effective model building, and effective field theory construction in quantum field theory, can be viewed as special cases of manifold learning. I argue that this helps to shed light on all of these (...) techniques. First, it suggests that the effective model building procedure depends upon a certain kind of algorithmic compressibility requirement. All three approaches assume that real-world systems exhibit certain redundancies, due to regularities. The use of these regularities to build simplified models is essential for scientific progress in many different domains. (shrink)

Nowadays, depression is the world’s major health concern and economic burden worldwide. However, due to the limitations of current methods for depression diagnosis, a pervasive and objective approach is essential. In the present study, a psychophysiological database, containing 213 subjects, was constructed. The electroencephalogram signals of all participants under resting state and sound stimulation were collected using a pervasive prefrontal-lobe three-electrode EEG system at Fp1, Fp2, and Fpz electrode sites. After denoising using the Finite Impulse Response filter combining the Kalman (...) derivation formula, Discrete Wavelet Transformation, and an Adaptive Predictor Filter, a total of 270 linear and nonlinear features were extracted. Then, the minimal-redundancy-maximal-relevance feature selection technique reduced the dimensionality of the feature space. Four classification methods distinguished the depressed participants from normal controls. The classifiers’ performances were evaluated using 10-fold cross-validation. The results showed thatK-Nearest Neighbor had the highest accuracy of 79.27%. The result also suggested that the absolute power of the theta wave might be a valid characteristic for discriminating depression. This study proves the feasibility of a pervasive three-electrode EEG acquisition system for depression diagnosis. (shrink)

According to Hans Kamp and Frank Vlach, the two-dimensional tense operators “now” and “then” are ineliminable in quantified tense logic. This is often adduced as an argument against tense logic, and in favor of an extensional account that makes use of explicit quantification over times. The aim of this paper is to defend tense logic against this attack. It shows that “now” and “then” are eliminable in quantified tense logic, provided we endow it with enough quantificational structure. The operators (...) might not be redundant in some other systems of tense logic, but this merely indicates a lack of quantificational resources and does not show any deep-seated inability of tense logic to express claims about time. The paper closes with a brief discussion of the modal analogue of this issue, which concerns the role of the actuality operator in quantified modal logic. (shrink)

Reinforcement learning has recently received much attention as a learning method for complicated systems, e.g., robot systems. It does not need prior knowledge and has higher capability of reactive and adaptive behaviors. However increase in dimensionality of the action-state space makes it diffcult to accomplish learning. The applicability of the existing reinforcement learning algorithms are effective for simple tasks with relatively small action-state space. In this paper, we propose a new reinforcement learning algorithm: “Q-learning with Dynamic Structuring of Exploration Space (...) Based on Genetic Algorithm ”. The algorithm is applicable to systems with high dimensional action and interior state spaces, for example a robot with many redundant degrees of freedom. To demonstrate the effectiveness of the proposed algorithm simulations of obstacle avoidance by a 50 links manipulator have been carried out. It is shown that effective behavior can be learned by using the proposed algorithm. (shrink)

Spontaneous collapse theories provide a promising solution to the measurement problem. But they also introduce a number of problems of their own concerning dimensionality, vagueness, and locality. In response to these problems, advocates of collapse theories have proposed various accounts of the primitive ontology of collapse theories—postulated underlying entities governed by the collapse theory and underwriting our observations. The most prominent of these are a mass density distribution over three-dimensional space, and a set of discrete “flash” events at space-time (...) points. My argument here is that these primitive ontologies are redundant, in the sense that the structures exhibited by the primitive ontologies that allow them to solve the problems facing spontaneous collapse theories are also present in the wave function. But redundancy is not nonexistence; indeed, the fact that the relevant structures are already there in the wave function shows that the mass density ontology and the flash ontology exist whether they are explicitly postulated or not. By the same token, there is no need to decide between a wave function ontology, a mass density ontology and a flash ontology. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:A Hypothesis Concerning the Character of Islamic ArtAsli GocerWhy Islamic art has the distinctive features it has continues to generate clashing explanations. The Islamic visual treasury has no figural images, for instance, and three-dimensional sculpture or large scale oil painting, but instead contains miniatures, vegetal ornaments, arabesque surface patterns, and complex geometrical designs. To account for the phenomena the following radically opposing theories have been offered: the influence (...) of Judaism, the Quranic prohibition against making images, 1 Islamic resentment of the glory of Byzantine icons, 2 logocentricism of classical Islam, 3 the spiritual dimension of Islam, 4 tacit Islamic assertion of “otherness,” 5 and contingency of history. 6 The merits of these theories have been roundly discussed in the literature, and so I will not repeat the task here. I will insist that none of these theories offer a coherent explanation for all arts, but my presumption is that such an explanation is possible. In nonvisual arts the Muslim prefers simple tunes over that of the symphony, for instance, whirling dervishes over the ballet, and lyric poetry over dramatic literature. In my view what explains the common characteristic of all these arts is a certain kind of Islamic attitude informed by a certain philosophical outlook. Although it would be hasty to suggest the existence of a monolithic [End Page 683] Islamic art, it would be equally rash to deny some striking commonalities among its diverse examples. 7The following observation by a Muslim scholar is notable in this regard: “Whether in the great courtyard of the Delhi Mosque or the Qarawiyyin in Fez, one feels oneself within the same artistic and spiritual universe despite all the local variations in material, structural techniques, and the like.” 8 Some cite geometry as what mediates that feeling to the observer despite the cultural divergences in style. 9 Even those who have given up the search for the universal or the spiritual in Islamic art cannot help but see in it the classical ideal of beauty. 10 It is this classical heritage that in fact holds one of the important keys to the puzzle at hand. In particular I shall claim that Islamic art is the living image of what Plato has in mind for art in a theocratic state. Clearly, to refer to Plato and art in the same breath invites trouble. As is well enough known, giving a general interpretation of Plato’s views on the nature of art is a very complex endeavor. 11 Even in the face of grave difficulties in textual exegesis, however, there is sufficient evidence that Plato has some settled views on art. Those pertinent to our discussion here involve two claims, that beauty and goodness are divine and that all human endeavor (including artistic creation) must imitate the divine. 12 Although Platonic strain in Islam has been noted in other areas, its persistent legacy has been overlooked in art. 13 I shall argue that the Platonic influence on Islamic thought can be traced not only to political philosophy 14 and geometry, 15 as it has been commonly accepted, but also aesthetics. 16 A philosophical explanation of the Islamic attitude toward art may therefore be derivable from the Platonic axiom that god is the paradigm of beauty, which is the cosmological principle of [End Page 684] order and harmony; and as all created things, art, too, must reflect the divine paradigm.Before defending this ahistorical hypothesis on the character of Islamic art so reviled in recent literature, a few caveats are in order. “Islamic art” contains redundant terms. Strictly speaking all art in Islam is “Islamic,” because for the Muslim art is a crucial point of contact with the divine. That art should direct the mind to the divine is also Plato’s view. 17 Second, the categories that have traditionally been used to describe Islamic art such as “aniconic” and “nonrepresentational” are unhelpful for the problem at hand. 18 When it comes to the issue of iconography in Islamic arts, there is no consensus, for Islamicists are notably divided on the semiotic dimension of the Islamic visual language. The question of whether the geometric surface pattern is essentially iconography, for instance, is yet... (shrink)

Regularization may be used as an alternative to dimensionality reduction when the number of variables in a model is much larger than the number of available observations. In a recent study from our group regularized regression was employed to quantify brain functional connectivity in a sample of healthy controls using a brain parcellation and resting state fMRI images. Here regularization is applied to evaluate resting state connectivity abnormalities at the voxel level in a sample of patients with schizophrenia. Specifically, ridge (...) regression is implemented with different degrees of regularization. Results are compared to those delivered by the weighted global brain connectivity method, which is based on averaged bivariate correlations and from the non-redundant connectivity method, a dimensionality reduction approach that applies supervised principal component regressions. Ridge regression is able to detect a larger set of abnormally connected regions than both GBC and NRC methods, including schizophrenia related connectivity reductions in fronto-medial, somatosensory and occipital structures. Due to its multivariate nature, the proposed method is much more sensitive to group abnormalities than the GBC, but it also outperforms the NRC, which is multivariate too. Voxel based regularized regression is a simple and sensitive alternative for quantifying brain functional connectivity. (shrink)

Due to the huge amount of data being generating from different sources, the analyzing and extracting of useful information from these data becomes a very complex task. The difficulty of dealing with big data optimization problems comes from many factors such as the high number of features, and the existing of lost data. The feature selection process becomes an important step in many data mining and machine learning algorithms to reduce the dimensionality of the optimization problems and increase the performance (...) of the classification or clustering algorithms. In this paper, a set of hybrid and efficient genetic algorithms are proposed to solve feature selection problem, when the handled data has a large feature size. The proposed algorithms use a new gene-weighted mechanism that can adaptively classify the features into strong relative features, weak or redundant features, and unstable features during the evolution of the algorithm. Based on this classification, the proposed algorithm gives the strong features high priority and the weak features less priority when generating new candidate solutions. In the same time, the proposed algorithm tries to more concentrate on unstable features that sometimes appear and sometimes disappear from the best solutions of the population. The performance of proposed algorithms is investigated by using different datasets and feature selection algorithms. The results show that our proposed algorithms can outperform the other feature selection algorithms and effectively enhance the classification performance over the tested datasets. (shrink)

In recent years, with the rapid development of computer storage capabilities and network transmission capabilities, users can easily share their own video and image information on social networking sites, and the amount of multimedia data on the network is rapidly increasing. With the continuous increase of the amount of data in the network, the establishment of effective automated data management methods and search methods has become an increasingly urgent need. This paper proposes a retrieval method of human motion data based (...) on motion capture in index space. By extracting key frames from the original motion to perform horizontal dimensionality reduction and defining features based on Laban motion analysis, the motion segment is subjected to vertical feature dimensionality reduction. After extracting features from the input motion segment, motion matching is performed on the index space. This paper designs the optimization method of the phased dynamic time deformation algorithm in time efficiency and analyzes the optimization method of the phased dynamic time deformation algorithm in time complexity. Considering the time efficiency redundancy, this paper optimizes the time complexity of the phased dynamic time deformation method. This improves the time efficiency of the staged dynamic time warping algorithm, making it suitable for larger-scale human motion data problems. Experiments show that the method in this paper has the advantage of speed, is more in line with the semantics of human motion, and can meet the retrieval requirements of human motion databases. (shrink)

Ecology, with its emphasis on coupled processes and massive heterogeneity, is not amenable to complete mechanical reduction, which is frustrated for reasons of history, dimensionality, logic, insufficiency, and contingency. Physical laws are not violated, but can only constrain, not predict. Outcomes are predicated instead by autocatalytic configurations, which emerge as stable temporal series of incorporated contingencies. Ecosystem organization arises out of agonism between autocatalytic selection and entropic dissolution. A degree of disorganization, inefficiency, and functional redundancy must be retained by (...) all living systems to ensure flexibility in the face of novel disturbances. That physical and biological dynamics exhibit significant incongruencies argues for the formulation of alternative metaphysical assumptions, referred to here as “Process Ecology”. (shrink)

The ICD-11 personality disorder model is the first fully dimensional assessment of personality pathology. It consists of a personality disorder dysfunction-severity dimension, which encompasses both self- and interpersonal dysfunction, and six optional qualifiers for five prominent personality traits—Negative Affectivity, Detachment, Dissociality, Disinhibition, and Anankastia —plus a borderline pattern that is defined by the criteria of DSM-IV borderline PD. This article reports on the development of a new self-report measure to assess self- and interpersonal dysfunction and the five trait qualifiers. (...) It is the first comprehensive measure of the ICD-11 PD model in that it is the only one to include both PD dysfunction-severity as well as trait scales and because it is based on the Clinical Description and Diagnostic Guidelines, which are more detailed than the “statistical” model description that is currently on the ICD-11 website. The authors wrote 992 items and then reduced the pool to 300 items by eliminating redundancy and selecting the consensus best few items for each subconstruct. Data were collected using an online sample of 383 Prolific workers. Using exploratory factor analysis, seven domain scales were developed, each of which contained two to four scales assessing components of the domain. These preliminary scales’ psychometrics were excellent, as were the domains’ and their components’ convergent and discriminant validity, with a few generally minor exceptions. Structural analyses at the component level revealed a three-factor structure consisting of two moderately correlated Internalizing factors, one centered on Self Dysfunction with two NA components and a DSN component and the other on Interpersonal Dysfunction with DET and ANK components; as well as an Externalizing factor with DSL and a DSN component that was uncorrelated with the other two factors. Two aspects of the results in particular are striking: ANK was not the opposite end of a DSN dimension, but rather contributed to an Internalizing Interpersonal Dysfunction dimension and DSN had both an Internalizing and an Externalizing component. Implications of the findings and study limitations are discussed. (shrink)

Remote sensing image simulation is a very effective method to verify the feasibility of sensor devices for ground observation. The key to remote sensing image application is that simultaneous interpreting of remote sensing images can make use of the different characteristics of different data, eliminate the redundancy and contradiction between different sensors, and improve the timeliness and reliability of remote sensing information extraction. The hotspots and difficulties in this direction are based on remote sensing image simulation of 3D scenes (...) on the ground. Therefore, constructing the 3D scene model on the ground rapidly and accurately is the focus of current research. Because different scenes have different radiation characteristics, therefore, when using MATLAB to write a program generated by 3D scenes, 3D scenes must be saved as different text files according to different scene types, and then extension program of the scene is written to solve the defect that the calculation efficiency is not ideal due to the huge amount of data. This paper uses POV ray photon reverse tracking software to simulate the imaging process of remote sensing sensors, coordinate transformation is used to convert a triangle text file to POV ray readable information and input the RGB value of the base color based on the colorimetry principle, and the final 3D scene is visualized. This paper analyzes the thermal radiation characteristics of the scene and proves the rationality of the scene simulation. The experimental results show that introducing the chroma in the visualization of the scene model makes the whole scene have not only fidelity, but also radiation characteristics in shape and color. This is indispensable in existing 3D modeling and visualization studies. Compared with the complex radiation transmission method, using the multiple angle two-dimensional image generated by POV rays to analyze the radiation characteristics of the scene, the result is intuitive and easy to understand. (shrink)

For a better detection in Network information security monitoring system, the author proposes a method based on adaptive depth detection. A deep belief network was designed and implemented, and the intrusion detection system model was combined with a support vector machine. The data set adopts the NSL-KDD network communication data set, and this data set is authoritative in the security field. Redundant cleaning, data type conversion, normalization, and other processing operations are performed on the data set. Using the data conversion (...) method based on the probability mass function probability mass function coding, a standard data set with low redundancy and low dimensionality can be obtained. Research indicates that when the batch size reaches 64, the accuracy of the test set reaches its maximum value. As the batch size increases, the accuracy first increases and then decreases. When the batch size continues to increase, the model will inevitably fall into the local optimal state, resulting in the degradation of the detection performance of the system. In terms of the false alarm rate, the DBN-SVM model is also the highest; however, it is only 10.73%. Under the premise of increasing the detection rate, the false alarm rate is improved; for the overall detection performance of the model, it is within an acceptable range. In terms of accuracy, the DBN-SVM model also scored the highest. The accuracy rate is the ratio of normal and correct classification for intrusion detection. It can explain the detection ability of the model. In summary, the overall detection ability of the DBN-SVM model is the best. The good classification ability to use SVM is proved, and the classification of low-dimensional features is expected to increase the detection rate of the system. (shrink)

Depression has become one of the most common mental illnesses, and the widespread use of social media provides new ideas for detecting various mental illnesses. The purpose of this study is to use machine learning technology to detect users of depressive patients based on user-shared content and posting behaviors in social media. At present, the existing research mostly uses a single detection method, and the unbalanced class distribution often leads to a low recognition rate. In addition, a large number of (...) irrelevant or redundant features in high-dimensional data sets interfere with the accuracy of recognition. To solve this problem, this paper proposes a hybrid feature selection and stacking ensemble strategy for depression user detection. First, recursive elimination method and extremely randomized trees method are used to calculate feature importance and mutual information value, calculate feature weight vector, and select the optimal feature subset according to the feature weight. Second, naive bayes, k-nearest neighbor, regularized logistic regression and support vector machine are used as base learners, and a simple logistic regression algorithm is used as a combination strategy to build a stacking model. Experimental results show that compared with other machine learning algorithms, the proposed hybrid method, which integrates feature selection and ensemble, has a higher accuracy of 90.27% in identifying online patients. We believe this study will help develop new methods to identify depressed people in social networks, providing guidance for future research. (shrink)

It is commonly held that p is a reason for A to ϕ only if p explains why A ought to ϕ. I argue that this view must be rejected because there are reasons for A to ϕ that would be redundant in any ex...

Graeme Forbes (2011) raises some problems for two-dimensional semantic theories. The problems concern nested environments: linguistic environments where sentences are nested under both modal and epistemic operators. Closely related problems involving nested environments have been raised by Scott Soames (2005) and Josh Dever (2007). Soames goes so far as to say that nested environments pose the “chief technical problem” for strong two-dimensionalism. We call the problem of handling nested environments within two-dimensional semantics “the nesting problem”. We show that (...) the two-dimensional semantics for attitude ascriptions developed in Chalmers (2011a) has no trouble accommodating certain forms of the nesting problem that involve factive verbs such as “know” or “establish”. A certain form of the nesting problem involving apriority and necessity operators does raise an interesting puzzle, but we show how a generalized version of the nesting problem arises independently of two-dimensional semantics—it arises, in fact, for anyone who accepts the contingent a priori. We, then, provide a two-dimensional treatment of the apriority operator that fits the two-dimensional treatment of attitude verbs and apply it to the generalized nesting problem. We conclude that two-dimensionalism is not seriously threatened by cases involving the nesting of epistemic and modal operators. (shrink)

I propose an amendment of Lewis's counterfactual analysis of causation, designed to overcome some difficulties concerning redundant causation.

In his most seminal book, Herbert Marcuse sharply objects to what he saw as pervasive one-dimensional thinking-the uncritical and conformist acceptance of existing structures, norms and behaviours. Originally published in 1964, One Dimensional Man quickly became one of the most important texts in the politically radical sixties. Marcuse's searing indictment of Western society remains as chillingly relevant today as it was at its first writing.

I provide a fairly systematic analysis of when quantities that are variant under a dynamical symmetry transformation should be regarded as unobservable, or redundant, or unreal; of when models related by a dynamical symmetry transformation represent the same state of affairs; and of when mathematical structure that is variant under a dynamical symmetry transformation should be regarded as surplus. In most of these cases the answer is `it depends': depends, that is, on the details of the symmetry in question. A (...) central feature of the analysis is that in order to draw any of these conclusions for a dynamical symmetry it needs to be understood in terms of its possible extensions to other physical systems, in particular to measurement devices. (shrink)

Dimensional analysis can offer us explanations by allowing us to answer What-if–things-had-been-different? questions rather than in virtue of, say, unifying diverse phenomena, important as that is. Additionally, it is argued that dimensional analysis is a form of modelling as it involves several of the aspects crucial in modelling, such as misrepresenting aspects of a target system. By highlighting the continuities dimensional analysis has with forms of modelling we are able to describe more precisely what makes dimensional (...) analysis explanatory and understand otherwise puzzling aspects of dimensional reasoning, such as introducing fictitious dimensions and excluding dimensionally relevant information to characterise some systems. Finally, thinking of dimensional arguments as a form of modelling allows an explication of the role abstraction and multiple realisability; not as compatibility with other possible worlds but as compatibility with different fictional descriptions of our own world. (shrink)

Based on Fricker’s conceptualization of epistemic injustice and moral justice forgiveness, I propose an analysis of the relationship between epistemic injustice and redundant blame. Situated in the Colombian post-conflict context, it is argued that the negative identity prejudices applied to former guerrilla members produce a kind of epis- temic injustice and redundant blame that yields structural violence. It is suggested that a proper understanding of JEP and the Truth Commission’s work, as well as the concept of transitional justice, would work (...) as interpretative resources to favour the ex-rebels testimonial credibility. I conclude that the exercise of power which manipulates the in- terpretative resources available for a collective understanding of practices of justice and forgiveness in the post-conflict, is the cause of the structural violence against ex-rebels. (shrink)

Two-dimensional approaches to semantics, broadly understood, recognize two "dimensions" of the meaning or content of linguistic items. On these approaches, expressions and their utterances are associated with two different sorts of semantic values, which play different explanatory roles. Typically, one semantic value is associated with reference and ordinary truth-conditions, while the other is associated with the way that reference and truth-conditions depend on the external world. The second sort of semantic value is often held to play a distinctive role (...) in analyzing matters of cognitive significance and/or context-dependence. (shrink)

Abstract Since their inception, distributional models of semantics have been criticized as inadequate cognitive theories of human semantic learning and representation. A principal challenge is that the representations derived by distributional models are purely symbolic and are not grounded in perception and action; this challenge has led many to favor feature-based models of semantic representation. We argue that the amount of perceptual and other semantic information that can be learned from purely distributional statistics has been underappreciated. We compare the representations (...) of three feature-based and nine distributional models using a semantic clustering task. Several distributional models demonstrated semantic clustering comparable with clustering-based on feature-based representations. Furthermore, when trained on child-directed speech, the same distributional models perform as well as sensorimotor-based feature representations of children’s lexical semantic knowledge. These results suggest that, to a large extent, information relevant for extracting semantic categories is redundantly coded in perceptual and linguistic experience. Detailed analyses of the semantic clusters of the feature-based and distributional models also reveal that the models make use of complementary cues to semantic organization from the two data streams. Rather than conceptualizing feature-based and distributional models as competing theories, we argue that future focus should be on understanding the cognitive mechanisms humans use to integrate the two sources. (shrink)

In Elder-Vass’s response to my critical discussion of his social ontology, it is maintained (1) that a social object is not identical with but is merely composed of its suitably interrelated parts, (2) that a social object is necessarily indistinguishable in terms of its causal capacities from its interrelated parts, and (3) that ontological individualism lacks an adequate ontological justification. In this reply, I argue that in view of (1) the so-called redescription principle defended by Elder-Vass ought to be reformulated (...) and renamed; that the conjunction of (1) and (2) renders social objects causally redundant; and that ontological individualism can be coherently formulated and theoretically justified within Elder-Vass’s own metaphysics of objects with causal powers. (shrink)

Against the background of studies on redundancy in law that completely omit the visual element in law and of studies on traffic signs that are laconic about their redundancies, the present study proposes more focused investigation into the redundancies of traffic signs. After presentation of the broader context of existing studies on traffic signs and on redundancy in law, and following a discussion of the direct inspiration for embarking upon research into this topic, the article moves to present (...) and discuss six proposed types of redundancies of signs. Utilizing Franciszek Studnicki’s distinction between sign-types and sign-realizations, and given that traffic signs exist in various complicated relationships with each other, with written formulations in legal texts, and with the environments in which they are placed, the study comments on six types of redundancy: sign-type–basic task of road traffic law; of sign-type’s elements; sign-type–sign-type; sign-type–legal text; sign-realization–sign-realization; and sign-realization–environment. Analysis of each type is supported through examples, various subdivisions, and additional lines of inquiry. The study has value for both strictly theoretical and more practical enterprises related both to traffic signs themselves and to the wider realm of visualization of norms. (shrink)

Two-dimensional (2D) semantics is a formal framework that is used to characterize the meaning of certain linguistic expressions and the entailment relations among sentences containing them. 2D semantics has also been applied to thought contents. In contrast with standard possible worlds semantics, 2D semantics assigns extensions and truth-values to expressions relative to two possible world parameters, rather than just one. So a 2D semantic framework provides finer-grained semantic values than those available within standard possible world semantics, while using the (...) same basic model-theoretic resources. The 2D framework itself is just a formal tool. To develop a semantic theory for someone’s language, a proponent of 2D semantics must do three things: (i) explain what exactly the two possible world parameters represent, (ii) explain the rules for assigning 2D semantic values to a person’s words and sentences, and (iii) explain how 2D semantic values help in understanding the meanings of the person’s words and sentences. (shrink)

We investigate higher dimensional chain conditions, where the largeness notion is given by Fubini products of a given ideal. From strong saturation properties of an ideal, we derive abstractly versions of higher dimensional [Formula: see text]-system lemma, which imply many posets, including any finite support iteration of [Formula: see text]-centered posets and measure algebras, satisfy the higher dimensional chain conditions. We then show that if a poset satisfies a strengthening of the [Formula: see text]-finite chain condition by (...) Horn and Tarski, then it satisfies higher dimensional chain conditions. As an application, we derive Ramsey-theoretic consequences, namely various partition hypotheses as studied by Bannister, Bergfalk, Moore and Todorcevic, from the existence of ideals satisfying strong chain conditions. (shrink)

Awareness logic is a type of belief logic in which an agent's beliefs are restricted to those sentences that the agent is aware of. Awareness logic is a successful way to circumvent the problem of omniscience so that actual belief is modelled in a reasonable way. In this paper, we suggest a new method modelling awareness and actual belief by using two-dimensional logics. We show that the two-dimensional logics are flexible tools. Different types of concepts of awareness can (...) be easily modelled by this method. (shrink)

A strong and weak version of the redundancy theory of truth are distinguished. An argument put forth by Michael Dummett concludes that the weak version is vitiated by truth-value gaps. The weak version is defended against this argument. The strong version, however, is vitiated by truth-value gaps.

Two-dimensional semantics is a framework that helps us better understand some of the most fundamental issues in philosophy: those having to do with the relationship between the meaning of words, the way the world is, and our knowledge of the meaning of words. This selection of new essays by some of the world's leading authorities in this field sheds fresh light both on foundational issues regarding two-dimensional semantics and on its specific applications. Contributors: Richard Breheny, Alex Byrne, David (...) Chalmers, Martin Davies, Gareth Evans, Manuel Garcia-Carpintero, Josep Maci`, Martine Nida-Rumelin, Christopher Peacocke, James Pryor, Francois Recanati, Scott Soames, Cara Spencer, Robert Stalnaker, Kai-Yee Wong, Stephen Yablo. (shrink)

In recent years, two-dimensional (2D) semantics has been used to develop a broadly descriptivist approach to meaning that seeks to accommodate externalists’ counterexamples to traditional descriptivism. The 2D possible worlds framework can be used to capture a speaker’s implicit dispositions to identify the reference of her words on the basis of empirical information about her actual environment. Proponents of 2D semantics argue that this aspect of linguistic understanding plays the core theoretical role of meanings: 2D semantics allows us to (...) specify a reference-fixing criterion implicit mastery of which constitutes semantic competence a particular meaning. (shrink)

Biological systems exhibit complexity at all levels of organization. It has recently been argued by Michael Behe that at the biochemical level a type of complexity exists--irreducible complexity--that cannot possibly have arisen as the result of natural, evolutionary processes and must instead be the product of (supernatural) intelligent design. Recent work on self-organizing chemical reactions calls into question Behe's analysis of the origins of biochemical complexity. His central interpretative metaphor for biochemical complexity, that of the well-designed mousetrap that ceases to (...) function if critical parts are absent, is undermined by the observation that typical biochemical systems exhibit considerable redundancy and overlap of function. Real biochemical systems, we argue, manifest redundant complexity--a characteristic result of evolutionary processes. (shrink)

Modal logics, originally conceived in philosophy, have recently found many applications in computer science, artificial intelligence, the foundations of mathematics, linguistics and other disciplines. Celebrated for their good computational behaviour, modal logics are used as effective formalisms for talking about time, space, knowledge, beliefs, actions, obligations, provability, etc. However, the nice computational properties can drastically change if we combine some of these formalisms into a many-dimensional system, say, to reason about knowledge bases developing in time or moving objects. To (...) study the computational behaviour of many-dimensional modal logics is the main aim of this book. On the one hand, it is concerned with providing a solid mathematical foundation for this discipline, while on the other hand, it shows that many seemingly different applied many-dimensional systems (e.g., multi-agent systems, description logics with epistemic, temporal and dynamic operators, spatio-temporal logics, etc.) fit in perfectly with this theoretical framework, and so their computational behaviour can be analyzed using the developed machinery. We start with concrete examples of applied one- and many-dimensional modal logics such as temporal, epistemic, dynamic, description, spatial logics, and various combinations of these. Then we develop a mathematical theory for handling a spectrum of 'abstract' combinations of modal logics - fusions and products of modal logics, fragments of first-order modal and temporal logics - focusing on three major problems: decidability, axiomatizability, and computational complexity. Besides the standard methods of modal logic, the technical toolkit includes the method of quasimodels, mosaics, tilings, reductions to monadic second-order logic, algebraic logic techniques. Finally, we apply the developed machinery and obtained results to three case studies from the field of knowledge representation and reasoning: temporal epistemic logics for reasoning about multi-agent systems, modalized description logics for dynamic ontologies, and spatio-temporal logics. The genre of the book can be defined as a research monograph. It brings the reader to the front line of current research in the field by showing both recent achievements and directions of future investigations (in particular, multiple open problems). On the other hand, well-known results from modal and first-order logic are formulated without proofs and supplied with references to accessible sources. The intended audience of this book is logicians as well as those researchers who use logic in computer science and artificial intelligence. More specific application areas are, e.g., knowledge representation and reasoning, in particular, terminological, temporal and spatial reasoning, or reasoning about agents. And we also believe that researchers from certain other disciplines, say, temporal and spatial databases or geographical information systems, will benefit from this book as well. Key Features: Integrated approach to modern modal and temporal logics and their applications in artificial intelligence and computer science Written by internationally leading researchers in the field of pure and applied logic Combines mathematical theory of modal logic and applications in artificial intelligence and computer science Numerous open problems for further research Well illustrated with pictures and tables. (shrink)

New nursing researchers are faced with a smorgasbord of competing methodologies. Sometimes, they are encouraged to adopt the research paradigms beloved of their senior colleagues. This is a problem if those paradigms are no longer of contemporary methodological relevance. The aim of this paper was to provide clarity about current research paradigms. It seeks to interrogate the continuing viability of positivism as a guiding paradigm for nursing research. It does this by critically analysing the methodological literature. Five major paradigms are (...) addressed: the positivist; the interpretivist/constructivist; the transformative; the realist; and the postpositivist. Acceptance of interpretivist, transformative or realist approaches necessarily entails wholesale rejection of positivism, while acceptance of postpositivism involves its partial rejection. Postpositivism has superseded positivism as the guiding paradigm of the scientific method. The incorporation in randomized controlled trials of postpositivist assumptions indicates that even on the methodological territory that it once claimed as its own, positivism has been rendered redundant as an appropriate paradigm for contemporary nursing research. (shrink)

Clinical research has at least three problematic features: it tends to be redundant, secretive, and isolated.1 Research with these features not only wastes resources and causes harm, it also fails to meet a basic ethical requirement of research: scientific validity. As bioethicists, we should be asking why, if research with these three features is ethically unjustified, it has been so routinely approved by research ethics committees over the past half century. In what follows, I provide one answer to this question. (...) The first section of this paper outlines empirical evidence for the redundant, secretive, and isolated nature of much contemporary clinical research. Next, I argue that a lack of clarity .. (shrink)

Redundant publication in biomedical sciences is the presentation of the same information or data set more than once. Forms of redundant publication include “salami slicing”, in which similar text accompanies data presented in disaggregated fashion in different publications and “duplicate or multiple publication” in which identical information is presented with a virtually identical text. Estimates of prevalence of the phenomenon put it at 10 to 25% of published literature. Redundant publication can be considered unethical, or fraudulent, when the author(s) attempt (...) to conceal the existence of duplicate publication from editors and readers. Redundant publication in the area of clinical trials is potentially dangerous as it tends to overestimate the effects of interventions. The scientific community at large and governments should take urgent steps to safeguard the public from the possible effects of fraudulent multiple publications. (shrink)

¿Qué hace un juez al emitir un enunciado probatorio (está probado que p)? Responder a esta pregunta exige explicitar las dimensiones epistémicas, interpretativas y axiológicas involucradas en la emisión de un enunciado probatorio. También requiere acudir a la filosofía pragmática del lenguaje para dilucidar los alcances conceptuales de la noción de fuerza ilocucionaria. Conforme a las clasificaciones afianzadas en el debate probatorio, sostengo que el juez no describe que p está probado, sino que, a partir de la constitución de la (...) suficiencia probatoria, adscribe el predicado “probado” a p. (shrink)