This paper proposes underwater target identification with local features and a feature tracking algorithm for acoustic image sequences. Feature detectors and descriptors are key to feature tracking. Their performance in underwater scene is evaluated by the change of multitarget parameters. A comprehensive quantitative investigation into the performance of feature tracking is thereby presented. Experimental results confirm that the proposed algorithm can accurately track potential targets and determine whether the potential targets are static targets, dynamic targets, (...) or false alarms according to the tracking trajectories and statistical data. (shrink)

The origin of features from nonfeatural information is a problem that should concern all theories of object categorization and recognition, not just the flexible feature approach. In contrast to the idea that new features must originate from combinations of simpler fixed features, we argue that holistic features can be created from a direct imprinting on the visual medium. Furthermore, featural descriptions can emerge from processes that by themselves do not operate on feature detectors. Once acquired, features can (...) be decomposed into component features if required by other categorizations. We therefore argue that it is not necessary to separate holistic and componential approaches to representations, because the latter is a development of the former. The requirements for representational flexibility outstrip the performance of any existing computational models, but specific mechanisms of feature creation are discussed and evaluated. Challenges for feature creation mechanisms are discussed together with the constraints (perceptual, statistical, functional, and task) they will need to satisfy. (shrink)

A new edge detection technique based on the texture feature coding method is proposed. The TFCM is a texture analysis scheme that is generally used in texture-based image segmentation and classification applications. The TFCM transforms an input image into a texture feature image whose pixel values represent the texture information of the pixel in the original image. Then, on the basis of the transformed image, several features are calculated as texture descriptors. In this article, the TFCM is employed (...) differently to construct an edge detector. In particular, the texture feature number of the TFCM is considered. In other words, the TFN image is used for subsequent processes. After obtaining the TFN image, a simple thresholding scheme is employed for obtaining the coarse edge image. Finally, an edge-thinning procedure is used to obtain the tuned edges. We conducted several experiments on a variety of images and compared the results with the popular existing methods such as the Sobel, Prewitt, Canny, and Canny–Deriche edge detectors. The obtained results were evaluated quantitatively with the Figure of Merit criterion. The experimental results demonstrated that our proposed method improved the edge detection performance greatly. We further implemented the proposed edge detector with a hardware system. To this end, a field programmable gate array chip was used. The related simulations were carried out with the MATLAB Simulink tool. Both software and hardware implementations demonstrated the efficiency of the proposed edge detector. (shrink)

This study aims to examine the main determinants of efficiency of both conventional and Islamic Saudi banks and then choose the best fit model among machine learning prediction models, Chi-squared automatic interaction detector, linear regression, and neural network ). The data were collected from the annual financial reports of Saudi banks from 2014 to 2018. The Saudi banking sector consists of 11 banks, 4 of which are Islamic. In this study, the major financial ratios are subgrouped into the profitability ratios, (...) managerial practices, asset and loans, capital adequacy ratios, and liquidity. First, regression analysis is implemented with efficiency ratio as a dependent variable and the proxies of banks’ profitability, liquidity, asset quality, management ratios, and capital adequacy ratios as independent variables. Next, the feature selection is applied for different prediction models. Subsequently, 4 prediction models were developed to choose the best fit. The performance metrics have also been evaluated. Regression results exhibit that the efficiency of both conventional and Islamic banks is highly affected by profitability, liquidity, and managerial practices. Finally, we choose the best prediction model with the highest R2 in the training and the testing phases with/out feature selection that is the CHAID model. The best predictors of cost efficiency for Saudi banks are the capital ratios, namely, CAR total and CAR tier 1. Findings are theoretically and practically important to academics, investors, and policymakers. Policymakers can benefit from the novelty of this study in building an early warning system using the CHAID model to predict different financial distress scenarios. (shrink)

Structural representations are increasingly popular in philosophy of cognitive science. A key virtue they seemingly boast is that of meeting Ramsey's job description challenge. For this reason, structural representations appear tailored to play a clear representational role within cognitive architectures. Here, however, I claim that structural representations do not meet the job description challenge. This is because even our most demanding account of their functional profile is satisfied by at least some receptors, which paradigmatically fail the job description challenge. Hence, (...) the functional profile typically associated with structural representations does not identify representational posits. After a brief introduction, I present, in the second section of the paper, the job description challenge. I clarify why receptors fail to meet it and highlight why, as a result, they should not be considered representations. In the third section I introduce what I take to be the most demanding account of structural representations at our disposal, namely Gładziejewski's account. Provided the necessary background, I turn from exposition to criticism. In the first half of the fourth section, I equate the functional profile of structural representations and receptors. To do so, I show that some receptors boast, as a matter of fact, all the functional features associated with structural representations. Since receptors function merely as causal mediators, I conclude structural representations are mere causal mediators too. In the second half of the fourth section I make this conclusion intuitive with a toy example. I then conclude the paper, anticipating some objections my argument invites. (shrink)

There has been much discussion recently about the scope and limits of purely symbolic models of the mind and about the proper role of connectionism in cognitive modeling. This paper describes the symbol grounding problem : How can the semantic interpretation of a formal symbol system be made intrinsic to the system, rather than just parasitic on the meanings in our heads? How can the meanings of the meaningless symbol tokens, manipulated solely on the basis of their shapes, be grounded (...) in anything but other meaningless symbols? The problem is analogous to trying to learn Chinese from a Chinese/Chinese dictionary alone. A candidate solution is sketched: Symbolic representations must be grounded bottom-up in nonsymbolic representations of two kinds: iconic representations, which are analogs of the proximal sensory projections of distal objects and events, and categorical representations, which are learned and innate feature-detectors that pick out the invariant features of object and event categories from their sensory projections. Elementary symbols are the names of these object and event categories, assigned on the basis of their categorical representations. Higher-order symbolic representations, grounded in these elementary symbols, consist of symbol strings describing category membership relations. Connectionism is one natural candidate for the mechanism that learns the invariant features underlying categorical representations, thereby connecting names to the proximal projections of the distal objects they stand for. In this way connectionism can be seen as a complementary component in a hybrid nonsymbolic/symbolic model of the mind, rather than a rival to purely symbolic modeling. Such a hybrid model would not have an autonomous symbolic module, however; the symbolic functions would emerge as an intrinsically dedicated symbol system as a consequence of the bottom-up grounding of categories ' names in their sensory representations. Symbol manipulation would be governed not just by the arbitrary shapes of the symbol tokens, but by the nonarbitrary shapes of the icons and category invariants in which they are grounded. (shrink)

Many of the computing systems programmed using Machine Learning are opaque: it is difficult to know why they do what they do or how they work. Explainable Artificial Intelligence aims to develop analytic techniques that render opaque computing systems transparent, but lacks a normative framework with which to evaluate these techniques’ explanatory successes. The aim of the present discussion is to develop such a framework, paying particular attention to different stakeholders’ distinct explanatory requirements. Building on an analysis of “opacity” from (...) philosophy of science, this framework is modeled after accounts of explanation in cognitive science. The framework distinguishes between the explanation-seeking questions that are likely to be asked by different stakeholders, and specifies the general ways in which these questions should be answered so as to allow these stakeholders to perform their roles in the Machine Learning ecosystem. By applying the normative framework to recently developed techniques such as input heatmapping, feature-detector visualization, and diagnostic classification, it is possible to determine whether and to what extent techniques from Explainable Artificial Intelligence can be used to render opaque computing systems transparent and, thus, whether they can be used to solve the Black Box Problem. (shrink)

Many philosophers and psychologists have attempted to elucidate the nature of mental representation by appealing to notions like isomorphism or abstract structural resemblance. The ‘structural representations’ that these theorists champion are said to count as representations by virtue of functioning as internal models of distal systems. In his 2007 book, Representation Reconsidered, William Ramsey endorses the structural conception of mental representation, but uses it to develop a novel argument against representationalism, the widespread view that cognition essentially involves the manipulation of (...) mental representations. Ramsey argues that although theories within the ‘classical’ tradition of cognitive science once posited structural representations, these theories are being superseded by newer theories, within the tradition of connectionism and cognitive neuroscience, which rarely if ever appeal to structural representations. Instead, these theories seem to be explaining cognition by invoking so-called ‘receptor representations’, which, Ramsey claims, aren’t genuine representations at all—despite being called representations, these mechanisms function more as triggers or causal relays than as genuine stand-ins for distal systems. I argue that when the notions of structural and receptor representation are properly explicated, there turns out to be no distinction between them. There only appears to be a distinction between receptor and structural representations because the latter are tacitly conflated with the ‘mental models’ ostensibly involved in offline cognitive processes such as episodic memory and mental imagery. While structural representations might count as genuine representations, they aren’t distinctively mental representations, for they can be found in all sorts of non-intentional systems such as plants. Thus to explain the kinds of offline cognitive capacities that have motivated talk of mental models, we must develop richer conceptions of mental representation than those provided by the notions of structural and receptor representation. (shrink)

The laugh- and/or smile-evoking potency of laughter was evaluated by observing responses of 128 subjects in three undergraduate psychology classes to laugh stimuli produced by a “laugh box.” Subjects recorded whether they laughed and/or smiled during each of 10 trials, each of which consisted of an 18-sec sample of laughter, followed by 42 sec of silence. Most subjects laughed and smiled in response to the first presentation of laughter. However, the polarity of the response changed quickly. By the 10th trial, (...) few subjects laughed and/or smiled, and most found the stimulus “obnoxious.” Although other research has described canned-laughter effects, it did not consider the hypothesis confirmed here, that laughter itself evokes laughter, perhaps by activating a laughter-specific auditory-feature detector. This result is relevant to the neurological basis of social communication, human ethology, and theories of speech production and perception. (shrink)

It is proposed to conceive of representation as an emergent phenomenon that is supervenient on patterns of activity of coarsely tuned and highly redundant feature detectors. The computational underpinnings of the outlined concept of representation are (1) the properties of collections of overlapping graded receptive fields, as in the biological perceptual systems that exhibit hyperacuity-level performance, and (2) the sufficiency of a set of proximal distances between stimulus representations for the recovery of the corresponding distal contrasts between stimuli, (...) as in multidimensional scaling. The present preliminary study appears to indicate that this concept of representation is computationally viable, and is compatible with psychological and neurobiological data. (shrink)

The thresholds of human observers detecting line targets improve significantly when the targets are presented in a spatial context of collinear inducing stimuli. This phenomenon is referred to as spatial facilitation, and may reflect the output of long-range interactions between cortical feature detectors. Spatial facilitation has thus far been observed with luminance-defined, achromatic stimuli on achromatic backgrounds. This study compares spatial facilitation with line targets and collinear, edge-like inducers defined by luminance contrast to spatial facilitation with targets and (...) inducers defined by color contrast. The results of a first experiment show that achromatic inducers facilitate the detection of achromatic targets on gray and colored backgrounds, but tend to suppress the detection of chromatic targets. Chromatic inducers facilitate the detection of chromatic targets on gray and colored backgrounds, but tend to suppress the detection of achromatic targets. Chromatic spatial facilitation appears to be strongest when inducers and background are isoluminant. The results of a second experiment show that spatial facilitation with chromatic targets and inducers requires a longer exposure duration of the inducers than spatial facilitation with achromatic targets and inducers, which is already fully effective at an inducer exposure of 30 ms only. The findings point towards two separate mechanisms for spatial facilitation with collinear form stimuli: one that operates in the domain of luminance, and one that operates in the domain of color contrast. These results are consistent with neural models of boundary and surface formation which suggest that achromatic and chromatic visual cues are represented on different cortical surface representations that are capable of selectively attracting attention. Multiple copies of these achromatic and chromatic surface representations exist corresponding to different ranges of perceived depth from an observer, and each can attract attention to itself. Color and contrast differences between inducing and test stimuli, and transient responses to inducing stimuli, can cause attention to shift across these surface representations in ways that sometimes enhance and sometimes interfere with target detection. (shrink)

A key question in studying consciousness is how neural operations in the brain can identify streams of sensory input as belonging to distinct modalities, which contributes to the representation of qualitatively different experiences. The basis for identification of modalities is proposed to be constituted by self-organized comparative operations across a network of unimodal and multimodal sensory areas. However, such network interactions alone cannot answer the question how sensory feature detectors collectively account for an integrated, yet phenomenally differentiated experiential (...) content. This problem turns out to be different from, although related to, the binding problem. It is proposed that the neural correlate of an enriched, multimodal experience is constituted by the attractor state of a dynamic associative network. Within this network, unimodal and multimodal sensory maps continuously interact to influence each other’s attractor state, so that a feature change in one modality results in a fast re-coding of feature information in another modality. In this scheme, feature detection is coded by firing-rate, whereas firing phase codes relational aspects. (shrink)

A neurally plausible model of how the process of visually perceiving a letter in the context of a word is learned, and how such processing occurs in adults is proposed. The model consists of a collection of abstract letter feature detector neurons and their interconnections. The model also includes a learning rule that specifies how these interconnections evolve with experience. The interconnections between neurons can be interpreted as representing the spatially redundant, sequentially redundant, and transgraphemic information in letter string (...) displays. Anderson, Silverstein, Ritz, and Jones's (1977) “Brain‐State‐in‐a‐Box” (BSB) neural mechanism is then used to implement the proposed model. The resulting system makes explicit qualitative predictions using both letter recognition accuracy and reaction time as dependent measures. In particular, the model offers an integrated explanation of some experiments involving manipulations of orthographic regularity, masking, case alternations, and experience with words. The similarities and differences between the model and models proposed by Adams (1979) and McClelland and Rumelhart (1981) are also discussed. (shrink)

The early, largely automatic stages of human visual processing involve things like feature detectors (e.g., edge detectors) that do not involve our concepts or beliefs. These stages are called data-driven or bottom up aspects of perceptual information processing. But in the later stages of processing perception often is affected by our concepts, beliefs, and expectations. Such processes are said to be hypothesis-driven or expectation-driven; they are also known as..

Perruchet & Vinter do not fully resolve issues about the role of consciousness and the unconscious in cognition and learning, and it is doubtful that consciousness has been computationally implemented. The cascade-correlation (CC) connectionist model develops high-order feature detectors as it learns a problem. We describe an extension, knowledge-based cascade-correlation (KBCC), that uses knowledge to learn in a hierarchical fashion.

Clark & Thornton's “superficially distinct ploys and mechanisms” are in fact very different: there is a deep difference between (a) filters and feature detectors, which “let the information in,” and (b) contentful representations and theories, which reconfigure it into a computationally tractable form. (a) is bringing abilities to experience whereas (b) is bringing content to experience. Both have well known problems. I outline an evolutionary story that avoids these problems and begins to explain how representations and theories developed (...) out of feature detectors and filters. (shrink)

Arguments by Sorkin (Impossible measurements on quantum fields. In: Directions in general relativity: proceedings of the 1993 International Symposium, Maryland, vol 2, pp 293–305, 1993) and Borsten et al. (Phys Rev D 104(2), 2021. https://doi.org/10.1103/PhysRevD.104.025012 ) establish that a natural extension of quantum measurement theory from non-relativistic quantum mechanics to relativistic quantum theory leads to the unacceptable consequence that expectation values in one region depend on which unitary operation is performed in a spacelike separated region. Sorkin [ 1 ] labels (...) such scenarios ‘impossible measurements’. We explicitly present these arguments as a no-go result with the logical form of a reductio argument and investigate the consequences for measurement in quantum field theory (QFT). Sorkin-type impossible measurement scenarios clearly illustrate the moral that Microcausality is not by itself sufficient to rule out superluminal signalling in relativistic quantum theories that use Lüders’ rule. We review three different approaches to formulating an account of measurement for QFT and analyze their responses to the ‘impossible measurements’ problem. Two of the approaches are: a measurement theory based on detector models proposed in Polo-Gómez et al. (Phys Rev D, 2022. https://doi.org/10.1103/physrevd.105.065003 ) and a measurement framework for algebraic QFT proposed in Fewster and Verch (Commun Math Phys 378(2):851–889, 2020). Of particular interest for foundations of QFT is that they share common features that may hold general morals about how to represent measurement in QFT. These morals are about the role that dynamics plays in eliminating ‘impossible measurements’, the abandonment of the operational interpretation of local algebras \({\mathcal {A}}(O)\) as representing possible operations carried out in region _O_, and the interpretation of state update rules. Finally, we examine the form that the ‘impossible measurements’ problem takes in histories-based approaches and we discuss the remaining challenges. (shrink)

The recent emergence of machine-manipulated media raises an important societal question: How can we know whether a video that we watch is real or fake? In two online studies with 15,016 participants, we present authentic videos and deepfakes and ask participants to identify which is which. We compare the performance of ordinary human observers with the leading computer vision deepfake detection model and find them similarly accurate, while making different kinds of mistakes. Together, participants with access to the model’s prediction (...) are more accurate than either alone, but inaccurate model predictions often decrease participants’ accuracy. To probe the relative strengths and weaknesses of humans and machines as detectors of deepfakes, we examine human and machine performance across video-level features, and we evaluate the impact of preregistered randomized interventions on deepfake detection. We find that manipulations designed to disrupt visual processing of faces hinder human participants’ performance while mostly not affecting the model’s performance, suggesting a role for specialized cognitive capacities in explaining human deepfake detection performance. -/- . (shrink)

We introduce the Relational Blockworld (RBW) as a paradigm for deflating the mysteries associated with quantum non-separability/non-locality and the measurement problem. We begin by describing how the relativity of simultaneity implies the blockworld, which has an explanatory potential subsuming both dynamical and relational explanations. It is then shown how the canonical commutation relations fundamental to non-relativistic quantum mechanics follow from the relativity of simultaneity. Therefore, quantum mechanics has at its disposal the full explanatory power of the blockworld. Quantum mechanics exploits (...) this expanded explanatory capability since event distributions among detectors per the density matrix follow from spacetime relations (symmetry group) alone. Thus, the event distributions of non-relativistic quantum mechanics follow from a blockworld wherein spacetime relations are fundamental. Per RBW "quantum mysteries" are deflated and the implications for consciousness and the perception of temporal flow and absolute becoming are explored. We conclude that given RBW, consciousness is no less fundamental than any "physical" feature of the world such as brain states. Further, active consciousness is needed to explain the illusion that it is a dynamical world and consciousness in its most fundamental state is relational and non-local. (shrink)

Religion is not an evolutionary adaptation per se, but a recurring by-product of the complex evolutionary landscape that sets cognitive, emotional and material conditions for ordinary human interactions. Religion involves extraordinary use of ordinary cognitive processes to passionately display costly devotion to counterintuitive worlds governed by supernatural agents. The conceptual foundations of religion are intuitively given by task-specific panhuman cognitive domains, including folkmechanics, folkbiology, folkpsychology. Core religious beliefs minimally violate ordinary notions about how the world is, with all of its (...) inescapable problems, thus enabling people to imagine minimally impossible supernatural worlds that solve existential problems, including death and deception. Here the focus is on folkpsychology and agency. A key feature of the supernatural agent concepts common to all religions is the triggering of an "Innate Releasing Mechanism," or “agency detector,” whose proper domain encompasses animate objects relevant to hominid survival - such as predators, protectors and prey - but which actually extends to moving dots on computer screens, voices in wind, faces on clouds. Folkpsychology also crucially involves metarepresentation, which makes deception possible and threatens any social order; however, these same metacognitive capacities provide the hope and promise of open-ended solutions through representations of counterfactual supernatural worlds that cannot be logically or empirically verified or falsified. Because religious beliefs cannot be deductively or inductively validated, validation occurs only by ritually addressing the very emotions motivating religion. Cross-cultural experimental evidence encourages these claims. (shrink)

This article compares treatments of the Stern–Gerlach experiment across different physical theories, building up to a novel analysis of electron spin measurement in the context of classical Dirac field theory. Modeling the electron as a classical rigid body or point particle, we can explain why the entire electron is always found at just one location on the detector but we cannot explain why there are only two locations where the electron is ever found. Using non-relativistic or relativistic quantum mechanics, we (...) can explain both uniqueness and discreteness. Moving to more fundamental physics, both features can be explained within a quantum theory of the Dirac field. In a classical theory of the Dirac field, the rotating charge of the electron can split into two pieces that each hit the detector at a different location. In this classical context, we can explain a feature of electron spin that is often described as distinctively quantum but we cannot explain another feature that could be explained within any of the other theories. (shrink)

We analyze the interrelation of quantum and classical entanglement. The latter notion is widely used in classical optic simulation of some quantum-like features of light. We criticize the common interpretation that “quantum nonlocality” is the basic factor differing quantum and classical realizations of entanglement. Instead, we point to the breakthrough Grangier et al. experiment on coincidence detection which was done in 1986 and played the crucial role in rejection of classical field models in favor of quantum mechanics. Classical entanglement sources (...) produce light beams with the coefficient of second order coherence \} \ge 1.\) This feature of classical entanglement is obscured by using intensities of signals in different channels, instead of counting clicks of photo-detectors. The interplay between intensity and clicks counting is not just a technicality. We elevate this issue to the high foundational level. (shrink)

Paul Feyerabend once made a remark to the effect that his pragmatic theory of observation can be traced back to proposals put forward by leading Logical Empiricists during the height of the protocol sentence debate. In this paper I want to vindicate the systematic side of Feyerabend’s remark and show that a pragmatic theory of observation can in fact be found in Rudolf Carnap’s writings of 1932. I first proceed to dispel a misunderstanding concerning the term “pragmatic” raised by Thomas (...) Oberdan. Following Morris’ and Carnap’s documented usage, I show that the intended meaning of “pragmatic” refers to a specific semiotic relation between users of a language and their environment describable by empirical means. I reconstruct such a pragmatic theory in terms of a detector model that interprets observation sentences as bodily dispositions indicating physical events in the surroundings of the detector. I then proceed to show how Feyerabend’s later theory of observation picks up central features of Carnap’s account and also shares some of the motivations. I conclude by noting how an empirical theory of observation sentences offers a bootstrapping solution to the “basis problem”. (shrink)

We propose a novel edge detector in the presence of Gaussian noise with the use of proximal support vector machine (PSVM). The edges of a noisy image are detected using a two-stage architecture: smoothing of image is first performed using regularized anisotropic diffusion, followed by the classification using PSVM, termed as regularized anisotropic diffusion-based PSVM (RAD-PSVM) method. In this process, a feature vector is formed for a pixel using the denoised coefficient’s class and the local orientations to detect edges (...) in all possible directions in images. From the experiments, conducted on both synthetic and benchmark images, it is observed that our RAD-PSVM approach outperforms the other state-of-the-art edge detection approaches, both qualitatively and quantitatively. (shrink)

Initial evaluation structures (IESs) currently proposed as the earliest detectors of affective stimuli (e.g., amygdala, orbitofrontal cortex, or insula) are high-order structures (a) whose response latency cannot account for the first visual cortex emotion-related response (~80 ms), and (b) lack the necessary infrastructure to locally analyze the visual features that define emotional stimuli. Several thalamic structures accomplish both criteria. The lateral geniculate nucleus (LGN), a first-order thalamic nucleus that actively processes visual information, with the complement of the thalamic reticular (...) nucleus (TRN) are proposed as core IESs. This LGN–TRN tandem could be supported by the pulvinar, a second-order thalamic structure, and by other extrathalamic nuclei. The visual thalamus, scarcely explored in affective neurosciences, seems crucial in early emotional evaluation. (shrink)

Artificial Immune Systems (AIS) are intelligent algorithms derived on the principles inspired by human immune system. In this research work, electroencephalography (EEG) signals for four distinct motor movement of human limbs are detected and classified using Negative Selection Classification Algorithm (NSCA). For this study, a widely studied open source EEG signal database (BCI IV - Graz dataset 2a, comprising 9 subjects) has been used. Mel Frequency Cepstral Coefficients (MFCCs) are extracted as selected feature from recorded EEG signals. Dimensionality reduction (...) of data is carried out by applying two hidden layered stacked auto-encoder. Genetic Algorithm (GA) optimized detectors (Artificial Lymphocytes) are trained using Negative Selection Algorithm (NSA) for detection and classification of four motor movements. The trained detectors consist of four sets of detectors, each set is trained for detection and classification of one of the four movements from the other three movements. The optimized radius of detector is small enough not to mis-detect the sample. Euclidean distance of each detector with every training dataset sample is taken and compared with optimized radius of detector as a non-self detector. Our proposed approach achieved a mean classification accuracy of 86.39% for limb movements over 9 subjects with a maximum individual subject classification accuracy of 97.5 % for subject number eight. (shrink)

High-spin states in the odd-odd N = Z nucleus Co-54 have been investigated by the fusion-evaporation reaction Si-28(S-32,1 alpha 1p1n)Co-54. Gamma-ray information gathered with the Ge detector array Gammasphere was correlated with evaporated particles detected in the charged particle detector system Microball and a 1 pi neutron detector array. A significantly extended excitation scheme of Co-54 is presented, which includes a candidate for the isospin T = 1, 6(+) state of the 1f(7/2)(-2) multiplet. The results are compared to large-scale shell-model (...) calculations in the fp shell. Effective interactions with and without isospin-breaking terms have been used to probe isospin symmetry and isospin mixing. A quest for deformed high-spin rotational cascades proved negative. This feature is discussed by means of cranking calculations. (shrink)

Two rotational bands have been identified and characterized in the proton-magic N = Z + 1 nucleus Ni-57. These bands complete the systematics of well-and superdeformed rotational bands in the light nickel isotopes starting from doubly magic Ni-56 to Ni-60. High-spin states in Ni-57 have been produced in the fusion-evaporation reaction Si-28(S-32, 2p1n)Ni-57 and studied with the gamma-ray detection array GAMMASPHERE operated in conjunction with detectors for evaporated light charged particles and neutrons. The features of the rotational bands in (...) Ni-57 are compared to those of neighbouring isotopes and interpreted by means of configuration-dependent cranked Nilsson-Strutinsky calculations. The two observed high-spin bands are considered signature partners and assigned to configurations with one 1g(9/2) proton and one 1g(9/2) neutron, resulting in an unambiguous understanding of the energetically favoured signature alpha = -1/2 band but a somewhat less satisfactory description of the signature alpha = +1/2 band. (shrink)

We study the synchronization of complex networks by using event-sampling information. The nodes of the network are connected with event-triggered communication via multiple couplings. The couplings are split into several channels. Not all the channels are connected. Only a part of the states of each node can be communicated by the channels. An event detector is designed for each channel to independently determine the sampling moments. The couplings of the network are partial and event-triggered. Both features make that less information (...) can be used for synchronization. The pinning controllers are also designed based on the sampled information. By establishing a time-dependent Lyapunov functional and utilizing an efficient event condition, we derive less conservative criteria for the synchronization of complex networks. Finally, the effectiveness of our main results is verified by an illustrative example, and comparisons are also presented to show how much conservatism can be reduced. (shrink)

The identification and analysis of the spatiotemporal dynamic traffic patterns in citywide road networks constitute a crucial process for complex traffic management and control. However, city-scale and synchronal traffic data pose challenges for such kind of quantification, especially during peak hours. Traditional studies rely on data from road-based detectors or multiple communication systems, which are limited in not only access but also coverage. To avoid these limitations, we introduce real-time, traffic condition digital maps as our input. The digital maps (...) keep spatiotemporal urban traffic information in nature and are open to access. Their pixel colors represent traffic conditions on corresponding road segments. We propose a stacked convolutional autoencoder-based method to extract a low-dimension feature vector for each input. We compute and analyze the distances between vectors. The statistical results show different traffic patterns during given periods. With the actual data of Chongqing city, we compare the feature extraction performance between our proposed method and histogram. The result shows our proposed method can extract spatiotemporal features better. For the same data set, there is little difference in the number distribution of red pixels found in the statistics result of the histogram, while differences do exist in the results of our proposed method. We find the most fluctuated morning is on Friday; the most fluctuated evening is on Tuesday; and the most stable evening is on Wednesday. The distance captured by our method can represent the evolution of different traffic conditions during the morning and evening peak hours. Our proposed method provides managers with assistance to sense the dynamics of citywide traffic conditions in quantity. (shrink)

Motivation: There is an ongoing search for definitive and reliable biomarkers to forecast or predict imminent seizure onset, but to date most research has been limited to EEG with sampling rates <1,000 Hz. High-frequency oscillations have gained acceptance as an indicator of epileptic tissue, but few have investigated the temporal properties of HFOs or their potential role as a predictor in seizure prediction. Here we evaluate time-varying trends in preictal HFO rates as a potential biomarker of seizure prediction.Methods: HFOs were (...) identified for all interictal and preictal periods with a validated automated detector in 27 patients who underwent intracranial EEG monitoring. We used LASSO logistic regression with several features of the HFO rate to distinguish preictal from interictal periods in each individual. We then tested these models with held-out data and evaluated their performance with the area-under-the-curve of their receiver-operating curve. Finally, we assessed the significance of these results using non-parametric statistical tests.Results: There was variability in the ability of HFOs to discern preictal from interictal states across our cohort. We identified a subset of 10 patients in whom the presence of the preictal state could be successfully predicted better than chance. For some of these individuals, average AUC in the held-out data reached higher than 0.80, which suggests that HFO rates can significantly differentiate preictal and interictal periods for certain patients.Significance: These findings show that temporal trends in HFO rate can predict the preictal state better than random chance in some individuals. Such promising results indicate that future prediction efforts would benefit from the inclusion of high-frequency information in their predictive models and technological architecture. (shrink)

Revealing the different types of deception and how to interpret body language and vocal clues, this reference shows how to spot deception from friends, lovers, colleagues, and strangers. Whether in the form of omission, misdirection, evasion, or bald-faced lie, attempts to deceive are ubiquitous in everyday life. With the right tools, inside knowledge from the latest psychological research, and a bit of practice, anyone can improve their ability to sniff out lies—from the well-intentioned white lie to the harmful whopper. Featuring (...) case studies and quizzes to test understanding and developing skill, this is an indispensable guide for anyone who wants to become a better lie detector—or even perfect their own deception techniques. (shrink)

In ‘Of Sensory Systems and the “Aboutness” of Mental States’, Kathleen Akins (1996) argues against what she calls ‘the traditional view’ about sensory systems, according to which they are detectors of features in the environment outside the organism. As an antidote, she considers the case of thermoreception, a system whose sensors send signals about how things stand with themselves and their immediate dermal surround (a ‘narcissistic’ sensory system); and she closes by suggesting that the signals from many sensory systems (...) may not in any familiar sense be about anything at all. Her presentation of the issues, however, overlooks resources available to ‘the traditional view’—or so I shall argue. Akins’s own thumbnail sketch of what is wrong with the traditional view is that it asks, concerning a given sensory system, ‘what is it detecting?’, when we should instead be asking ‘what is it doing?’ (352). Her point is that on the traditional view the function of a sensory system—what it's ‘for’—is to detect or indicate (values of) features of the outside environment. But at least on one version of the traditional view—namely Ruth Millikan’s—this would never be the sole or main proper function of a sensory system. (Akins does not list Millikan as a traditionalist, but Millikan fits squarely Akins’s description of them, since she believes in a naturalistic theory of aboutness and thinks it should begin with the senses.) For Millikan (1989, 1993), the proper function of a sensory system is in the first instance enabling behavioural systems—in the simplest case, motor routines—to perform their proper function. This they do, roughly, by switching on and steering the behavioural routines. Where features of the outside environment come in is as Normal (= assumed-by-the-design) conditions for the successful performance of the sensory system's proper function. That is, the only strategy for switching on and steering that is simple enough for evolution to have hit upon it, and reliable enough for evolution to have liked it, is a strategy which gears the steering to (values of) features of the outside environment. But as soon as one starts fleshing out the details of this story, one notices that they are probably quite different in the case of thermoreception from how they are with ‘distance’ senses such as vision and olfaction--a point which Akins overlooks.. (shrink)

High-frequency oscillations (HFO) are a promising biomarker for the identification of epileptogenic tissue. While HFO rates have been shown to predict seizure outcome, it is not yet clear whether their morphological features might improve this prediction. We validated HFO rates against seizure outcome and delineated the distribution of HFO morphological features. We collected stereo-EEG recordings from 20 patients (231 electrodes; 1,943 contacts). We computed HFO rates (the co-occurrence of ripples and fast ripples) through a validated automated detector during non-rapid eye (...) movement sleep. Applying machine learning, we delineated HFO morphological features within and outside epileptogenic tissue across mesial temporal lobe (MTL) and Neocortex. HFO rates predicted seizure outcome with 85% accuracy, 79% specificity, 100% sensitivity, 100% negative predictive value, and 67% positive predictive value. The analysis of HFO features showed larger amplitude in the epileptogenic tissue, similar morphology for epileptogenic HFO in MTL and Neocortex, and larger amplitude for physiological HFO in MTL. We confirmed HFO rates as a reliable biomarker for epilepsy surgery and characterized the potential clinical relevance of HFO morphological features. Our results support the prospective use of HFO in epilepsy surgery and contribute to the anatomical mapping of HFO morphology. (shrink)

Two studies examined gender differences in lying when the truth-telling bias prevailed and when inspiring lying and disbelief. The first study used 156 community participants in pairs. First, participants completed the Narcissistic Personality Inventory, the Lie- and Truth Ability Assessment Scale, and the Rational-Experiential Inventory. Then, they participated in a deception game where they performed as senders and receivers of true and false communications. Their goal was to retain as many points as possible according to a payoff matrix that specified (...) the reward they would gain for any possible outcome. Results indicated that men lied more and were more successful lie-tellers than women. In addition, men believed the sender less than women but were not more successful detectors of lies and truths. Higher perceived lie-telling ability, narcissistic features, and experiential thinking style explained men’s performance. The second study used 100 volunteers who underwent the same procedure. However, the payoff matrix encouraged lying and disbelieving. Results showed again that men lied more than women. As to performance, men were more successful lie detectors than women, but there was no truth detection difference. Women did not differ in their success in telling and detecting lies and truths. The inconsistent gender differences in production and detection lies and truths dictate caution in interpreting them. (shrink)

Speaker recognition under mismatched conditions is a challenging task. Speech signal is nonlinear and nonstationary, and therefore, difficult to analyze under realistic conditions. Also, in real conditions, the nature of the noise present in speech data is not known a priori. In such cases, the performance of speaker identification or speaker verification degrades considerably under realistic conditions. Any SR system uses a voice activity detector as the front-end subsystem of the whole system. The performance of most VADs deteriorates at the (...) front end of the SR task or system under degraded conditions or in realistic conditions where noise plays a major role. Recently, speech data analysis and processing using Norden E. Huang’s empirical mode decomposition combined with Hilbert transform, commonly referred to as Hilbert–Huang transform, has become an emerging trend. EMD is an a posteriori, adaptive, data analysis tool used in time domain that is widely accepted by the research community. Recently, speech data analysis and speech data processing for speech recognition and SR tasks using EMD have been increasing. EMD-based VAD has become an important adaptive subsystem of the SR system that mostly mitigates the effect of mismatch between the training and the testing phase. Recently, we have developed a VAD algorithm using a zero-frequency filter-assisted peaking resonator and EMD. In this article, the efficacy of an EMD-based VAD algorithm is studied at the front end of a text-independent language-independent SI task for the speaker’s data collected in three languages at five different places, such as home, street, laboratory, college campus, and restaurant, under realistic conditions using EDIROL-R09 HR, a 24-bit wav/mp3 recorder. The performance of this proposed SI task is compared against the traditional energy-based VAD in terms of percentage identification rate. In both cases, widely accepted Mel frequency cepstral coefficients are computed by employing frame processing from the extracted voiced speech regions using the respective VAD techniques from the realistic speech utterances, and are used as a feature vector for speaker modeling using popular Gaussian mixture models. The experimental results showed that the proposed SI task with the VAD algorithm using ZFFPR and EMD at its front end performs better than the SI task with short-term energy-based VAD when used at its front end, and is somewhat encouraging. (shrink)

In our previous work, a new approach to the notorious problem of quantum measurement was proposed. Existing treatments of the problem were incorrect because they ignored the disturbance of measurement by identical particles and standard quantum mechanics had to be modified to obey the cluster separability principle. The key tool was the notion of separation status. Changes of separation status occur during preparations, registrations and scattering on macroscopic targets. Standard quantum mechanics does not provide any correct rules that would govern (...) these changes. This gives us the possibility to add new rules to quantum mechanics that would satisfy the objectification requirement. The method of the present paper is to start from the standard unitary evolution and then introduce minimal corrections. Several representative examples of registration and particle scattering on macroscopic targets are analysed case by case in order to see their common features. The resulting general Rule of Separation Status Changes is stated in the Conclusion. (shrink)

The study addresses the cyclically temporal aspect of sequence recognition, storage and recall using the Recurrent Oscillatory Self-Organizing Map (ROSOM), first introduced by Kaipainen, Papadopoulos and Karhu (1997). The unique solution of the network is that oscillatory States are assigned to network units, corresponding to their `readiness-to-fire''. The ROSOM is a categorizer, a temporal sequence storage system and a periodicity detector designed for use in an ambiguous cyclically repetitive environment. As its external input, the model accepts a multidimensional stream of (...) environment-describing feature configurations with implicit periodicities. The output of the model is one or a few closed cycles abstracted from such a stream, mapped as trajectories on a two-dimensional sheet with an organization reminiscent of multi-dimensional scaling. The model''s capabilities are explored with a variety of workbench data. (shrink)

This paper discusses the introduction of fraudulent “molecular detector” technology into Mexico. The case is used to argue that contemporary science and technology studies’ approaches to scientific policy-making make basic assumptions about the societies they operate in that are inconsistent with the Mexican context. This paper also argues that contrary to what happens in the so-called Global North, the relative power of Mexican science in government and policy circles is as much limited by its relatively weak position as much as (...) it is by self-censorship and unrealized impact in the country’s fragile democracy. The case is also used to highlight the necessity for more politically involved scientific institutions in Mexico, as these become critical safeguards against incoming destabilizing technologies from more powerful nations into the local “peripheral” context. (shrink)

We consider the questions of whether or not large language models (LLMs) have beliefs, and, if they do, how we might measure them. First, we consider whether or not we should expect LLMs to have something like beliefs in the first place. We consider some recent arguments aiming to show that LLMs cannot have beliefs. We show that these arguments are misguided. We provide a more productive framing of questions surrounding the status of beliefs in LLMs, and highlight the empirical (...) nature of the problem. With this lesson in hand, we evaluate two existing approaches for measuring the beliefs of LLMs, one due to Azaria and Mitchell (The internal state of an llm knows when its lying, 2023) and the other to Burns et al. (Discovering latent knowledge in language models without supervision, 2022). Moving from the armchair to the desk chair, we provide empirical results that show that these methods fail to generalize in very basic ways. We then argue that, even if LLMs have beliefs, these methods are unlikely to be successful for conceptual reasons. Thus, there is still no lie-detector for LLMs. We conclude by suggesting some concrete paths for future work. (shrink)

Discovering high-level causal relations from low-level data is an important and challenging problem that comes up frequently in the natural and social sciences. In a series of papers, Chalupka etal. (2015, 2016a, 2016b, 2017) develop a procedure forcausal feature learning (CFL) in an effortto automate this task. We argue that CFL does not recommend coarsening in cases where pragmatic considerations rule in favor of it, and recommends coarsening in cases where pragmatic considerations rule against it. We propose a new (...) technique, pragmatic causal feature learning (PCFL), which extends the original CFL algorithm in useful and intuitive ways. We show that PCFL has the same attractive measure-theoretic properties as the original CFL algorithm. We compare the performance of both methods through theoretical analysis and experiments. (shrink)

The influence of light on the lives of living organisms is all-pervasive, affecting movement, vision, behavior, and physiological activity. This book is a biophysically grounded comparative survey of how animals detect light and perceive their surroundings. Included are discussions of photoreceptors, light emitters, and eyes. The book focuses in particular on the kinds of optical systems that have evolved, beginning with unicellular organisms that detect and respond to light through to more advanced and complex designs for imaging. The relevance of (...) these studies extends beyond biology, since these findings can be used to help develop photoreceptor energy conversion and information systems, and optical imaging devices with a wide range of everyday applications. The book will appeal to biophysicists, photobiologists, bioengineers, neuroscientists, and all researchers working in the area of vision and visual optics. (shrink)

Terms of service of on-line platforms too often contain clauses that are potentially unfair to the consumer. We present an experimental study where machine learning is employed to automatically detect such potentially unfair clauses. Results show that the proposed system could provide a valuable tool for lawyers and consumers alike.

The idea that concepts play a significant role in some perceptions is widespread but everybody seems to differ as to where to draw the line. Some researchers say that the difference between direct and indirect, concept driven acts of perception manifests itself whenever we perceive abstract or general properties. Others point at second order properties or causal properties. I call this inability to precisely differentiate between acts of direct and indirect perception “The Division Problem”. Furthermore there is always a question (...) as to how widespread indirect perceptions are. Can we attribute them to prelingual cognitive systems? I call this second problem “The Distribution Problem”. -/- The main aim of the paper is providing a solution to both problems by proposing a naturalistic explication of the notion of “concept”. -/- I propose to identify the role concepts were supposed to play in perception with a mechanism of “soft detection”. Unlike hard detectors which react to a specific target in virtue of their constitution and placement in the system, soft detectors are understood as dynamic categorization devices enabling the cognitive system to selectively react to an undetectable property via flexible exploitation of data from hard detectors. -/- I conclude by showing how the notion of soft detection retains some of the aspects traditionally attributed to concepts and how does it differ from similar accounts known from contemporary literature. (shrink)

Recent work by Wan and McLean has shown that all quantum measurements may be reduced to local position measurements. Using an array of particle detectors as the measuring apparatus we show how a model employing superselection rules and unitary evolution leads to a single detector triggering in each act of measurement. We also present an explicit model of particle detection as a unitary ionization process producing a single ion in the detector, subsequent amplification of which to the visible can (...) be described adequately in classical terms. (shrink)