Here, a streamlined, scalable, laboratory approach is discussed that enables medium‐to‐large dataset analysis. The presented approach combines data management, artificial intelligence, containerization, cluster orchestration, and quality control in a unified analytic pipeline. The unique combination of these individual building blocks creates a new and powerful analysis approach that can readily be applied to medium‐to‐large datasets by researchers to accelerate the pace of research. The proposed framework is applied to a project that counts the number of plasmonic nanoparticles bound to peripheral (...) blood mononuclear cells in dark‐field microscopy images. By using the techniques presented in this article, the images are automatically processed overnight, without user interaction, streamlining the path from experiment to conclusions. (shrink)

We review state‐of‐the‐art computational methods for constructing, from image data, generative statistical models of cellular and nuclear shapes and the arrangement of subcellular structures and proteins within them. These automated approaches allow consistent analysis of images of cells for the purposes of learning the range of possible phenotypes, discriminating between them, and informing further investigation. Such models can also provide realistic geometry and initial protein locations to simulations in order to better understand cellular and subcellular processes. To determine (...) the structures of cellular components and how proteins and other molecules are distributed among them, the generative modeling approach described here can be coupled with high throughput imaging technology to infer and represent subcellular organization from data with few a priori assumptions. We also discuss potential improvements to these methods and future directions for research. (shrink)

Graphical AbstractDeep learning, data management, automated processing, virtualisation, clustering and cloud computing should be part of the lexicon of biomedical researchers. In article number 1900004, Germán González and Conor L. Evans show that these techniques can be used to turn large amounts of data into actionable insights. The authors apply them to generate an automated image analysis pipeline that performs cell detection, cell analysis, offers a quality control interface and fi nally aggregates the data to draw (...) conclusions, Biomedical Image Processing with Containers and Deep Learning: An Automated Analysis Pipeline DOI: 10.1002/bies.201900004. (shrink)

Most experimental studies of facial expression processing have used static stimuli (photographs), yet facial expressions in daily life are generally dynamic. In its original photographic format, the Karolinska Directed Emotional Faces (KDEF) has been frequently utilized. In the current study, we validate a dynamic version of this database, the KDEF-dyn. To this end, we applied animation between neutral and emotional expressions (happy, sad, angry, fearful, disgusted, and surprised; 1,033-ms unfolding) to 40 KDEF models, with morphing software. Ninety-six human observers (...) categorized the expressions of the resulting 240 video-clip stimuli, and automated face analysis assessed the evidence for 6 expressions and 20 facial action units (AUs) at 31 intensities. Low-level image properties (luminance, signal-to-noise ratio, etc.) and other purely perceptual factors (e.g., size, unfolding speed) were controlled. Human recognition performance (accuracy, efficiency, and confusions) patterns were consistent with prior research using static and other dynamic expressions. Automated assessment of expressions and AUs was sensitive to intensity manipulations. Significant correlations emerged between human observers’ categorization and automated classification. The KDEF-dyn database aims to provide a balance between experimental control and ecological validity for research on emotional facial expression processing. The stimuli and the validation data are available to the scientific community. (shrink)

Throughout his cinema studies, Deleuze tends to define and to praise the cinematic in opposition to the theatrical. Cinema, for Deleuze, retains the potential to automate our perception of its images. Further, this capacity allows the cinema to profoundly disrupt the habitual patterns of its audience's thought. This article asks, however, whether Beckett's theatrical practice can be productively analysed through concepts derived from Deleuze's work on the cinema. In Beckett's Play and Not I, we see theatrical productions that strive for (...) and attain an automation of their audience's perception. While this theatrical experience is not identical to the ‘camera-consciousness’ that Deleuze observes in film, it can be understood through Deleuze's (Bergsonian) processes of habitual and attentive recognition, their failure and their subsequent transformation into passages of crystalline description. Finally, we can begin to elaborate the novel idea of a ‘crystal-theatre’; a theatre where the audience are entrapped within its construction, caught in a loop or circuit that runs between and complicates the realms of reality and illusion, immediately lived experience and artistic representation, the actual and the virtual. (shrink)

Bioassessment is the process of using living organisms to assess the ecological health of a particular ecosystem. It typically relies on identifying specific organisms that are sensitive to changes in environmental conditions. Benthic macroinvertebrates are widely used for examining the ecological status of freshwaters. However, a time-consuming process of species identification that requires high expertise represents one of the key obstacles to more precise bioassessment of aquatic ecosystems. Partial automation of this process using deep learning-based image classification is the (...) goal of an ongoing project AIAQUAMI we are participating in. One of the project goals is to develop software support for image classification with visualization and reporting. For that purpose, we developed desktop and web applications that we open-sourced as Imagelytics Suite. Both desktop and web applications rely on a convolutional neural network (CNN) to classify images and the Grad-CAM algorithm to produce heatmaps of the image areas that mostly influenced the network decision. Along with the source code of the applications, we also open-sourced scripts that can be used to train CNN on an arbitrary dataset and produce required metadata, so it can be used with Imagelytics applications. In this article, we presented technical details regarding the design of the applications and the training method that will enable their general use for image classification tasks. As a part of the evaluation, we will show a use case related to species identification of non-biting midges (Diptera: Chironomidae). (shrink)

How can one ‘see’ the operationalization of contemporary visual culture, given the imperceptibility and apparent automation of so many processes and dimensions of visuality? Seeing – as a position from a singular mode of observation – has become problematic since many visual elements, techniques, and forms of observing are highly distributed through data practices of collection, analysis and prediction. Such practices are subtended by visual cultural techniques that are grounded in the development of image collections, image formatting and (...) hardware design. In this article, we analyze recent transformations in forms of prediction and data analytics associated with spectacular performances of computation. We analyze how transformations in the collection and accumulation of images as ensembles by platforms have a qualitative and material effect on the emergent sociotechnicality of platform ‘life’ and ‘perception’. Reconstructing the visual transformations that allow artificial intelligence assemblages to operate allows some sense of their heteronomous materiality and contingency. (shrink)

In the past twenty years, all the key authors who wrote about the state of postmodernity either began to be engaged in other research areas (Fredric Jameson) or declared that the postmodernism is dead (Linda Hutcheon). Since 2000, when the fatigue from the postmodernism became evident to everyone, various researchers, critics and theorists began to offer their concepts of our era. However, all these theories, emphasizing the change of cultural paradigms, interpret culture traditionally not paying attention to total digitalization and (...) the introduction of new technologies into our lives. However, in two concepts of our time these processes become central. These are the concepts of the digimodern and automodern. The focus of this article is the idea of automodernism, proposed by the American social theorist Robert Samuels in 2007/2009. He believes that our world is characterized by two contradictory tendencies – automation and the desire for autonomy (personal freedom). From his point of view, the former often does not allow to reach the latter due to certain circumstances. Samuels, using the example of a car, a personal computer, the Internet, etc., shows what exactly our culture is in the broadest sense. Analyzing the concept of “digital youth,” he also pays attention to the formation of a new subjectivity of the era of automodernity. Finally, the most interesting part of the concept of automodernism, which is most relevant today, is the criticism of leftwing social and philosophical concepts (Slavoj Žižek, Jameson) and cultural theories (Henry Jenkins). At the end of the article, the author mentions Adam Greenfield’s latest book Radical Technologies: The Design of Everyday Life. Thanks to this book, Samuels’ theory can be verified. (shrink)

This volume explores how functional brain imaging techniques like positron emission tomography have influenced cognitive studies. The first chapter outlines efforts to relate human thought and cognition in terms of great books from the late 1800s through the present. Chapter 2 describes mental operations as they are measured in cognitive science studies. It develops a framework for relating mental operations to activity in nerve cells. In Chapter 3, the PET method is reviewed and studies are presented that use PET to (...) map the striate cortex and to activate extrastriate motion, color, and form areas. Chapter 4 shows how top down processes involving attention can lead to activation of these same areas in the detection of targets, visual search, and visual imagery. This chapter reveals complex networks of activations. Chapters 5 and 6 deal with the presentation of words. Chapter 5 illustrates PET studies of the anatomy of visual word processing and shows how the circuitry used for generating novel uses of words changes as the task becomes automated. Chapter 6 applies high density electrical recording to explore these activations in real time and to show how a constant anatomy can be reprogrammed by task instructions to produce and perform different cognitive tasks. Chapter 7 shows how studies of brain lesions and PET converge on common networks underlying attentional functions such as visual orienting, target detection, and maintenance of the alert state. Chapters 8 and 9 apply the network approach to examine normal development of attention in infants and pathological conditions resulting from brain damage, and psychiatric pathologies of depression, schizophrenia, and attention deficit disorder. In Chapter 10, new developments such as functional MRI are discussed in terms of future developments and integration of cognitive neuroscience. (shrink)

Algorithmic vision, the computational process of making meaning from digital images or visual information, has changed the relationship between the image and the human subject. In this paper, I explicate on the role of algorithmic vision as a technique of algorithmic governance, the organization of a population by algorithmic means. With its roots in the United States post-war cybernetic sciences, the ontological status of the computational image undergoes a shift, giving way to the hegemonic use of automated (...) facial recognition technologies towards predatory policing and profiling practices. By way of example, I argue that algorithmic vision reconfigures the philosophical links between vision, image, and truth, paradigmatically changing the way a human subject is represented through imagistic data. With algorithmic vision, the relationship between subject and representation challenges the humanistic discourse around images, calling for a critical displacement of the human subject from the center of an analysis of how computational images make meaning. I will explore the relationship between the operative image, the image that acts but is not seen by human eyes, and what Louise Amoore calls an “emergent subject,” a subject that is made visible through algorithmic techniques. Algorithmic vision reveals subjects to power in a mode that requires a new approach towards analyzing the entanglement and invisiblization of the human in automated decision-making systems. (shrink)

Content-based image retrieval (CBIR) is a technique used to retrieve image from an image database. However, the CBIR process suffers from less accuracy to retrieve many images from an extensive image database and prove the privacy of images. The aim of this article is to address the issues of accuracy utilizing deep learning techniques such as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon–Kim–Kim–Song (CKKS). The system (...) has been proposed, namely RCNN_CKKS, which includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a new dataset. In the second part (online processing), the client sends the encrypted image to the server, which depends on the CNN model trained to extract features of the sent image. Next, the extracted features are compared with the stored features using a Hamming distance method to retrieve all similar images. Finally, the server encrypts all retrieved images and sends them to the client. Deep-learning results on plain images were 97.87% for classification and 98.94% for retriever images. At the same time, the NIST test was used to check the security of CKKS when applied to Canadian Institute for Advanced Research (CIFAR-10) dataset. Through these results, researchers conclude that deep learning is an effective method for image retrieval and that a CKKS method is appropriate for image privacy protection. (shrink)

Advances in artificial intelligence, as well as its increased presence in everyday life, have brought the emergence of many new phenomena, including an intriguing appearance of what seems to be a variant of body dysmorphic disorder, coined “Snapchat dysmorphia”. Body dysmorphic disorder is a DSM-5 psychiatric disorder defined as a preoccupation with one or more perceived defects or flaws in physical appearance that are not observable or appear slight to others. Snapchat dysmorphia is fueled by automated selfie filters that (...) reflect unrealistic sociocultural standard. In this paper, we discuss how body dysmorphic disorder and related body image distortions could arise, using the conceptual resources provided by the active inference framework. We suggest that these disorders involve dysfunctional self-modelling which entails maladaptive internalization of sociocultural preferences during adolescent identity formation. Identity formation is hereby described as cycles of interpersonal active inference that arbitrate between identity exploration and commitment. We propose that impaired self-modelling is unable to reduce interpersonal uncertainty during identity exploration, which, over time, degenerates into uncontrollable epistemic habits that isolate the body image from corrective sensory evidence. In light of these insights, we subsequently explore some of the consequences of image-centered social media platforms on the identity formation process. We conclude that heightened interpersonal uncertainty in this novel context could precipitate the onset of body dysmorphic disorder and related body image distortions, particularly when selfie filters are involved. (shrink)

The ongoing coronavirus 2019 pandemic caused by the severe acute respiratory syndrome coronavirus 2 has resulted in a severe ramification on the global healthcare system, principally because of its easy transmission and the extended period of the virus survival on contaminated surfaces. With the advances in computer-aided diagnosis and artificial intelligence, this paper presents the application of deep learning and adversarial network for the automatic identification of COVID-19 pneumonia in computed tomography scans of the lungs. The complexity and time limitation (...) of the reverse transcription-polymerase chain reaction swab test makes it disadvantageous to depend solely on as COVID-19’s central diagnostic mechanism. Since CT imaging systems are of low cost and widely available, we demonstrate that the drawback of the RT-PCR can be alleviated with a faster, automated, and reduced contact diagnostic process via the use of a neural network model for the classification of infected and noninfected CT scans. In our proposed model, we explore the benefit of transfer learning as a means of resolving the problem of inadequate dataset and the importance of semisupervised generative adversarial network for the extraction of well-mapped features and generation of image data. Our experimental evaluation indicates that the proposed semisupervised model achieves reliable classification, taking advantage of the reflective loss distance between the real data sample space and the generated data. (shrink)

After the Event Horizon Telescope Collaboration released in April 2019 the first empirical images of a black hole, an astrophysical object previously thought “unseeable,” much of the public discourse has approached these images as straightforward visual depictions of a black hole. This article challenges this view by showing that the first images of a black hole went beyond merely making an invisible cosmic object visible and that the images published in April 2019 were just the first in a series of (...) black hole images the researchers continue producing. Drawing primarily on Sybille Krämer’s concept of the cartographic impulse, the article demonstrates that the Event Horizon Telescope images are, first and foremost, epistemic tools. These epistemic tools enable researchers to actively explore various physical aspects and dynamic properties of a black hole’s immediate environment and test theoretical predictions about it, thus making this elusive environment empirically knowable. To demonstrate this, the article analyses the mapping operations that combined automated algorithmic procedures with expert human judgment and through which these images were produced, read, and interpreted. It also examines how the different Event Horizon Telescope images relate to one another, which particular epistemic functions they fulfil in the research context, under which conditions, and with which limitations, thus tracing how these images facilitate the production of new scientific knowledge about black holes. (shrink)

The unprecedented development of medical informatics is constantly transforming the concept of expertise in medical sciences in a way that has far-reaching consequences for both the theory of knowledge and the philosophy of informatics. Deep medicine is based on the assumption that medical diagnosis should take into account the wide array of possible health factors involved in the diagnostic process, such as not only genome analysis alone, but also the metabolome (analysis of all body metabolites important for e.g. drug-drug interactions), (...) microbiome (i.e. analysis of all bodily microorganisms interacting with host cells) or exposome (analysis of all environmental factors triggering potentially harmful cell mutations, such as UV radiation, heavy metals, various carcinogens, etc.). Deep data analysis is of tantamount importance for personalized diagnosis but, at the same time, hardly achievable by a regular human being. However, adequately designed artificial intelligence (e.g. a deep neural network) can undeniably be of great help for finding correlations between symptoms and underlying diseases. Nowadays AI applies to nearly every aspect of medicine, starting from the data analysis of scientific literature, through the diagnostic process, to the act of communication between physicians and their patients. Medical image processing algorithms greatly enhance the chances of successful recognition of melanoma or intestinal polyps. Communication tools designed for physicians use techniques known from social media to provide users with an opportunity to consult the case with colleagues from the same discipline. Natural language processing tools significantly improve doctor-patient communication by the automation of note-taking. Is this enough to support the claim that the non-epistemic competences in medicine are becoming more and more important? Can we attribute expertise only to a person? How is medical informatics changing the way most people usually understand human-computer interactions? (shrink)

Systems with human-centered artificial intelligence are always as good as their ability to consider their users’ context when making decisions. Research on identifying people’s everyday activities has evolved rapidly, but little attention has been paid to recognizing both the activities themselves and the motions they make during those tasks. Automated monitoring, human-to-computer interaction, and sports analysis all benefit from Web 4.0. Every sport has gotten its move, and every move is not known to everyone. In ice hockey, every move (...) cannot be monitored by the referee. Here, Convolution Neural Network-based Real-Time Image Processing Framework (CNN-RTIPF) is introduced to classify every move in Ice Hockey. CNN-RTIPF can reduce the challenges in monitoring the player’s move individually. The image of every move is captured and compared with the trained data in CNN. These real-time captured images are processed using a human-centered artificial intelligence system. They compared images predicted by probability calculation of the trained set of images for effective classification. Simulation analysis shows that the proposed CNN-RTIPF can classify real-time images with improved classification ratio, sensitivity, and error rate. The proposed CNN-RTIPF has been validated based on the optimization parameter for reliability. To improve the algorithm for movement identification and train the system for many other everyday activities, human-centered artificial intelligence-based Web 4.0 will continue to develop. (shrink)

In step with rapid advancements in computer vision, vehicle classification demonstrates a considerable potential to reshape intelligent transportation systems. In the last couple of decades, image processing and pattern recognition-based vehicle classification systems have been used to improve the effectiveness of automated highway toll collection and traffic monitoring systems. However, these methods are trained on limited handcrafted features extracted from small datasets, which do not cater the real-time road traffic conditions. Deep learning-based classification systems have been proposed (...) to incorporate the above-mentioned issues in traditional methods. However, convolutional neural networks require piles of data including noise, weather, and illumination factors to ensure robustness in real-time applications. Moreover, there is no generalized dataset available to validate the efficacy of vehicle classification systems. To overcome these issues, we propose a convolutional neural network-based vehicle classification system to improve robustness of vehicle classification in real-time applications. We present a vehicle dataset comprising of 10,000 images categorized into six-common vehicle classes considering adverse illuminous conditions to achieve robustness in real-time vehicle classification systems. Initially, pretrained AlexNet, GoogleNet, Inception-v3, VGG, and ResNet are fine-tuned on self-constructed vehicle dataset to evaluate their performance in terms of accuracy and convergence. Based on better performance, ResNet architecture is further improved by adding a new classification block in the network. To ensure generalization, we fine-tuned the network on the public VeRi dataset containing 50,000 images, which have been categorized into six vehicle classes. Finally, a comparison study has been carried out between the proposed and existing vehicle classification methods to evaluate the effectiveness of the proposed vehicle classification system. Consequently, our proposed system achieved 99.68%, 99.65%, and 99.56% accuracy, precision, and F1-score on our self-constructed dataset. (shrink)

The implicit activities of the living body in sports (such as heart rate, involuntary gestures, stress, reflex, emotional regulation and interaction expressions) emerge in the consciousness of the lived body without our voluntary control. We demonstrate physiological emersion, and how, including in dramaturgical perception, physiological flows and processes collide with the image of a whole body. In this paper, we introduce corporeal non-property as the missing (?) link between phenomenology and neuroscience, renewed by research on the cerebral unconscious and (...) the perception of their lived body. Rather than mindfulness, physical activity obliges the subject to learn the unconscious and his motor skills from his living body: a new psychoanalysis of sport is thus established by studying what emerges from the activity of the living body up to the level of the conscious description of motor action. In this paper, we explain why that awareness occurs, and why it matters for the understanding of unconscious activity of the athlete’s living body. This is potentially interesting, although it needs, as a theory, to overcome the obvious reliance of the body on unconscious or habitual/automated physiological processes. But the incorporation of body techniques forms a habitus. (shrink)

Bioimage analysis plays a critical role in extracting information from biological images, enabling deeper insights into cellular structures and processes. The integration of machine learning and deep learning techniques has revolutionized the field, enabling the automated, reproducible, and accurate analysis of biological images. Here, we provide an overview of the history and principles of machine learning and deep learning in the context of bioimage analysis. We discuss the essential steps of the bioimage analysis workflow, emphasizing how machine learning and (...) deep learning have improved preprocessing, segmentation, feature extraction, object tracking, and classification. We provide examples that showcase the application of machine learning and deep learning in bioimage analysis. We examine user‐friendly software and tools that enable biologists to leverage these techniques without extensive computational expertise. This review is a resource for researchers seeking to incorporate machine learning and deep learning in their bioimage analysis workflows and enhance their research in this rapidly evolving field. (shrink)

The EU AI Act is the first step toward a comprehensive legal framework for AI. It introduces provisions for AI systems based on their risk levels in relation to fundamental rights. Providers of AI systems must conduct Conformity Assessments before market placement. Recent amendments added Fundamental Rights Impact Assessments for high-risk AI system users, focusing on compliance with EU and national laws, fundamental rights, and potential impacts on EU values. The paper suggests that automating business process compliance can help standardize (...) these assessments and outlines some methodological guidelines. (shrink)

In many scientific fields, today’s practices of empirical enquiry rely heavily on the production of images that display the investigated phenomena. And while scientific images of phenomena have been important for a long time, what is striking now is that scientists have found ways to visualize such widely different types of phenomena. In the past twenty or thirty years, we have become accustomed to seeing images of galaxies, of cells, of the human brain but also of blood flow or of (...) turbulent fluids. This success in making images relies first on the set of imaging devices that have flourished in the twentieth century, instruments such as radio-telescopes, electronic microscopes, MRI and many more. Without these... (shrink)

Automated facial recognition methods have become widely used as a way to ascertain the identity of individuals. Yet the methods by which facial recognition technologies (FRT) operate – the machinic performance of the perception of the human face – are often invisible to those under their gaze. This article investigates the machinic perception of the face through an FRT method known as eigenface, in order to both reveal and problematize the ways of seeing that underlie it. As part of (...) its algorithmic processes, eigenface produces an image. This image can be understood as a portrait of machine recognition, making visible the processes through which the algorithm performs recognition and ‘sees’ the human face. The eigenface portrait reveals a way of seeing that is based on statistical processes of pattern recognition. An analogue antecedent of this application of statistics to the recognition of facial images can be found in the composite portrait. Through a dialectical discussion of composite portraiture in multiple disciplinary fields ranging from sociology to philosophy and the visual arts, this article experiments with providing a cultural and social translation of machine processes of visual perception. The discussion shifts the focus of enquiry towards the aesthetics of the algorithmic process in order to provide an entry point for critique and a possible reimagination on algorithmic knowledge production. (shrink)

In terms of image processing, encryption plays the main role in the field of image transmission. Using one algorithm of deep learning, such as neural network backpropagation, increases the performance of encryption by learning the parameters and weights derived from the image itself. The use of more than one layer in the neural network improves the performance of the algorithm. Also, in the process of image encryption, randomness is an important component, especially when used by (...) smart learning methods. Deep neural networks are related to pixels used to manipulate position and value according to the predicted new value given from a variable neural system. It also includes messy encrypted images used via applying randomness and increasing the key space in addition to using the logistic and Henon map for complexity. The main goal of any encryption method is to increase the complexity of the encrypted image to be difficult or impossible to decrypt the image without the proposed key. One of the important measurements for image encryption is the histogram and how it can be uniformed by the proposed method. Variables of randomness are used as features for the deep learning system, with feedback during iteration. An ideal image processing encryption yields high messy images by keeping the quality. Experimental results showed the backpropagation algorithm achieved better results than other algorithms. (shrink)

This paper is an attempt of proposing the processing approach of neutrosophic technique in image processing.

Images are an important source of data and information in the agricultural sciences. The use of image-processing techniques has outstanding implications for the analysis of agricultural operations. Fruit and vegetable classification is one of the major applications that can be utilized in supermarkets to automatically detect the kinds of fruits or vegetables purchased by customers and to determine the appropriate price for the produce. Training on-site is the underlying prerequisite for this type of arrangement, which is generally caused (...) by the users having little or no expert knowledge. We explored various methods used in addressing fruit and vegetable classification and in recognizing fruit disease problems. We surveyed image-processing approaches used for fruit disease detection, segmentation and classification. We also compared the performance of state-of-the-art methods under two scenarios, i.e., fruit and vegetable classification and fruit disease classification. The methods surveyed in this paper are able to distinguish among different kinds of fruits and their diseases that are very alike in color and texture. (shrink)

Filmmaking with Artificial Intelligence Image Generation Models In just about one year, OpenAI’s release of ChatGPT 4 has caused panic in our daily lives. After a year, OpenAI introduced Sora, a moving image-generating model from text, similar to DALL-E for still images. Even though Sora is not yet available to the public, the very potential itself has raised issues in film production from the perspectives of producers and studios, as well as directors, actors, writers, and editors. In this (...) chapter, the role and expected impact of AI video generation technologies, such as OpenAI Sora and Stable Diffusion 3, will be considered in regard to filmmaking. To discuss these issues, it is necessary to further analyze the concept of artificial intelligence, what it means, and how it is misunderstood by the general public. These misunderstandings also lead to sci-fi fantasy and doomsday talk, adding nothing valuable to the debate. Once this concept is defined, the argument of why an artificial general intelligence akin to a human being is unlikely will be set, mostly referring to Hubert Dreyfus and David Chalmers. However, even though the good old-fashioned AI seems impossible, the AI tools we have now seem to be enough to cause many of the problems that the thought of a complete artificial intelligence also brings forth. It is important to treat these tools as tools and not entities in their current forms to focus on the more practical problems regarding human labor, interaction, and experience in the world. In this regard, it is important to look back in history to see how technology has shifted ways of making films. When thought of as such, it becomes clearer that these tools will likely not end human involvement in the practice of creating art but transform the methods and aesthetics of film production, challenging conventions in both artistic and commercial works in some ways and exaggerating them in others. Furthermore, the chapter will consist of the investigation of the impact of various AI tools on human creativity. Regarding human creativity, commercial films will most likely go through a paradigm shift. Production companies will most likely regard this shift as a way of improving performance and production. However, this advancement poses dire questions in the field and pursuit of creating art. AI tools help automate and accelerate the filmmaking process at the cost of filmmaking as an art form. The discussion will address why commercial filmmaking will see a paradigm shift and loss of some human labor, but in an optimistic world of philosophical thought, film as fine art will gain much in return. This is because AI tools in their current and foreseeable state are not capable of willing to make art due to their limitations regarding embodied cognition, experience, unconsciousness, and intuition. These things make us what we are more than we think. There is no better way to explain why human beings make art than to show how tools do not matter but the ideas and the will to do it. -/- . (shrink)

Modifying images for scientific publication is now quick and easy due to changes in technology. This has created a need for new image processing guidelines and attitudes, such as those offered to the research community by Doug Cromey (Cromey 2010). We suggest that related changes in technology have simplified the task of detecting misconduct for journal editors as well as researchers, and that this simplification has caused a shift in the responsibility for reporting misconduct. We also argue that (...) the concept of best practices in image processing can serve as a general model for education in best practices in research. (shrink)

AI-generated images of “cats” offer novel opportunities to consider the semic role of expectations in sign formation where they act as constraints on semiosis through the potential identification of the AImage as “correct,” or as a “glitch.” Because the identification of “errors” depends on a range of technical and cultural expertise, they offer valuable insights into the interpretive process. The automated generation of media by AI separates the artist’s decision-making process from image production, continuing a trajectory that began (...) with the invention of photography in the nineteenth century that brings the sign formation process into consciousness by distinguishing “intentional” and “unintentional” encoding. The identification AI-produced images as-glitched provides a vehicle to consider how the sign formation process informs identifications of creative action as an intentional action: aesthetic appraisals are central to this process where cultural beliefs about creativity become ideological constraints on interpretation. The potential to understand AI “glitches” as expressive features of the image-object, rather than errors, proceeds via the aesthetics and affects of earlier art, such as the “painterly motion” shown in old master paintings by Peter Paul Rubens, or via the heritage of Surrealism. These affective constraints on sign formation reveal the central role of “glitches” in the distinction of creative and uncreative action. (shrink)

Connected devices, such as smartphones and tablets, are exposed to a large variety of attacks. Their protection is often challenged by their resource constraints in terms of CPU, memory and energy. Security chains, composed of security functions such as firewalls, intrusion detection systems and data leakage prevention mechanisms, offer new perspectives to protect these devices using software-defined networking and network function virtualization. However, the complexity and dynamics of these chains require new automation techniques to orchestrate them. This chapter describes an (...) automated orchestration methodology for security chains in order to secure connected devices and their applications. This methodology exploits process learning to establish behavioral models and infer security constraints represented as logical predicates. It then generates and merges a set of chains of security functions on the basis of these predicates. These chains are finally compiled into low-level configuration rules and deployed into the network, optimizing for the underlying topology. The benefits and limits of such a methodology combining machine learning and verification techniques are evaluated by a set of experimental results. (shrink)

Background: Magnetic resonance spectroscopic imaging is a neuroimaging technique that may be useful for non-invasive mapping of brain temperature over a large brain volume. To date, intra-subject reproducibility of MRSI-based brain temperature has not been investigated. The objective of this repeated measures MRSI-t study was to establish intra-subject reproducibility and repeatability of brain temperature, as well as typical brain temperature range.Methods: Healthy participants aged 23–46 years were scanned at two time points ~12-weeks apart. Volumetric MRSI data were processed by reconstructing (...) metabolite and water images using parametric spectral analysis. Brain temperature was derived using the frequency difference between water and creatine for 47 regions of interest delineated by the modified Automated Anatomical Labeling atlas. Reproducibility was measured using the coefficient of variation for repeated measures, and repeatability was determined using the standard error of measurement. For each region, the upper and lower bounds of Minimal Detectable Change were established to characterize the typical range of TCRE values.Results: The mean global brain temperature over all subjects was 37.2°C with spatial variations across ROIs. There was a significant main effect for time [F = 37.0, p < 0.0001] and for brain region [F = 2.66, p < 0.0001]. The time*brain region interaction was not significant [F = 0.80, p = 0.83]. Participants' TCRE was stable for each ROI across both time points, with ROIs' COVrep ranging from 0.81 to 3.08% ; majority of ROIs had a COVrep <2.0%.Conclusions: Brain temperature measurements were highly consistent between both time points, indicating high reproducibility and repeatability of MRSI-t. MRSI-t may be a promising diagnostic, prognostic, and therapeutic tool for non-invasively monitoring brain temperature changes in health and disease. However, further studies of healthy participants with larger sample size and numerous repeated acquisitions are imperative for establishing a reference range of typical brain TCRE, as well as the threshold above which TCRE is likely pathological. (shrink)

Background As noise brings great error in the analysis of metallographic images, an adaptive weighted mean filtering method proposed to overcome the shortcomings of the standard mean filtering method. Methods The method used to detect the pulse noise points in the image, and then the modified mean method used to filter out the detected noise points. Patents on metallographic image processing have discussed for the development of the proposed methodology. Results It is shown that filter window can (...) be filtered in comparison with the conventional 3×3, 5×5 and 7×7 filt window to reduce noise detection and reduce the complexity of the weight calculation. Conclusion It can be concluded that this method can better protect the details of the image, has better filtering effect than the standard mean filtering, and its processing speed is faster than the median filtering of the large window, which has profound significance for the edge detection and processing of the metallographic image. (shrink)

This work intends to apprehend and emphasize the contribution of image-processing techniques and computer vision in the treatment of clay-based material known in Meknes region. One of the various characteristics used to describe clay in a qualitative manner is porosity, as it is considered one of the properties that with “kill or cure” effectiveness. For this purpose, we use scanning electron microscopy images, as they are considered the most powerful tool for characterising the quality of the microscopic pore (...) structure of porous materials. We present various existing methods of segmentation, as we are interested only in pore regions. The results show good matching between physical estimation and Voronoi diagram-based porosity estimation. (shrink)

Historically, the dynamic between philosophy of artificial intelligence and its practical application has been essential for the development of both, and thus the encounter between theory of AI and architectural/urban theory should be a site of considerable productivity. However, in many ways, it is not. This is due to two primary factors, one arising from each side of this encounter. First, legacies of overly-anthropomorphic models of AI permeate design discourses, where issues of how well AI can be constrained to social (...) issues of philosophy of mind exclude more foundational and cross-cultural questions about artificial intelligence as material process in the physical world that could inform new philosophical insights. Concurrently, the mobilization of investment in “Smart Cities” discourses dominates the space of application of AI at urban scale in ways that prematurely fixes solutions in the skeuomorphic image of architectural and urban conventions. To break this impasse, we held a series of think-tanks, workshops, and design charettes that brought together leading figures in philosophy of artificial intelligence, urban design, and commercial AI platforms. The goal was to re-think from first principles how alternative philosophical models of AI as a distributed, discontinuous, landscape-scale technology in a direct encounter with the applications in contexts of ecological sensing, automation’s impact on urban form, and issues of algorithmic governance. The design brief for this research establishes a generative framework for conceiving how embedded machine sensing and intelligence is already changing urban form and could change it in the future. The framework focuses on issues of urban zoning and architectural programming, data modeling and governance, platform cognition and design, and how these inform shifts in dynamics of public and private institutions. (shrink)

The tendency to idealise artificial intelligence as independent from human manipulators, combined with the growing ontological entanglement of humans and digital machines, has created an “anthrobotic” horizon, in which data analytics, statistics and probabilities throw our agential power into question. How can we avoid the consequences of a reified definition of intelligence as universal operation becoming imposed upon our destinies? It is here argued that the fantasised autonomy of automated intelligence presents a contradistinctive opportunity for philosophical consciousness to understand (...) itself anew as holistic and co-creative, beyond the recent “analytic” moment of the history of philosophy. Here we introduce the concept of “crealectic intelligence”, a meta-analytic and meta-dialectic aspect of consciousness. Intelligent behaviour may consist in distinguishing discrete familiar parts or reproducible functions in the midst of noise via an analytic process of segmentation; intelligence may also manifest itself in the constitution of larger wholes and dynamic unities through a dialectic process of association or assemblage. But, by contrast, crealectic intelligence co-creates realities in the image of an ideal or truth, taking into account the desiring agent imbued with a sense of possibility, in a relationship not only with the Real but also with the creative sublime or “Creal”. (shrink)

This paper considers the role of informal networks in securing post‐public school occupational advantage. Both the ‘official’ view of the private sector and the experiences of recent pupils are cited. A significant disparity is found between the two. A denial of the relevance of the ‘old boy network’ is revealed in the sector's publications, a position fully consistent with the overall reconstruction of image currently being pursued. In contrast, ex‐pupils unequivocally asserted the continued influence of non‐meritocratic means of advancement, (...) though crucially, only for an element of pupils. It is argued that adequate social analysis requires not simply an awareness of the presence of covert mechanisms, but also an acceptance of the socially restricted, rather than universally available, nature of the processes. Recognition is needed that contemporary informal networks have evolved from an historically familiar form, yet constitute a particular, dynamic, era‐specific manifestation of it. (shrink)

Say "cheese"! Taking great pictures is a snap when you follow the tips, tricks, and techniques packed inside Photography For Dummies, which takes you all the way from choosing the right film to using your computer to turn your photos into greeting cards or Web-ready online images. Whether you're taking photos for fun or profit, you'll find expert advice on all the angles -- from taking family pictures to action, sports, and travel shots -- alongside hundreds of color and black-and-white (...) examples that show you how to make your good pictures great, and your great pictures even better. Geared for novice photographers armed with automated point-and-shoot cameras, Photography For Dummies takes you step-by-step through the entire photographic process, from choosing the right film and photo processing to using your camera's special features. And when you're ready to take the next step in photography with digital cameras, you'll find all sorts of helpful information right here, all explained in clear, easy-to-understand language. (shrink)

Emotional facial expressions can inform researchers about an individual's emotional state. Recent technological advances open up new avenues to automatic Facial Expression Recognition (FER). Based on machine learning, such technology can tremendously increase the amount of processed data. FER is now easily accessible and has been validated for the classification of standardized prototypical facial expressions. However, applicability to more naturalistic facial expressions still remains uncertain. Hence, we test and compare performance of three different FER systems (Azure Face API, Microsoft; Face++, (...) Megvii Technology; FaceReader, Noldus Information Technology) with human emotion recognition (A) for standardized posed facial expressions (from prototypical inventories) and (B) for non-standardized acted facial expressions (extracted from emotional movie scenes). For the standardized images, all three systems classify basic emotions accurately (FaceReader is most accurate) and they are mostly on par with human raters. For the non-standardized stimuli, performance drops remarkably for all three systems, but Azure still performs similarly to humans. In addition, all systems and humans alike tend to misclassify some of the non-standardized emotional facial expressions as neutral. In sum, emotion recognition by automated facial expression recognition can be an attractive alternative to human emotion recognition for standardized and non-standardized emotional facial expressions. However, we also found limitations in accuracy for specific facial expressions; clearly there is need for thorough empirical evaluation to guide future developments in computer vision of emotional facial expressions. (shrink)

Academic misconduct in all its various forms is a challenge for degree-granting institutions. Whilst text-based plagiarism can be detected using tools such as Turnitin™, Plagscan™ and Urkund™, contract cheating and collusion can be more difficult to detect, and even harder to prove, often falling to no more than a ‘balance of probabilities’ rather than fact. To further complicate the matter, some students will make deliberate attempts to obfuscate cheating behaviours by submitting work in Portable Document Format, in image form, (...) or by inserting hidden glyphs or using alternative character sets which text matching software does not always accurately detect.Educators do not tend to think of academic misconduct in terms of criminality per se, but the tools and techniques used by digital forensics experts in law enforcement can teach us much about how to investigate allegations of academic misconduct. The National Institute of Standards and Technology’s Glossary describes digital forensics as ‘the application of computer science and investigative procedures involving the examination of digital evidence - following proper search authority, chain of custody, validation with mathematics, use of validated tools, repeatability, reporting, and possibly expert testimony.’. These techniques are used in criminal investigations as a means to identify the perpetrator of, or accomplices to, a crime and their associated actions. They are sometimes used in cases relating to intellectual property to establish the legitimate ownership of a variety of objects, both written and graphical, as well as in fraud and forgery. Whilst there have been some research articles and case studies that demonstrate the use of digital forensics techniques to detect academic misconduct as proof of concept, there is no evidence of their actual deployment in an academic setting.This paper will examine some of the tools and techniques that are used in law enforcement and the digital forensics field with a view to determining whether they could be repurposed for use in an academic setting. These include methods widely used to determine if a file has been tampered with that could be repurposed to identify if an image is plagiarised; file extraction techniques for examining meta data, used in criminal cases to determine authorship of documents, and tools such as FTK™ and Autopsy™ which are used to forensically examine single files as well as entire hard drives. The paper will also present a prototype of a bespoke software tool that attempts to repurpose some of these techniques into an automated process for detecting plagiarism and / or contract cheating in Word documents.Finally, this article will discuss whether these tools have a place in an academic setting and whether their use in determining if a student’s work is truly their own is ethical. (shrink)

With the development of mobile Internet technology, firms need to complete the entire process of consumer targeting, ad content generation, and ad display in a very short time window. Therefore, computational advertising, such as native ads on social media platforms, has become the mainstream of online advertising with its automation and personalization features. However, computational advertising faces some problems when using artificial intelligence technology to generate content. First, the images should have a significant enough impact on consumers and be easy (...) to adjust to save computational power at the same time; second, the iteration of the computational advertising system relies on consumer behaviors or advertising effectiveness, and firms need to learn the relationship between ad design and consumer behaviors. Under the above two problems, this paper selects visual distance as the main variable, and images can be adjusted by cropping to save computational power. This paper incorporates image design and ad effectiveness metrics into the construal level theory framework, under which the effectiveness metrics can be quickly determined. Following previous studies, we use click-through rate to represent the early stage of the sales funnel and a higher construal level and CVR to represent the later stage of the sales funnel and a lower construal level. Therefore, visually distant images bring distant psychological distance or higher construal level, which can get higher CTR; visually proximate images bring near psychological distance or lower construal level, which can bring higher CVR. These findings suggest that firms can improve the efficiency of their advertising systems and gain more revenue by understanding consumer psychological states. (shrink)

Este trabajo surge a partir de la investigación general de las técnicas hidropónicas teniendo en cuenta sus ventajas y desventajas para de esta forma poder encontrar aquel factor determinante a través de una comparación de técnicas hidropónicas que permitan clasificarlas y escoger la mejor opción que genere menos impacto ambiental negativo y demuestre ser más productivo en los entornos urbanos. Adicionalmente, un factor determinante en las ciudades es su espacio limitado por lo que la mejor opción también deberá incluir un (...) óptimo manejo del espacio que permita a casi cualquier individuo poder aplicarlos desde su entorno sin recurrir a excesivas modificaciones. Como principal resultado se escogió a la Hidroponía recirculante como método predominante por los excelentes resultados que se obtienen con relación a los demás, adicionalmente, este puede ser fácilmente aplicado en los ambientes urbanos por su versatilidad y buen manejo de recursos. Palabras Clave: Hidroponia, ambiente, urbano, comparativa, técnicas, cultivo. Referencias [1]J. López, «La producción hidropónica de cultivos,» IDESIA, vol. 36, nº 2, pp. 139-141, 2018. [2]J. Lee, A. Rahman, J. Behrens, C. Brennan, B. Ham, H. Seok Kim, C. Won, S. Yun, H. Azam y M. Kwon, «Nutrient removal from hydroponic wastewater by a microbial consortium,» New Biotechnology, vol. 41, pp. 15-24, 2018. [3]H. Ku, C. Tiong, A. Suresh y B. Ong, «“Active” hydroponic greenhouse system to kick-start and augment reforestation program through carbon sequestration e an experimental and theoretical feasibility study,» Journal of Cleaner Production, vol. 129, pp. 637-646, 2016. [4]J. Beltrano y D. Gimenez, Cultivo en hidroponía, Buenos Aires: Universidad de la Plata, 2015. [5]L. Ramírez, M. Pérez, P. Jiménez, H. Giraldo y E. Gómez, «Evaluación preliminar de sistemas acuapónicos e hidropónicos en cama flotante para el cultivo de orégano,» Revista Facultad de Ciencias Básicas, vol. 7, nº 2, pp. 242-259, 2011. [6]S. Hosseinzadeh, D. Testai, M. BKheet y J. De Graeve, «Degradation of root exudates in closed hydroponic systems using UV/H2O2: Kinetic investigation, reaction pathways and cost analysis,» Science of the Total Environment, vol. 1, pp. 1-9, 2019. [7]N. Camarena, A. Rojas y M. Santos, «Fluoride bioaccumulation by hydroponic cultures of camellia,» Chemosphere, vol. 136, pp. 56-62, 2015. [8]W. Wang, Y. Ma, L. Fu, Y. Cui y M. Yaqoob, «Physical an mechanical properties of hydroponic lettuce for automatic harvesting,» Informatión processing in agriculture, vol. 1, pp. 2214-3173, 2020. [9]M. Zárate, Manual de Hidroponia, Coyoacán: Universidad Autónoma de Mexico, 2014. [10]S. Magwaza, L. Magwaza, A. Odindo y C. Buckley, «Partially treated domestic wastewater as a nutrient source for tomatoes grown in a hydroponic system: effect on nutrientabsorption and yield,» Heliyon, vol. 6, nº 12, pp. 2405-8440, 2020. [11]C. ARANO, «Hidroponía: Algunas paginas de historia,» Tecnología de Producción, nº 58, pp. 24-32, 2007. [12]G. Guzmán, Hidroponia en Casa: Una actividad familiar, Costa Rica: Ministerio de Agricultura y ganaderia, 2004. [13]J. Gilsanz, HIDROPONIA, Montevideo : Unidad de Comunicación y Transferencia de Tecnología, 2007. [14]C. Miller, «El debate de hidroponia orgánica: Perspectivas norteamericanas sobre si la producción hidropónica merece ser certificada como orgánica.,» Productores de Hortalizas, nº 6, pp. 36-38, 2017. [15]A. Herrera, «Manejo de la solución nutritiva en la producción de tomate en hidroponía,» Terra Latinoamericana, vol. 17, nº 3, pp. 221-229, 1999. [16]C. Espinal y D. Matulić, «Recirculating Aquaculture Technologies,» Biomedical and Life Sciences, pp. 35-76, 2020. [17]H. Resh, «Técnicas de cultivo con flujo laminar de nutrientes,» de Cultivos Hidroponicos, España, Mundi-Prensa, 2001, pp. 35-37. [18]P. Blanca y L. Teresa, «Sistemas recirculantes y su interés en el cutlivo de ornamentales,» Tecnología de producción, nº 35, pp. 34-36, 2006. [19]C. Magán, «Recirculación de las soluciones nutritivas, Manejo y Control Microbiologico,» InfoAgro, nº 2, pp. 1-2, 2016. [20]S. Goddek, A. Joyce, B. Kotzen y M. Dos-Santos, «Aquaponics and Global Food Challenges,» Aquaponics Food Production Systems. Springer, vol. 1, nº 1, pp. 3-17, 2019. [21]S. G. Verdoliva, D. Gwyn Jones, A. Detheridge y P. Robson, «Controlled comparisons between soil and hydroponic systems reveal increased water use efficiency and higher lycopene and β-carotene contents in hydroponically grown tomatoes,» Scientia Horticulturae, pp. 3002-4238, 2020. [22]A. Chaudhry y V. Mishra, «A Comparative Analysis of Vertical Agriculture Systems in Residential Apartments, » de 2019 Advances in Science and Engineering Technology International Conferences, Dubai, United Arab Emirates, United Arab Emirates, 2019. [23]T. Mazhar, G. Jianmin, L. Imran, S. Kashif, Q. Waqar, S. Sher y C. Jiedong, «Modern plant cultivation technologies in agriculture under controlled nvironment: a review on aeroponics,» Journal of Plant Interactions, vol. 13, nº 1, pp. 338-352, 2012. [24]K. Janiak, A. Jurga, J. Kuźma, W. Breś y M. Muszyński, «Surfactants effect on aeroponics and important mass balances of regenerative life support system – Lettuce case study,» Science of the Total Environment, vol. 718, nº137324, pp. 1-12, 2020. [25]F. Rahman, I. Jahan, R. Biplob, N. Farhin y J. Uddin, «Automated Aeroponics System for Indoor Farming using Arduino,» de 2018 Joint 7th International Conference on Informatics, Electronics & Vision and 2018 2nd International Conference on Imaging, Vision & Pattern Recognition, Kitakyushu, Japan, 2018. [26]M. Caldeyro Stajano, «La Hidroponía Simplificada como Tecnología apropiada, para implementar la Seguridad Alimentaria en la Agricultura Urbana.,» Cuadernos del CEAgro, nº 8, pp. 71-76, 2006. (shrink)

The author, using a systematic approach, forms a picture of the process of historical development as the process of formation of the system "man and nature", the interaction of which is mediated by the system "public consciousness — public practice". The cycle of formation of the system "man and nature" goes through four stages: from unity with the nature of primitive man through the stages of contradictions: from dependence on nature and domination over it to conscious unity with nature. The (...) onset of each stage of this process is associated with the achievement of a new quality of the individual's system, with the dominance of the picture of the unity of the world in the public consciousness, with the strengthening of the interaction of subjective and objective. The completion of the formation of the system "man and nature" and the transition to the stage of unity is associated with the formation and dissemination of the worldview of unity — a systemic worldview. In this picture of the developing world, as the basis of a systemic worldview, the logic of the development of the individual's system, social consciousness and social practice has a non-linear character of the formation of opposite hierarchies with the subsequent transition to dialectical unity in full accordance with the dialectical logic identified by G.W.F. Hegel: thesis — antithesis — synthesis. This is exactly how the development of Russian society takes place, in which the new quality of the individual's system is associated with the development of social consciousness: idealism — materialism — a systemic worldview, and social practice: capitalism — socialism — a social state with a market economy. (shrink)

In this article, I provide an account of the development of the "translate" concept from the verbs used in Old English through the Middle English period, including the establishment of the Latin-based translate. The development and current pattern of polysemy are described through the elaboration of a Lakoffian cognitive model structured by image schemas and various types of action on those schemas--more specifically combination, dissolution, and metaphoric projection. Concordance and corpus data illustrate the development at various stages.