This article reads the uptake of facial-matching algorithms by fertility clinics in Spain through the lens of ‘the fertility fix’: a software fix to the social reconfiguration of kinship and a fixed capital investment made by competing fertility companies and firms. ‘The fertility fix’ is proposed as a critical, ethical lens through which to situate algorithmic facial-matching in assisted reproduction in the context of the racial politics of the face and phenotype and the spatial politics (...) of market expansion. While an ‘infertility crisis’ is often mentioned when explaining the growth of the assisted reproductive technologies (ARTs) industry, the use of donated reproductive cells is tied up in societal, ecological and economic shifts. Combining Software Studies analysis with Marxist Feminist and trans*feminist perspectives on shifting re/production dynamics, the article details the role of computational technologies in promoting certain ideas and beliefs about family and fixing certain territories of capital flow. (shrink)

This article reads the uptake of facial-matching algorithms by fertility clinics in Spain through the lens of ‘the fertility fix’: a software fix to the social reconfiguration of kinship and a fixed capital investment made by competing fertility companies and firms. ‘The fertility fix’ is proposed as a critical, ethical lens through which to situate algorithmic facial-matching in assisted reproduction in the context of the racial politics of the face and phenotype and the spatial politics (...) of market expansion. While an ‘infertility crisis’ is often mentioned when explaining the growth of the assisted reproductive technologies (ARTs) industry, the use of donated reproductive cells is tied up in societal, ecological and economic shifts. Combining Software Studies analysis with Marxist Feminist and trans*feminist perspectives on shifting re/production dynamics, the article details the role of computational technologies in promoting certain ideas and beliefs about family and fixing certain territories of capital flow. (shrink)

In face recognition systems, highly robust facial feature representation and good classification algorithm performance can affect the effect of face recognition under unrestricted conditions. To explore the anti-interference performance of convolutional neural network reconstructed by deep learning framework in face image feature extraction and recognition, in the paper, first, the inception structure in the GoogleNet network and the residual error in the ResNet network structure are combined to construct a new deep reconstruction network algorithm, with the random gradient descent (...) and triplet loss functions as the model optimizer and classifier, respectively, and it is applied to the face recognition in Labeled Faces in the Wild face database. Then, the portrait pyramid segmentation and local feature point segmentation are applied to extract the features of face images, and the matching of face feature points is achieved using Euclidean distance and joint Bayesian method. Finally, Matlab software is used to simulate the algorithm proposed in this paper and compare it with other algorithms. The results show that the proposed algorithm has the best face recognition effect when the learning rate is 0.0004, the attenuation coefficient is 0.0001, the training method is SGD, and dropout is 0.1, and the algorithm proposed in this paper has the largest mean average precision compared to other CNN algorithms. The correct rate of face feature matching of the algorithm proposed in this paper is 84.72%, which is higher than LetNet-5, VGG-16, and VGG-19 algorithms, the correct rates of which are 6.94%, 2.5%, and 1.11%, respectively, but lower than GoogleNet, AlexNet, and ResNet algorithms. At the same time, the algorithm proposed in this paper has a faster matching time and a higher correct matching rate than the joint Bayesian method, indicating that the deep reconstruction network algorithm proposed in this paper can be used in face image recognition, FE, and matching, and it has strong anti-interference. (shrink)

Mark Coeckelbergh starts his book with a very powerful picture based on a real incident: On the 9th of January 2020, Robert Williams was wrongfully arrested by Detroit police officers in front of his two young daughters, wife and neighbors. For 18 hours the police would not disclose the grounds for his arrest (American Civil Liberties Union 2020; Hill 2020). The decision to arrest him was primarily based on a facial detection algorithm which matched Mr. Williams’ driving license photo (...) with the picture of a man who was suspected of watch theft two years earlier. Not only did the computer ‘get it wrong’ as one of the detectives said, when Mr. Williams made them aware that the picture of the suspect obviously wasn’t resembling him, the probably unreliable algorithm very likely contributed to racial discrimination (Hill 2020). It is well documented that many available facial detection algorithms at this time had significant problems (e.g. a comparably high false positive rate) with respect to black persons, like Mr. Williams (NIST 2019). Multiple causes may exist, such as unbalanced training datasets and insufficient optimization. Coeckelbergh compares the disturbing case of Mr. Williams with a political interpretation of Franz Kafka’s The Trial, where the protagonist, Josef K., is accused of an unspecified crime by an opaque, oppressive and absurd bureaucracy: “In the 21st-century United States, Josef K. is black and is falsely accused by an algorithm, without explanation” (p. 2). (shrink)

This paper discusses prominent examples of what we call “algorithmic anxiety” in artworks engaging with algorithms. In particular, we consider the ways in which artists such as Zach Blas, Adam Harvey and Sterling Crispin design artworks to consider and critique the algorithmic normativities that materialize in facial recognition technologies. Many of the artworks we consider center on the face, and use either camouflage technology or forms of masking to counter the surveillance effects of recognition technologies. Analyzing their works, (...) we argue they on the one hand reiterate and reify a modernist conception of the self when they conjure and imagination of Big Brother surveillance. Yet on the other hand, their emphasis on masks and on camouflage also moves beyond such more conventional critiques of algorithmic normativities, and invites reflection on ways of relating to technology beyond the affirmation of the liberal, privacy-obsessed self. In this way, and in particular by foregrounding the relational modalities of the mask and of camouflage, we argue academic observers of algorithmic recognition technologies can find inspiration in artistic algorithmic imaginaries. (shrink)

In the process of children’s psychological development, various levels of psychological distress often occur, such as attention problems, emotional problems, adaptation problems, language problems, and motor coordination problems; these problems have seriously affected children’s healthy growth. Scene matching in the treatment of psychological distress can prompt children to change from a third-person perspective to a first-person perspective and shorten the distance between scene contents and child’s perceptual experience. As a part of machine learning, deep learning can perform mapping transformations (...) in huge data, process huge data with the help of complex models, and extract multilayer features of scene information. Based on the summary and analysis of previous research works, this paper expounded the research status and significance of the scene matching method for children’s psychological distress, elaborated the development background, current status, and future challenges of deep learning algorithm, introduced the methods and principles of depth spatiotemporal feature extraction algorithm and dynamic scene understanding algorithm, constructed a scene matching model for children’s psychological distress based on deep learning algorithm, analyzed the scene feature extraction and matching function construction of children’s psychological distress, proposed a scene matching method for children’s psychological distress based on deep learning algorithm, performed scene feature matching and information processing of children’s psychological distress, and finally conduced a simulation experiment and analyzed its results. The results show that the deep learning algorithm can have a deep and abstract mining on the characteristics of children’s psychological distress scenes and obtain a large amount of more representative characteristic information through training on large-scale data, thereby improving the accuracy of classification and matching of children’s psychological distress scenes. The study results of this paper provide a reference for further researches on the scene matching method for children’s psychological distress based on deep learning algorithm. (shrink)

A vehicle-commodity matching problem is presented for service providers to reduce the cost of the logistics system. The vehicle classification model is built as a Gaussian mixture model, and the expectation-maximization algorithm is designed to solve the parameter estimation of GMM. A nonlinear mixed-integer programming model is constructed to minimize the total cost of VCMP. The matching process between vehicle and commodity is realized by GMM-EM, as a preprocessing of the solution. The design of the vehicle-commodity matching (...) platform for VCMP is designed to reduce and eliminate the information asymmetry between supply and demand so that the order allocation can work at the right time and the right place and use the optimal solution of vehicle-commodity matching. Furthermore, the numerical experiment of an e-commerce supply chain proves that a hybrid evolutionary algorithm is superior to the traditional method, which provides a decision-making reference for e-commerce VCMP. (shrink)

In the Internet age, information security is threatened anytime and anywhere and the copyright protection of audio and video as well as the need for matching detection is increasingly strong. In view of this need, this paper proposes a zero-watermarking algorithm for audio and video matching based on NSCT. The algorithm uses NSCT, DCT, SVD, and Schur decomposition to extract video features and audio features and generates zero-watermark stream through synthesis, which is stored in a third-party organization for (...) detection and identification. The detection algorithm can obtain zero watermark from the audio and video to be tested and judge and locate tampering by comparing with the zero watermark of the third party. From the experimental results, this algorithm can not only detect whether the audio and video are mismatched due to tampering attacks but also locate the mismatched audio and video segments and protect the copyright. (shrink)

A revolutionary study of the correlations between facial expressions and type, as first defined by C.G. Jung. This book rewrites what we know of typology and presents an empirical case for its existence.

This paper presents an in-depth analysis of tennis match scene classification using an adaptive Gaussian mixture model parameter estimation simulation algorithm. We divided the main components of semantic analysis into type of motion, distance of motion, speed of motion, and landing area of the tennis ball. Firstly, for the problem that both people and tennis balls in the video frames of tennis matches from the surveillance viewpoint are very small, we propose an adaptive Gaussian mixture model parameter estimation algorithm, which (...) has good accuracy and speed on small targets. Secondly, in this paper, we design a sports player tracking algorithm based on role division and continuously lock the target player to be tracked and output the player region. At the same time, based on the displacement information of the key points of the player’s body and the system running time, the distance and speed of the player’s movement are obtained. Then, for the problem that tennis balls are small and difficult to capture in high-speed motion, this paper designs a prior knowledge-based algorithm for predicting tennis ball motion and landing area to derive the landing area of tennis balls. Finally, this paper implements a prototype system for semantic analysis of real-time video of tennis matches and tests and analyzes the performance indexes of the system, and the results show that the system has good performance in real-time, accuracy, and stability. (shrink)

A variety of theoretical frameworks predict the resemblance of behaviors between two people engaged in communication, in the form of coordination, mimicry, or alignment. However, little is known about the time course of the behavior matching, even though there is evidence that dyads synchronize oscillatory motions (e.g., postural sway). This study examined the temporal structure of nonoscillatory actions—language, facial, and gestural behaviors—produced during a route communication task. The focus was the temporal relationship between matching behaviors in the (...) interlocutors (e.g., facial behavior in one interlocutor vs. the same facial behavior in the other interlocutor). Cross-recurrence analysis revealed that within each category tested (language, facial, gestural), interlocutors synchronized matching behaviors, at temporal lags short enough to provide imitation of one interlocutor by the other, from one conversational turn to the next. Both social and cognitive variables predicted the degree of temporal organization. These findings suggest that the temporal structure of matching behaviors provides low-level and low-cost resources for human interaction. (shrink)

The original target tracking algorithm based on a single model has long been unable to meet the complex and changeable characteristics of the target, and then there are problems such as poor tracking accuracy, target loss, and model mismatch. The interactive multimodel algorithm uses multiple motion models to track the target, obtains the degree of adaptation between the actual motion state of the target and each model according to the calculated likelihood function, and then combines the updated weight values of (...) each filter to obtain a weighted sum. Therefore, the interactive multimodel algorithm can achieve better performance. This paper proposes an improved interactive multimodel algorithm that can achieve player tracking and trajectory feature matching. First, this paper proposes an improved Kalman filtering algorithm. This method is developed from the unbiased conversion measurement Kalman filter, which can obtain more accurate target state and covariance estimation. Secondly, using the parallel processing mode of the IMM algorithm to efficiently solve the data association between multiple filters, the IMM-IKF model is proposed. Finally, in order to solve the problem of low computational efficiency and high mismatch rate in image feature point matching, a method of introducing a minimum spanning tree in two-view matching is proposed. Experimental results show that the improved IMM-IKF algorithm can quickly respond to changes in the target state and can find the matching path with the lowest matching cost. In the case of ensuring the matching accuracy, the real-time performance of image matching is ensured. (shrink)

Research on facial emotion expression has mostly focused on emotion recognition, assuming that a small number of discrete emotions is elicited and expressed via prototypical facial muscle configurations as captured in still photographs. These are expected to be recognized by observers, presumably via template matching. In contrast, appraisal theories of emotion propose a more dynamic approach, suggesting that specific elements of facial expressions are directly produced by the result of certain appraisals and predicting the facial (...) patterns to be expected for certain appraisal configurations. This approach has recently been extended to emotion perception, claiming that observers first infer individual appraisals and only then make categorical emotion judgments based on the estimated appraisal patterns, using semantic inference rules. Here we report two related studies to empirically investigate the facial action unit configurations that are used by actors to convey specific emotions in short affect bursts and to examine to what extent observers can infer a person’s emotions from the predicted facial expression configurations. The results show that 1) professional actors use many of the predicted facial action unit patterns to enact systematically specified appraisal outcomes in a realistic scenario setting, and 2) naïve observers infer the respective emotions based on highly similar facial movement configurations with a degree of accuracy comparable to earlier research findings. Based on estimates of underlying appraisal criteria for the different emotions we conclude that the patterns of facial action units identified in this research correspond largely to prior predictions and encourage further research on appraisal-driven expression and inference. (shrink)

I would like to introduce the notion of machine hermeneutics in this paper. The notion refers to hermeneutical activity performed by machines. Machines are now capable of making the very interpretive tasks, using artificial intelligence algorithms based on the technology of machine learning that used to be the exclusive domain of human beings. In making this claim, I am not talking about possible conscious machines of the future, but those existing here and now. With facial recognition algorithms, (...) for example, machines are now performing routinely what must be regarded as hermeneutical analyses with astounding accuracy and power. Thus, machine hermeneutics supplements Don Ihde’s notion of material hermeneutics. In the latter, it is still human beings who do the interpretation, through the lenses provided the natural sciences; in this case, the natural sciences, or the technology afforded by the sciences, intervene between the human being and the world. In machine hermeneutics, on the contrary, the intervening comes in two layers. On the one hand, there is the usual intervention that Ihde talks about, but on the other, the artificial intelligence algorithm performs its own kind of intervention and interpretation, presenting an already interpreted result to the human beings, who then perceive it through the aid of the usual intervention such as the normal eyeglasses. Then the paper discusses the problem of how to justify the kind of perception that undergoes this process. In what sense can it be said that the algorithm is performing the right action, i.e., one such that the process comes up with a right picture of the world? I contend that this does not merely consist of technical excellence for the technology involved, but also ethical excellence. The two cannot be considered one apart from the other. (shrink)

Facial recognition is an artificial intelligence-based technology that, like many other forms of artificial intelligence, suffers from an accuracy deficit. This paper focuses on one particular use of facial recognition, namely identification, both as authentication and as recognition. Despite technological advances, facial recognition technology can still produce erroneous identifications. This paper addresses algorithmic identification failures from an upstream perspective by identifying the main causes of misidentifications (in particular, the probabilistic character of this technology, its ‘black box’ nature (...) and its algorithmic bias) and from a downstream perspective, highlighting the possible legal consequences of such failures in various scenarios (namely liability lawsuits). In addition to presenting the causes and effects of such errors, the paper also presents measures that can be deployed to reduce errors and avoid liabilities. (shrink)

This article reports results from a program that produces high‐quality animation of facial expressions and head movements as automatically as possible in conjunction with meaning‐based speech synthesis, including spoken intonation. The goal of the research is as much to test and define our theories of the formal semantics for such gestures, as to produce convincing animation. Towards this end, we have produced a high‐level programming language for three‐dimensional (3‐D) animation of facial expressions. We have been concerned primarily with (...) expressions conveying information correlated with the intonation of the voice: This includes the differences of timing, pitch, and emphasis that are related to such semantic distinctions of discourse as “focus,”“topic,” and “comment,”“theme” and “rheme,” or “given” and “new” information. We are also interested in the relation of affect or emotion to facial expression. Until now, systems have not embodied such rule‐governed translation from spoken utterance meaning to facial expressions. Our system embodies rules that describe and coordinate these relations: intonation/information, intonation/affect, and facial expressions/affect. A meaning representation includes discourse information: What is contrastive/background information in the given context, and what is the “topic” or “theme” of the discourse? The system maps the meaning representation into how accents and their placement are chosen, how they are conveyed over facial expression, and how speech and facial expressions are coordinated. This determines a sequence of functional groups: lip shapes, conversational signals, punctuators, regulators, and manipulators. Our algorithms then impose synchrony, create coarticulation effects, and determine affectual signals, eye and head movements. The lowest level representation is the Facial Action Coding System (FACS), which makes the generation system portable to other facial models. (shrink)

Background: Clinical and experimental findings have suggested that insomnia is associated with altered emotion processing, such as facial emotion recognition and impairments in executive functions. However, the results still appear non-consensual and have recently been presented by a few number of studies. Accordingly, the aim of the present study was to investigate whether patients with Insomnia disorder will present alterations in recognition of facial emotions and that such alterations will be related to Executive Functions and that Insomnia Disorder (...) patients will exhibit a lower Executive Functions performance when compared to normal controls individuals. Method: A total of 11 individuals diagnosed with insomnia disorder and 15 control participants took part in the present cross-sectional study. They completed questionnaires covering socio-demographic data, a sleep and mood evaluation, and a cognitive assessment. Moreover, they underwent a computerized Facial Emotional Recognition test, consisting of facial emotion labeling and facial emotion matching. Results: Individuals with insomnia presented a lower recognition of facial expressions of fear and sadness in comparison to control volunteers. Perceptual Organization Index was found to be statistically significant lower in the insomnia group compared to the control group. There was a statistically significant association between facial recognition emotional and cognitive processes of in executive functions performance, especially in processes related to the inhibitory control, planning capacity, problem solving and cognitive flexibility in insomnia group. Conclusions: Insomnia disorder impairs the facial emotion recognition of the fear and sadness. Insomniacs with impairment in the facial emotion recognition had impaired performance of executive functions. There is a negative impact on processes related to cognitive-emotional capacity than on processes related to social-emotional recognition. Keywords: insomnia, facial emotional recognition, sleep deprivation, cognition, executive functions. (shrink)

This paper firstly introduces the basic knowledge of music, proposes the detailed design of a music retrieval system based on the knowledge of music, and analyzes the feature extraction algorithm and matching algorithm by using the features of music. Feature extraction of audio data is the important research of this paper. In this paper, the main melody features, MFCC features, GFCC features, and rhythm features, are extracted from audio data and a feature fusion algorithm is proposed to achieve the (...) fusion of GFCC features and rhythm features to form new features under the processing of principal component analysis dimensionality reduction. After learning the main melody features, MFCC features, GFCC features, and rhythm features, based on the property that PCA dimensionality reduction can effectively reduce noise and improve retrieval efficiency, this paper proposes vector fusion by dimensionality reduction of GFCC features and rhythm features. The matching retrieval of audio features is an important task in music retrieval. In this paper, the DTW algorithm is chosen as the main algorithm for retrieving music. The classification retrieval of music is also achieved by the K-nearest neighbor algorithm. In this paper, after implementing the research and improvement of algorithms, these algorithms are integrated into the system to achieve audio preprocessing, feature extraction, feature postprocessing, and matching retrieval. This article uses 100 different kinds of MP3 format music as the music library and randomly selects 4 pieces each time, and it tests the system under different system parameters, recording duration, and environmental noise. Through the research of this paper, the efficiency of music retrieval is improved and theoretical support is provided for the design of music retrieval software integration system. (shrink)

Human homogamy may be caused in part by individuals’ preference for phenotypic similarities. Two types of preference can result in homogamy: individuals may prefer someone who is similar to themselves (self-referent phenotype matching) or to their parents (a sexual-imprinting-like mechanism). In order to examine these possibilities, we compare faces of couples and their family members in two ways. First, “perceived” similarity between a pair of faces is quantified as similarity ratings given to the pair. Second, “physical” similarity between two (...) groups of faces is evaluated on the basis of correlations in principal component scores generated from facial measurements. Our results demonstrate a tendency to homogamy in facial characteristics and suggest that the tendency is due primarily to self-referent phenotype matching. Nevertheless, the presence of a sexual-imprinting-like effect is also partially indicated: whether individuals are involved in facial homogamy may be affected by their relationship with their parents during childhood. (shrink)

With the recent advent of facial transplant (FT) treatment, patients who live with facial disfigurement have a new hope of improved facial aesthetics and quality of life. However, FT has been the subject of intense ethical debate, and there are numerous important ethical considerations surrounding FT that require further in-depth exploration. In the present review, the numerous ethical issues surrounding FT are elucidated, especially the weighty psychosocial impacts of FT, issues surrounding patients’ consent, selection and donor (...) class='Hi'>matching, and current challenges with postoperative complication management and the facial reconstruction of donors. These are discussed with a key focus on stakeholders’ perspectives including recipients, donors’ families, and the medical teams involved. This review found that a number of key ethical questions remain unanswered in the field of FT, and further consideration is needed for this novel surgical procedure to have the same evidence-based ethical backing as conventional surgical procedures. (shrink)

Over the last few years, automatic facial micro-expression analysis has garnered increasing attention from experts across different disciplines because of its potential applications in various fields such as clinical diagnosis, forensic investigation and security systems. Advances in computer algorithms and video acquisition technology have rendered machine analysis of facial micro-expressions possible today, in contrast to decades ago when it was primarily the domain of psychiatrists where analysis was largely manual. Indeed, although the study of facial micro-expressions (...) is a well-established field in psychology, it is still relatively new from the computational perspective with many interesting problems. In this survey, we present a comprehensive review of state-of-the-art databases and methods for micro-expressions spotting and recognition. Individual stages involved in the automation of these tasks are also described and reviewed at length. In addition, we also deliberate on the challenges and future directions in this growing field of automatic facial micro-expression analysis. (shrink)

The question whether facial expression processing may be impaired in Parkinson’s disease (PD) patients so far has yielded equivocal results – existing studies, however, have focused on testing expression processing in recognition tasks with static images of six standard, emotional facial expressions. Given that non-verbal communication contains both emotional and non-emotional, conversational expressions and that input to the brain is usually dynamic, here we address the question of potential facial expression processing differences in a novel format: we (...) test a range of conversational and emotional, dynamic facial expressions in three groups – PD patients ( n = 20), age- and education-matched older healthy controls ( n = 20), and younger adult healthy controls ( n = 20). This setup allows us to address both effects of PD and age-related differences. We employed a rating task for all groups in which 12 rating dimensions were used to assess evaluative processing of 27 expression videos from six different actors. We found that ratings overall were consistent across groups with several rating dimensions (such as arousal or outgoingness) having a strong correlation with the expressions’ motion energy content as measured by optic flow analysis. Most importantly, we found that the PD group did not differ in any rating dimension from the older healthy control group (HCG), indicating highly similar evaluation processing. Both older groups, however, did show significant differences for several rating scales in comparison with the younger adults HCG. Looking more closely, older participants rated negative expressions compared to the younger participants as more positive, but also as less natural, persuasive, empathic, and sincere. We interpret these findings in the context of the positivity effect and in-group processing advantages. Overall, our findings do not support strong processing deficits due to PD, but rather point to age-related differences in facial expression processing. (shrink)

This paper offers the first philosophical analysis of a form of artificial intelligence (AI) which the author calls facial profiling technology (FPT). FPT is a type of facial analysis technology designed to predict criminal behavior based solely on facial structure. Marketed for use by law enforcement, face classifiers generated by the program can supposedly identify murderers, thieves, pedophiles, and terrorists prior to the commission of crimes. At the time of this writing, an FPT company has a contract (...) with the United States federal government. After recounting how FPT resurrects the same moral problems associated with the pseudoscience of physiognomy, the author of this manuscript develops and defends the ‘Liberal Argument Against Facial Discrimination’ (LAAFD), which concludes that government use of FPT poses a significant risk of violating the classical liberal value of equality before the law by committing unjust discrimination against groups of people whose faces happen to match FPT classifiers. A key move in the argument suggests how a future scenario that results in widespread discrimination based solely on facial structure could be as unjustified and harmful, mutatis mutandis, as similar discrimination based solely on racial background. In the final section, the author of this paper develops prima facie policy proposals designed to protect classical liberal values if FPT is to be utilized by governments in liberal democratic societies. (shrink)

Patients with behavioral variant of frontotemporal dementia (FTD) have difficulties recognizing facial emotions, a deficit that may contribute to their impaired social skills. In three experiments, we investigated the FTD deficit in recognition of facial emotions, by comparing six patients with impaired social conduct, nine Alzheimer’s patients, and 10 age-matched healthy adults. Experiment 1 revealed that FTD patients were impaired in the recognition of negative facial emotions. Experiment 2 replicated these findings when participants had to determine whether (...) two faces were expressing the same or different emotions. Experiment 3 was a control study in which participants had to discriminate whether two faces were of the same sex. In this non-emotional processing task, both patient groups performed worse than normal participants, but FTD patients performed as well as Alzheimer’s patients. We conclude that FTD patients are impaired in the recognition of negative facial emotions. © 2005 Elsevier Ltd. All rights reserved. (shrink)

Given two strings, text t of length n, and pattern p = p1…pk of length k, and given a natural number w, the subsequence matching problem consists in finding the number of size w windows of text t which contain pattern p as a subsequence, i.e. the letters p1,…,pk occur in the window, in the same order as in p, but not necessarily consecutively . Subsequence matching is used for finding frequent patterns and association rules in databases. We (...) generalize the Knuth–Morris–Pratt pattern matching algorithm; we define a non-conventional kind of RAM, the MP-RAMs which model more closely the microprocessor operations; we design an O on-line algorithm for solving the subsequence matching problem on MP-RAMs. (shrink)

This book constitutes the refereed proceedings of the 13th International Scandinavian Symposium and Workshops on Algorithm Theory, SWAT 2012, held in Helsinki, Finland, in July 2012, co-located with the 23rd Annual Symposium on Combinatorial Pattern Matching, CPM 2012. The 34 papers were carefully reviewed and selected from a total of 127 submissions. The papers present original research and cover a wide range of topics in the field of design and analysis of algorithms and data structures.

As government pressure on major technology companies builds, both firms and legislators are searching for technical solutions to difficult platform governance puzzles such as hate speech and misinformation. Automated hash-matching and predictive machine learning tools – what we define here as algorithmic moderation systems – are increasingly being deployed to conduct content moderation at scale by major platforms for user-generated content such as Facebook, YouTube and Twitter. This article provides an accessible technical primer on how algorithmic moderation works; examines (...) some of the existing automated tools used by major platforms to handle copyright infringement, terrorism and toxic speech; and identifies key political and ethical issues for these systems as the reliance on them grows. Recent events suggest that algorithmic moderation has become necessary to manage growing public expectations for increased platform responsibility, safety and security on the global stage; however, as we demonstrate, these systems remain opaque, unaccountable and poorly understood. Despite the potential promise of algorithms or ‘AI’, we show that even ‘well optimized’ moderation systems could exacerbate, rather than relieve, many existing problems with content policy as enacted by platforms for three main reasons: automated moderation threatens to further increase opacity, making a famously non-transparent set of practices even more difficult to understand or audit, further complicate outstanding issues of fairness and justice in large-scale sociotechnical systems and re-obscure the fundamentally political nature of speech decisions being executed at scale. (shrink)

There are many ways to assess face perception skills. In this study, we describe a novel task battery FEAST (Facial Expression Action Stimulus Test) developed to test recognition of identity and expressions of human faces as well as stimulus control categories. The FEAST consists of a neutral and emotional face memory task, a face and object identity matching task, a face and house part-to-whole matching task, and a human and animal facial expression matching task. The (...) identity and part-to-whole matching tasks contain both upright and inverted conditions. The results provide reference data of a healthy sample of controls in two age groups for future users of the FEAST. (shrink)

Subgraph matching on a large graph has become a popular research topic in the field of graph analysis, which has a wide range of applications including question answering and community detection. However, traditional edge-cutting strategy destroys the structure of indivisible knowledge in a large RDF graph. On the premise of load-balancing on subgraph division, a dominance-partitioned strategy is proposed to divide a large RDF graph without compromising the knowledge structure. Firstly, a dominance-connected pattern graph is extracted from a pattern (...) graph to construct a dominance-partitioned pattern hypergraph, which divides a pattern graph as multiple fish-shaped pattern subgraphs. Secondly, a dominance-driven spectrum clustering strategy is used to gather the pattern subgraphs into multiple clusters. Thirdly, the dominance-partitioned subgraph matching algorithm is designed to conduct all isomorphic subgraphs on a cluster-partitioned RDF graph. Finally, experimental evaluation verifies that our strategy has higher time-efficiency of complex queries, and it has a better scalability on multiple machines and different data scales. (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)

This paper presents a procedure to select equitable stable allocations in two-sided matching markets without side payments. The Equitable set is computed using the Equitable algorithm. The algorithm limits the set of options available for each agent throughout the procedure. The stable matchings selected are generally not extreme, form a lattice and satisfy the condition of being “Ralwsian” in each partition of the market. The Equitable algorithm can also be used to select a particular matching from the Equitable (...) Set favoring particular agents independent of the side of the market to which they belong. (shrink)

For a many-to-many matching model with contracts, where all the agents have substitutable preferences, we provide an algorithm to compute the full set of stable allocations. This is based on the lattice structure of such set.

Emotions are believed to converge both through emotional mimicry and social appraisal. The present study compared contagion of anger and happiness. In Experiment 1, participants viewed dynamic angry and happy faces, with facial electromyography recorded from the zygomaticus major and corrugator supercilii as emotional mimicry. Self-reported emotional experiences were analyzed as emotional contagion. Experiment 2 manipulated social appraisal as the gaze of expression toward the target. The results showed that there was emotional contagion for angry and happy expressions both (...) in Experiment 1 and Experiment 2. Experiment 1 indicated an overt mimicry pattern for happy faces, but not for angry faces. Experiment 2 found an influence of social appraisal on angry contagion but not on happy diffusion. The two experiments suggest that the underlying processes of emotional mimicry and social appraisal are differentially relevant for different emotional contagion, with happiness processing following a mimicry-based path to emotional contagion, and anger processing requiring social appraisal. (shrink)

Advances in technology have transformed and expanded the ways in which policing is run. One new manifestation is the mass acquisition and processing of private facial images via automatic facial recognition by the police: what we conceptualise as AFR-based policing. However, there is still a lack of clarity on the manner and extent to which this largely-unregulated technology is used by law enforcement agencies and on its impact on fundamental rights. Social understanding and involvement are still insufficient in (...) the context of AFR technologies, which in turn affects social trust in and legitimacy and effectiveness of intelligent governance. This article delineates the function creep of this new concept, identifying the individual and collective harms it engenders. A technological, contextual perspective of the function creep of AFR in policing will evidence the comprehensive creep of training datasets and learning algorithms, which have by-passed an ignorant public. We thus argue individual harms to dignity, privacy and autonomy, combine to constitute a form of cultural harm, impacting directly on individuals and society as a whole. While recognising the limitations of what the law can achieve, we conclude by considering options for redress and the creation of an enhanced regulatory and oversight framework model, or Code of Conduct, as a means of encouraging cultural change from prevailing police indifference to enforcing respect for the human rights violations potentially engaged. The imperative will be to strengthen the top-level design and technical support of AFR policing, imbuing it with the values implicit in the rule of law, democratisation and scientisation-to enhance public confidence and trust in AFR social governance, and to promote civilised social governance in AFR policing. (shrink)

The paper defines a measure on the set of stable matchings in the marriage problem. This measure is based on the minimization of the envy difference between the sets of men and women, while preserving stability and selects stable matchings with the least conflict of interest between both groups of agents. The solution concept proposed is called Sex-equal Matching (SEM) and the paper also provides an algorithm to compute the set of SEM.

Deficits in recognition of facial expressions of emotions are considered to be an important factor explaining impairments in social functioning and affective reactions of schizophrenic patients. Many studies confirmed such deficits while controversies remained concerning the emotion valence and modality. The aim of the study was to explore the process of recognizing facial expressions of emotion in the group of schizophrenic patients by analyzing the role of emotion valence, modality and gender of the model. Results of the group (...) of 35 patients and 35 matched controls indicate that while schizophrenic patients show general impairment in recognizing facial expressions of both positive and the majority of negative emotions, there are differences in deficits for particular emotions. Expressions also appeared to be more ambiguous for the patients while variables connected with gender were found less significant. (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)

Pricing algorithms are computerized procedures a seller may use to adapt instantaneously its price to market conditions, including to prices quoted by its rivals. These algorithms are related to the extensive use of web-collectors which contribute in many industries to identifying the best price. In such settings, price competition operates between algorithms, no longer between executives of brick and mortar companies. In this context, the question is to know how implicit forms of collusion may arise between the (...) sellers. This paper is aimed at discussing this conceptual issue in a price-setting homogeneous product oligopoly with decreasing returns to scale where algorithms implement matching policies. Using fixed point argument, we find a family of equilibrium prices encompassing Cournot and Pareto efficient solutions, if matching is allowed upward and downward. Dynamical stability is studied in the linear demand constant return case. When matching operates only for price undercutting, this family is extended up to a bottom value of the market price, close to the Walrasian price. Pricing algorithms may solve the Bertrand–Edgeworth paradox. (shrink)

Everyday surveillance work is increasingly performed by non-human algorithms. These entities can be conceptualised as machinic flâneurs that engage in distanciated flânerie: subjecting urban flows to a dispassionate, calculative and expansive gaze. This paper provides some theoretical reflections on the nascent forms of algorithmic practice materialising in two Australian cities, and some of their implications for urban relations and social justice. It looks at the idealisation – and operational black boxing – of automated watching programs, before considering their impacts (...) on notions such as ‘the right to the city’ and ‘the right to the face’. It will argue that the turn to facial recognition software for the purposes of automating urban governance reconstitutes the meanings and phenomenology of the face. In particular, the fleshly and communicative physicality of the face is reduced to a measurable object that can be identified by a virtualised referent and then consequently tracked. Moreover, the asymmetrical and faceless nature of these machinic programs of recognition unsettles conventional notions of civil inattention and bodily sovereignty, and the prioritisation given to pattern recognition renders them amenable to ideas/ideals from phrenology and physiognomy. In this way, algorithmic governance may generate not only forms of facial vulnerability and estrangement, but also facial artifice, where individuals come to develop tacit and artful ways of de-facing and re-facing in order to subvert the processes of recognition which leverage these modes of biopower. Thus, the datafication of urban governance gives rise to a dynamic biopolitics of the face. (shrink)

Through the analysis of facial feature extraction technology, this paper designs a lightweight convolutional neural network. The LW-CNN model adopts a separable convolution structure, which can propose more accurate features with fewer parameters and can extract 3D feature points of a human face. In order to enhance the accuracy of feature extraction, a face detection method based on the inverted triangle structure is used to detect the face frame of the images in the training set before the model extracts (...) the features. Aiming at the problem that the feature extraction algorithm based on the difference criterion cannot effectively extract the discriminative information, the Generalized Multiple Maximum Dispersion Difference Criterion and the corresponding feature extraction algorithm are proposed. The algorithm uses the difference criterion instead of the entropy criterion to avoid the “small sample” problem, and the use of QR decomposition can extract more effective discriminative features for facial recognition, while also reducing the computational complexity of feature extraction. Compared with traditional feature extraction methods, GMMSD avoids the problem of “small samples” and does not require preprocessing steps on the samples; it uses QR decomposition to extract features from the original samples and retains the distribution characteristics of the original samples. According to different change matrices, GMMSD can evolve into different feature extraction algorithms, which shows the generalized characteristics of GMMSD. Experiments show that GMMSD can effectively extract facial identification features and improve the accuracy of facial recognition. (shrink)

Love is often seen as the most intimate aspect of our lives, but it is increasingly engineered by a few programmers with Artificial Intelligence (AI). Nowadays, numerous dating platforms are deploying so-called smart algorithms to identify a greater number of potential matches for a user. These AI-enabled matchmaking systems, driven by a rich trove of data, can not only predict what a user might prefer but also deeply shape how people choose their partners. This paper draws on Jürgen Habermas’s (...) “colonization of the lifeworld” thesis to critically explore the insidious influence of delegating romantic decision-making to an algorithm. The love lifeworld is colonized inasmuch as online dating algorithms encroach into our romantic relations to the extent that communicative action within romance is replaced by the technocratic rules of an algorithm. (shrink)