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(Series Information) European Papers - A Journal on Law and Integration, 2021 6(2), 1193-1228 | Article | (Table of Contents) I. Preliminary remarks. - II. The increasing attractiveness of cartels in the age of big data analytics. - III. Collusion between rational algorithms: the relation between market transparency and artificial intelligence in a world of big data. - IV. Existing vs created market conditions: tacit collusion or algorithmic concerted practices? - V. The limited role played by intent and imputability in the antitrust realm: the case of parent company liability and its applicability by analogy to the relation undertakings vis-à-vis algorithms. - VI. Big data analytics does create competitive concerns: should the Commission and national competition authorities commit to tackling algorithmic collusion? - VII. Conclusions. | (Abstract) Due to digital markets' transparency, algorithmic collusion may occur even if algorithms are designed to maximize profits rather than to conspire. The literature suggests that competition rules may not cover algorithmic collusion, being the latter an example of tacit collusion: by monitoring market conditions, each algorithm unilaterally and rationally decides to maintain supra-competitive prices. Data analytics ease the monitoring and reaction to competitors' behaviours, increasing the number of markets subject to tacit collusion. Yet, intention to conspire seems absent. In this Article, it is submitted that algorithmic collusion is different from tacit collusion and can be tackled under EU competition law. In the traditional scenario, undertakings base their rational decisions on the existing markets conditions. While designing their algorithms to maximize profits, undertakings are contributing to create the conditions allowing "tacit" collusion to occur. Moreover, a quasi-strict liability regime applies to antitrust offences, so that intention and imputability play limited roles. As a consequence, if algorithms programmed to maximize profits end up colluding, a rebuttable presumption of the existence of a concerted practice should apply. The practice should be prohibited unless undertakings can prove that, in the specific case, a concerted practice did not occur or that art. 101(3) TFEU applies. Moreover, competition rules may be enforced even without ascertaining any antitrust infringement. Competitive concerns are enough to adopt commitment decisions. Here, the Commission (or a National Competition Authority) may negotiate with the concerned undertakings technical remedies to prevent algorithmic collusion by intervening on the way the algorithms work.

Copyright of Nature & Technology / Nature & Technologie is the property of Nature et Technologie Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Synthetic biology is an emerging science that aims to create new biological functions that do not exist in nature, based on the knowledge acquired in life science over the last century. Since the beginning of this century, several projects in synthetic biology have emerged. The complexity of the developed artificial bio-functions is relatively low so that empirical design methods could be used for the design process. Nevertheless, with the increasing complexity of biological circuits, this is no longer the case and a large number of computer aided design softwares have been developed in the past few years. These tools include languages for the behavioral description and the mathematical modelling of biological systems, simulators at different levels of abstraction, libraries of biological devices and circuit design automation algorithms. All of these tools already exist in other fields of engineering sciences, particularly in microelectronics. This is the approach that is put forward in this paper., (© 2017 médecine/sciences – Inserm.)

Copyright of Governance Review / Revue Gouvernance is the property of University of Ottawa, Center on Governance and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The rapidly growing academic and public attention to algorithmic-selection applications such as search engines and social media is indicative of their alleged great social relevance and impact on daily life in digital societies. To substantiate these claims, this paper investigates the hitherto little explored subjective relevance that Internet users assign to algorithmic-selection applications in everyday life. A representative online survey of Internet users comparatively reveals the relevance that users ascribe to algorithmic-selection applications and to their online and offline alternatives in five selected life domains: political and social orientation, entertainment, commercial transactions, socializing and health. The results show that people assign a relatively low relevance to algorithmic-selection applications compared to offline alternatives across the five life domains. The findings vary greatly by age and education. Altogether, such outcomes complement and qualify assessments of the social impact of algorithms that are primarily and often solely based on usage data and theoretical considerations.

The mediation of love and sexuality has often relied on dating advice. This paper analyses a corpus of dating guides concerning the popular app Tinder. Our analysis suggests that the practice of algorithmic blackboxing, that is, characterizing algorithms as black boxes, is central to these guides that rely on the alleged opacity of Tinder’s algorithms to praise certain products, advice, or services that aim to facilitate matchmaking. The practice of algorithmic blackboxing primarily encourages users to hack Tinder. In this context, the notion of hack stresses the importance for users to modulate their behaviours in ways that make them more algorithmically recognisable, especially in relation to their gender. Thus, we suggest that Tinder’s algorithms participate in reproducing a speculative dating economy.

Copyright of Global Media Journal: Canadian Edition is the property of Global Media Journal: Canadian Edition and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract: A granular structure is an aggregation of grains whose sizes are characterized by a given distribution. A sample of this kind of structure is often modeled by a rectangle filled with disks in two dimensions or a parallelepiped containing spherical balls in three dimensions. Therefore, the geometrical modeling of such a structure consists in determining a “dense” repartition of disjoint disks (or spherical balls) with respect to the specified size distribution. In this paper, a new sphere packing algorithm based on an advancing-front approach, commonly used in meshing methods, is proposed. Significant improvements in computing time and density have been obtained comparing to existing methods. In addition, we show that the generated circular grains can be transformed into polygonal (polyhedral) cells generally observed in reality. An example of a metallic nanostructure model is presented. To cite this article: P. Laug et al., C. R. Mecanique 336 (2008). [Copyright &y& Elsevier]

The article presents a paper on the possible uses of self-organizing maps, especially in classification and data-set visualization purposes, through various examples and approaches. From the point of view of applicability and of statistical problems, the diversity of the examples proposes different characteristic ownership of the self-organizing maps in reference to more traditional methods. The statistical algorithm is presented as a general implementation, which introduces a notion of neighborhood between the classes of the algorithm of the mobile centers. The algorithms of classification take into account at the same time the effects of big distance and local effects. Apart from clustering, self-organizing maps are also useful as a visualization tool for the description of data-set intrinsic structure.

Abstract: The bi-potential method has been successfully applied for the modeling of frictional contact problems in static cases. This paper presents the application of this method for dynamic analysis of impact problems with multiple deformable bodies. A first order algorithm is applied for numerical integration of the time-discretized equation of motion. The numerical results show clearly the physical energy dissipation introduced by frictional effects between the solids in contact. To cite this article: B. Magnain et al., C. R. Mecanique 333 (2005). [Copyright &y& Elsevier]

This paper presents a study devoted to the composite fabric shaping simulation in finite strain analysis. We introduce a new geometrical approach based on the fishnet method for which the deformation of a fabric mesh element consists in a pure trellis effect. Such a fabric mesh element is then defined by a curved quadrilateral whose edges are geodesic lines with the same length plotted onto the surface to drape. Given three vertices of the fabric mesh element on the surface, we propose an optimization algorithm to define the fourth vertex of the fabric mesh element. This algorithm allows us to drape the surface using an advancing front approach from the data of an initial impact point between the fabric and the surface and the initial fibre directions at this point. A numerical draping simulation example using this approach is given. To cite this article: H. Borouchaki, A. Cherouat, C. R. Mecanique 331 (2003). [Copyright &y& Elsevier]

The impact of artificial intelligence algorithms is widely felt on many different aspects of life, and because of the efficiency and speed of such algorithms, decisions can be taken as well as their implementation on behalf of humans in the field of criminal justice. Despite the progress that has been made, there are still great concerns on the issue of rapid mechanization of the justice sector in general, and the judiciary in particular. Therefore, discussion and analysis of the impact of such algorithms on the justice system in this paper is of high importance. Such discussions will be carried out through three chapters; while chapter one reviews the concept of algorithms and their importance in criminal justice, chapters two and three are devoted to discuss the use of artificial intelligence algorithms in pre-trail and during trail stages respectively. This work, however, ended with a conclusion that contained the main results of the research and recommendations

The impact of artificial intelligence algorithms is widely felt on many different aspects of life, and because of the efficiency and speed of such algorithms, decisions can be taken as well as their implementation on behalf of humans in the field of criminal justice. Despite the progress that has been made, there are still great concerns on the issue of rapid mechanization of the justice sector in general, and the judiciary in particular. Therefore, discussion and analysis of the impact of such algorithms on the justice system in this paper is of high importance. Such discussions will be carried out through three chapters; while chapter one reviews the concept of algorithms and their importance in criminal justice, chapters two and three are devoted to discuss the use of artificial intelligence algorithms in pre-trail and during trail stages respectively. This work, however, ended with a conclusion that contained the main results of the research and recommendations

In the era of the data revolution (Kitchin, 2014), new kinds of data and data sources allow researchers to share innovative ways of studying society and its dynamics to comprehend the peculiarities related to the territory. In fact, the analysis of space-time data extracted from social media can support the comprehension of complex social phenomena such as, for example, mobility (Noulas, Scellato, Lathia, & Mascolo, 2012; Yuan et al., 2017; Zhang et al., 2016) or where and when certain social activities are carried out, such e.g., the participation in big events, tourist experiences or the monitoring and management of emergencies and security. Following the actual dissemination of use of social media in the cities, the analysis of the spatial dimension is considered particularly promising in the field of urban analysis (Singleton et al., 2018) and in the emerging line of digital studies. Nowadays, the intentional action of many people is increasingly contributing to the production and sharing of spatial data with a relevant impact on the construction of Territorial Information Systems (Zupi, 2017). This new category of spatial data is commonly known "Volunteered Geographic Information" (VGI) (Goodchild, 2007). The analysis of this kind of data leads to an innovative scenario for the collection and diffusion of geographic information from millions of users all over the world. It provides valuable insight into their perceptions and needs, opinions on places, events, and daily routes, which allow researchers to better follow traces about the knowledge of the local identities of a given place (Campaign, 2014), information flows, and social networks within society (Stefanidis et al., 2013). However, a clear awareness of the limits of these tools of investigation is needed. For instance, problems may arise regarding representativeness of population, or even technical issues, such as for scarping systems which are not able to offer all the effective amount of data available to the researcher. Despite this, these kinds of studies are taking hold in the social sciences which are paying particular attention to both data and source contextualisation. As a result, they are interesting and valid tools to study issues that classic instruments are not able to perform. Among the different kinds of digital platforms, Twitter allows the combination of textual and geo-referenced data, making this platform an interesting choice, for instance, to detect or monitor different kinds of events (Korkmaz et al.,2015), or it could be used to study the dissemination of influence (Generous et al., 2014). Algorithms are, in this way, extraordinary tools for organising and spreading information. According to these claims, our work aims to understand, both theoretically and methodologically, how the research about territory, as a field of study, has been adapted to prolifically use data coming from algorithms of geo-location or geoparsing (Middleton et al, 2018).Specifically, this work aims to critically discuss the elements and the steps that characterize this emerging approach in order to highlight how the use of geo-localized data can be advantageous for territorial analysis and for which kinds of phenomena..Thus, after showing the most commonly used ways of collecting information about territory using algorithms, we will discuss strategies and techniques of analysis used to combine online (social media) and offline (territorial) sources and try to identify the possible applications for each type of technique. Moreover, a third step allows us to identify the different meanings and operational processes made regarding the concept of territory. That will allow us to recognize the different conceptions of sociological space emerging from the analysis and suggest how to avoid the use of geo-localized data with a simple data-driven perspective (Kitchin, 2014) that does not consider the sociological peculiarities of the space. We will try to answer these questions by examining papers that used Twitter as the source of data. In particular, the analysis of articles will be led thanks to a third kind of content analysis following Rositi’s categorisation (Rositi, 1988). Also, the extraction of the articles will be made using PRISMA methodology (Moher et. Al, 2018) for systematic review.

It has been argued that the fundamental laws of physics do not face a ‘problem of provisos’ equivalent to that found in other scientific disciplines (Earman, Roberts and Smith 2002) and there is only the appearance of exceptions to physical laws if they are confused with differential equations of evolution type (Smith 2002). In this paper I argue that even if this is true, fundamental laws in physics still pose a major challenge to standard Humean approaches to lawhood, as they are not in any obvious sense about regularities in behaviour. A Humean approach to physical laws with exceptions is possible, however, if we adopt a view of laws that takes them to be the algorithms in the algorithmic compressions of empirical data. When this is supplemented with a distinction between lossy and lossless compression, we can explain exceptions in terms of compression artefacts present in the application of the lossy laws.

This article analyzes the scientific literature on k-means clustering and considers how this method is used in psychological studies, based on a sample of articles. It is shown that the majority of publications contains insufficient description of k-means clustering procedures, which can lead to non-reproducibility of research results. This article describes in detail the general steps to follow to perform a k-mean clustering analysis and the decisions to be taken in accordance with its use in the research practice. Recommendations for further improving the quality of scientific papers using k-means clustering are given.

This paper proposes an initial discussion about the production of automatized journalistic narratives. Despite being a topic discussed in specialized sites and international conferences in communication area, the concepts are still deficient in academic research. For this article, we studied the concepts of narrative, databases and algorithms, indicating a theoretical trend that explains this automatized journalistic narratives. As characterization, we use the cases of Los Angeles Times, Narrative Science and Automated Insights.

The Internet in Canada is an assemblage of private and public networks. A variety of institutions and networking codes manage these networks. Conflicts exist between these parties despite their interconnection. Tensions heightened when commercial ISPs began managing traffic on their network using sophisticated routing algorithms. Concerned parties demanded legislation based on a network neutrality principle to prevent undue discrimination. While the network neutrality controversy has been addressed as a question of public policy, the controversy also includes a conflict between various codes constituting networks in Canada. The conflict between codes involve two key networking software that manifest incongruous networks. Their algorithms, the logics embedded in code, differentiate the different types of networking code. The two types of algorithms are Quality of Service and End-to-End. These algorithms treat different modalities of Internet communication differently, in part due to their deployment by different institutions. Quality of Service allows for the tiering of traffic by carriers. Commercial carriers have popularized this algorithm to promote value-added services and prevent network congestions. End-to-end algorithms, on the other hand, enforce a strict equality between modalities of communication. Peer-to-peer applications have popularized an extreme version of the end-to-algorithm, treating all nodes as equals. The popularity and growth of both these algorithms pulls the Internet in different directions, creating conflicts over its future. Through an extended review of these two algorithms and their intersection, this paper confronts how code plays a role in the network neutrality controversy.