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The investigating judge was first mentioned in the French Code of Criminal Procedure in 1808, and then in other countries, including Russia, where a similar procedural person was called a court investigator and was abolished in the early years of Soviet power. Currently, there is a debate in national jurisprudence about the return of the court investigator, showing the ambiguous attitude to this problem. The purpose of the article is to analyze the current state of legal regulation of the institute of investigating judges in the French criminal procedure legislation in order to determine the effectiveness of the performance of its tasks; as well as the nature of criminal procedure relations between the participants of the French criminal proceedings in comparison to similar national ones. The findings make it possible to present a coherent, logical, time-tested construction of the institution of the investigating judge. These activities are characterized by much more detailed regulation, including in the interests of the defense, with a general focus on the protection of individual rights, the exclusion of accusatory bias and the existence of effective safeguards for this purpose. The article shows the real possibilities of the investigating judge to exercise his autonomy and independence from the prosecutor. At the same time, such regulation is sufficiently effective to achieve an objective approach. Other positive consequences are possible in the form of elements of attorney investigation and the deposit of certain types of evidence.

This article discusses the stability of a two-species ecosystem composed of an ammensal (x) and an adversarial (y) species that are continuously harvested. A mathematical model is defined by a system of two nonlinear ordinary differential equations of first order. The considered system's boundedness is investigated. The local stability of the system is described using a variational matrix, while the global stability is examined using Lyapunov's function. The prerequisite for the system to exist in bionomic equilibrium has been identified. The ideal harvesting technique is determined using the maximal principle proposed by Pontryagin. In MATLAB simulations, the stability of the deterministic system is demonstrated for the specified set of parameters.

This article examines the concept of defense disclosures within the theory of managerialism in criminal proceedings in Ghana. Through a doctrinal and comparative legal analysis with the English jurisdiction, it finds that in substance, the requirement of defense disclosure seeks to move the criminal process from its core protectionist ideology that insulates the accused from matters of proof toward a managerial process informed by objectives of truth-finding, trial efficiency and case management. Ironically, this new direction in the criminal trial process is in practice denounced as being at odds with the procedural due process values that shield the accused from matters of proof and pretrial disclosures. The problem is that unlike in England where the move towards defense disclosures is informed by a clear policy change, the managerial policy introduced by the Judiciary in Ghana is not grounded in any articulated theory or policy direction. While pursuing a path of ensuring effective criminal adjudication through mutual disclosures by the parties, it is important to find a proper balance between the denounced but yet adopted procedural concept of defense disclosures and the highly valued protectionist rights of the accused.

Achieving a fair trial and ensuring justice in the trial is initially subject to identifying the principles governing the trial and adapting it to the principles and rules of the national and transnational legal system and adapting it to the circumstances prevailing in each judicial authority. As a quasi-judicial authority with a conciliatory approach and compromise, on the one hand, the deliberations of the council in accordance with the laws and regulations are not subject to the procedures and principles of the trial, and on the other hand, the deliberations of the council in terms of principles and rules are subject to the rules of civil and criminal procedure. Due to the absence of the judge in the council meeting, this issue causes inconsistencies and conflicts in the issuance of the verdict. Sub-vote is the result of the review process and in practice the council judge does not play a key role in it. Therefore, in order to comply with the rules and principles of procedure, it is necessary to separate the issues raised in the council in terms of compromise and compensation from the beginning. Compromise issues without observing the court proceedings by the members of the council and dispute issues with the presence of the council judge in the hearing in accordance with the principles of the court and the governing procedures to be considered in order to achieve a fair trial in practice in this judicial authority.Keywords: Judicial Authority, Dispute Resolution Council, Fair Trial

True-color imagery of satellites provides various atmospheric and surface information for intuitive understanding and visualization. This article presents a conditional generative adversarial network method for generating daytime and nighttime hypothetical visible (VIS) bands of the advanced meteorological imager (AMI) sensor onboard the geostationary Korea multipurpose satellite. The AMI datasets in the form of albedo and brightness temperature (${{\boldsymbol{T}}}_{\boldsymbol{B}}$) were normalized and denormalized between 0 and 1 data-to-data (D2D) translation. The D2D model was trained and tested using data pair of the albedos at AMI VIS bands and AMI infrared (IR) bands or ${{\boldsymbol{T}}}_{\boldsymbol{B}}$ differences between two AMI IR bands. The constructed D2D model showed that the statistical results of bias, root-mean-square-error, and correlation coefficient between the observed and D2D-generated AMI VIS bands during daytime were −0.006 and 0.047 in albedo, and 0.941 for the blue band; −0.007 and 0.05 in albedo and 0.939 for the green band; −0.01 and 0.061 in albedo, and 0.917 for the red band, respectively. The proposed D2D method is being officially used by the Korea meteorological administration. Except for simulating desert areas as clouds at night, the D2D model demonstrated excellent performance, generating hypothetical AMI VIS bands at day and night. Consequently, this article could significantly contribute to the monitoring and understanding of meteorological phenomena over one-third of the Earth. Additionally, the method can be extended to other geostationary weather satellites, including Himawari-8, Fengyun-4A, meteosat third generation, and geostationary operational environmental satellites.

The level of realization of the right to a fair trial is one of the crucial indicators of democracy in any state. In order to ensure this right, all the minimum standards deriving from it must be clearly understood by law enforcement agencies and their practice must meet these standards. As equality of arms, the right to a fair trial, is not directly enshrined in the text of Article 6 of the European Convention on Human Rights (hereafter - the Convention) and is of implicit character; the issues like its essence, content and the way it should manifest in practice are open for discussion. For this reason, the focus on those issues is highly relevant. The aim of this article is, with reference to the case law of the European Court of Human Rights (hereafter - ECHR) and the modern doctrine based on this right, to explain the role of this principle and the essence of its mutual relations with the other elements of the right to a fair trial. Selected case law of ECHR bears great interest compared with other decisions and is discussed in the form of empirical materials of the study. From the doctrinal materials, interpretation of Article 6 of the Convention and theoretical sources related to the European standards in the criminal procedure are also analyzed. The article exercises methods of dialectical comprehension; they are determinism, induction, deduction, case studies and methods of law interpretation. As a result of the study, a unique doctrinal commentary has been obtained in the context of adversariality and impartial and independent court principles of the concept of equality of arms, as well as, interaction of the minimum rights of persons subject to criminal prosecution, guaranteed by the Convention.

As the internet continues to be populated with new devices and emerging technologies, the attack surface grows exponentially. Technology is shifting towards a profit-driven Internet of Things market where security is an afterthought. Traditional defending approaches are no longer sufficient to detect both known and unknown attacks to high accuracy. Machine learning intrusion detection systems have proven their success in identifying unknown attacks with high precision. Nevertheless, machine learning models are also vulnerable to attacks. Adversarial examples can be used to evaluate the robustness of a designed model before it is deployed. Further, using adversarial examples is critical to creating a robust model designed for an adversarial environment. Our work evaluates both traditional machine learning and deep learning models’ robustness using the Bot-IoT dataset. Our methodology included two main approaches. First, label poisoning, used to cause incorrect classification by the model. Second, the fast gradient sign method, used to evade detection measures. The experiments demonstrated that an attacker could manipulate or circumvent detection with significant probability.

The present study, utilizing a descriptive approach and quantitative analysis, analyzed questions in the political interviews in Iran and the United States in order to show what types of adversarial are used in the journalists’ questions and whether there are differences in the use of adversarial between Iranian and American journalists. To this end, the questions addressing the presidents in Iran (i.e. Presidents AhmadiNejad and Roohani) and presidents in the US (i.e. Presidents Obama and Trump), around 70 journalists (35 in each corpus) in political press conference, were randomly collected from 2012 to 2017. The data were then analyzed based Clayman et al.’s (2006) framework to examine how language is used to express adversarial questions. The findings showed that preface tilt was significantly used more in American corpus while other-referencing frames and global adversarial were significantly used more in Iranian corpus. Moreover, in the two corpora, negative questions were the least frequently used type of question and declarative questions was absent in American corpus.

The article gives a brief historical description of the role of the court in the collection of evidence. The arguments in favor of strengthening the role of the court for the recovery of evidence are presented. In particular, the Author substantiates the conclusion that it is necessary to impose on the court the obligation to independently demand evidence in civil proceedings. The Author comes to the conclusion that strengthening the role of the court in the process of proof in civil proceedings are dictated by the requirements due to the many flaws in civil procedural law, the unequal social status of participants in the process, making decisions not in accordance with actual circumstances of the case.

Abstract Fair classification has become an important topic in machine learning research. While most bias mitigation strategies focus on neural networks, we noticed a lack of work on fair classifiers based on decision trees even though they have proven very efficient. In an up-to-date comparison of state-of-the-art classification algorithms in tabular data, tree boosting outperforms deep learning (Zhang et al. in Expert Syst Appl 82:128–150, 2017). For this reason, we have developed a novel approach of adversarial gradient tree boosting. The objective of the algorithm is to predict the output Y with gradient tree boosting while minimizing the ability of an adversarial neural network to predict the sensitive attribute S. The approach incorporates at each iteration the gradient of the neural network directly in the gradient tree boosting. We empirically assess our approach on four popular data sets and compare against state-of-the-art algorithms. The results show that our algorithm achieves a higher accuracy while obtaining the same level of fairness, as measured using a set of different common fairness definitions.

The database of faces containing sensitive information is at risk of being targeted by unauthorized automatic recognition systems, which is a significant concern for privacy. Although there are existing methods that aim to conceal identifiable information by adding adversarial perturbations to faces, they suffer from noticeable distortions that significantly compromise visual perception, and therefore, offer limited protection to privacy. Furthermore, the increasing prevalence of appearance anxiety on social media has led to users preferring to beautify their faces before uploading images. In this paper, we design a novel face database protection scheme via beautification with chaotic systems. Specifically, we construct the adversarial face with better visual perception via beautification for each face in the database. In the training, the face matcher and the beautification discriminator are federated against the generator, prompting it to generate beauty-like perturbations on the face to confuse the face matcher. Namely, the pixel changes produced by face beautification mask the adversarial perturbations. Moreover, we use chaotic systems to disrupt the order of adversarial faces in the database, further mitigating the risk of privacy leakage. Our scheme has been extensively evaluated through experiments, which show that it effectively defends against unauthorized attacks while also yielding good visual results.

El principio de igualdad de armas es un mandato esencial que consiste en que “cada parte debe tener una oportunidad razonable para presentar su caso en condiciones que no la pongan en desventaja con respecto a su oponente”1. Esta figura, a pesar de su connotada y evidente importancia, no ha sido objeto de estudio profundo y serio en la doctrina y la jurisprudencia colombianas. Lo anterior ha permitido un uso irresponsable y equivocado de este concepto, y es de ahí que nace la necesidad de este artículo, el cual tiene por objeto, sin pretender ser exhaustivo, dar una mayor claridad sobre este mandato de op­timización, empezando por revisar sus antecedentes; pasando por el análisis de cada uno de sus elementos esenciales; la referencia a algunas categorías desarrolladas en la jurisdicción internacional que son de suma importancia para alcanzar un entendimiento íntegro de dicho principio; el señalamiento de las diferentes posiciones sobre su fundamento, definición y alcance; y una diferenciación con otros derechos y principios con los que suele confundirse. De esta manera, se sentarán las bases para que, posteriormente, sea posible abrir un debate organizado acerca de esta figura que haga viable un ejercicio optimizado y responsable de ella.

Artificial Intelligence (AI) is one of the hottest topics in our society, especially when it comes to solving data-analysis problems. Industry are conducting their digital shifts, and AI is becoming a cornerstone technology for making decisions out of the huge amount of (sensors-based) data available in the production floor. However, such technology may be disappointing when deployed in real conditions. Despite good theoretical performances and high accuracy when trained and tested in isolation, a Machine-Learning (M-L) model may provide degraded performances in real conditions. One reason may be fragility in treating properly unexpected or perturbed data. The objective of the paper is therefore to study the robustness of seven M-L and Deep-Learning (D-L) algorithms, when classifying univariate time-series under perturbations. A systematic approach is proposed for artificially injecting perturbations in the data and for evaluating the robustness of the models. This approach focuses on two perturbations that are likely to happen during data collection. Our experimental study, conducted on twenty sensors’ datasets from the public University of California Riverside (UCR) repository, shows a great disparity of the models’ robustness under data quality degradation. Those results are used to analyse whether the impact of such robustness can be predictable—thanks to decision trees—which would prevent us from testing all perturbations scenarios. Our study shows that building such a predictor is not straightforward and suggests that such a systematic approach needs to be used for evaluating AI models’ robustness.

El presente documento tiene como propósito efectuar una aproximación, desde el punto de vista jurisprudencial y legal, del desarrollo que ha tenido la prueba oficiosa en el sistema penal adversarial de tendencia acusatoria, implementado en Colombia con la Ley 906 de 2004, a fin de establecer la tensión existente entre los principios de imparcialidad, igualdad de armas y legalidad, frente al principio de justicia material y en el contexto del rol del juez en el proceso. En efecto, esta es una de las discusiones que enfrentan quienes administran justicia y quienes acuden a ella para resolver los conflictos sociales, en la que se evidencia que la construcción de un sistema acusatorio es un proceso inacabado y en constante evolución. Para ello se hace necesario abordar no solo un concepto meramente legalista, sino que se requiere recabar en la filosofía misma del sistema penal acusatorio y las realidades en que este se aplica, para cumplir los cometidos sociales para los cuales fue creado.

Machine learning models are vulnerable to adversarial inputs that induce seemingly unjustifiable errors. As automated classifiers are increasingly used in industrial control systems and machinery, these adversarial errors could grow to be a serious problem. Despite numerous studies over the past few years, the field of adversarial ML is still considered alchemy, with no practical unbroken defenses demonstrated to date, leaving PHM practitioners with few meaningful ways of addressing the problem. We introduce turbidity detection as a practical superset of the adversarial input detection problem, coping with adversarial campaigns rather than statistically invisible one-offs. This perspective is coupled with ROCtheoretic design guidance that prescribes an inexpensive domain adaptation layer at the output of a deep learning model during an attack campaign. The result aims to approximate the Bayes optimal mitigation that ameliorates the detection model’s degraded health. A proactively reactive type of prognostics is achieved via Monte Carlo simulation of various adversarial campaign scenarios, by sampling from the model’s own turbidity distribution to quickly deploy the correct mitigation during a real-world campaign.

International criminal tribunals have procedural rules of both an adversarial and inquisitorial nature. Such tribunals portray that it is possible to amalgamate what are often thought of as dichotomous models. This essay seeks to show that these are, in fact, not dichotomous models but are increasingly converging in both national and international judicial systems. The reasons for the adversarial/inquisitorial distinction being a redundant conversation are threefold: firstly, there is no longer a “pure” adversarial or inquisitorial system, with national judicial systems increasingly incorporating elements of both; secondly, the norms of human rights necessitate the convergence of the two models; and finally, the unique context and goals of international justice mean that the perceived dichotomy of the adversarial/inquisitorial system is no longer relevant. As a result, international criminal tribunals portray that it is possible to incorporate elements of both systems into a single judicial system.

Los modelos adversariales fueron instaurados en el Ecuador en todas sus materias. Un modelo de justicia basado en audiencias requiere a un Juez preparado no solo para conducir de forma adecuada una audiencia, sino también, una preparación para poder almacenar y sistematizar información de forma perfecta. El presente trabajo de investigación nos aclara la forma como se debe no solo preinstalar una audiencia en un modelo adversarial, sino instalarla, desarrollarla y resolverla de forma adecuada en función del tipo de procedimiento invocado.

Many real-world decision-making problems involve multiple conflicting objectives that can not be optimized simultaneously without a compromise. Such problems are known as multi-objective Markov decision processes and they constitute a significant challenge for conventional single-objective reinforcement learning methods, especially when an optimal compromise cannot be determined beforehand. Multi-objective reinforcement learning methods address this challenge by finding an optimal coverage set of non-dominated policies that can satisfy any user's preference in solving the problem. However, this is achieved with costs of computational complexity, time consumption, and lack of adaptability to non-stationary environment dynamics. In order to address these limitations, there is a need for adaptive methods that can solve the problem in an online and robust manner. In this paper, we propose a novel developmental method that utilizes the adversarial self-play between an intrinsically motivated preference exploration component, and a policy coverage set optimization component that robustly evolves a convex coverage set of policies to solve the problem using preferences proposed by the former component. We show experimentally the effectiveness of the proposed method in comparison to state-of-the-art multi-objective reinforcement learning methods in stationary and non-stationary environments.

The best-interest-of-the-child concept should guide the legislative framework with regard to the approach followed as well as the disciplinary processes used in schools. Currently schools revert mostly to a retributive and adversarial approach to discipline that is not compatible with the best-interests-of-the-child standard. In this article, the provisions of section 8 of the Schools Act are scrutinised and it is concluded that these provisions are supporting an adversarial and punitive approach to school discipline. This is evident from the lack of prescriptions ensuring that sanctions serve the best interest of children, the insufficient provision for support measures and structures for counselling, the undue focus on the best interests of the transgressor and the lack of guidance concerning the appointment of an intermediary. The introduction of restorative discipline as an alternative approach to discipline is recommended. The latter approach is recommended, because it is submitted that amendments to the existing legislative provisions would not address the key objection to the legislative framework namely its retributive and adversarial character.

The best-interest-of-the-child concept should guide the legislative framework with regard to the approach followed as well as the disciplinary processes used in schools. Currently schools revert mostly to a retributive and adversarial approach to discipline that is not compatible with the best-interests-of-the-child standard. In this article, the provisions of section 8 of the Schools Act are scrutinised and it is concluded that these provisions are supporting an adversarial and punitive approach to school discipline. This is evident from the lack of prescriptions ensuring that sanctions serve the best interest of children, the insufficient provision for support measures and structures for counselling, the undue focus on the best interests of the transgressor and the lack of guidance concerning the appointment of an intermediary. The introduction of restorative discipline as an alternative approach to discipline is recommended. The latter approach is recommended, because it is submitted that amendments to the existing legislative provisions would not address the key objection to the legislative framework namely its retributive and adversarial character.

It is of significant importance for any classification and recognition system, which claims near or better than human performance to be immune to small perturbations in the dataset. Researchers found out that neural networks are not very robust to small perturbations and can easily be fooled to persistently misclassify by adding a particular class of noise in the test data. This, so-called adversarial noise severely deteriorates the performance of neural networks, which otherwise perform really well on unperturbed dataset. It has been recently proposed that neural networks can be made robust against adversarial noise by training them using the data corrupted with adversarial noise itself. Following this approach, in this paper, we propose a new mechanism to generate a powerful adversarial noise model based on K-support norm to train neural networks. We tested our approach on two benchmark datasets, namely the MNIST and STL-10, using muti-layer perceptron and convolutional neural networks. Experimental results demonstrate that neural networks trained with the proposed technique show significant improvement in robustness as compared to state-of-the-art techniques.

En unión de la tendencia a garantizar la imparcialidad judicial, encomendando la investigación de los delitos al fiscal, surgen dos cuestiones importantes:a) cómo se garantiza la imparcialidad del órgano acusador a la hora de efectuar el juicio de acusación; y b) las dificultades de la defensa para ejercitar sus derechos en el seno de dicho juicio de acusación. Ilustran estos temas, sendas referencias al proceso penal anglosajón y norteamericano; dos modelos internacionales, como son la CPI y los proyectos de la UE (Libro Verde y Corpus Iuris); y dos ejemplos de ordenamientos europeos, objetos de sendas reformas: Italia y EspañaTogether with the tendency to guarantee the juridical objectivity; commending the investigation of offences to the public prosecutor, two important issues arise: a) How the objectivity of the prosecuting organ is guaranteed at the time of_executing the prosecution trial. b) The difficulties of the defense to practice its rights in the frame of such_prosecution trial. Important references to the North American and Anglo-Saxon legal process illustrate this topic; two international models such as the CPI and the EU projects (Green Book and Corpus Iuris); and two examples of European ordinances, object of important reforms: Italy and Spain