Reviewerly/exHarmony huggingface dataset:
The Role of the Digital Environment in the Context of Cultural Rights

The rapid development of information and communication technologies has created the need for digital transformation, changed the cultural sector and the opportunities and risks of accessing and consuming culture. This paper will analyze how these processes have affected the exercise of cultural rights.
Mathematical Model, Development of Algorithms and Measurement of Parameters of Objects in Monitoring Systems for Protection of Cultural Heritage

This article is devoted to the creation of a mathematical model processing the output signal of video surveillance systems, based on information about the characteristics of the signals of the objects of observation, in order to protect cultural heritage. The subject of the study is the relationship between the structure and parameters of the output signal, certain changes in the situation in the area of observation and detection of a signal from foreign objects against the background of noise. Typical physical conditions for the functioning of video surveillance systems are defined and general recommendations for maintaining the operating point are offered. Algorithms have been developed that realize the functionality of the optimal detector device by numerical methods.
Vid2Param: Modelling of Dynamics Parameters from Video

Videos provide a rich source of information, but it is generally hard to extract dynamical parameters of interest. Inferring those parameters from a video stream would be beneficial for physical reasoning. Robots performing tasks in dynamic environments would benefit greatly from understanding the underlying environment motion, in order to make future predictions and to synthesize effective control policies that use this inductive bias. Online physical reasoning is therefore a fundamental requirement for robust autonomous agents. When the dynamics involves multiple modes (due to contacts or interactions between objects) and sensing must proceed directly from a rich sensory stream such as video, then traditional methods for system identification may not be well suited. We propose an approach wherein fast parameter estimation can be achieved directly from video. We integrate a physically based dynamics model with a recurrent variational autoencoder, by introducing an additional loss to enforce desired constraints. The model, which we call Vid2Param, can be trained entirely in simulation, in an end-to-end manner with domain randomization, to perform online system identification, and make probabilistic forward predictions of parameters of interest. This enables the resulting model to encode parameters such as position, velocity, restitution, air drag and other physical properties of the system. We illustrate the utility of this in physical experiments wherein a PR2 robot with a velocity constrained arm must intercept an unknown bouncing ball with partly occluded vision, by estimating the physical parameters of this ball directly from the video trace after the ball is released.
Automated Customized Bug-Benchmark Generation

We introduce Bug-Injector, a system that automatically creates benchmarks for customized evaluation of static analysis tools. We share a benchmark generated using Bug-Injector and illustrate its efficacy by using it to evaluate the recall of two leading open-source static analysis tools: Clang Static Analyzer and Infer. Bug-Injector works by inserting bugs based on bug templates into real-world host programs. It runs tests on the host program to collect dynamic traces, searches the traces for a point where the state satisfies the preconditions for some bug template, then modifies the host program to inject a bug based on that template. Injected bugs are used as test cases in a static analysis tool evaluation benchmark. Every test case is accompanied by a program input that exercises the injected bug. We have identified a broad range of requirements and desiderata for bug benchmarks; our approach generates on-demand test benchmarks that meet these requirements. It also allows us to create customized benchmarks suitable for evaluating tools for a specific use case (e.g., a given codebase and set of bug types). Our experimental evaluation demonstrates the suitability of our generated benchmark for evaluating static bug-detection tools and for comparing the performance of different tools.
Music Emotion Representation Learning Based on Multisource Data Fusion and Its Application

Based on the multisource data fusion and fusion of music emotion expression learning and its application, this paper further analyzes the actual influence of music emotion and Internet multisource data in emotion learning. This paper uses multisource data to improve the professionalism and concentration of music emotion and uses modern Internet technology to help users quickly integrate into music emotion learning. At the same time, the multisource data structure can develop the music learning structure to a high-quality level. It is precisely because of the emphasis of the multisource data model architecture that the learning mechanism of musical emotion representation can be continuously updated and improved, which is mutually promoted jointly with Internet technology.
A Simulation of How a Cloud Service Provider from the Midwest Should Behave When Faced with a Potential Cyber-Attack, Where Many of Its Customers Do Business in the Healthcare, Banking, and Educational Industries

This essay aims to explain to the senior management of a company what must be accomplished to be compliant with federal sectoral privacy laws. It is a byzantine maze of pitfalls where a single cyber-attack can lead to extensive oversight by the Federal Trade Commission. The path taken by this paper is that a cloud computing provider should implement the most stringent security framework in existence that encompasses the myriad number of privacy laws in the United States. The reason is that vigorously embracing a strict standard makes a firm likely to comply with the various sectoral privacy laws. However, suppose a company is cyber-attacked and has the misfortune of being prosecuted by the Federal Trade Commission. In that case, the article suggests that the firm take a mature approach to the litigation, not complaining to the agency that it is the victim. A mature approach to federal oversight might lessen the time of the supervisory period. By admitting security omissions and commissions and robustly accepting regulatory guidance, a firm can proceed in conducting its business, not fretting over the de facto guardianship by the Federal Trade Commission.
Designing the Next Generation of Intelligent Personal Robotic Assistants for the Physically Impaired

The physically impaired commonly have difficulties performing simple routine tasks without relying on other individuals who are not always readily available and thus make them strive for independence. While their impaired abilities can in many cases be augmented (to certain degrees) with the use of assistive technologies, there has been little attention to their applications in embodied AI with assistive technologies. This paper presents the modular framework, architecture, and design of the mid-fidelity prototype of MARVIN: an artificial-intelligence-powered robotic assistant designed to help the physically impaired in performing simple day-to-day tasks. The prototype features a trivial locomotion unit and also utilizes various state-of-the-art neural network architectures for specific modular components of the system. These components perform specialized functions, such as automatic speech recognition, object detection, natural language understanding, speech synthesis, etc. We also discuss the constraints, challenges encountered, potential future applications and improvements towards succeeding prototypes.
impact of ESG strategies integration on the operational and reputational risks

This study aimed to demonstrate the impact of strategies integration of environmental, social and corporate governance strategies (ESG) on operational and reputational risks: a literature review for insurance companies listed on the Amman Stock Exchange. where the study population consisted of 22 Jordanian insurance companies, while the sample consisted of 8 companies, and one was excluded due to the lack of data, and based on the descriptive analytical approach, the study reviewed many previous studies related to its subject, and using the method of content analysis for annual reports and disclosures issued by Major insurance companies during the period 2020-2021, where a survey list was designed to measure the extent of the research companies' commitment to environmental, social and corporate governance strategies. The study concluded with many results, perhaps the most prominent of which is the presence of disclosure about social responsibility activities in the annual reports, and that all companies focused in their activities on providing donations and support to the local community and supporting education and health issues during the Covid pandemic period,,,
role of talent management in developing technological competencies: The mediating role of information technology

This study aimed to clarify the role of talent management in the development of technological competencies as the mediating role of information technology. The study population consisted of the Jordanian private universities, where the application was applied to a sample that included a group of (department manager, human resources manager, department head, and administrative employee). The researcher relied on the quantitative approach in collecting primary data by making a questionnaire, developing it and distributing it to the Jordanian private universities. The hypotheses were analyzed and tested using appropriate statistical methods and the use of the Statistical Package for Social Sciences (SPSS). The final sample amounted to (220) questionnaires. The study reached a set of results, the most important of which is that there is a statistically significant effect at the level of significance (α≥0.05) for talent management in developing the technological competencies. One of the most important recommendations of the study is the keenness to use appropriate advertising media in identifying talented people.
SIGN LANGUAGE DETECTION USING LSTM NEURAL NETWORK

The main aim of the project is to create a user-friendly interface between normal people and deaf and dumb people. Humans communicate with one another using natural language channels such as words and writing, or by body language (gestures) such as hand motions, head gestures, facial expression, lip motion, and so forth. Comprehending sign language is equally as vital as understanding natural language. The predominant mode of communication is sign language among the deaf and the hearing-impaired people all over the world. sign language said to have different gestures where each gesture has specific meaning. Hearing-impaired people use sign language as their primary mode of communication. Without a translation, people with hearing impairments have difficulty speaking with other hearing people. As a result, implementing a system that recognises sign language would have a substantial positive impact on the social lives of deaf people. We propose a modified for continuous sequences of gestures, the LSTM model is used. also known as continuous SLD, that detects a series of related motions in this research. It is based on the division the division of a continuous symbol into sub-units and the modelling of these sub-units using neural networks. As a result, different combinations of sub-units are not necessary to be considered in the course of training. The suggestion is that approach has been put to the test with the help of Indian Sign Language signed sentences (ISL). Different sign terms are used to recognise these sign sentences.
Ordinal Conditional Functions for Abstract Argumentation

We interpret and formalise ordinal conditional functions (OCFs) in abstract argumentation frameworks based on ideas and concepts defined for conditional logics. There, these functions are used to rank interpretations, and we adapt them to rank extensions instead. Using conflict-freeness and admissibility as two essential principles to define the semantics of OCFs, we obtain a framework that allows to rank sets of arguments wrt. their plausibility. We analyse the properties of this framework in-depth, and in doing so we establish a formal bridge between the approaches of abstract argumentation and conditional logics.
Arguing About the Existence of Conflicts1

In this paper we formalise a meta-argumentation framework as an ASPIC+ extension which enables reasoning about conflicts between formulae of the argumentation language. The result is a standard abstract argumentation framework that can be evaluated via grounded semantics.
Automated Reasoning with Epistemic Graphs Using SAT Solvers

Epistemic graphs have been developed for modelling an agent’s degree of belief in an argument and how belief in one argument may influence the belief in other arguments. These beliefs are represented by constraints on probability distributions. In this paper, we present a framework for reasoning with epistemic graphs that allows for beliefs for individual arguments to be determined given beliefs in some of the other arguments. We present and evaluate algorithms based on SAT solvers.
Explaining Change in Quantitative Bipolar Argumentation1

This paper presents a formal approach to explaining change of inference in Quantitative Bipolar Argumentation Frameworks (QBAFs). When drawing conclusions from a QBAF and updating the QBAF to then again draw conclusions (and so on), our approach traces changes – which we call strength inconsistencies – in the partial order that a semantics establishes on the arguments in the QBAFs. We trace the strength inconsistencies to specific arguments, which then serve as explanations. We identify both sufficient and counterfactual explanations for strength inconsistencies and show that our approach guarantees that explanation arguments exist if and only if an update leads to strength inconsistency.
Reasoning With and About Norms in Logical Argumentation

Normative reasoning is inherently defeasible. Formal argumentation has proven to be a unifying framework for representing nonmonotonic logics. In this work, we provide an argumentative characterization of a large class of Input/Output logics, a prominent defeasible formalism for normative reasoning. In many normative reasoning contexts, one is not merely interested in knowing whether a specific obligation holds, but also in why it holds despite other norms to the contrary. We propose sequent-style argumentation systems called Deontic Argument Calculi (DAC), which serve transparency and bring meta-reasoning about the inapplicability of norms to the object language level. We prove soundness and completeness between DAC-instantiated argumentation frameworks and constrained Input/Output logics. We illustrate our approach in view of two deontic paradoxes.
Explainable Logic-Based Argumentation

Explainable artificial intelligence (XAI) has gained increasing interest in recent years in the argumentation community. In this paper we consider this topic in the context of logic-based argumentation, showing that the latter is a particularly promising paradigm for facilitating explainable AI. In particular, we provide two representations of abductive reasoning by sequent-based argumentation frameworks and show that such frameworks successfully cope with related challenges, such as the handling of synonyms, justifications, and logical equivalences.
The Skeptic Web Service: Utilising Argument Technologies for Reason-Checking

Skeptic is a web service aimed at automatically providing pointers for the critical assessment of a persuasive text. That is, with a natural language text as input, the web service returns a ranked list of questions designed to help readers reason-check fake news and other contentious texts. Internally, Skeptic maps argumentative features of the text to methods for critical assessment, such as the critical questions of argument schemes, ways of evaluating different types of propositions, and signs of possible biased reasoning. The argumentative features are retrieved by utilising extant techniques for argument mining and classification.
PyArg for Solving and Explaining Argumentation in Python: Demonstration

We introduce PyArg, a Python-based solver and explainer for both abstract argumentation and ASPIC+. A large variety of extension-based semantics allows for flexible evaluation and several explanation functions are available.
Well, to Be Honest, I Wouldnt Start from Here at All

Computational complexity theory and the related area of efficient algorithms have formed significant subfields of Abstract Argumentation going back over 20 years. There have been major contributions and an increased understanding of the computational issues that influence and beset effective implementation of argument methods. My aim, in this article, is to attempt to take stock of the standing of work in complexity theory as it presently is within the field of Computational Argument, as well as offering some personal views on its future direction.
Annotating Very Large Arguments

We present a method of annotating very large arguments, with the use of IMC-Tool. IMC-Tool aids in creating long-distance argument structure relations, by providing a simple annotation tool, and integration software to synthesise argument annotations at scale.
Rule-PSAT: Relaxing Rule Constraints in Probabilistic Assumption-Based Argumentation

Probabilistic rules are at the core of probabilistic structured argumentation. With a language L, probabilistic rules describe conditional probabilities Pr(σ0|σ1,…,σk) of deducing some sentences σ0∈L from others σ1,…,σk∈L by means of prescribing rules σ0←σ1,…,σk with head σ0 and body σ1,…,σk. In Probabilistic Assumption-based Argumentation (PABA), a few constraints are imposed on the form of probabilistic rules. Namely, (1) probabilistic rules in a PABA framework must be acyclic, and (2) if two rules have the same head, then the body of one rule must be the subset of the other. In this work, we show that both constraints can be relaxed by introducing the concept of Rule Probabilistic Satisfiability (Rule-PSAT) and solving the underlying joint probability distribution on all sentences in L. A linear programming approach is presented for solving Rule-PSAT and computing sentence probabilities from joint probability distributions.
Accessibility Challenges with CAPTCHA Services in Digital Libraries

In the paper are discussed security problems related to online digital libraries and portals. Special attention is placed to one the methods to distinguish usage of online digital libraries from non-human users. The approaches known under the abbreviation CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart) are considered in the context of their accessibility to the users with different types of disabilities.
probo2: A Benchmark Framework for Argumentation Solvers

We introduce probo2, an end-to-end benchmark framework for abstract argumentation solvers. It offers evaluation capabilities and analysis features for a wide range of computational problems and is easily customizable.
Serialisable Semantics for Abstract Argumentation

We investigate the recently proposed notion of serialisability of semantics for abstract argumentation frameworks. This notion describes semantics where the construction of extensions can be serialised through iterative addition of minimal non-empty admissible sets. We investigate general relationships between serialisability and other principles from the literature. We also investigate the novel unchallenged semantics as a new instance of a serialisable semantics and, in particular, analyse it in terms of satisfied principles and computational complexity.
Polemicist: A Dialogical Interface for Exploring Complex Debates

In this paper, we present Polemicist 2, a dialogical interface for exploring complex debates from the BBC Radio 4 programme The Moral Maze. Polemicist allows the user to interact with software agents representing the participants in the original programme. The software enables the user to explore the topic as they wish, asking questions to dive deeper on the areas that interest them most.
Peculiarities of using web 2.0 technologies as the main tool of image sociocommunication technologies

The purpose of the article is to define the features of the use of Web 2.0 technologies as the main tool of image socio-communication technologies of higher education institutions. The methodology of the research is based on the general scientific and special methods of cognition such as analysis, synthesis,logical method, monitoring, and the method of visualization of the research results. The scientific novelty is because Web 2.0 technologies are a modern tool for establishing social interaction between participants in the educational process. The peculiarities of using Web 2.0 technologies as the main tool of image sociocommunication technologies are determined. Conclusions. The prospects for the use of Web 2.0 technologies as the main tool for image socio-communication technologies of the university are determined: the presence of its own page in the encyclopedia "Wikipedia", which is intended to popularize the institution of higher education and inform the target audience of different countries of the world (submission of the text of articles in different languages); issuance of the university website for a search query in top search engines, which ensures credibility among potential consumers of educational services, advertising and promotion of educational services, as well as establishing information and communication relations with representatives of the target audience; corporate portal with internal communication systems as an opportunity to form an effective internal image of the university through the implementation of information openness and effective communication between participants in the educational process; interactive distancelearning using an electronic library and cloud services for teachers and students as an Internet platform to meet the information needs of scientists and teachers at a qualitatively new level, as well as the possibility of providing educational services to students with disabilities; information resources of social networks and the video hosting service "YouTube" as a tool that, due to its prevalence and popularity, can influence the consciousness of a significant number of the population, form and maintain an effective, sustainable and competitive image of the institution in them. The choice of presented SCT Web 2.0 is determined by the possibility of forming an effective image of the university, taking into account the information needs of the target audience.Key words: image, higher education institution, Web 2.0 technologies.