Reviewerly/exHarmony huggingface dataset:
Security and Safety Aspects of AI in Industry Applications

In this relatively informal discussion-paper we summarise issues in the domains of safety and security in machine learning that will affect industry sectors in the next five to ten years. Various products using neural network classification, most often in vision related applications but also in predictive maintenance, have been researched and applied in real-world applications in recent years. Nevertheless, reports of underlying problems in both safety and security related domains, for instance adversarial attacks have unsettled early adopters and are threatening to hinder wider scale adoption of this technology. The problem for real-world applicability lies in being able to assess the risk of applying these technologies. In this discussion-paper we describe the process of arriving at a machine-learnt neural network classifier pointing out safety and security vulnerabilities in that workflow, citing relevant research where appropriate.
Face editing with GAN -- A Review

In recent years, Generative Adversarial Networks (GANs) have become a hot topic among researchers and engineers that work with deep learning. It has been a ground-breaking technique which can generate new pieces of content of data in a consistent way. The topic of GANs has exploded in popularity due to its applicability in fields like image generation and synthesis, and music production and composition. GANs have two competing neural networks: a generator and a discriminator. The generator is used to produce new samples or pieces of content, while the discriminator is used to recognize whether the piece of content is real or generated. What makes it different from other generative models is its ability to learn unlabeled samples. In this review paper, we will discuss the evolution of GANs, several improvements proposed by the authors and a brief comparison between the different models. Index Terms generative adversarial networks, unsupervised learning, deep learning.
Towards Global Optimality in Cooperative MARL with the Transformation And Distillation Framework

Decentralized execution is one core demand in cooperative multi-agent reinforcement learning (MARL). Recently, most popular MARL algorithms have adopted decentralized policies to enable decentralized execution and use gradient descent as their optimizer. However, there is hardly any theoretical analysis of these algorithms taking the optimization method into consideration, and we find that various popular MARL algorithms with decentralized policies are suboptimal in toy tasks when gradient descent is chosen as their optimization method. In this paper, we theoretically analyze two common classes of algorithms with decentralized policies -- multi-agent policy gradient methods and value-decomposition methods to prove their suboptimality when gradient descent is used. In addition, we propose the Transformation And Distillation (TAD) framework, which reformulates a multi-agent MDP as a special single-agent MDP with a sequential structure and enables decentralized execution by distilling the learned policy on the derived ``single-agent" MDP. This approach uses a two-stage learning paradigm to address the optimization problem in cooperative MARL, maintaining its performance guarantee. Empirically, we implement TAD-PPO based on PPO, which can theoretically perform optimal policy learning in the finite multi-agent MDPs and shows significant outperformance on a large set of cooperative multi-agent tasks.
4th IR – The Impact the Use of Mobile Teaching Devices will have on Higher Education

Students and lecturers use mobile devices more and more and within a few years they will become indispensable tools in the classroom.Recent research clearly indicates that mobile devices such as smartphones, laptops and tablets are the tools of choice for students, scholars, teachers, and lecturers.It is playing a major role in teaching and learning, especially in higher education.It is therefore indisputable that the development of artificial intelligence and new ways of communication take their place in the classroom during the 4 th IR.The integration of these new technologies into the teaching and learning experience in the classroom will be dependent on effective pedagogical implementation and planning to be successful.Taking this into account, this paper explores the effect that mobile devices have in the classroom on the teaching and learning experience of the student as viewed from the student's perspective.The advantages of the implementation of mobile devices must be weighed against the negative influence they may have.All the participants in the study reported that they have access to and use mobile devices to use the internet to source information.
THE NEED FOR LIFELONG LEARNING AND PROFESSIONAL DEVELOPMENT OF SPORTS MANAGERS

Abstract. The development of the intellectual abilities of managers is an essential mechanism for the modernization of the society in a continuous phenomenon of globalization. According to A.N. Dakhin, this means that, in fact, "the ability to generate, reproduce, master and use knowledge becomes the main resource of a person in the 21st century". Another point of view in this direction is the opinion of Michael Barber, one of the world's leading experts in educational policy, who states that the need for a transition to a school model, "whose purpose is to prepare students, has become obvious, for the knowledge-based economy, developing the ability to search, synthesize and critically understand an increasing volume of information, as well as the simple assimilation of knowledge. " Thus, managers certainly need to train and develop appropriate skills to perform their activities in optimal and efficient conditions”. M. Barber suggests that the educational outcomes of graduates depend mainly on the quality of teaching. One of the structural elements that characterizes an efficient education system is the professional teaching staff and the "continuous improvement of the qualities and skills of the staff". A large number of studies have been devoted to the problem of professional development of a teacher, but the issue of leading teachers learning we find it in less researches.
Kernel Contraction and the Order of Relevance

The postulate of relevance provides a suitable and general notion of minimal change for belief contraction. Relevance is tightly connected to smooth kernel contractions when an agent's epistemic state is represented as a logically closed set of formulae. This connection, however, breaks down when an agent's epistemic state is represented as a set of formulae not necessarily logically closed. We investigate the cause behind this schism, and we reconnect relevance with smooth kernel contractions by constraining the behaviour of their choice mechanisms and epistemic preference relations. Our first representation theorem connects smooth kernel contractions with a novel class of epistemic preference relations. For our second representation theorem, we introduce the principle of symmetry of removal that relates relevance to epistemic choices. For the last theorem, we devise a novel class of smooth kernel contractions, that satisfy relevance, which are based on epistemic preference relations that capture the principle of symmetry of removal.
On Dynamics in Structured Argumentation Formalisms

In this paper we contribute to the investigation of dynamics in assumption-based argumentation (ABA) and investigate situations where a given knowledge base undergoes certain changes. We show that two frequently investigated problems, namely enforcement of a given target atom and deciding strong equivalence of two given ABA frameworks, are intractable in general. Interestingly, these problems are both tractable for abstract argumentation frameworks (AFs) which admit a close correspondence to ABA by constructing semantics-preserving instances. Inspired by this observation, we search for tractable fragments for ABA frameworks by means of the instantiated AFs. We argue that the usual instantiation procedure is not suitable for the investigation of dynamic scenarios since too much information is lost when constructing the AF. We thus consider an extension of AFs, called cvAFs, equipping arguments with conclusions and vulnerabilities in order to better anticipate their role after the underlying knowledge base is extended. We investigate enforcement and strong equivalence for cvAFs and present syntactic conditions to decide them. We show that the correspondence between cvAFs and ABA frameworks is close enough to capture ABA also in dynamic scenarios. This yields the desired tractable ABA fragment. We furthermore discuss consequences for the corresponding problems for logic programs.
Defining Defense and Defeat in Abstract Argumentation From Scratch -- A Generalizing Approach

We propose a general framework to investigate semantics of Dung-style argumentation frameworks (AFs) by means of a generic defeat notion formalized by refute operators. After establishing the technical foundations, we propose natural generic versions of Dung's classical semantics. We demonstrate how classical as well as recent proposals can be captured by our approach when utilizing suitable notions of refutal. We perform an investigation of basic properties which semantics inherit from the underlying refute operator. In particular, we show under which conditions a counterpart to Dung's fundamental lemma can be inferred and how it ensures the existence of the generalized version of complete extensions. We contribute to a principle-based study of AF semantics by discussing properties tailored to compare different refute operators. Finally, we report computational complexity results for basic reasoning tasks which hold in our general framework.
Towards an Enthymeme-Based Communication Framework in Multi-Agent Systems

Communication is one of the most important aspects of multi-agent systems. Among the different communication techniques applied to multi-agent systems, argumentation-based approaches have received special interest from the community, because allowing agents to exchange arguments provides a rich form of communication. In contrast to the benefits that argumentation-based techniques provide to multi-agent communication, extra weight on the communication infrastructure results from the additional information exchanged by agents, which could restrict the practical use of such techniques. In this work, we propose an argumentation framework whereby agents are able to exchange shorter messages when engaging in dialogues by omitting information that is common knowledge (e.g., information about a shared multi-agent organisation). In particular, we focus on using enthymemes, shared argumentation schemes (i.e., reasoning patterns from which arguments are instantiated), and common organisational knowledge to build an enthymeme-based communication framework. We show that our approach addresses some of Grice's maxims, in particular that agents can be brief in communication, without any loss in the content of the intended arguments.
On the Expressive Power of Intermediate and Conditional Effects in Temporal Planning

Automated planning is the task of finding a sequence of actions that reach a desired goal, given a description of their applicability and their effects on the world. In temporal planning, actions have a duration and can overlap in time. In modern temporal planning formalisms, two features have been introduced which are very useful from a modeling perspective, but are not yet thoroughly understood: intermediate conditions and effects (ICE) and conditional effects. The expressive power of such constructs is yet not well comprehended, especially when time is dense, and no minimum separation is required between mutex events. This paper reveals that both ICE and conditional effects do not add expressive power with regards to common temporal planning formalisms. In particular, we show how they can be compiled away using a polynomial-size encoding that makes no assumptions on the time domain. This encoding advances our understanding of these features, and allow their use with simple temporal planners that lack their support. Moreover, it provides a constructive proof that temporal planning with ICE and conditional effects remains PSPACE-complete.
Tools For Cyber Forensics

Digital Forensics &amp; Cyber Security Graduate Programme Department Of Information Systems &amp; Innovations Ghana Institute of Management &amp; Public Administration Greenhill, Accra, Ghana E-mails: peeuncle3@gmail.com Phone: +233242776968 ABSTRACT Digital forensics, or Cyber security, has become a vital part of almost every research, and digital forensics tools' users are becoming more diverse in their backgrounds and interests. As a result, usability is an important section of these tools. This paper investigates the usability aspect of forensics tools. The study results highlight several usability issues that need to be considered when designing and implementing digital forensics tools. Cyber-attacks are fast-moving and surging in number and severity. When the attacks occur, the attacked enterprise responds with predetermined actions. Applying digital forensics helps in recovering and investigating material on digital media and networks is one of these actions. Cyber Forensic Investigation includes the Capture and Analysis of digital data either to prove or disprove whether the internet-related theft has been committed or not. Earlier, Computers were used only to store large volumes of data and perform many operations on them, but nowadays, it has expanded and occupied a prior role in Crime Investigation. To solve these cyber-related problems, the selection and usage of Forensic tools are essential. The developers have created many cyber forensic tools for better research and quick investigation. Cop departments and investigation agencies select the tools based on various factors, including budget and available experts on the team. This paper describes the different types of existing computer forensic tools and their usage. The article gives detailed information on all related works by other scholars in the area of this paper. Keywords: Digital Forensics; Forensics, GUI, User Interface, Digital Forensics, and its framework, Cyber forensics tools. BOOK Chapter ǀ Research Nexus in IT, Law, Cyber Security &amp; Forensics. Open Access. Distributed Free Citation: Peter Oppong Baafi (2022): Toosl For Cyber Forensics Book Chapter Series on Research Nexus in IT, Law, Cyber Security &amp; Forensics. Pp 285-290 www.isteams.net/ITlawbookchapter2022. dx.doi.org/10.22624/AIMS/CRP-BK3-P46
Discovering User-Interpretable Capabilities of Black-Box Planning Agents

Several approaches have been developed for answering users' specific questions about AI behavior and for assessing their core functionality in terms of primitive executable actions. However, the problem of summarizing an AI agent's broad capabilities for a user is comparatively new. This paper presents an algorithm for discovering from scratch the suite of high-level "capabilities" that an AI system with arbitrary internal planning algorithms/policies can perform. It computes conditions describing the applicability and effects of these capabilities in user-interpretable terms. Starting from a set of user-interpretable state properties, an AI agent, and a simulator that the agent can interact with, our algorithm returns a set of high-level capabilities with their parameterized descriptions. Empirical evaluation on several game-based scenarios shows that this approach efficiently learns descriptions of various types of AI agents in deterministic, fully observable settings. User studies show that such descriptions are easier to understand and reason with than the agent's primitive actions.
PENGARUH PEMBELAJARAN DARING, PENGUASAAN IT, DAN TANGGUNG JAWAB GURU TERHADAP PRESTASI BELAJAR SISW DI MI SE-KECAMATAN LEMPUING SUMATERA SELATAN

The objective of this study is to find out the effect of online learning, mastery of IT, and teacher responsibility on student achievement in MI of Lempuing Subdistrict, South Sumatra. Information and communication technology in the current pandemic conditions has a major influence on the world of education, especially in planning, process, and evaluation activitiesThis type of research was correlation research with 100 samples. This study used multiple regression analysis to determine whether there is a significant effect between the variables X on Y.After the data were collected, then hypothesis testing was carried out using SPSS 22.0 For Windows and obtained the following results: (1) Results Based on the analysis obtained Fcount = 4.070 and Fable = 3.94 at a significance level of 5% because Fcount &gt; Ftable means that there was a significant effect of learning on student achievement. (2) Based on the results of the analysis obtained Fcount = 4,400 and Fable = 3, 94 at the 5% significance level because Fcount &gt; Ftable means that there was a significant influence on IT mastery on student achievement. (3) Based on the analysis obtained Fcount = 4.211 and Fable = 3.94 at a significance level of 5% because Fcount &gt; Ftable means that there was a significant effect of teacher responsibility on learning achievement. (4) Based on the analysis shown by the ANOVA output with Fount &gt; Ftable (4,844 &gt; 3,94) and the coefficient of output level 0,004 &lt; 0,05. It could be concluded that Ho was rejected and he was accepted so there was a significant influence on IT mastery, teacher responsibility, and learning courage on student achievement in MI of Lempuing Subdistrict, South Sumatra.
Library Organization Issues in The Digital Era (Case Study: Copyright and Plagiarism in The Library Environment)

This article describes the issues that occur in library organizations in the digital era. One of them is about plagiarism and copyright. Both are interrelated as a result of technological developments in this digital era. The purpose of this article is to provide an overview to the reader about one of the issues that occur in library organizations and what steps should be taken to avoid this issue. The research method used is literature study, the data obtained from books and journals related to the problems discussed in this article. The focus of this article is on plagiarism and copyright in the library environment. What is the role of libraries in dealing with plagiarism and copyright issues. From this study, the results obtained are that it is known that along with the times, some human activities can be carried out online using information technology networks. The positive impact of this is that information technology is used to disseminate and can easily obtain information instantly, and make it easier to do tasks. However, the negative side is that there is plagiarism against the work of someone who violates the copyright of the work. Based on the results of a literature study of an article, it is known that not a few people commit plagiarism. So, from this research, it can be concluded that one of the most basic preventions to eliminate the negative side is honesty with oneself, and in writing scientific papers, clear sources must be included in order to avoid plagiarism of the paper. In addition, technological advances have created software that can minimize writers from plagiarizing written works.
Sentiment Analysis of JNE User Perception using Naïve Bayes Classifier Algorithm

The logistics industry is growing very rapidly. One of big industry in Indonesia is PT. Tiki Line Nugraha Ekakurir (JNE), which has been established for 29 years. This company has an extensive network in all cities in Indonesia, with service points of 1,500 locations. JNE has an application called my JNE on Google Play, which received more than 86,000 reviews and since December 2019 only got a rating of 2.4 stars out of a total rating of 5 stars. This study is obtained to analysis JNE user review data from Google Play. The reviews used in this study totaled 1,876 classified into positive and negative sentiment classes using the Naïve Bayes Classifier algorithm and word associations were also implemented. Classification with naïve bayes classifier with 90% training data and 10% test data had the best accuracy of 85.87%. Furthermore, for the text association, information is obtained that JNE users are talking about "send", "package", "courier", "good", "application", "fast", "service", "receive", "help", and "star". Whereas in the class of negative sentiment users often talk about "send", "package", "courier", "disappointed", "service", "service", "bad", "application", "severe", and "slow".
An Empirical Test of Stacked Autoencoder as Recommendation Model

The Autoencoder method can be used for multiple scenarios, as it is very variable.In this case, the method is used for suggesting actions.This paper describes the theoretical aspects of the recommendation models.The next section describes the use of the autoencoder.There will be provided two experiments.The first one, recommendations for movie lens dataset with process of transformation datasets and proper model dimension setting included.The results of the first experiment are favorable.The second experiment for suggesting actions from custom workflow inspired dataset.In this experiment, two ways of preparing a dataset for a model will be tested.Unfortunately, results are worse than model example.The article concludes with a discussion of the results achieved in comparison with other authors where results with movie datasets.
PENERAPAN METODE MAUT, COPRAS DAN EDAS DALAM PEMILIHAN MEDIA PEMBELAJARAN ONLINE DI MASA PANDEMIC COVID-19

The Covid-19 pandemic period is a time when all conditions are not as usual for all people, including the world of education. In order for education to continue to run well, an online learning media is needed. Online learning media is media that is equipped with a controller that can be operated by the user so that the user can control and access what the user needs, such as downloading or uploading material. The lecturers usually do online learning only through online media, namely Google Classroom, even though there are several online media that can be done for online learning, such as WhatsApp, Zoom Meeting, Google Meeting and Moodle so that learning can still run well. In order to help the lecturers in the selection of learning media, a decision support system is needed. The method applied in this research is the MAUT, COPRAS and EDAS methods. In the application of these three methods, it is expected to be able to produce the best alternative. As for the results of the research on the Selection of Online Learning Media in the Covid-19 Pandemic Period, the best alternative produced is the online learning media "WhatsApp" with the MAUT method calculation with a value of Ui = 0.9273, the calculation of the COPRAS method with a value of Ui = 100% and calculation of EDAS method with ASI value = 0.165