Reviewerly/exHarmony huggingface dataset:
The Guidelines to Adopt an Applicable SIEM Solution

The need for SIEM (Security Information and even Management) systems increased in the last years.Many companies seek to reinforce their security capabilities to better safeguard against cybersecurity threats, so they adopt multi-layered security strategies that include using a SIEM solution.However, implementing a SIEM solution is not just an installation phase that fits any scenario within any organization; the best SIEM system for an organization may not be suitable at all for another one.An organization should consider other factors along with the technical side when evaluating a SIEM solution.This paper proposes an approach to aid enterprises, in selecting an applicable SIEM.It starts by suggesting the requirements that should be addressed in a SIEM using a systematic way, and then proposes a methodology for evaluating SIEM solutions that measures the compliance and applicability of any SIEM solution.This approach aims to support companies that are seeking to adopt SIEM systems into their environments, suggesting suitable answers to preferred requirements that are believed to be valuable prerequisites an SIEM system should have; and to suggest criteria to judge SIEM systems using an evaluation process composed of quantitative and qualitative methods.This approach, unlike others, is customer driven which means that customer needs are taken into account when following the whole approach, specifically when defining the requirements and then evaluating the suppliers' solutions.
A Novel Topology for End-to-end Temporal Classification and Segmentation with Recurrent Neural Network

Connectionist temporal classification (CTC) has matured as an alignment free to sequence transduction and shows competitive for end-to-end speech recognition. In the CTC topology, the blank symbol occupies more than half of the state trellis, which results the spike phenomenon of the non-blank symbols. For classification task, the spikes work quite well, but as to the segmentation task it does not provide boundaries information. In this paper, a novel topology is introduced to combine the temporal classification and segmentation ability in one framework.
Representation of Federated Learning via Worst-Case Robust Optimization Theory

Federated learning (FL) is a distributed learning approach where a set of end-user devices participate in the learning process by acting on their isolated local data sets. Here, we process local data sets of users where worst-case optimization theory is used to reformulate the FL problem where the impact of local data sets in training phase is considered as an uncertain function bounded in a closed uncertainty region. This representation allows us to compare the performance of FL with its centralized counterpart, and to replace the uncertain function with a concept of protection functions leading to more tractable formulation. The latter supports applying a regularization factor in each user cost function in FL to reach a better performance. We evaluated our model using the MNIST data set versus the protection function parameters, e.g., regularization factors.
Algebraic constructions of rotated unimodular lattices and direct sum of Barnes–Wall lattices

In this paper, we construct some families of rotated unimodular lattices and rotated direct sum of Barnes–Wall lattices [Formula: see text] for [Formula: see text] and [Formula: see text] via ideals of the ring of the integers [Formula: see text] for [Formula: see text] and [Formula: see text]. We also construct rotated [Formula: see text] and [Formula: see text]-lattices via [Formula: see text]-submodules of [Formula: see text]. Our focus is on totally real number fields since the associated lattices have full diversity and then may be suitable for signal transmission over both Gaussian and Rayleigh fading channels. The minimum product distances of such constructions are also presented here.
On Simulation and Trajectory Prediction with Gaussian Process Dynamics

Established techniques for simulation and prediction with Gaussian process (GP) dynamics often implicitly make use of an independence assumption on successive function evaluations of the dynamics model. This can result in significant error and underestimation of the prediction uncertainty, potentially leading to failures in safety-critical applications. This paper discusses methods that explicitly take the correlation of successive function evaluations into account. We first describe two sampling-based techniques; one approach provides samples of the true trajectory distribution, suitable for `ground truth' simulations, while the other draws function samples from basis function approximations of the GP. Second, we propose a linearization-based technique that directly provides approximations of the trajectory distribution, taking correlations explicitly into account. We demonstrate the procedures in simple numerical examples, contrasting the results with established methods.
Virtual Reality Marketing: A Review and Prospects

We define VR marketing as the application of virtual reality technology to any aspect of marketing. Throughout practice and literature, VR is employed to improve either or both the utility and experientiality of aspects of the marketing value chain.With the advent of the internet in the 1990s, marketing was revolutionized in terms of its information propagation efficiency. Today, pervasively across the entire value chain, marketing is facing yet another revolution: Virtual Reality (VR). While in the 1990s, the internet made marketing hugely efficient, and it reduced the experiential nature of marketing that exists, e.g., in bricks-and-mortar marketing. The potential of the current wave of virtual reality in marketing is seen to stem from combining the efficiency of digital platforms with the immersiveness, experientiality and multisensory nature of physical” marketing environments. However, while the narrative of the potential of VR in marketing may seem as intuitively appealing, there is still a lack of coherent understanding as to whether these benefits have been realized in VR marketing. Therefore, we firstly seek to define VR marketing, and secondly, to review the expanding literature related to it. In particular, we review in which areas of marketing VR has been researched, how it has been researched, which kinds of technologies have been used, and which theories this corpus of literature draws from and contributes to. Moreover, we review the effects of VR marketing on consumer experience and behavior that the extant literature has been able to tease out.Next, we examine VR marketing in four different marketing domains, namely marketing research, product innovation, advertising and retailing, which represent aspects of value determination, value creation, value communication and value delivery during the marketing value chain. Virtual reality marketing is used to improve both the utility and experientiality of aspects of the marketing value chain.Furthermore, we examine the trends of related theories in the relevant research, and find that virtual reality is viewed either as a kind of media that highlights products’ attributes and improves the consumer learning process or as a way to reshape shopping environments in the computer-based virtual world which can influence consumer affection. We can also realize that researchers have recently begun to integrate more values realized by VR marketing into their research frameworks. Based on this, we propose a generally conceptual framework for future VR marketing research.According to the current body of literature, virtual reality technology shows considerable promise for the areas of marketing. However, current research still lacks in-depth insights as to how virtual reality works in marketing, and which factors can influence its marketing success. Given these findings, we offer a detailed discussion of the future agenda for VR marketing research.
Metode McCall’s untuk Pengujian Kualitas Sistem Informasi Administrasi Tugas Akhir (SIATA)

Department of English, Politeknik Negeri Bandung applies the Information System of Final Project Administration to aid the final assignment administration management. However, when the system is applied some new problems appear. The problems affect the ongoing performances of administrative services. This study aims to analyze and test the quality of SIATA to find out the occurring problems and factors that influence SIATA’s quality. This study uses McCall’s method to measure the quality of software and its product. This analysis method is used to acquire specific problems. The analysis was conducted on product operation aspects consisting of quality factors of correctness, reliability, efficiency, integrity, and usability. Data were collected using questionnaires from 58 respondents comprised of lecturers, students, and administrative staff of the Department of English, Politeknik Negeri Bandung. The results of the research showed that the overall SIATA’s quality stood at the level of 55,22% (the quality was fairly good based on the scales of criteria to interpret the percentages of quality factors). The research comes up with some recommendations that can be used to improve the performance of SIATA’s quality.
CoSimLex: A Resource for Evaluating Graded Word Similarity in Context

State of the art natural language processing tools are built on context-dependent word embeddings, but no direct method for evaluating these representations currently exists. Standard tasks and datasets for intrinsic evaluation of embeddings are based on judgements of similarity, but ignore context; standard tasks for word sense disambiguation take account of context but do not provide continuous measures of meaning similarity. This paper describes an effort to build a new dataset, CoSimLex, intended to fill this gap. Building on the standard pairwise similarity task of SimLex-999, it provides context-dependent similarity measures; covers not only discrete differences in word sense but more subtle, graded changes in meaning; and covers not only a well-resourced language (English) but a number of less-resourced languages. We define the task and evaluation metrics, outline the dataset collection methodology, and describe the status of the dataset so far.
A Semantic Characterization ASP Base Revision

The paper deals with base revision for Answer Set Programming (ASP). Base revision in classical logic is done by the removal of formulas. Exploiting the non-monotonicity of ASP allows one to propose other revision strategies, namely addition strategy or removal and/or addition strategy. These strategies allow one to define families of rule-based revision operators. The paper presents a semantic characterization of these families of revision operators in terms of answer sets. This semantic characterization allows for equivalently considering the evolution of syntactic logic programs and the evolution of their semantic content. It then studies the logical properties of the proposed operators and gives complexity results.&#x0D;
Crypto Currency Bitcoin and Bitcoin Market in Turkey

Bitcoin, which emerged in 2008 and is now being used rapidly in various sectors, is a crypto currency. Bitcoin was revealed by Satoshi Nakamoto (who or who is not specific to the person or a group). An official or private regulator is exported independently of the institution and therefore has no guarantee. Bitcoin was first used in the market in 2009. Although more than one crypto currency has emerged, Bitcoin has maintained its leadership since its release. However, in the years ahead, another crypto currency, Ethereum, will also go ahead of Bitcoin. Although there are countries that are prohibited to be used in countries of the world, the number of countries in which it is used is increasing day by day. In Turkey, shipping fees, employee salaries, cost of books, such as food shopping are being used in many fields.
Quantitative Analysis on verb valence evolution of Chinese

The paper aims at studying the evolution of syntactic valency of Chinese verbs.We construct three corpora of ancient classical Chinese ， ancient vernacular Chinese and modern vernacular Chinese.From these corpora, ten main verbs are selected to probe into the evolution of their valency, namely, their complements and adjuncts.The paper reveals that the syntactic structures has a trend toward complex.The ancient classical Chinese and the ancient vernacular Chinese are similar in sentence structure.With the transformation from the ancient vernacular to the modern vernacular, syntactic complexity increases dramatically, indicating drastic changes in sentence structure.
Are Talkative AI Agents More Likely to Win the Werewolf Game?

The Werewolf game is a communication game where, usually, two teams compete against each other.As players discuss and share ideas during the game to define their strategy, being talkative or not is one of the characteristics that define them.This paper presents a data analysis over logs from the shared task of The 1st International Workshop of AI Werewolf and Dialogue System to discuss if being talkative or not can be related to winning or losing when AI agents play the Werewolf game.Overall results show that the difference in the average of utterances sent by winning and losing players is not significant.However, they also suggest further analysis and discussion.
Threat Perceptions, Avoidance Motivation and Security Behaviors Correlations

As the economy increases its dependence on the internet to increase efficiency and productivity in all aspects of society, close attention has been directed to solve the challenges related to internet security.Despite the large amount of resource invested so far in this area, cybersecurity challenges are still great as the media frequently report new cyber breaches.Although researchers acknowledge that great progress has been made in protecting digital assets, cybercriminals are still successful in their operations which are no longer limited to government entities and corporations but also individual computer users.To improve users' security posture, the researcher examined the relationship between Millennials' perceptions of cybersecurity threat, users' online security behaviors and avoidance motivation.The study focused on three constructs which are Perceived Threat (PTH), Online Security Behaviors (OSB) and Avoidance Motivation (AMO).The researcher administered a survey to 109 participants randomly selected in the United States.The Spearman's correlation test performed supported the analysis of the strength of the relationship and the level of significance between the independent variable and the dependent variables.The results from the statistical test provided enough evidence to fail to reject the null hypothesis related to relationships between PTH and OSB and to reject the null hypothesis regarding the relationship between PTH and AMO.
Formal Definitions of Conservative PDFs

Under ideal conditions, the probability density function (PDF) of a random variable, such as a sensor measurement, would be well known and amenable to computation and communication tasks. However, this is often not the case, so the user looks for some other PDF that approximates the true but intractable PDF. Conservativeness is a commonly sought property of this approximating PDF, especially in distributed or unstructured data systems where the data being fused may contain un-known correlations. Roughly, a conservative approximation is one that overestimates the uncertainty of a system. While prior work has introduced some definitions of conservativeness, these definitions either apply only to normal distributions or violate some of the intuitive appeal of (Gaussian) conservative definitions. This work provides a general and intuitive definition of conservativeness that is applicable to any probability distribution that is a measure over $\mathbb{R}^m$ or an infinite subset thereof, including multi-modal and uniform distributions. Unfortunately, we show that this \emph{strong} definition of conservative cannot be used to evaluate data fusion techniques. Therefore, we also describe a weaker definition of conservative and show it is preserved through common data fusion methods such as the linear and log-linear opinion pool, and homogeneous functionals, \rev{assuming the input distributions can be factored into independent and common distributions}. In addition, we show that after fusion, weak conservativeness is preserved by Bayesian updates. These strong and weak definitions of conservativeness can help design and evaluate potential correlation-agnostic data fusion techniques.
On the Effectiveness of the Training Programs in the Learning Process

One of the main problems of the education system is to improve the training quality of the younger generation for professional activities in the information society. At the present stage of higher education development, many methodological innovations are associated with the use of IT-based teaching. One of the areas of computer technology use in education is e-learning tools that help to better and more quickly master the most difficult sections of a particular subject. The use of computer-based teaching programs in the educational process, in particular, the Photoshop Graphic Editor program in the Delphi programming environment, allows the teaching process to differentiate, contributes to increasing the motivation and motivational readiness of students to apply acquired knowledge and skills in real life. The authors single out a comparative analysis of pedagogical literature as one of the leading methods in the study of this problem. It was revealed on its basis, that the study of the Adobe Photoshop graphics editor within the school curriculum is not considered, and attention should be paid to the pedagogical experiment that justified the use of the Photoshop Graphic Editor program in the Delphi programming environment when studying basic disciplines. The main result of the research is the development of the Photoshop Graphic Editor teaching program in the Delphi programming environment. The significance of the results obtained is in solving such a major scientific problem as the development of basic competence in the field of computer graphics by future teachers in the natural science cycle. The research results fill in the existing gaps in the theory of higher education and also contribute to the solution of questions on the motivation in learning computer sciences by students of pedagogical departments of universities.
Patterns of teacher-students interaction in eighth grade of junior high school

The objectives of this research are to: (1) reveal the teacher-students’ interaction patterns applied between teacher and students during teaching and learning process in SMP Muhammadiyah Imogiri., and (2) describe the interactional features used by the teacher related to the pedagogic goals during teaching learning process SMP Muhammadiyah Imogiri. This research belongs to discourse analysis which aims at describing conversation and interaction of teacher-students during English teaching learning process in the eighth grade of SMP Muhammadiyah Imogiri. The data were collected through observation and were analyzed using the theory of IRF exchange structure and the SETT Framework. The result showed there were 30 patterns of interaction of 30 exchange structures used in seven types of transaction. The transactions greeting session, introduction, re-checking session, explaining session, instruction session, practicing session, note taking session. There were 12 types of interactional features used by the teacher with the total number of 135. It appears the display question interactional feature plays an important role in this case. Through display question, the teacher raises up the students’ desire to learn and participate in the teaching learning process. The teacher ‘24’ form-focused on feedback interactional features backs up the students when they did a mistake. That is a good unity to build the students competencies.
Neural Simile Recognition with Cyclic Multitask Learning and Local Attention

Simile recognition is to detect simile sentences and to extract simile components, i.e., tenors and vehicles. It involves two subtasks: {\it simile sentence classification} and {\it simile component extraction}. Recent work has shown that standard multitask learning is effective for Chinese simile recognition, but it is still uncertain whether the mutual effects between the subtasks have been well captured by simple parameter sharing. We propose a novel cyclic multitask learning framework for neural simile recognition, which stacks the subtasks and makes them into a loop by connecting the last to the first. It iteratively performs each subtask, taking the outputs of the previous subtask as additional inputs to the current one, so that the interdependence between the subtasks can be better explored. Extensive experiments show that our framework significantly outperforms the current state-of-the-art model and our carefully designed baselines, and the gains are still remarkable using BERT.
Mitigar el discurs d’odi a Nigèria: les possibilitats de la intel·ligència artificial

Anàlisi is a science journal published by the Journalism and Communication Sciences Department of the Autonomous University of Barcelona (UAB). The journal has been published by the UAB Journalism Department since 1980. Anàlisi publishes science articles in the fields of the communication sciences: journalism, advertising and public relations, audiovisual communication, internet, multimedia and similar areas, always from the social and cultural viewpoint and following the theoretical and methodological approaches of the media studies disciplines. Anàlisi will especially value articles from competitive research projects, with a clear articulation of theory and methodology, a well-defined and up-to-date theoretical framework, and proposed as a significant contribution to their subject area and field.
General Information Bottleneck Objectives and their Applications to Machine Learning

We view the Information Bottleneck Principle (IBP: Tishby et al., 1999; Schwartz-Ziv and Tishby, 2017) and Predictive Information Bottleneck Principle (PIBP: Still et al., 2007; Alemi, 2019) as special cases of a family of general information bottleneck objectives (IBOs). Each IBO corresponds to a particular constrained optimization problem where the constraints apply to: (a) the mutual information between the training data and the learned model parameters or extracted representation of the data, and (b) the mutual information between the learned model parameters or extracted representation of the data and the test data (if any). The heuristics behind the IBP and PIBP are shown to yield different constraints in the corresponding constrained optimization problem formulations. We show how other heuristics lead to a new IBO, different from both the IBP and PIBP, and use the techniques from (Alemi, 2019) to derive and optimize a variational upper bound on the new IBO. We then apply the theory of general IBOs to resolve the seeming contradiction between, on the one hand, the recommendations of IBP and PIBP to maximize the mutual information between the model parameters and test data, and on the other, recent information-theoretic results (see Xu and Raginsky, 2017) suggesting that this mutual information should be minimized. The key insight is that the heuristics (and thus the constraints in the constrained optimization problems) of IBP and PIBP are not applicable to the scenario analyzed by (Xu and Raginsky, 2017) because the latter makes the additional assumption that the parameters of the trained model have been selected to minimize the empirical loss function. Aided by this insight, we formulate a new IBO that accounts for this property of the parameters of the trained model, and derive and optimize a variational bound on this IBO.