Reviewerly/exHarmony huggingface dataset:
Heuristic Interpretation as Rational Inference: A Computational Model of the N400 and P600 in Language Processing

Much inquiry in psycholinguistics has focused on evidence from the N400 and P600 components of the event-related potential (ERP) signal---and a central theoretical challenge in this area is accounting for the so-called "semantic P600", which involves unexpected patterns in these components relative to traditional theories of the underlying mechanisms. In this paper we present a computational model of the language processing mechanisms underlying these ERP components, which builds on existing psycholinguistic theories in positing a heuristic interpretation stage of processing, but which deviates from existing theories in formulating this heuristic interpretation process as probabilistic selection via a noisy channel model, and which further strengthens the explanatory power by quantifying and accounting for fine-grained variation in statistical and representational properties of individual stimuli. Our model successfully simulates N400 and P600 results from seven psycholinguistic experiments reflecting N400-only, P600-only, and biphasic N400-P600 effects, indicating that the model represents a strong candidate theory for the mechanisms underlying the observed patterns. Analysis of the model's behaviors in the simulations supports the value of the heuristic interpretation process for explaining observed patterns, and also highlights the critical importance of additionally accounting for fine-grained variation in stimulus properties, which exert non-trivial impact on the ultimate effects generated by the posited mechanisms.
Transparency by Design: Reducing Informational Vulnerabilities Through UX Design

Can transparency help us solve the challenges posed by dark patterns and other unfair practices online? Despite the many weaknesses of transparency obligations in the data protection arena, I suggest that a Transparency by Design (TbD) approach can assist us in better achieving data protection goals, especially by empowering data subjects with accessible information, facilitating the exercise of data protection rights, and helping to reduce informational vulnerabilities. TbD proposes that compliance with transparency rules should happen in all levels of design and user interaction, instead of being restricted to Privacy Policies (PPs) or similar legal statements. In a previous work, I discussed how manipulative design can exploit behavioral biases and generate unfairness; here, I show how failing to support data subjects with accessible information, adequate design and meaningful choices can similarly create an unfair online environment.This work highlights the shortcomings of transparency rules in the context of the General Data Protection Regulation (GDPR). I demonstrate that, in practice, GDPR obligations do not result in effective transparency for data subjects, increasing unfairness in the data protection context. Consequently, data subjects are most of the time unaware of how, why, and when their data is collected, are uninformed about the risks or broader consequences of their personal data- fueled online activities, do not know their rights regarding their data, and do not have access to meaningful choices.In order to answer these shortcomings, I propose TbD, so that we – the data subjects – are not only effectively informed of the collection and use of our data, but can also exercise our data subjects’ rights, make meaningful privacy choices, and mitigate our informational vulnerabilities.The main goal of TbD is that data subjects will be served with information that is meaningful and actionable, instead of a standard block of text that acts as a liability document for the controller’s legal department – as currently happens with PPs. Design, manifested through User Experience (UX), is a central tool in this framework, as it should embed TbD’s values and premises and empower data subjects throughout their interaction with the controller.
Formation of professional inclusive competencies among employees of educational organizations in rural areas

This article is devoted to disclose one of the key tasks of modern Russian education — the creation of conditions for accessibility of education for persons with disabilities (hereinafter HIA) and permanent disablement. The subject of experimental study was the system of secondary vocational education, in the context of ensuring the availability of training programs for mid-level specialists, skilled workers and employees for applicants with disabilities and HIA. The basis for ensuring accessibility, according to the author, is undoubtedly the readiness of administrative and managerial personnel and teaching staff as a whole to implement inclusive secondary vocational education. The author considers in detail the issues of determining and developing special (personnel, program-methodical, material-technical, organizational) conditions in educational organizations of secondary vocational education. The results of a monitoring study of the state of employees’ readiness in technical schools and colleges for inclusive education are presented. The methods used in the monitoring process were: questionnaires, questionnaires for heads of educational organizations, support specialists, teachers, production masters and parents of students with disabilities. According to the results of the study, personnel shortages were identified and the directions of development of the personnel in colleges and technical schools on the organization and implementation of inclusive education were described. One of the issues under consideration is the organization and implementation of training of defectological personnel for special and inclusive education in conditions of professional educational organizations (colleges, universities). And also the issue of the use of human resources within the framework of networking of educational organizations, including those implementing training programs for mid-level specialists, skilled workers and employees.
Odia Handwritten Characters Recognition Through Cost–Benefit Analysis

Optical character recognition (OCR) document may be in handwritten or machine-printed script that can be used as input for a system to convert into an digital text format with read/write operation. OCR documents for different language scripts are an emerging concepts of today research. Particularly, in Indian languages, it is highly required in the current research era. This is an attempt toward making an OCR system for the Indian regional language such as Odia script. Local language such as Odia has great challenges to design the OCR character due to the big number and form of character within the Odia alphabet, the delicate ways within which they combine and lots of characters being roundish and similar in looks. In this paper, we present the classification approaches for Odia character recognition with cost–benefit analysis. Hence, our research work was focused toward analysis of a machine learning algorithm to classify the offline Odia handwritten character recognition through decision table and Naive Bayes in WEKA environment with cost–benefit analysis.
Geo-technologies Applied to the Spatial Analysis of Territorial Inequalities - Case Study of Latacunga, Central Ecuador

This research zonifies territorial inequalities in Latacunga (Ecuador), considered one of the cities with high global vulnerability to risks due to its geo-graphic location. Based on the information generated by the former Ecuadorian Space Institute, through the project “Generation of geospatial information at a scale of 1: 5 000 for the determination of the physical fitness of the territory and urban development through the use of geotechnologies”, taking landscape ecology as a methodological synthesis, the hypothesis of the existing spatial relationship between socioeconomic level (SES) versus constructive physical aptitude (CFA) is proposed to determine territorial inequalities. For the CFA, five categories were determined (defined by the analysis of the geomorphological characteristics -such as slope and geological factor- and edaphic -such as water table, drainage, texture and stony-), prevailing the suitable areas with severe limitations in 70% of the territory. Regarding the SES (granted by the type of housing, availability of basic services, level of education and economic activity), the medium-low status predominates with 44%, showing marked differences between the five levels obtained. From the interaction between SES and CFA, 9 homogeneous units were established that determine territorial inequalities, prevailing, in 54%, the unit with CFA with severe to extreme limitations with a low SES. Therefore, it is evident that the geospatial knowledge generated when determining the relationship between the SES and the CFA of the territory allows decision-making authorities to design policies and projects that reduce territorial inequalities, through the understanding of the relationships between housing, services, space and characteristics of the soil.
Heritability of Morphological and Behavioural Traits in Evolving Robots

In the field of evolutionary robotics, choosing the correct genetic representation is complicated and delicate matter, especially when robots evolve behaviour and morphology at the same time. With the objective of improving our understanding of the mapping process from representations to functional robots, we introduce the biological notion of heritability, which captures the proportion of phenotypic variation caused by genotypic variation and is often used to better understand the transmissability of traits in real biological systems. In our analysis we compare the heritability of various traits in robots evolved from two different representations: a direct representation and an indirect representation. In addition we investigate changes in heritability during the course of the evolutionary process and how this relates to phenotypic diversity. In particular, we investigate how direct and indirect genotypes can exhibit preferences for exploration or exploitation throughout the course of evolution. We observe how an exploration or exploitation trade-off can be more easily understood by examining patterns in heritability and phenotypic diversity. In conclusion, we show how heritability can be a useful tool to better understand the relationship between genotypes and phenotypes. This is especially helpful when designing more complicated systems where complex individuals and environments can adapt and influence each other.
Managing Software Testing Technical Debt Using Evolutionary Algorithms

Technical debt (TD) happens when project teams carry out technical decisions in favor of a short-term goal(s) in their projects, whether deliberately or unknowingly. TD must be properly managed to guarantee that its negative implications do not outweigh its advantages. A lot of research has been conducted to show that TD has evolved into a common problem with considerable financial burden. Test technical debt is the technical debt aspect of testing (or test debt). Test debt is a relatively new concept that has piqued the curiosity of the software industry in recent years. In this article, we assume that the organization selects the testing artifacts at the start of every sprint. Implementing the latest features in consideration of expected business value and repaying technical debt are among candidate tasks in terms of the testing process (test cases increments). To gain the maximum benefit for the organization in terms of software testing optimization, there is a need to select the artifacts (i.e., test cases) with maximum feature coverage within the available resources. The management of testing optimization for large projects is complicated and can also be treated as a multi-objective problem that entails a trade-off between the agile software’s short-term and long-term value. In this article, we implement a multi-objective indicator-based evolutionary algorithm (IBEA) for fixing such optimization issues. The capability of the algorithm is evidenced by adding it to a real case study of a university registration process.
Problems of the Formation and Development of the Interaction System of the Pedagogical University and the Region

The implementation of the third mission of universities implies the growth of the social responsibility of universities. This process affects the educational and research activities of the university, expands the capabilities of universities to interact with partners, and strengthens their role in the region. The problems of choosing the most effective forms of partnership are becoming more and more urgent in the context of the growing role of universities in the socioeconomic life of the regions. Each university chooses the formats of interaction with the region, taking into account the existing peculiarities and deficits. Regional clusters are one of the most effective formats for such interaction. The article used the methods of system analysis, comparison and generalization of various sources (theoretical and empirical), summarizes the experience of the regional sociopedagogical cluster of Minin University, describes the main elements of the cluster, the principles of their interaction, analyzed the results of the cluster’s activities, the problems of functioning and the prospects for its development. The purpose of the article is to study the content and development prospects of the regional socio-pedagogical cluster of Minin University. The practical results of the cluster’s activities, the proposed set of measures may represent novelty and interest. The conclusion about the need to combine all the elements of the cluster on a single digital platform in order to increase the efficiency of each element of the cluster and the cluster structure as a whole was made based on the results of the study.
Multi-Dimensional Attention With Similarity Constraint for Weakly-Supervised Temporal Action Localization

Weakly-supervised temporal action localization (WTAL) is a challenging task in understanding untrimmed videos, in which no frame-wise annotation is provided during training, only the video-level category label is available. Current methods mainly adopt temporal attention branches to conduct foreground-background separation with RGB and optical flow features simply concatenated, regardless of the discriminative spacial features and the complementarity between different modalities. In this work, we propose a Multi-Dimensional Attention (MDA) method to explore attention mechanism across three dimensions in weakly supervised action localization, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</i> . <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">e</i> ., 1) temporal attention that focuses on segments containing action instances, 2) channel attention that discovers the most relevant cues for action description, and 3) modal attention that fuses RGB and flow information adaptively based on feature magnitudes during background modeling. In addition, we introduce a similarity constraint loss to refine the action segment representation in feature space, which helps the network to detect less discriminative frames of an action to capture the full action boundaries. The proposed MDA with similarity constraints can be easily applied to existing action detection frameworks with few parameters. Extensive experiments on THUMOS’14 and ActivityNet v1.2 datasets show that the proposed method outperforms the current state-of-the-art WTAL approaches, and achieves comparable results with some advanced fully-supervised methods.
Fifty Shades of Personal Data – Partial Re-identification and GDPR

This paper takes a look at data re-identification as an economic game where the attacker is assumed to be rational, i.e. performs attacks for a gain. In order to evaluate expectancy for this gain, we need to assess the attack success probability, which in turn depends on the level of re-identification. In the context of GDPR, possibility of various levels of re-identification is a grey area – it is neither explicitly prohibited, nor endorsed. We argue that the risk-based approach of GDPR would benefit from greater clarity in this regard. We present an explicit, yet general, attacker model that does not fit well into the current treatment of GDPR, and give it a high-level game-theoretic analysis.
Measure of Homodyne Nonclassical Area to Quantify the Nonclassicality of Light

We propose a legitimate and easily computable measure of nonclassicality for the states of electromagnetic field based on the standard deviation in the measurement of the homodyne rotated quadrature operator. The proposed measure is the nonclassical area projected by the optical tomogram of the state on the optical tomographic plane. If the nonclassical area projected by the optical tomogram of a quantum state is greater than zero, the state is strictly nonclassical and is zero for the classical state. It is also noted that the nonclassical area of a quantum state increases with an increase in the strength of nonclassicality inducing operations on the state. We have also shown that the nonclassical area measure is robust against environment-induced decoherence of the states. Nonclassical area projected by the optical tomogram of a quantum state of light is experimentally tractable using the balanced homodyne detection of the quadrature operator of the field.
An Accurate Dynamic Forecast of Photovoltaic Energy Generation

The accurate forecast of the photovoltaic generation (PVG) process is essential to develop optimum installation sizing and pragmatic energy planning and management.This paper proposes a PVG forecast model for a PVG/ Battery installation.The forecasting strategy is built on a Medium-Term Energy Forecasting (MTEF) approach refined dynamically every hour (Dynamic Medium-Term Energy Forecasting (DMTEF)) and adjusted by means of a Short-Term Energy Forecasting (STEF) strategy.The MTEF predicts the generated energy for a day ahead based on the PVG of the last 15 days.As for STEF, it is a combination between PVG Short-Term (ST) forecasting and DMTEF methods obtained by selecting the least inaccurate PVG estimation every 15 minutes.The algorithm results are validated by measures taken on a 3 KWp standalone PVG/Battery installation.The proposed approaches have been integrated into a management algorithm in order to make a pragmatic decision to ensure load supply considering relevant constraints and priorities and guarantee the battery safety.Simulation results show that STEF provides accurate results compared to measures in stable and perturbed days.The NMBE (Normalized Mean Bias Error) is equal to -0.58% in stable days and 26.10% in perturbed days.
Dementia Detection Using Bi-LSTM and 1D CNN Model

Neurogenerative sicknesses including dementia could affect a person’s discourse, language, and, therefore, everyday correspondence abilities. A current investigated utilization of (CA-Conversation Analysis) meetings among patients and nervous system specialists as an approach to recognize among patients with progress neurodegenerative memory sickness (ND) and those with (non-reformist) (FMD-practical memory illness) to improve dementia acknowledgment exactness. Manual CA, on the opposite side, is expensive and complex to increase for regular clinical utilization. In this article, we propose an early dementia identification conspire utilizing discourse acknowledgment and examination dependent on NLP method utilizing a bidirectional long short-term memory (LSTM) and 1D CNN structure neural network architecture which amazingly catches the transient highlights and long-haul conditions from chronicled information to demonstrate the capacities of arrangement models over a feed-forward neural architecture in determining discourse investigation-related issues.
Obstacles and Lessons Implementing a Differential Privacy-Based Open Data Program

In recent years, the open government movement has gained momentum. This movement aims to make the administration transparent, bringing the State closer to the citizenry, but also opening information repositories in order to promote the advancement of knowledge in various research areas. In this context, various actors of the judiciary system in Argentina have implemented data opening programs, including Criminal, Misconduct and Misdemeanor Court No. 10 of the Autonomous City of Buenos Aires. However, these initiatives to democratize data and knowledge come up against a challenge: that of individual privacy. Given the great expansion of the Internet, the increase in access to new and massive data sets and in the computing power and data manipulation technology; traditional privacy protection techniques and approaches are insufficient. To overcome these threats to privacy in the implementation of its open data program, we will be collaborating with Court No. 10 in order to propose a data opening strategy capable of guaranteeing high privacy standards for individuals. At the end of this work, we will make an alternative proposal to the workflow currently used by the Court. To do this, we will use a new technique called Differential Privacy, which allows us to carry out the distribution of data sets, but controlling the amount of private information that is allowed to be leaked.
Design and Commons: A Lacanian Approach

This article presents a literature review of the field of social sciences in connection with design theory, more specifically on the issue of collaboration. What we perceive as design today has undergone major changes, mostly in the ways it is expressed by visual and material means. But in the definition of a design ontology, one can trace some common characteristics. Transformation, among the most important of those characteristics, has always acted as core signifier within the various definitions of design practice and theory. With design today being more ubiquitous than ever, we see its contemporary expression acting in tangible ways, traced prominently in the service design field. This has the capacity for various levels of collaboration, which makes the notion central within design studies. Collaboration is also a near tautology to the activity of sharing, a core process of the commons. The commons has been proposed by many scholars as an alternative to capitalism in order to sustain our planet and the human race in general. Can design be linked with the commons? On what grounds? Lacanian psychoanalysis is proposed as an answer to the human tragedy, a tragedy that characterizes human beings and will probably continue to do so. It offers an interpretive mechanism and (complex) ways of operation of our psychic reality within humanity. This article ultimately is a proposal to connect these three seemingly unconnected fields, in that the core of their activity comprises human beings and their distinct existence in the world.
Security and privacy in cloud-/edge-/fog-based schemes

In these COVID times, there are many rapid transformations that have been made in smart healthcare sectors. In this paper, we are going to discuss the challenges and the future research work that can happen in 5G for smart healthcare. Besides that, there are various security, trust, and privacy issues. This paper will discuss the cloud-and fog-based schemes. There are several limitations in Internet of Things (IoT) devices that create difficulty in executing security protocols and algorithms. The chapter will provide techniques for privacy-aware communication and how user approval and trust can be ensured by providing strong privacy policies. This paper will also discuss how data integrity and authenticity can be maintained. We will also discuss briefly the architecture of 5G healthcare, IoT, and blockchain. This chapter depicts a survey of various nations’ expenditure in the health sector and will provide the SWOT analysis of companies in the healthcare sector that use blockchain.