Reviewerly/exHarmony huggingface dataset:
Ontology literature review as guidelines for improving Croatian Qualification Framework

Development of information systems dealing with education and labour market using web and grid service architecture enables their modularity, expandability and interoperability. Application of ontologies to the web helps with collecting and selecting the knowledge about a certain field in a generic way, thus enabling different applications to understand, use, reuse and share the knowledge among them. A necessary step before publishing computer-interpretable data on the public web is the implementation of common standards that will ensure the exchange of information. Croatian Qualification Framework (CROQF) is a project of standardization of occupations for the labour market, as well as standardization of sets of qualifications, skills and competences and their mutual relations. This paper analysis a respectable amount of research dealing with application of ontologies to information systems in education during the last decade. The main goal is to compare achieved results according to: 1) phases of development/classifications of education-related ontologies; 2) areas of education and 3) standards and structures of metadata for educational systems. Collected information is used to provide insight into building blocks of CROQF, both the ones well supported by experience and best practices, and the ones that are not, together with guidelines for development of own standards using ontological structures.
Nested monte carlo search expression discovery for the automated design of fuzzy ART category choice functions

While the performance of many neural network and machine learning schemes has been improved through the automated design of various components of their architectures, the automated improvement of Adaptive Resonance Theory (ART) neural networks remains relatively unexplored. Recent work introduced a genetic programming (GP) approach to improve the performance of the Fuzzy ART neural network employing a hyper-heuristic approach to tailor Fuzzy ART's category choice function to specific problems. The GP method showed promising results. However, GP is not the only tool that can be used for automatic improvement. Among other methods, Nested Monte Carlo Search (NMCS) was recently applied to expression discovery and outperformed traditional evolutionary approaches by finding better solutions in fewer evaluations. This work applies NMCS to the discovery of new Fuzzy ART category choice functions targeted to specific problems with results demonstrating its ability to find better performing Fuzzy ART networks than the GP approach.
A Speech Data-Driven Stakeholder Analysis Methodology Based on the Stakeholder Graph Models

Among the requirements elicitation activities, the stakeholder analysis is the main source of requirements. In this article, we propose a new model of data-driven stakeholder analysis, named SIG (Stakeholder Intention Graph), a semantic extension of property graph model that can represent the stakeholders' intentions and their relationships. To elicit the stakeholders' intentions from the speech data during meetings, we developed a system of structural analysis and SIG generation method from speech data. Based on the graph theory, we also propose an analysis methodology of stakeholders' intentions and their structure with both global and local graph analyses. We implemented a speech data-driven stakeholder analysis system on the graph database Neo4j. As the output, the analysis system automatically generates the stakeholder matrix from the speech data at the meetings. We applied the analysis method and system to the speech data of actual development meetings on the public service systems, and demonstrated the effectiveness of the proposed method.
A New Privacy Protection Security Scheme for Blockchain

Abstract The strong security and strong privacy protection features of the blockchain are important aspects of the development of the blockchain, but the security and privacy protection features of the blockchain are not perfect. With the continuous development and wide application of blockchain technology, the problem of privacy leakage is becoming more and more prominent and must be fully taken seriously. This paper proposes a new blockchain signature scheme based on the combination of aggregate signature and ring signature for the privacy protection of transaction addresses in blockchain. This scheme uses a ring signature as the basis for the signature algorithm. On the basis of this, it combines the aggregate signature, which hides the address information of the signer on the one hand and fixes the signature length on the other hand. This enhances the privacy protection capability of the transaction address in the blockchain, and also effectively reduces the signature space of the blockchain system, and solves the problem of capacity expansion to some extent.
A Solution Development Model for Industry Based on Design Thinking

This work presents the program BlueJourney that was created with the objective of identifying problems and challenges of our clients and, in a process of collaboration, develop processes and systems innovation projects. BlueJourney was designed by ThinkLab Brazil, the innovation laboratory of IBM Research that has an environment suitable for co-creation and a specialized team. The program is based on Design Thinking techniques, therefore, innovation is achieved with a focus on people’s need, and with technical and business feasibility analysis. With defined steps, we engage industry, technology, business and research experts in activities like co-creation, research, interviews, prototype development and testing. The experts understands and explores the challenges of the subject or area to be transformed and create the most complete solutions. At the end of the program, we have a list of projects to be developed, changes in processes and systems, and people who have learned to seek innovation in a creative, collaborative and engaged way. The most important is a change of mindset, because solutions might be about human needs. In this article, we’ll present in detail the steps of BlueJourney applied in a real case.
Image Authentication by Single Target Region Detection

Digital image has been widely used in people's daily life, and image authentication technology is more and more important. This paper proposes an image authentication method based on convolutional neural nets, which performed better compared with the VGG and Alex-Net. A single target region detection method under the attention model is proposed and it helps a lot in distinguish the source images and the derived images with watermarks or mosaic.
Flexibly and Securely Shape Your Data Disclosed to Others

This work is to enhance existing fine-grained access control to support a more expressive access policy over arithmetic operation results. We aim to enable data owners to flexibly bind a user's identity with his/her authorized access target according to a given access control policy, which indicates how a piece of data obfuscated by different noises. To this end, we design a cryptographic primitive that decouples the noisy data to two components, one associated with user identity, and the other one shared and dynamically changes, with the composite of these two components evaluated and revealed at user sides. The security of our scheme is formally proven using game based approach. We implement our system on a commercial cloud platform and use extensive experiments to validate its functionality and performance.
Increasing Virtual Reality Immersion Through Smartwatch Lower Limb Motion Tracking

Virtual reality locomotion has been a subject of study as it plays an important role that affects immersion and presence. Walking constitute a challenging interaction in virtual reality installments as it is a complex task to recreate. Some approaches have focused on input devices employing diverse technologies including robotics, omnidirectional treadmills, reorientation through tracking, and most recently, inertial measurement units, optical tracking, and low-friction surfaces. Amongst the various solutions, those targeting consumer-level VR products are gaining momentum as VR headsets become more affordable, creating the opportunity to mass impact content creation in entertainment, tourism, healthcare, training, education, and simulation applications employing VR. In this paper, we present the development of a lower limb virtual reality room-scale environment where users walk while using a Smartwatch as a tool to capture walking data without requiring external sensors or tracking systems. A preliminary study focused on a usability assessment to gather perceptions on the use of a smartwatch as a suitable tracking tool for VR installments.
A Modified Smart Contract Execution Enviroment for Safe Function Calls

When a Solidity smart contract has a problem in calling a function of another contract, the "fallback function" of the contract is supposed to be executed automatically. However, in many cases, a fallback function is arbitrarily created and called, with their behaviors unknown to developers, so that its execution is vulnerable to exploits by attackers. To reduce these risks, this paper proposes a method that provides developers with new keywords by modifying existing Solidity compiler and Ethereum Virtual Machine (EVM). Developers mark their intention using the newly introduced keywords, and the modified existing Solidity compiler and EVM uses flags and conditional statements to prevent calls of fallback functions to reduce the risk of calls to fallback functions.
Memories and Brain Maps

Departing from an approach focused on the cooperation between Architecture, Urbanism and Neuroscience, we investigate the impacts of the urban environment of the city of Campinas (São Paulo, Brazil) downtown area on the declarative semantic memories consolidated in the brain maps of the city’s inhabitants/users. Through field research with two hundred and sixty-six participants, the memories about this space/place are evoked and recorded in the testimonies made by these individuals, as well as represented in drawings made by themselves. We focused on the modulation of these memories through the emotions and feelings, respectively related to fear, risk and insecurity in this urban space. The main results are: the absence of identification with and the repulsion of the inhabitants/users of the public space; the restricted use of the urban space and the remote possibility of citizens “experiencing” the city; and the threat to the homeostatic balance of these individuals. Such discussions evince the responsibility of public policies, as well as of architects, designers and urban planners in the ways human beings feel, perceive, and appropriate the urban space.
The Effectiveness of Quantum Learning Method to Students’ English Learning Achievement at SMK N 9 Padang

This research aimed to find out the effectiveness of Quantum Learning Method to students’ English learning achievement. This research was pre-experimental design in the form of one group Pretest- Posttest. It was conducted at SMK N 9 Padang. The sample of this research was class X Hotel Acomodation 3 with total number of sample was 27. The instrumentation used as a data collection was test. The findings showed the effectiveness of using quantum learning methods which can be seen from the value of learning achievement. The findings of this research; quantum learning method is quite effective to improve students' English learning achievement on the material "announcement", this is indicated by the value of 5.17 was bigger than the value of 2.060 with level of significance 0.05.
International Standard Setting in Biomedicine – Foundations and New Challenges

This article examines current challenges for a normative framework regulating biomedicine, including those arising from the use of big data and machine learning tools, and from the use of the CRISPR/Cas-9 technology, as for instance gene drives. The article focusses on the question of legitimate standard setting and takes into account both “hard” and “soft” law as well as private rule making. This includes international treaties and declarations in the area of human rights law and environmental law, such as the International Covenant on Civil and Political Rights, the Cartagena Protocol on Biosafety to the Convention on Biological Diversity, the Rio Declaration on Environment and Development, and, more specifically, the UNESCO Declaration on Bioethics and Human Rights. The author argues that, as instruments of biotechnology and biomedicine merge, international environmental law has to be interpreted in the light of human rights law. In order to adapt to new challenges, the article calls for a humanisation of international environmental law and, because of the ongoing disruptive technological development, argues that further legitimate standard setting is required. Keywords: Biomedicine, Biotechnology, Gene Drives, Standard Setting, CRISPR/Cas-9, Artificial Intelligence
Feel Autism VR – Adding Tactile Feedback to a VR Experience

Feel Autism VR is a new virtual reality (VR) system which builds upon an Autism VR system which was developed in the past year. The aim of the original system was to design a novel VR environment to boost user's awareness about autism and in so doing, increase the level of empathy towards autistic children. We sought to create a VR environment which provides total immersion to its users. A touching-without-feeling technique was used to send an ultrasound signal to the user's body when the VR experience displays a touching scenario. Sound, vision and virtual touching elements could increase the awareness of presence, of the autistic children. A novel approach has been implemented which will allow users to feel tactile feedback physically without being touched. In so doing, we can recreate the annoyance felt by the autistic child throughout the day. Ultrasound waves will be generated via an ultrasound speaker which send the waves through the air and create pressure to simulate a real-life event. This concept will be inserted in the narrative of the original VR Autism project in order to mimic physical touching between an autistic child and his classmates, teachers, etc. The results were very promising whereby 50% of the users declared that after the experience, they are in a better position to understand children with autism.
Overview of Natural Language Processing Approaches in Modern Search Engines

This article provides an overview of modern natural language processing and understanding methods. All the monitored technologies are covered in the context of search engines. The authors do not consider any particular implementations of the search engines; however take in consideration some scientific research to show natural language processing techniques application prospects in the informational search industry.
Advances in Real-time Tracking and Data Fusion using Multiple Passive Radar Sensors

The creation of an air situation picture is a task that can be tackled with a variety of different sensor types. Continuous improvements in all parts of the processing chain have made passive radar one emerging technology suited for that task. HENSOLDT has developed a passive radar system based on analog and digital audio and/or video broadcasting stations that is capable to detect and track, in real-time, airliners, small and maneuvering aircraft as well as fighters alike. The system can be operated as a single sensor but also in a sensor cluster. This paper recalls the underlying principles and building blocks of the tracking and data fusion software of the HENSOLDT Passive Radar System and briefly sketches the main challenges to be dealt with. Tracking results obtained with a cluster of four stations will demonstrate the overall surveillance performance as well as the claimed tracking capabilities.
Tackling the Issue of Student Debt Through Data Sonification and Musical Scores

The issue of student debt is an invisible but ever-present aspect of the college experience within the United States.While this debt can sometimes be deemed necessary to cover the increasing costs of attending college, the risks are high with just over 10% of borrowers defaulting within three years of receiving a loan.Research has shown that many students are unaware of the size of the loan they have taken out to cover expenses and that some students are even unaware they have taken loans out to begin with.This implies that there is an opportunity to present new ways of engaging with student populations about the risks regarding student loan debt.I will present a paper on my work of art "A Good Education (Explorations in Data and Music)" that discusses the design process, the aesthetic issues surrounding the translation of data into musical scores, and the recording and exhibiting of this body of work.The work is comprised of three musical scores and accompanying audio recordings.Each score explores a different set of data with varying compositional methodologies and instrumentation.I will also discuss the challenges of presenting this body of work, the outcomes, and audience response over the duration of the exhibition. Music composition. Student debt.
FaceTimeMap

In this article, the authors study bitmap indexing for temporal querying of faces that appear in videos. Since the bitmap index is originally designed to select a set of records that satisfy a value in the domain of the attribute, there is no clear strategy for how to apply it for temporal querying. Accordingly, the authors introduce a multi-level bitmap index that the authors call “FaceTimeMap” for temporal querying of faces in videos. The first level of the FaceTimeMap index is used for determining whether a person appears in a video or not, whereas the second level of the index is used for determining intervals when a person appears. First, the authors analyze the co-appearance query where two or more people appear simultaneously in a video, and then examine next-appearance query where a person appears right after another person. In addition, to consider the gap between the appearance of people, the authors study eventual- and prior-appearance queries. Queries are satisfied by applying bitwise operations on the FaceTimeMap index. The authors provide some performance studies associated with this index.
History-Driven Entity Categorization

Knowledge of entity histories is often necessary for comprehensive understanding and characterization of entities. In this paper we introduce a novel task of history-based entity categorization. Taking a set of entity-related documents as an input we detect latent entity categories whose members share similar histories, effectively, grouping entities based on the similarities of their historical developments. Next, we generate comparative timelines for each generated group allowing users to spot similarities and differences in entity histories. We evaluate our approach on several datasets of different entity types demonstrating its effectiveness against competitive baselines.
A memory-compact and fast sketch for online tracking heavy hitters in a data stream

Network traffic measurement is important for network management, including bandwidth management to mitigate network congestion, and security management to detect DDOS attacks and worm spreading. However, with the explosive volume of network data and the fast transmission speed of network packets (in giga or even tera bps), it is a challenging task to measure the size of each network flow both accurately and memory-efficiently, using the size-limited SRAM memory of line card. Therefore, many sublinear space algorithms for processing data streams have been proposed, such as CountMin (CM), Count Sketch (CS) and Virtual Active Counters (VAC), which achieve extreme memory compactness by providing probabilistic guarantees on flow size measurement accuracy. However, these existing algorithms can still be greatly improved as to the performance of both online recording and querying the per-flow size, which is needed for online tracking heavy hitters. Our paper proposes a highly compact and efficient counter architecture, called CountMin virtual active counter (CM-VAC), which provides more accurate measurement results than CM and CS under a very tight memory space. We also achieve higher query speed than VAC by modifying its query policy. We demonstrate the superior performance of our algorithm by both experimental results and theoretical analysis based on CAIDA network traces.
Technologies for building e-catalogs on local history: Transformations in the digital environment

Significant transformations in the technologies of e-catalog building in the area of local history are discussed. The author examines the main changes. She focuses on the local lore and history e-catalogs of the RF libraries and their specific features. The document support of the catalog development is presented. Based on the element structure of the technological process (goal, objects, subjects, resources, processes, instruments, methods, regulation documents, and results), the transformations in the technology are revealed. The author concludes that these changes are due to the expanding objects covered by the catalogs (including the networked); complicating regulations for the objects (mandatory competences for machine-readable cataloguing); radical changes to the advantage of digital information resources; need for continuing upgrade of hardand software; exacerbating problems of linguistic support of machine-readable cataloguing; new regulations, etc. The author also points to significantly complicating technologies. The author suggests that the solution may lie in labor consumption and efficiency calculations for the processes of the e-catalog elements design and use.
Predication and cognitive context: Between minimalism and contextualism

Abstract In this paper, we suggest a strategy for modelling cognitive context within a truth‐conditional semantics, using Asher's model of predication. This allows us to introduce the notion of type presupposition intended as a lexical constraint to the composition of the truth‐conditional content. More specifically, we suggest that this model of predication produces a notion of truth‐conditional meaning where the cognitive context fixes a set of lexical restrictions and forced modifications. We conclude that this model might offer an intermediate position between Minimalism and Contextualism: an account that provides intuitive truth conditions within a formal semantic theory.
PrivBUD-Wise: Differentially Private Frequent Itemsets Mining in High-Dimensional Databases

In this paper, we study the problem of mining frequent itemsets in high-dimensional databases with differential privacy, and propose a novel algorithm, PrivBUD-Wise, which achieves high result utility as well as a high privacy level. Instead of limiting the cardinality of transactions by truncating or splitting approaches, which causes extra information loss and result in unsatisfactory performance in utility, PrivBUD-Wise doesn't make any preprocessing on original database and guarantees high result utility by reducing extra $$privacy\ budget$$ consumption on irrelevant itemsets as much as possible. To achieve that, we first propose a Report Noisy mechanism with optional number of reported itemsets: SRNM, and what is more important is that we give a strict proof for SRNM in the appendix. Moreover, PrivBUD-Wise first proposes a biased $$privacy\ budget$$ allocation strategy and no assumption or estimation on the maximal cardinality needs to be made. The good performance in utility and efficiency of PrivBUD-Wise is shown by experiments on three real-world datasets.