Reviewerly/exHarmony huggingface dataset:
On the Expressive Power of Description Logics with Cardinality Constraints on Finite and Infinite Sets

In recent work we have extended the description logic (DL) $$\mathcal {ALC\!Q}$$ by means of more expressive number restrictions using numerical and set constraints stated in the quantifier-free fragment of Boolean Algebra with Presburger Arithmetic (QFBAPA). It has been shown that reasoning in the resulting DL, called $$\mathcal {ALCSCC}$$ , is PSpace-complete without a TBox and ExpTime-complete w.r.t. a general TBox. The semantics of $$\mathcal {ALCSCC}$$ is defined in terms of finitely branching interpretations, that is, interpretations where every element has only finitely many role successors. This condition was needed since QFBAPA considers only finite sets. In this paper, we first introduce a variant of $$\mathcal {ALCSCC}$$ , called $$\mathcal {ALCSCC} ^\infty $$ , in which we lift this requirement (inexpressible in first-order logic) and show that the complexity results for $$\mathcal {ALCSCC}$$ mentioned above are preserved. Nevertheless, like $$\mathcal {ALCSCC}$$ , $$\mathcal {ALCSCC} ^\infty $$ is not a fragment of first-order logic. The main contribution of this paper is to give a characterization of the first-order fragment of $$\mathcal {ALCSCC} ^\infty $$ . The most important tool used in the proof of this result is a notion of bisimulation that characterizes this fragment.
A Novel Authentication Protocol with Strong Security for Roaming Service in Global Mobile Networks

In today’s society, Global Mobile Networks (GLOMONETs) have become an important network infrastructure that provides seamless roaming service for mobile users when they leave their home network. Authentication is an essential mechanism for secure communication among the mobile user, home network, and foreign network in GLOMONET. Recently, Madhusudhan and Shashidhara presented a lightweight authentication protocol for roaming application in GLOMONET. However, we found their protocol not only has design flaws, but is also vulnerable to many attacks. To address these weaknesses, this paper proposes a novel authentication protocol with strong security for GLOMONET based on previous work. The fuzzy verifier technique makes the protocol free from smart card breach attack, while achieving the feature of local password change. Moreover, the computational intractability of the Discrete Logarithm Problem (DLP) guarantees the security of the session key. The security of the protocol is verified by the ProVerif tool. Compared with other related protocols, our protocol achieves a higher level of security at the expense of small increases in computational cost and communication cost. Therefore, it is more suitable for securing the roaming application in GLOMONET.
Augmented reality smartphone compasses

The development of augmented reality capabilities on smartphones has led to the emergence of a range of AR apps, including AR compasses. Some of these apps claim to be as good as professional magnetic navigation compasses, and suitable for navigation use. This poster presents detailed measurements of compass deviation (error) curves and offset errors for augmented reality compass apps on 17 mobile devices. The magnitude of the deviation errors measured casts serious doubt on claims the apps are appropriate for navigation purposes. This in turn emphasizes the need for the ubiquitous computing community to help ensure adequate awareness of the limitations of some onboard sensors, including compasses, on devices such as smartphones.
Ensuring the Consistency Between User Requirements and GUI Prototypes: A Behavior-Based Automated Approach

In a user-centered design process, graphical user interface (GUI) prototypes may be seen as an important early artifact to design and validate user requirements before making strong commitments with a full-fledged version of the user interface. Ensuring the consistency of GUI prototypes with other representations of the user requirements is then a critical aspect of the design process. This paper presents an approach which extends Behavior-Driven Development (BDD) by employing an ontology in order to provide automated assessment for GUI prototypes as design artifacts. The approach has been evaluated by exploiting user requirements described by a group of experts in the flight tickets e-commerce domain. Such requirements gave rise to a set of User Stories that have been used to automatically check the consistency of Balsamiq prototypes which were reengineered from an existing web system for booking business trips. The results have shown our approach was able to identify different types of inconsistencies in the set of analyzed artifacts, allowing to build an effective correspondence between user requirements and their representation in GUI prototypes.
The MLLP-UPV Spanish-Portuguese and Portuguese-Spanish Machine Translation Systems for WMT19 Similar Language Translation Task

This paper describes the participation of the MLLP research group of the Universitat Politècnica de València in the WMT 2019 Similar Language Translation Shared Task.We have submitted systems for the Portuguese ↔ Spanish language pair, in both directions.They are based on the Transformer architecture as well as on a novel architecture called 2D alternating RNN.Both systems have been domain adapted through fine-tuning that has been shown to be very effective.
Multimedia Based on Virtual Reality in Indonesian for Foreign Speakers Learning

Abstract Virtual Reality technology can manifest 3D virtual environments that are computer-simulated, and allows for the emergence of various interactions in 360° space. Virtual Reality is a technology that allows users to interact with an environment simulated by a computer. This study aims to create multimedia in the form of videos and photos based on Virtual Reality in the context of learning Indonesian for Foreign Speakers (BIPA). This research is based on Research and Development (R &amp; D). The steps taken in this research process were: (1) research and data collection, (2) planning, (3) product development, (4) initial field trials, (5) revision of trial results, (6) product improvement and (7) final field implementation test. Based on the validation of experts, both Indonesian linguists and media experts, this Virtual Reality multimedia is feasible to be used as BIPA learning media. In addition, based on limited test results, this Virtual Reality multimedia fulfills three variables, namely: functionality, efficiency, and usability.
Sentiment Analysis Through Machine Learning for the Support on Decision-Making in Job Interviews

In this paper, we propose a sentiment analysis model using machine learning for the support on decision-making in the process of job interviews. To do this, a characterization of the analysis of sentiments, job interviews and machine learning algorithms is first performed. Then, supervised machine learning with artificial neural networks is implemented in a prototype, due to the non-linear behavior described in the variables taken in the study and applying the Eye tracking technique. Finally, tests are carried out with people, in which, by asking questions of these, the involuntary movements of the pupil of the eye are analyzed, through the processing of a volume of data and the results of the ocular patterns are interpreted. Correlated with the questions of the test and with it, a final judgment is presented for the support of the decision making.
User Study: A Detailed View on the Effectiveness and Design of Tactile Charts

Charts such as bar or pie charts are often used to represent data and their relation. Tactile charts are widely used to enable blind and visually-impaired people to explore charts through the sense of touch. Effective tactile chart design differs from its visual counterpart due to sequential nature of touch. Accordingly, in a study with 48 blind and visually-impaired participants we investigated the preferences for chart types, design features and errors in reading data values. We developed bar, line and pie charts as well as scatterplots with different layouts and novel design properties. Participants answered questions concerning the readability, content and data, specific design aspects as well as a personal rating. Overall, participants answered 80% of nominal questions regarding minima, maxima, and comparisons, correctly. Blind participants achieved a corrected mean error rate of 4.5%, when reading single points or intersections, for example. More specifically, we directly compare chart types, and discuss the results for specific design considerations (e.g. distances between bars, width of bars, design and use of grid lines in scatterplots) by comparing different charts.
APPLYING THINK-TALK-WRITE (TTW) IN THE TEACHING OF READING COMPREHENSION IN RELATION TO STUDENTS’ CRITICAL THINKING SKILLS

This research was aimed at finding out the effect of Think Talk Write (TTW) towards students’ critical thinking skills in reading comprehension at the first grade of SMKN 2 Lingsar. The research was experimental research. The design was quasi-experimental design by with nonequivalent control group design. The two classes were chosen as the samples in this research which consist of 32 students. They were chosen by using purposive sampling technique. The research instruments consist of reading tests and questionnaire. Reading test was employed in the form of a multiple choice and essay. Meanwhile, the questionnaire was used to attain the students’ critical thinking skills. In analyzing the data, researchers applied statistical analysis. It showed the value of t-test = 2,482 ≥ t-table = 1,697 at the significant level 5% (0.05). Based on the results of the analysis, it can be concluded that Think Talk Write has a positive effect on students' critical thinking in reading comprehension at first-grade student of SMKN 2 Lingsar. In other words, the alternative hypothesis (Ha) is accepted and null hypothesis (Ho) is rejected.
Adaptable Deep Learning Generation by Automatic Service Composition

A novel framework and method to generate automatically deep learning (DL) services for developers who are not artificial intelligence (AI) experts is presented. Two issues have been considered for the framework: 1) separation of the knowledge on DL from DL generation engines, and 2) cooperation between Automatic Service Composition (ASC) and the CRoss-Industry Standard Process for Data Mining (CRISP-DM) procedure. First, the separation of knowledge on DL from DL generation engines is necessary to adapt to advances and changes in DL technology. Ontology and rules for knowledge and experience in regard to DL technology applications will therefore be constructed for DL generation engines. Second, a framework to compose a target service for generation of a DL architecture requested by non-AI domain experts will be constructed using ASC that works with input involving user requirements based on the CRISP-DM procedure. The created ontology, rules, and composition procedure based on a scenario for special document classification are explained.
A Framework for Learning Cell Interestingness from Cube Explorations

In this paper, we discuss the problem of organizing the different ways of computing the interestingness of a particular cell derived from a cube in the context of a hierarchical, multidimensional space. We start from an in-depth study of the interestingness aspects in the study of human behavior and include in our survey the approaches taken by computer-science efforts in the area of data mining and user recommendations. We move on to structure interestingness along different fundamental, high level aspects, and, due to their high-level nature, we also move towards much more concrete data-oriented definitions of interestingness aspects.
Quantum steering of Bell-diagonal states with generalized measurements

The phenomenon of quantum steering in bipartite quantum systems can be reduced to the question of whether or not the first party can perform measurements such that the conditional states on the second party can be explained by a local hidden-state model. Clearly, the answer to this depends on the measurements which the first party is able to perform. We introduce a local hidden-state model explaining the conditional states for all generalized measurements on Bell-diagonal states of two qubits. More precisely, it is known for the restricted case of projective measurements and Bell-diagonal states characterized by the correlation matrix $T$ that a local hidden-state model exists if and only if ${R}_{T}=2\ensuremath{\pi}{N}_{T}\left|det(T)\right|\ensuremath{\ge}1$, where ${N}_{T}$ is defined by an integral over the Bloch sphere. For generalized measurements described by positive operator-valued measures we construct a model if ${R}_{T}\ensuremath{\ge}6/5$. Our work paves the way for a systematic study of steerability of quantum states with generalized measurements beyond the highly symmetric Werner states.
An Efficient Application Specific Instruction Set Processor (ASIP) for Tensor Computation

In the past decade, tensor computation is widely used in different areas. Various software toolbox have been released to assist tensor computation. However, there is still no hardware architecture to accelerate the tensor computation. This paper presents an efficient application specific instruction set processor (ASIP) for tensor computation. Different tensor computations are fully optimized in terms of resource usage and performance. We implement the ASIP on FPGA platform. We test our design by implementing the CANDECOMP/PARAFAC(CP) decomposition. Our design can achieve a low resource usage and run at 141 Mhz.
Percepciones actitudinales hacia la competencia digital docente del profesorado universitario formador de maestros en Rep. Dominicana

The purpose of this research is to analyze the attitude of teachers training university about the digital competence. It’s opt for a case study of descriptive character framed in the method of contrast of hypothesis and based on an attitude Scale Likert type applied to a representative sample. The study was conducted at the higher Institute of training teacher Salomé Ureña during the period 2014-2016, in the Dominican Republic, with a population of 256 teachers, of which 121 constituted study sample. The results lean toward the principal of the assumptions made, that is to say teachers presents favorable attitudes towards ict competences; it is considered that the motivation is a fundamental aspect to make such integration adequate and innovative and appreciate the effectiveness and possibilities these offer to the educational community in general.
Libra: Is it Really About the Money?

The announcement by Facebook that Libra will deliver on the promise of 'the internet of money' has drawn the attention of the financial world. Regulators, institutions, and users of financial products have all been prompted to react and, so far, no one managed to convince the association behind Libra to apply the brakes or to convince regulators to stop the project altogether. In this article, we propose that Libra might be best seen not as a financial newcomer, but as a critical enabler for Facebook to acquire a new source of personal data. By working with financial regulators seeking to address concerns with money laundering and terrorism, Facebook can position itself for privileged access to high-assurance digital identity information. For this reason, Libra merits the attention of not only financial regulators, but also the state actors that are concerned with reputational risks, the rule of law, public safety, and national defence.
Computing Sentiment Analysis through Aspect-based fuzzy Aggregations

The expression of a general opinion on a product or service may sometimes be broken down into different sub-opinions on the different aspects which characterize such a product or service.Sometimes, the general opinion about a product does not have to be the average of the other sub-opinions, but other user-dependent factors can make the aggregation of the sub-opinions more complex.This work studies some use cases with real opinions, in which fuzzy aggregation operators can help represent certain user behaviors, and hence, explain the overall assessment of an opinion with respect to partial opinions of aspects.
Residual Learning for FC Kernels of Convolutional Network

One of the most important steps in training a neural network is choosing its depth. Theoretically, it is possible to construct a complex decision-making function by cascading a number of shallow networks. It can produce a similar in accuracy result while providing a significant performance cost benefit. In practice, at some point, just increasing the depth of a network can actually decrease its performance due to overlearning. In literature, this is called “vanishing gradient descent”. Vanishing gradient descent is observed as a vanishing decrease of magnitudes of gradients of weights for each subsequent layer, effectively preventing the weight from changing its value in the lower layers of a deep network when applying the backward propagation of errors algorithm. There is an approach called Residual Network (ResNet) to solve this problem for standard convolutional networks. However, the ResNet solves the problem only partially, as the resulting network is not sequential, but is an ensemble of shallow networks with all drawbacks typical for them. In this article, we investigate a convolutional network with fully connected layers (so-called network in network architecture, NiN) and suggest another way to build an ensemble of shallow networks. In our case, we gradually reduce the number of parallel connections by using sequential network connections. This allows to eliminate the influence of the vanishing gradient descent and to reduce the redundancy of the network by using all weight coefficients and not using residual blocks as ResNet does. For this method to work it is not required to change the network architecture, but only needed to properly initialize its weights.
Application of the Theory of Planned Behavior to Predict Nutrition Students’ Intention to Work with Older Adults

As Registered Dietitian Nutritionists play an important role in providing nutrition care plans for successful aging, it is important to identify factors influencing nutrition students’ intention to work with older adults. A cross-sectional study was conducted to identify significant predictors of nutrition students’ intention to work with older adults by utilizing the Theory of Planned Behavior (TPB). A total of 183 students, majoring in Nutrition at a large Southern University, completed a questionnaire examining validated TPB constructs. Structural Equation Modeling with maximum likelihood was used to analyze the data. The structural model provided a good fit to the data (x2 = 44.95, df = 38, p < 0.01; RMSEA = 0.03, CFI = 0.99; TLI = 0.99. Attitude (γ = 0.49, p < 0.001) and subjective norm (γ = 0.39, p < 0.001) emerged as significant predictors of nutrition students’ intention to work with older adults. Findings highlight the importance of providing dietetics curricula that provide opportunities for students to develop positive attitudes toward working with older adults. Dietetic educators should present themselves as positive role models in working with older adults, as the educators influence students’ intention to work with this population.
Context-Aware Pervasive Systems

In the design of a pervasive system, the important element is the context. The context information has brought value to the user services and will exponentially increase the business in the coming years. The context and context management will help to understand the user requirements in precise and stands the heart-core element of the context-aware computing system. Having a precise discussion on the context and context management presented in Chap. 2 , this chapter has focused on the context-aware pervasive system. The elements of the context-aware computing system are presented at the beginning of this chapter. Also, keen attention has been given on the context-aware network in detail in this chapter. Though the context-aware computing system is promising, it is coming with a few important challenges. This chapter ends with a detailed description of the issues and challenges.
A Deep Learning Part-diagnosis Platform(DLPP) based on an In-vehicle On-board gateway for an Autonomous Vehicle

Autonomous driving technology is divided into 0~5 levels.Of these, Level 5 is a fully autonomous vehicle that does not require a person to drive at all.The automobile industry has been trying to develop Level 5 to satisfy safety, but commercialization has not yet been achieved.In order to commercialize autonomous unmanned vehicles, there are several problems to be solved for driving safety.To solve one of these, this paper proposes 'A Deep Learning Part-diagnosis Platform(DLPP) based on an In-vehicle On-board gateway for an Autonomous Vehicle` that diagnoses not only the parts of a vehicle and the sensors belonging to the parts, but also the influence upon other parts when a certain fault happens.The DLPP consists of an In-vehicle On-board gateway(IOG) and a Part Self-diagnosis Module(PSM).Though an existing vehicle gateway was used for the translation of messages happening in a vehicle, the IOG not only has the translation function of an existing gateway but also judges whether a fault happened in a sensor or parts by using a Loopback.The payloads which are used to judge a sensor as normal in the IOG is transferred to the PSM for self-diagnosis.The Part Self-diagnosis Module(PSM) diagnoses parts itself by using the payloads transferred from the IOG.Because the PSM is designed based on an LSTM algorithm, it diagnoses a vehicle's fault by considering the correlation between previous diagnosis result and current measured parts data.
Local probability conservation in discrete-time quantum walks

We show that probability is locally conserved in discrete-time quantum walks, corresponding to a particle evolving in discrete space and time. In particular, for a spatial structure represented by an arbitrary directed graph, and any unitary evolution of a particle which respects that locality structure, we can define probability currents which also respect the locality structure and which yield the correct final probability distribution.
Towards the Definition of an Intelligent Triage and Continuous Monitoring System for Hospital Emergency Departments and Clinics.

Recent statistics have demonstrated that Emergency Departments (EDs) in Greece lack in organization and service. In most cases, patient prioritization is not automatically implemented. The main objective of this paper is to present IntelTriage, a smart triage system, that dynamically assigns priorities to patients in an ED and monitors their vital signs and location during their stay in the clinic through wearable biosensors. Initital scenarios and functional requirements are presented as preliminary results.
Specular reflection detection algorithm for endoscopic images

Endoscopy is a process that allows viewing/ visualize the inside of a human body. In this article, we propose a specular reflection detection algorithm for endoscopic images that utilizes intensity, saturation and gradient information. The proposed algorithm is a two-stage procedure: (a) image enhancement using an adaptive alpha-rooting algorithm and (b) an efficient reflection detection algorithm in the HSV color space. The extensive computer simulations show a significant improvement over stateof-the-art results for specular reflection detection and segmentation accuracy.