Reviewerly/exHarmony huggingface dataset:
Social dimension of students’ problems under the development of the contemporary university infrastructure

Improving the quality of students’ life is an important task for every university and the educational system as a whole, which fits into the aims of the studies of the social dimension of students’ life. To solve this task, the study of students’ problems is a priority, while the second step can be the creation of university structures that would solve these problems effectively. The article presents an ideal model of the consulting center that can solve such problems. The authors conducted four focus groups in the RUDN University with students of different courses from different countries, and used projective techniques and group discussions to identify models of the consulting center, departments that it should consist of, and qualities of employees working in these departments. The general model of the consulting center includes an information department as its ‘core’ responsible for the distribution of students’ requests to necessary departments; IT department (site, corporate mail, etc.); department of social support (scholarships, financial support, etc.); residence department (registration, dormitory, etc.); department of science and education (grants, competitions, etc.); student committee (leisure). The students prefer to receive all necessary information online, by phone and also in person. The preferred social network for information is Facebook - for foreigners - and VK (Vkontakte) - for Russian students. The students also mentioned three main languages for distribution of information - Russian, English and Chinese. The focus-groups allowed to find out that although some necessary units designed to solve students’ problems already exist, they do not actually solve them due to bureaucratic or other reasons. Therefore, the proposed model of the consulting center can be an effective management solution ‘from the bottom’ that would help the university to communicate with students and to understand their real needs.
SECURE ATM AND BANK TRANSACTIONS USING BIOMETRIC AND BLOCKCHAIN

The conventional Automated Teller Machines in Nigeria have over the past few years been faced with inherent security challenges, which have mostly been attributed to the two-factor authentication structure (PIN and Card) of the ATM systems.The Nilson's report (2016) reveals that over 72% of ATM frauds within the period of the review were from card frauds, ranging from counterfeiting to card snatches.This record was able to soar so high since the identity thief is left with only one security clearance (PIN) to provide once the card is obtained.This work focuses on a multifactor approach to authentication which requires the presentation of three authentication factors: a knowledge factor ("something only the user knows"), a possession factor ("something only the user has"), and an inherence factor ("something only the user is").After the presentation, the first factor and either of the next two factors must be validated by the other party for authentication to occur.This is to give room for exigencies and unforeseen circumstances such as loss/unavailability of mobile phones or lost or damaged fingers through accidents and aging factors.Although the proposed system does not promise a total eradication of ATM card frauds, and implementation of this design, it will to a large extent, reduce the occurrence and frequency of loss of money through ATM and card fraud since it provides an additional level of security.This translates to a more secure user identity, more secured funds and resources for the user and a more difficult and a less probable unauthorized access to an individuals' account.
Operator for Construction of Archimedian Triangular Norms

Triangular norms and associative functions arebase of connectives in fuzzy logic and fuzzy systems. Newconnective operator that can generate different classes of fuzzyconnectives is proposed. It is proved that this operator satisfiesthe requirements of such axioms as commutativity, associativity,monotonicity and boundary conditions. It is parameterized andtherefore new triangular norms are obtained. Constructedparameterized triangular norms are of a strict and Archimediantype.
Verifying Cross-Layer Interactions Through Formal Model-Based Assertion Generation

Cross-layer runtime management (RTM) frameworks for embedded systems provide a set of standard application programming interfaces (APIs) for communication between different system layers (i.e., RTM, applications, and device) and simplify the development process by abstracting these layers. Integration of independently developed components of the system is an error-prone process that requires careful verification. In this letter, we propose a formal approach to integration testing through automatic generation of runtime assertions in order to test the implementation of the APIs. Our approach involves a formal model of the APIs developed using the Event-B formal method, which is automatically translated to a set of assertions and embedded in the existing implementation of APIs. The embedded assertions are used at runtime to check the correctness of the integration.
Penerapan K-Nearest Neighbour dalam Penerimaan Peserta Didik dengan Sistem Zonasi

Admission of new students is a routine activity at the beginning of each new meeting year in all formal educational institutions. At the moment the acceptance of new students uses the zoning system and has been regulated by Permendikbud No. 20 in 2019. This zoning system will accept students where their residence enters through the user area with the school environment. With this Permendikbud the government hopes that there will be an evenness in the quality of education in all schools, so that schools will no longer get the title of superior and non-superior schools. But in a system, the zoning improves anxieties in the school environment. This research supports to help the participating school students will be accepted in accordance with the provisions of the Ministry of Education and Culture. In overcoming problems that arise in the school environment there needs to be a system that can overcome that problem. In this study using the K-Nearest Neighbor (K-NN) method. Where the K-NN method will do the classification of new learners' residence with the school. In determining the classification using the K-NN method used for zoning and non-zoning areas, it is seen based on the closest K value. In finding the optimal value in this study using the Rapidminer application. The optimal high-level test results at K 5 where the value of this K is 83.36%
The Positive Side of Eliciting Negative Emotions: Survey Results of Visitor Responses to a Library Exhibit

Eliciting emotions, particularly uncomfortable emotions, through exhibition design can have a positive impact on the patrons’ reception of the exhibition. In this study, patrons visiting an exhibition designed to create a dark and macabre atmosphere were given an exit survey asking them to identify and rate the intensity of the emotions they felt during the experience. The survey also assessed visitor likelihood of returning to view the exhibition again. In general, visitors who recorded feeling negative emotions while viewing the exhibition were significantly more likely to visit multiple times than those who did not.
Developing without Developers: Choosing Labor-saving Tools for Language Documentation Apps

Application software has the potential to greatly reduce the amount of human labor needed in common language documentation tasks. But despite great advances in the maturity of tools available for apps, language documentation apps have not attained their full potential, and language documentation projects are forgoing apps in favor of less specialized tools like paper and spreadsheets. We argue that this is due to the scarcity of software development labor in language documentation, and that a careful choice of software development tools could make up for this labor shortage by increasing developer productivity. We demonstrate the benefits of strategic tool choice by reimplementing a subset of the popular linguistic annotation app ELAN using tools carefully selected for their potential to minimize developer labor.
High-dimensional Quantum Teleportation, 12-photon Entanglement and Scattershot Boson Sampling based on Spontaneous Parametric Down-Conversion

We experimentally realize the first high-dimensional quantum teleportation experiment, and proposed a general method for teleporting n-dimensional photon. We developed an optimal SPDC entangled photon-pair source, and implement 12-photon entanglement and scattershot boson sampling.
Open Dialog: SciELO’s Approach to Open Access Publishing

For over 20 years, Scientific Electronic Library Online (SciELO) has been engaged in an ambitious program of open access journal publishing. In Brazil and 15 other countries, society journals and other publications rely on SciELO for online publishing infrastructure and a platform that gives visibility to a global audience. SciELO’s network of national level collections has expanded to 16 countries and provides an alternative model to approaches centered around commercial publishers or new open access journals.
THE STUDENTS� PERCEPTIONS ON A TEST OF ENGLISH PROFICIENCY AS GRADUATION REQUIREMENT

TEP, Test of English Proficiency, is a type of English test which is held regularly by Language Center (LC) of Universitas Swadaya Gunung Jati (UGJ) Cirebon based on the Rectors decree as policy. It becomes one of the requirements for the students who are going to graduate from higher education. This research intends to 1) explore the students perception on a Test of English Proficiency and 2) find out about how is the implementation of TEP. The writers conducted a case study with 288 students as the respondents. They come from different majors and faculties. There are four techniques of collecting data: 1) interviews, 2) observation, 3) questionnaires, and 4) documents. To get the valid data, the writers used triangulation of sources to cross check and compare data. An interactive model (data collection, data display, data reduction, and conclusion) is used to analyze data. The research findings reveal that the students perceptions on TEP can be classified into three aspects: TEP activity, test instrument, and preparation while the implementation of TEP such as a registration system, information system, proctoring, and facilities get satisfactory responses from the students.DOI: 10.24071/llt.2019.220204
Cognitive-competency component of specialist`s readiness to implement a team interaction in terms of inclusion

In term of research: is the inclusive education, the problem of training future specialists to work in an inclusive educational space of elementary school, developing competencies of teacher's
A construction of $ \mathbb{F}_2 $-linear cyclic, MDS codes

In this paper we construct $ \mathbb{F}_2 $-linear codes over $ \mathbb{F}_{2}^{b} $ with length $ n $ and dimension $ n-r $ where $ n = rb $. These codes have good properties, namely cyclicity, low density parity-check matrices and maximum distance separation in some cases. For the construction, we consider an odd prime $ p $, let $ n = p-1 $ and utilize a partition of $ \mathbb{Z}_n $. Then we apply a Zech logarithm to the elements of these sets and use the results to construct an index array which represents the parity-check matrix of the code. These codes are always cyclic and the density of the parity-check and the generator matrices decreases to $ 0 $ as $ n $ grows (for a fixed $ r $). When $ r = 2 $ we prove that these codes are always maximum distance separable. For higher $ r $ some of them retain this property.
THE RELATIONSHIP BETWEEN SYNTACTIC AND SEMANTIC: A STUDY OF LINGUISTIC TYPOLOGY

This research entitled “The Relationship between Syntactic and Semantic : A Study of Linguistic Typology.” is intended to give a clear descriptions related to the relationship between syntactic and semantic on some languages. This research was focused on some clause structures typologycally either syntactically or semantically. The scope of this research was more focused on the transitive verbs to have more descriptions related to the relationship between syntactic and semantic to find out whether a clause structure on syntactic can be accepted or cannot be accepted semantically. The theory of linguistics typology was applied in this research because the principle of linguistics typpology is to find out the similarities and the differences among all the type of languages universally. The introspective reflexive and the descriptive method were applied to gain the data in this research and the qualitative descriptive method was applied to analyse the data.
Design of a System of Systems (SoS) for the Interoperability of Non-Invasive Sensors for the Care of Older People.

We propose the design of a system of systems (SoS) called Seniors Guardian as an integrated environment for healthcare monitoring, in which several non-invasive sensors coexist to monitor falls, nocturia, perseverant behaviors, air quality (carbon monoxide), humidity, and temperature in real time. The modular architecture also allows the integration of new components. This research adheres to the use of Internet of Things to develop ambient assisted living in smart homes.
Optimization of computational complexity of lossy compression algorithms for hyperspectral images

In this paper, we consider the solution of the problem of increasing the speed of the algorithm for hyperspectral images (HSI) compression, based on recognition methods. Two methods are proposed to reduce the computational complexity of a lossy compression algorithm. The first method is based on the use of compression results obtained with other parameters, including those of the recognition method. The second method is based on adaptive partitioning of hyperspectral image pixels into clusters and calculating the estimates of similarity only with the templates of one of the subsets. Theoretical and practical estimates of the increase in the speed of the compression algorithm are obtained.
Online Correction Method for Ratio Methods by Using Geomagnetic Sensors Based on Kalman Filter

By eliminating the data offset caused by a disturbing magnetic field during the flying condition of a spinning projectile, an adaptive unscented Kalman filter is applied to estimate the actual data of a geomagnetic field and the false value introduced by a disturbing magnetic field. For the ratio methods related to geomagnetic attitude measurement, the physical significance of the ratios obtained by all ratio methods is clarified. A new definition for the ratio is presented to ensure online estimation and numerical stability. The variation in the sensor outputs along the lateral directions is suggested to be a harmonic motion with the assumption that the spindle is fixed or in slow motion. The true data employed as a reference for comparison is generated by a dynamics model for spinning objects and by projecting the geomagnetic field to the measurement frame. Signal gathering and data preprocessing are considered. A signal-disturbing ratio is introduced to indicate the proportions of the real geomagnetic signal and the interference signal in the data acquisition process. The algorithm of the adaptive unscented Kalman filter is discussed. Simulations are performed using a 1 kHz sample rate and a duration of 60 seconds. The filtering results supported by a conventional unscented Kalman filter and adaptive unscented Kalman filters are compared with actual data for the conditions of different signal-disturbing ratios and 10 shifts of the disturbing magnetic field. The results of the simulation indicate that the proposed adaptive unscented Kalman filter with the introduced state equation achieves better performance than other filters mentioned in the paper. The filter has the ability to provide clean data from the noisy data flow measured from a spinning projectile for the ratio methods based on the geomagnetic measurements.
THUIR at the NTCIR-14 WWW-2 Task

The THUIR team participated in both Chinese and English subtasks of the NTCIR-14 We Want Web-2 (WWW-2) task. This paper describes our approaches and results in the WWW-2 task. In the Chinese subtask, we designed and trained two neural ranking models on the Sogou-QCL dataset. In the English subtask, we adopted learning to rank models by training them on MQ2007 and MQ2008 datasets. Our methods achieved the best performances in both Chinese and English subtasks. Through further analysis of results, we find that our neural models can achieve better performances in all navigational, informational and transactional queries in Chinese subtask. In the English subtask, the learning-to-rank methods have stronger modeling capabilities than BM25 by learning from effective hand-crafted features.
DESIGN OF IDENTIFICATION OF SINGLE DEPRESSION DISORDERS USING NATURAL LANGUAGE PROCESSING MODEL IN PATIENT COMPLAINTS

Unconsciously mental disorders often begin with mild symptoms such as anxiety and depression. In cases of depression with long periods of time can result in disruption of a person's mindset and suicidal arising. Based on WHO data in 2010 suicide rates due to depression in Indonesia reached 1.6 to 1.8 per 100,000 people. Unfortunately the symptoms of depressive disorders are often difficult to recognize because a series of patient complaints are in the form of medical narratives or unstructured texts written by doctors. So to get a diagnosis is done by extracting symptoms from complaints data in the form of medical narrative texts. In this study, a design for identifying a single depressive disorder will be built using rule-based reasoning and the Natural Language Processing approach to extract symptoms in a medical narrative or patient complaint text.
A Solution for Instant Response of Cloud Platform Based on Nginx + Keepalived

How to fulfill load balancing in high concurrency status and thereby to achieve instant response of cloud platform is always a focus of attention to the industry. This document presents an instant response solution for cloud platform based on Nginx + Keepalived, which, by means of Nginx, enables selection of proper load balancing algorithm based on the scenario requested by client, and detection of server working status by using Keepalived to solve single point of failure. This solution is implemented fully with open-source software, and will allow high-concurrency requests of tens of thousand per second ensure good user experience and achieve the goal of low cost and high availability, making it particularly suitable for small-/medium-sized cloud platforms with economic applicability requirements. Test results show that, with respect to analysis on 50% or 80% of the requests, the average response time for 10,000 concurrent requests is only 101 ms and 152 ms, with memory usage up to 22% and CPU peak power up to 80%, which meets the expected response time shorter than 3 seconds in high-concurrency scenario of tens of thousand visits per second.
Revisiting utility metrics for location privacy-preserving mechanisms

The literature has extensively studied various location privacy-preserving mechanisms (LPPMs) in order to improve the location privacy of the users of location-based services (LBSes). Such privacy, however, comes at the cost of degrading the utility of the underlying LBSes. The main body of previous work has used a generic distance-only based metric to quantify the quality loss incurred while employing LPPMs. In this paper, we argue that using such generic utility metrics misleads the design and evaluation of LPPMs, since generic utility metrics do not capture the actual utility perceived by the users. We demonstrate this for ride-hailing services, a popular class of LBS with complex utility behavior. Specifically, we design a privacy-preserving ride-hailing service, called PRide, and demonstrate the significant distinction between its generic and tailored metrics. Through various experiments we show the significant implications of using generic utility metrics in the design and evaluation of LPPMs. Our work concludes that LPPM design and evaluation should use utility metrics that are tailored to the individual LBSes.
Special Issue on Big Data Applications in Cyber Security and Threat Intelligence – Part 2

The papers in this special section focus on Big Data applications in cybersecurity and threat intelligence. The last decade has witnessed a tremendous rapid increase in volume, veracity, velocity and variety of data (also commonly referred to as the four V’s of big data in the literature1) generated by different cyber security solutions and as part of cyber investigation cases. When a significant amount of data is collected from or generated by different devices and sources, intelligent big-data analytical techniques are necessary to mine, interpret and visualize such data. To mitigate existing cyber security threats, it is important for big-data analytical techniques to keep pace. Therefore, in special issue we focus on cutting-edge from both academia and industry, with a particular emphasis on novel techniques to mine, interpret and visualize big-data from a wide range of sources and can be applied in cyber security, cyber forensics and threat intelligence context.
Investigating Mobile Edge-Cloud Trade-Offs of Object Detection with YOLO

With the advent of smart IoT applications empowered with AI, together with the democratization of mobile devices, moving the computation from cloud to edge is a natural trend in both academia and industry. A major challenge in this direction is enabling the deployment of Deep Neural Networks (DNNs), which usually demand lots of computational resources (i.e. memory, disk, CPU/GPU, and power), in resource limited edge devices. Among the possible strategies to tackle this challenge are: (i) running the entire DNN on the edge device (sometimes not feasible), (ii) distributing the computation between edge and cloud or (iii) running the entire DNN on the cloud. All these strategies involve trade-offs in terms of latency, communication, and financial costs. In this article we investigate such trade-offs in a real-world scenario involving object detection from video surveillance feeds. We conduct several experiments on two different versions of YOLO (You Only Look Once), a state-of-the-art DNN designed for fast and accurate object detection and location. Our experimental setup for DNN model partitioning includes a Raspberry PI 3 B+ and a cloud server equipped with a GPU. Experiments using different network bandwidths are performed. Our results provide useful insights about the aforementioned trade-offs.