Reviewerly/exHarmony huggingface dataset:
Prediction of Answer Keywords using Char-RNN

&lt;p&gt;Generating sequences of characters using a Recurrent Neural Network (RNN) is a tried and tested method for creating unique and context aware words, and is fundamental in Natural Language Processing tasks. These type of Neural Networks can also be used a question-answering system. The main drawback of most of these systems is that they work from a factoid database of information, and when queried about new and current information, the responses are usually bleak. In this paper, the author proposes a novel approach to finding answer keywords from a given body of news text or headline, based on the query that was asked, where the query would be of the nature of current affairs or recent news, with the use of Gated Recurrent Unit (GRU) variant of RNNs. Thus, this ensures that the answers provided are relevant to the content of query that was put forth.&lt;/p&gt;
Monitoring System for Emergency Service in a Hospital Environment

The hospital emergency service remains the first choice for the vast majority of patients. The large influx of hospital emergency services, combined with the lack of health professionals, often makes the patients susceptible to excessive waiting times. As a result, their health condition may worse after triage, until they are observed by a doctor. In the developed prototype, a bracelet is placed on the patient's wrist, which reads their vital signs, accompanied by a mobile phone with an Android application, designed to send the collected vital signs data, as well as patient's location, periodically, to a server. There is a database, with the information of all patients under care and, through a dashboard, the interface is made with the health professionals. Such interface alerts the professional whenever a situation is considered critical. The prototype was positively evaluated by the usability tests carried out and could be considered a Minimum Viable Product in the business perspective.
A Fuzzy Weighted Kalman Filter for GPS Positioning Precision Enhancement

Kalman Filter (KF) is the predominant implemented method where continuity in state space of latent variables is presented. The filter applications are chiefly in the fields of control, navigation, signal processing and robotic motion planning. This work proposes a novel fast weighted KF based on fuzzy classifier. This approach improves the functionality of this digital filter in general. The presented extension of KF is analyzed and validated for accurate positioning of moving objects which is one of the main issues that KF is expected to address. Accordingly, raw Global Positioning System (GPS) data, as the predominant means of obtaining position, is utilized as input observations for this filter. In weighting phase, the fuzzy classifier segregates observations based on different features of their signal. Therefore, it alleviates effects of deteriorating factors such as power and quality loss and multipath error. The suggested approach has been vetted upon three distinctly different motion scenarios. Evaluating the positioning results indicated that the new method has raised precision up to 35 percent, compared to Recursive Least Square (RLS) and classic KF.
Coherent Interaction Graphs

We introduce the notion of coherent graphs, and show how those can be used to define dynamic semantics for Multiplicative Linear Logic (MLL) extended with non-determinism.Thanks to the use of a coherence relation rather than mere formal sums of non-deterministic possibilities, our model enjoys some finiteness and sparsity properties.We also show how studying the semantic types generated by a single "test" within our model of MLL naturally gives rise to a notion of proof net, which turns out to be exactly Retoré's R&Bcographs.This revisits the old idea that multplicative proof net correctness is interactive, with a twist: types are characterized not by a set of counter-proofs but by a single non-deterministic counter-proof.
Solving ODEs by Obtaining Purely Second Degree Multinomials via Branch and Bound with Admissible Heuristic

Probabilistic evolution theory (PREVTH) forms a framework for the solution of explicit ODEs. The purpose of the paper is two-fold: (1) conversion of multinomial right-hand sides of the ODEs to purely second degree multinomial right-hand sides by space extension; (2) decrease the computational burden of probabilistic evolution theory by using the condensed Kronecker product. A first order ODE set with multinomial right-hand side functions may be converted to a first order ODE set with purely second degree multinomial right-hand side functions at the expense of an increase in the number of equations and unknowns. Obtaining purely second degree multinomial right-hand side functions is important because the solution of such equation set may be approximated by probabilistic evolution theory. A recent article by the authors states that the ODE set with the smallest number of unknowns can be found by searching. This paper gives the details of a way to search for the optimal space extension. As for the second purpose of the paper, the computational burden can be reduced by considering the properties of the Kronecker product of vectors and how the Kronecker product appears within the recursion of PREVTH: as a Cauchy product structure.
Impact of digital transformation for Mass healthcare

Mass Healthcare is the prominent field and it must be noted that over the last couple of decades, the entire healthcare industry has digitized health care landscape. Digitalization conveyed moment access to data, made the sharing of data simpler among social insurance experts and enhanced the efficiencies of patient results. Automation has substantially changed the medicinal services industry and made it more savvy for associations to run everyday tasks. Automation is the utilization of data innovation that lessens the requirement for human work in the making of results. The present mechanization advances are equipped for significantly more than human managers. For example, a decrease of managerial outstanding tasks at hand, enhancement of the consistency of patient consideration, end of waste, improvement of data trade, investigation of information, and checking of patients would all be able to be streamlined with information mechanization. There might be a piece of legitimacy to this stress; some social insurance clients essentially want to manage a human when they make arrangements or demand data.
Strengths of Fuzzy Techniques in Data Science

We show that many existing fuzzy methods for machine learning and data mining contribute to providing solutions to data science challenges, even though statistical approaches are often presented as major tools to cope with big data and modern user expectations of their exploitation. The multiple capacities of fuzzy and related knowledge representation methods make them inescapable to deal with various types of uncertainty inherent in all kinds of data.
Practical problem-based programming learning using video

The fundamental skills for information system development such as system designing, programming and project management are very similar to the fundamentals of general problem solving. In this paper, we proposed an education framework for practical problem solving based on system designing technologies and an application of proposed framework on video training materials to train the skills of modeling and understanding from ambiguous matter in practical problem via non-verbalized video training material. Our framework uses Resource Flow Diagram (RFD) to support the understanding of procedure and resources on problem solving. RFD is our proposed visualization method for procedure and resource management based on Sequence Diagram in Unified Modeling Language (UML). RFD is designed for the intuitive representation of the procedure flow and required resources since UML could not define them with single diagram. In this experiment, proposed education framework was applied for the understanding of cooking procedure from the cooking exhibition videos on the demonstrative lecture.
Inclusive Design for Immersive Spaces

It is vital when creating learning environments that attention is paid towards individuals using a given space, activities that they will carry out, and the available equipment that will facilitate this. It is also important that these spaces are created to be inclusive to all and to remove accessibility barriers that are caused by the designed environment. Our aim is to understand how technology can be used to inform design processes for creating educational spaces by collaborating with the primary users of this space: students. This paper is organised in three main sections. Firstly, we identify changes that academics have suggested in how designing for inclusive augmented and virtual-reality environments should be practised. Secondly, we present a workshop entitled Designing for Immersive Spaces. Finally, we discusses the implications of the issues raised and the practical constraints and difficulties of implementing Inclusive Design for Immersive Spaces that is being called for.
Adaptive network diagram constructions for representing big data event streams on monitoring dashboards

Critical systems that produce big data streams can require human operators to monitor these event streams for changes of interest. Automated systems which oversee many tasks can still have a need for the ‘human-in-the-loop’ operator to evaluate whether an intervention is required due to a lack of suitable training data initially offered to the system which would allow a correct course of actions to be taken. In order for an operator to be capable of reacting to real-time events, the visual depiction of the event data must be in a form which captures essential associations and is readily understood by visual inspection. A similar requirement can be found during inspections on activity protocols in a large organization where a code of correct conduct is prescribed and there is a need to oversee whether the activity traces match the expectations, with minimal delay. The methodology presented here addresses these concerns by providing an adaptive window sizing measurement for subsetting the data, and subsequently produces a set of network diagrams based upon event label co-occurrence networks. With an intuitive method of network construction the amount of time required for operators to learn how to monitor complex event streams of big datasets can be reduced.
An n-gram based approach to the automatic classification of schoolchildren’s writing

This article focuses on the analysis of schoolchildren’s writing (throughout the whole primary school period) using sets of morphological labels (n-grams). We analyzed the sets of bigrams and trigrams from a group of literary texts written by Catalan schoolchildren in order to identify which bigrams and trigrams can help discriminate between texts from the three cycles into which the Spanish primary education system is divided: lower cycle (6- and 7-year-olds), middle cycle (8- and 9-year- olds) and upper cycle (10- and 11-year-olds). The results obtained are close to 70% of correct classifications (77.5% bigrams and 68.6% trigrams), making this technique useful for automatic document classification by age.
Digital Technology for Preserving Cultural Heritage in Tonga

Cultural heritage embodies and carries the stories and values of our ancestors that define our understanding of who we are today. A society's heritage serves an important purpose for educating people about their own culture and aiding in understanding their traditional values. In Tonga, where this research has been conducted, the historical knowledge and cultural values have been usually transferred orally from generation to generation. However, due to the pressures of globalisation, westernisation and migration, cultural heritage is under threat. These threats can potentially impede the transferring of societies' idiosyncratic identity to future generations and erode cultural life. ICT as an option to preserve cultural heritage offers opportunities to not only capture and immortalise tangible and intangible cultural artefacts but also enables the accessibility of those artefacts to a wider audience through the internet. It is against this background that we explore how digital technologies are utilised in the process of preserving cultural heritage.
PERFORMANCE EVALUATION OF MACHINE LEARNING ALGORITHMS IN ECOLOGICAL DATASET

Classification is a key supervised machine learning technique, which is essential and interesting topic for ecological research.It deals a way to classify a dataset into subsets that share common designs.Particularly, there are many classification processes to select from, each creating firm assumptions about the data and about how classification should be grouped.In this paper, we applied eight machine learning classification algorithms such as Decision Trees, Random Forest, Artificial Neural Network, Support Vector Machine, Linear Discriminant Analysis, k-nearest neighbours, Logistic Regression and Naive Bayes on ecological data.The objective of this study is to compare different machine learning classification algorithms in ecological dataset.In this analysis we have checked the accuracy test among the algorithms.In our study we conclude that linear discriminant analysis and k-nearest neighbours are the best methods.
Identification of Deceptive Reviews by Sentimental Analysis and Characteristics of Reviewers

The purchase decisions of customers are influenced by the relevant reviews made by customers.Deceptive reviews are confusing and hard to detect.The existing identification method of deceptive reviews is based on the traditional algorithm of machine learning.However, the methods used to identify deceptive reviews must be improved.In order to improve the accuracy of the identification of deceptive reviews, a novel method integrating sentimental analysis and the characteristics of reviewers was proposed in this study.On the basis of the analysis of the emotional characteristics of the review texts and the behavioural characteristics of the reviewers, a method of deceptive review identification was established.The proposed method analyzed the intensity of emotions, the text similarity, the largest daily publishing comment index, and the extreme rating index on the basis of the feature-weighted model.This model verified the effectiveness of the proposed method.Results show that a direct correlation exists between the unreliability score of users and deceptive review identification.If the score exceeds 0.78, then the reviewer is deemed to be a deceptive reviewer, and the reviews made are deceptive reviews.The proposed method provides a good prospect to identify deceptive reviews.
Türkiye’de Paket Arıcılık Uygulamasının Ekonomik Olarak Uygulanabilirliği: Edirne İli Örneği

In this study, it was discussed whether the package beekeeping was an economical alternative to traditional beekeeping in Turkey.An experiment involving two different applications was carried out in the province of Edirne, which has a short production season due to the cold climate conditions.The control groups representing the colonies formed by the artificial swarms and the colonies formed by the package bees were compared in terms of economic feasibility in this experiment.The results of this study showed that package beekeeping was more advantageous for beekeeping enterprises when the artificial swarms' application was taken into consideration.The purchase price of package bees for beekeeping enterprises in Edirne Province should be below US$39.52.In other words, package beekeeping for Edirne province is profitable for enterprises at prices below US$ 39.52.The package beekeeping can provide savings for beekeepers whose bees overwinter in cold climates.It was determined that if the bees were not wintered, the beekeeping enterprises could save US$31.63 per hive in this study.According to the results, it is expected that the dissemination of package beekeeping will have a hugely positive impact on beekeeping enterprises for North, Northwest and Eastern Anatolia Regions of Turkey.
KED-AES algorithm: combined key encryption decryption and advance encryption standard algorithm

&lt;p&gt;Two existing cryptosystems are being combined and proposed. It is the enhanced combination of KED (Key Encryption Decryption), a cryptosystem that uses modulo 69 and the AES (Advance Encryption Standard) cryptography. The strength of the KED is that the keys are being used by the sender and the receiving end. The AES is easy to implement and has good defense against various attacks such as hacking.&lt;/p&gt;
Data Hiding in Color Images Using Huffman Coding and Histogram Modification

Data hiding in digital images provides a secure communication medium by embedding the payload in a cover image without compromising the image quality. In this work, a secure and high-capacity data hiding scheme is proposed using efficient compression, encryption, and steganography techniques. Dictionary-based coding along with Huffman coding is used to compress the secret data and hence increase the embedding capacity. Two encrypted keys are generated to control the data decompression and hence improve the level of security. In addition, a block-based histogram modification technique is applied to embed the compressed data into the chrominance components of the cover image to minimize the image distortion. The results indicate that the proposed scheme achieves high embedding capacity without degrading the quality of the cover image.
Secured smart ATM transaction

&lt;p&gt;The objective of this paper is to reduce the service tax during mobile transactions. To improve the security and to make the process easy and less time consuming this process is rendered with the help of GSM (Global System for Mobile communication), finger print sensors, PIC16F877A microcontroller and aadhaar number.&lt;/p&gt;
On-the-Fly Testing an Implementation of Arrow Lightweight PRNG Using a LabVIEW Framework

This work proposes a LabVIEW framework suitable for simulating and on-the-fly testing a hardware implementation of the Arrow lightweight pseudorandom generator. Its aim is twofold. The first objective is to provide a framework to simulate the pseudorandom generator behavior in a personal computer, allowing to modify dynamically the configuration parameters of the generator. Moreover, to visualize the randomness of the output sequences useful techniques like the chaos game and return maps are used. The second objective is to generate an architecture implementing the Arrow algorithm which can be downloaded into a real Complex Programmable Logic Device or a Field-Programmable Gate Array. Plots are shown which demonstrate the usefulness of the proposed framework.
On Topologies Induced by Graphs Under Some Unary and Binary Operations

Let G = (V (G),E(G)) be any simple undirected graph. The open hop neighborhood ofÂ v Ïµ V(G)Â is the set ð‘_ðº^2(ð‘£) = {u Ïµ V(G):Â ð‘‘_ðº (u,v) = 2}.Â Then G induces a topologyÂ Ï„_G on V (G) with base consisting of sets of the formÂ F_G^2[A] = V(G) \ N_G^2 [A] whereÂ N_G^2 [A] = A âˆª {vÂ Ïµ V(G):Â Â ð‘_ðº^2(ð‘£)Â âˆ© A â‰ âˆ… } and A ranges over all subsets of V (G). In this paper, we describe the topologies induced by the complement of a graph, the join, the corona, the composition and the Cartesian product of graphs.
ЗАСТОСУВАННЯ МОБІЛЬНОЇ ТЕХНОЛОГІЇ PLICKERS У ПРОЦЕСІ НАВЧАННЯ ФІЗИКИ

The article analyzes the possibilities of introduction of mobile technology of education in school practice as a means of forming information and digital competency of students. Based on the analysis of literary sources and educational practice, the methodical features of the application of mobile technology in the educational process, in particular during the frontal questioning of students using the mobile application Plickers, are outlined. According to the results of questionnaire survey of students and teachers revealed the main shortcomings of the introduction of mobile technology in the educational process. In particular, the inadequate preparation of students for the use of mobile technology in self-study, the low readiness of students and teachers to use mobile applications and services in the learning process has been confirmed. It is argued that the low level of introduction of mobile education in school practice is due to insufficient methodological support and improper description of ways of using mobile applications in specific didactic situations. The example of the Plickers mobile application demonstrates the possibilities of using it in the process of teaching physics. The article gives methodical recommendations on the application of Plickers during the frontal questioning of students in the process of studying quantum physics. Five options for the use of Plickers in physics classes are proposed, in particular: a frontal survey to diagnose student achievements or check the formation of certain concepts; double testing at the beginning and at the end of the lesson to determine the degree to which the purpose of the lesson is achieved; local or modular survey on specific pieces of educational material to identify its level; interviewing students in order to find out the success of tasks or solving problems; the use of a mobile tool for grouping students into groups in order to correct typical errors. It is emphasized that the rapid development of information and communication technologies and their widespread use in recent years in educational activities provide grounds for optimistic forecasts for the earliest possible introduction of mobile school education.
INSIDE-OUTSIDE CIRCLE AS THE WAY IN BUILDING STUDENTSâ€™ MOTIVATION AND INTERACTION IN SPEAKING CLASSROOM ACTIVITIES

ABSTRACT&#x0D; As the important factors in EFL speaking classroom activities, building studentsâ€™ motivation and interaction in EFL speaking classroom should be designed in meaningful ways. Many research studies reported the variety ways in minimizing the problems as well as proposed innovative ways in teaching speaking skill. One of the ways that recommended by the researches is inside-outside circle strategy. It is a way that students can work cooperatively and raise their motivation to talk and interact with others. The classroom-based research was conducted with only one cycle implemented the strategy. 30 students at the first grade of Multimedia Program at SMK Negeri 6 Ambon were participated in this study. The results showed that during the implementation of inside-outside circle strategy in the classroom activities, the students could actively involve in expressing their ideas based on the given topics, they could build good interaction in the inside and outside a group, and showed high motivation in speaking classroom activities.
USING VIDEO BLOG IN TEACHING SPEAKING

The objective of the research is to find out whether or not video blog can improve the speaking ability of the students of English Education Department of FTK UINAM in academic year 2017/2018. The researcher applied pre-experimental method, with one group pretest and posttest design which employed speaking test to find out the students’ speaking performance in terms of accuracy. The sample consisted of 20 students used purposive sampling technique taken from the population of the second semester students of Sulawesi Flight. The result of the data analysis indicated that there was significant difference of students’ speaking performance before and after being trained through video blog. It is proved by result of statistical analysis of the level significance 0.05 with degree of freedom (df) = N-1 = 20-1 = 19 which indicated that t-test value of final score I speaking ability (13.309) was greater than t-table (2.093). Therefore, video blog can improve speaking performance of the students.