Reviewerly/exHarmony huggingface dataset:
Convex Kernelized Sorting

Kernelized sorting is a method for aligning objects across two domains by considering within-domain similarity, without a need to specify a cross-domain similarity measure. In this paper we present the Convex Kernelized Sorting method where, unlike in the previous approaches, the cross-domain object matching is formulated as a convex optimization problem, leading to simpler optimization and global optimum solution. Our method outputs soft alignments between objects, which can be used to rank the best matches for each object, or to visualize the object matching and verify the correct choice of the kernel. It also allows for computing hard one-to-one alignments by solving the resulting Linear Assignment Problem. Experiments on a number of cross-domain matching tasks show the strength of the proposed method, which consistently achieves higher accuracy than the existing methods.
Group-based Spatial Reference in Linguistic Human-Robot Interaction

To enable a robot to interpret natural language instructions with regard to a specific object in a configuration, the robot needs to be equipped with a repertory of representations that human users might employ for reference. In this paper, we focus on the ways in which objects are referred to in relation to other similar objects, by analysing the results of an experiment involving a robot and human users unfamiliar with it. The robot is designed to understand reference via basic intrinsic and relative reference systems. Results showed that our implemented computational model could handle standard instances of spatial reference, but needed refinement to be able to interpret specific variations that were employed by users based on contextual factors analysed in this paper.
Registry Maintenance Notifications for the Extensible Provisioning Protocol (EPP)

This document describes an Extensible Provision Protocol (EPP) mappingfor domain name registry's maintenance notifications.
Automatic Text Processing for Historical Research

This article is devoted to the main possibilities of using natural language text processing technologies for historical research. The authors present a taxonomy of biographical facts and use text mining technologies (extraction of information from texts) to obtain biographical information from texts in Russian in accordance with the proposed types of biographical facts. The conducting of biographical research implies the need to view and study large amounts of textual information. The considerable part of the sources is currently presented in electronic form, which allows researchers to apply modern methods of extracting information to them. The article presents an overview of the main areas of application of technologies for automatic processing natural language texts in the humanities and describes the approach to the creation and implementation of the instrument for the extraction and systematization of biographical facts. This instrument will be useful to both historians and other users interested in biographical research.
BOOK: Storing Algorithm-Invariant Episodes for Deep Reinforcement Learning

We introduce a novel method to train agents of reinforcement learning (RL) by sharing knowledge in a way similar to the concept of using a book. The recorded information in the form of a book is the main means by which humans learn knowledge. Nevertheless, the conventional deep RL methods have mainly focused either on experiential learning where the agent learns through interactions with the environment from the start or on imitation learning that tries to mimic the teacher. Contrary to these, our proposed book learning shares key information among different agents in a book-like manner by delving into the following two characteristic features: (1) By defining the linguistic function, input states can be clustered semantically into a relatively small number of core clusters, which are forwarded to other RL agents in a prescribed manner. (2) By defining state priorities and the contents for recording, core experiences can be selected and stored in a small container. We call this container as ‘BOOK’. Our method learns hundreds to thousand times faster than the conventional methods by learning only a handful of core cluster information, which shows that deep RL agents can effectively learn through the shared knowledge from other agents.
PENERAPAN MODEL PEMBELAJARAN JIGSAW DENGAN MEDIA VISUALISASI CANDI UNTUK MENINGKATKAN KESADARAN SEJARAH DAN PRESTASI BELAJAR IPS KELAS VIIA SMP N 2 SAMBIREJO TAHUN 2014/2015

The research aims to uncover effektiveness application of learning models jigsaw with temple visualization media to raise awareness of history and learning achievements of students. This research as classroom action research. The obyect of research is the Class VIIA that consist of 25 students. The data collecting that are use by documents, structure observing, quisener and objective test. Based on the analysis of cycle I, II and III can be concluded application of learning models jigsaw with temple visualization media can be increase awareness of history and learning achievement of student. The average prosentage of awareness of history was increase from 79,17 % to the firts cycle, 82,98% % at second cycle and 83,73% at third cycle. And the average of learning achievements score was increased from 66,16 in the first cycle , 75,52 at second cycle and 80,64 at the third cycle. Based on the result could be concluded that application of learning models jigsaw with temple. visualization media can increased awareness of history and learning achievements of students class VIIA SMP N 2 Sambirejo Year 2014/2015.
External Plagiarism Detection based on Human Behaviors in Producing Paraphrases of Sentences in English and Persian Languages

With the advent of the internet and easy access to digital libraries, plagiarism has become a major issue. Applying search engines is one of the plagiarism detection techniques that converts plagiarism patterns to search queries. Generating suitable queries is the heart of this technique and existing methods suffer from lack of producing accurate queries, Precision and Speed of retrieved results. This research proposes a framework called ParaMaker. It generates accurate paraphrases of any sentence, similar to human behaviors and sends them to a search engine to find the plagiarism patterns. For English language, ParaMaker was examined against six known methods with standard PAN2014 datasets. Results showed an improvement of 34% in terms of Recall parameter while Precision and Speed parameters were maintained. In Persian language, statements of suspicious documents were examined compared to an exact search approach. ParaMaker showed an improvement of at least 42% while Precision and Speed were maintained.
Analisis sentimen kritik dan saran pelatihan aplikasi teknologi informasi (PATI) menggunakan algoritma support vector machine (SVM)

Public opinion is one of many instrument that can be used to evaluate of an event. This research based on several problems, they are (1) quality improvement are necessary for Pelatihan Aplikasi Teknologi Informasi, (2) too much of data make the participant’s opinion that has been collected has not been maximally utilized. Criticism and suggestions datas are taken from 2016/2017 th school year in amount of 1050. Support Vector Machine is used as a method in sentiment analysis. The data training process will produce the best hyperplane used as a reference  to determine which sentiment class is much appropriate for a sentence. The test is done by dividing the dataset into the test data as much as 20% and the training data as much as 80% so it can be done the analysis process up to 5 times iteration with different data arrangement. The test results show the calculation of Accuracy, Precision, Recall, and F-Measure generated by system is equal to 82,08%, 83,42%, 81,16%, and 81,82%.
Design of Optimal Scalar Quantizer for Sequential Coding of Correlated Sources

This paper addresses the design of a sequential scalar quantizer (SSQ) for finite-alphabet correlated sources in the fixed-rate (FR) and entropy-constrained (EC) cases. The optimization problem is formulated as the minimization of a weighted sum of distortions and rates. The proposed solution is globally optimal for the class of SSQs with convex cells and is based on solving the minimum-weight path (MWP) problem in the EC case, respectively, a length-constrained MWP problem in the FR case, in a series of weighted directed acyclic graphs. The asymptotic time complexity is O(K <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> K <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ), where K <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> and K <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> are the respective sizes of the alphabets of the two sources. Additionally, it is proved that, by applying the proposed algorithms to discretizations of correlated sources with continuous joint probability density function, the performance approaches that of the optimal EC-SSQ, respectively, FR-SSQ, with convex cells for the original sources as the accuracy of the discretization increases. Extensive experiments performed with correlated Gaussian sources validate the effectiveness in practice of the proposed approach in approximating the optimal SSQ for the case of continuous-alphabet sources.
Baran

The MapReduce method is widely used for big data solutions. This method solves big data problems on distributed hardware platforms. However, MapReduce architectures are inefficient. Data locality, network congestion, and low hardware performance are the main issues. In this chapter, the authors introduce a method that solves these problems. Baran is a method that, if an algorithm can satisfy its conditions, can dramatically improve performance and solve the data locality problem and consequences such as network congestion and low hardware performance. The authors apply this method to previous works on data warehouse, graph, and data mining problems. The results show that applying Baran to an algorithm can solve it on the MapReduce architecture properly.
Fast iterative algorithms for birefringent filter design

Fast iterative algorithms for designing birefringent filters with any specified spectral response are proposed. From the Jones formalism, we derive two polynomials representing the transmitted and rejected response of the filter, respectively. Once the coefficients of the filters are obtained, the orientation angle of each birefringent section and the phase shift introduced by each compensator can be determined by an iterative algorithm that gives an efficient solution to the birefringent filter design problem. Afterward, some design examples are presented to demonstrate the effectiveness of the proposed approach. In comparison with results reported in the literature, this approach provides the best performance in terms of accuracy and time complexity.
PEMEROLEHAN BAHASA PERTAMA TERHADAP ANAK USIA 2 SAMPAI 4 TAHUN MENURUT TATARAN MORFOLOGI DAN SINTAKSIS

The study aims to find out about the development of language in morphological and syntactic aspects. Research subjects were children aged 2 years 8 months who were in the research environment. The research method is descriptive because the study contains the description in the language pronunciation stages in children. The data collection techniques using recording and recording words spoken child. General conclusions on language acquired children aged 2 to 4 years can be developed with morphological and syntactic stages. Researchers found the process of obtaining the discussion among others is the first at the age of 2 to 4 years of morphology, the emergence of a more free form of free form. Both acquisition of syntax, the child is able to say a few words that can be a word. Third at the age of 2 to 4 years of morphological acquisition and the syntax of the child begins perfectly in the vowel sound and also accompanied by the sound of consonants.
Semantic Extension for the Linked Data Based on Semantically Enhanced Annotation and Reasoning

Linked Data, a new form of knowledge representation and publishing described by RDF, can provide more precise and comprehensible semantic structures. However, the current RDF Schema (RDFS) and SPARQL-based query strategy cannot fully express the semantics of RDF since they cannot unleash the implicit semantics between linked entities, so they cannot unleash the potential of Linked Data. To fill this gap, this chapter first defines a new semantic annotating and reasoning method which can extend more implicit semantics from different properties and proposes a novel general Semantically-Extended Scheme for Linked Data Sources to realize the semantic extension over the target Linked Data source. Moreover, in order to effectively return more information in the process of semantic data retrieval, we then design a new querying model which extends the SPARQL pattern. Lastly, experimental results show that our proposal has advantages over the initial Linked Data source and can return more valid results than some of the most representative similarity search methods.
Digital fuzzy control based on ANFIS for boost converter: Digital redesign

This study proposes the digital fuzzy control based on Adaptive-Network-based Fuzzy Inference System (ANFIS) to overcome the tracking problem of a DC-AC and DC-DC boost converter and to implement on a digital computer. The proposed method eliminates the trial and error commonly associated with fuzz y systems. In the proposed design scheme, we take the existing continuous controller as training data of the ANFIS such that the proposed digital fuzzy control can replace original continuous one and can keep the original system performance. It is a sense of digital redesign that this paper proposes a new digital control such that the state trajectories of the sampled-data closed loop systems close to the continuous-time one. An existing boost converter circuit has demonstrated the feasibility of the proposed methodology.
Information Distribution in Autonomic Networking

This document proposes a solution for information distribution inautonomic networks. Information distribution is categorized into twodifferent modes: 1) instantaneous distribution; 2) publication forretrieval. In the former case, the information is sent, propagates andis disposed of after reception. In the latter case, information needsto be stored in the network. The capabilities to distributeinformation are basic and fundamental needs for an autonomous network(cf. ANI [I-D.ietf-anima-reference- model]). This document describestypical use cases of information distribution in ANI and requirementsto ANI, such that rich information distribution can be nativelysupported. The document proposes extensions to the autonomic nodes andsuggests an implementation based on GRASP extensions as a protocol onthe wire.
SAW-Q: a dynamic composition approach of REST services based on queue model

Service composition is one of the principles of service-oriented architecture; it enables reuse and allows developers to combine existing services in order to create new services that in turn can be part of another composition. Dynamic composition requires that service components are chosen from a set of services with equal or similar functionality at runtime and possibly automatically. The adoption of the REST services in the industry has led to a growing number of services of this type, many with similar functionality. The existing dynamic composition techniques are method-oriented whereas REST is resource-oriented and consider only traditional (WSDL/SOAP) services. We propose SAW-Q, an extension of simple additive weighting (SAW), as a novel dynamic composition technique that follows the principles of the REST style. Additionally, SAW-Q models quality attributes as a function of the actual service demand instead of the traditional constant values. Our model is much more accurate when compared to real implementation, positively improving the quality of dynamic service compositions.
On aggregate and comparison functions for Motus/Lingo playing

Motus (Lingo) is a TV show based on a word game where each player has to guess a word, of which she knows only the length and the first letter. To do this, the player makes different proposals and she is given some hints based on the positions of the letters. We first show in this article that ther e is no strategy to find all the words with the available number of proposals. Next, we study different strategies based on aggregate functions and tie-breaks. All these strategies were tested on all the 5 to 10 letter French words, which finally leads us to discuss the respective performance of these strategies. We show that the criteria of average number of tries used, worst case and number of fails are conflicting.
A Cross-domain and Cross-language Knowledge-based Representation of Text and its Meaning

This research has been carried out in the framework of the European Commission project WIQ-EI IR-SES (no. 269180), and the national projects DIANA-APPLICATIONS - Finding Hidden Knowledge in Texts: Applications (TIN2012-38603-C02-01), Destilado de opiniones desde contenidos generados por usuarios (TIN2011-14726-E), and SomEMBED: SOcial Media language understanding - EMBEDing contexts (TIN2015-71147-C2-1-P).
Financing sources and social development: an empirical analysis

Purpose The purpose of this paper is to analyse, from an empirical point of view, the importance of each of the main sources of funding in developing countries (foreign direct investment, official development assistance, external debt and remittances) in achieving sustainable, social and inclusive development. Design/methodology/approach The methodology followed to achieve this purpose is the construction of three econometric models. The general model incorporates as a dependent variable the Human Development Index (HDI) and, as explanatory variables, the four sources of funding indicated above, as well as three exogenous variables (human capital, corruption and natural resources). This model is complemented by two extensions that aim to analyse the behaviour of explanatory variables in reducing inequalities and improving each of the HDI components. Findings The results of the estimations of the econometric models show that foreign direct investment and remittances are the sources of funding with the greatest impact on achieving development. Moreover, official development assistance while not making a positive contribution to the achievement of development as a whole, could be adequate to reduce inequalities. Originality/value The added value of this paper consists in carrying out a joint analysis of these four sources of funding because previous researches focussed the attention on some of them, drawing partial conclusions. The conclusion of this study is that the four sources of funding analysed can be considered complementary to promote sustainable and inclusive development, although foreign direct investment has a much more important role.
Base for algebraic cryptanalysis based on combined representation of S‐box

This study reveals an organised algebraic view on the Advanced Encryption Standard (AES), and in particular the S-box. A clear visualisation of algebraic expressions is granted for both the cipher part and the key schedule part of AES. Additionally, by introducing the combined representation of the S-box, alternative methods can be constructed to serve algebraic cryptanalysis on AES. The process to obtain a combined representation of the S-box, as a combination of four bits, the input value's multiplicative inverse and bytes in hexadecimal notion, may be of high importance for other proposed ciphers too built with layers of S-boxes.
Force from Motion: Decoding Control Force of Activity in a First-Person Video

A first-person video delivers what the camera wearer (actor) experiences through physical interactions with surroundings. In this paper, we focus on a problem of Force from Motion-estimating the active force and torque exerted by the actor to drive her/his activity-from a first-person video. We use two physical cues inherited in the first-person video. (1) Ego-motion: the camera motion is generated by a resultant of force interactions, which allows us to understand the effect of the active force using Newtonian mechanics. (2) Visual semantics: the first-person visual scene is deployed to afford the actor's activity, which is indicative of the physical context of the activity. We estimate the active force and torque using a dynamical system that can describe the transition (dynamics) of the actor's physical state (position, orientation, and linear/angular momentum) where the latent physical state is indirectly observed by the first-person video. We approximate the physical state with the 3D camera trajectory that is reconstructed up to scale and orientation. The absolute scale factor and gravitation field are learned from the ego-motion and visual semantics of the first-person video. Inspired by an optimal control theory, we solve the dynamical system by minimizing reprojection error. Our method shows quantitatively equivalent reconstruction comparing to IMU measurements in terms of gravity and scale recovery and outperforms the methods based on 2D optical flow for an active action recognition task. We apply our method to first-person videos of mountain biking, urban bike racing, skiing, speed-flying with parachute, and wing-suit flying where inertial measurements are not accessible.
Racism and Social Media: A Study in Indian Context

Racism is a kind of hatred behaviour, exhibited in written, verbal or physical form against the ethnicity or physical appearance of a group or an individual. Around the world, problematic behavioural incidents occur and in India, media often interpret it as towards people of colour or blacks. There was a lot of discussion about these incidents both online and offline, some groups consider that India is not free from racism and others view it is of misinformation processing. Therefore, there is a requirement of a system to evaluate and determine the possible scenarios towards racism in India. In this regard, using four different sets of keywords we created Twitter datasets. The data collected from social media are analysed to identify the polarity of content and the amount of racism using the software developed in R programming language. Contents are categorised in different polarities such as racist, non-racist and neutral.
Pathways of Divergence, Convergence, and Adaptation to Persistent Learning

This chapter proposes to examine how rapid change occurring in all sectors of our society as they relate to education paradigms must be addressed to embrace new avenues of learning and new charters for educational change.