Reviewerly/exHarmony huggingface dataset:
Embedded Representation of Relation Words with Visual Supervision

Word representation learned from the analysis of natural language does not usually reflect the true semantics of words. The paper proposes a new method, named Visually Supervised Word2Vec (VS-Word2Vec) model to achieve the representation of the relation words that are important in knowledge related tasks. Our method first computes the visual feature vector of relation words based on deep networks, and then achieve the visual similarity matrix for all relation words, which we think reflects their true semantics. VS-Word2Vec model then combines the visual similarity and the CBOW and builds an optimization problem to jointly learn the word vector representation. Therefore, VS-Word2Vec fuses the visual modality and natural language together. Experiments implemented over the public datasets demonstrate that VS-Word2Vec model really changes the distribution of word representation and achieves more effective results in describing their true semantics than CBOW model.
Quantitative Analyses on Effects from Constraints in Air-Writing

Very few existing works about inertial sensor based air-writing focused on writing constraints' effects on recognition performance. We proposed a LSTM-based system and made several quantitative analyses under different constraints settings against CHMM, DTW-AP and CNN. The proposed system shows its advantages in accuracy, real-time performance and flexibility.
A Novel Machine Translation Method based on Stochastic Finite Automata Model for Spoken English

Stochastic finite automata have been applied to a variety of fields, machine trans-lation is one of them. It can learn from data and build model automatically from training sets. Stochastic finite automata are well adapted for the constrained inte-gration of pairs of sentences for language processing. In this paper, a novel ma-chine translation method based on stochastic finite automata is proposed. The method formalized rational grammars by using stochastic finite automata. Through given pairs of source and target utterances, our proposed method will produce a series of conventional rules from which a stochastic rational grammar would be inferred, and the grammar is finally converted into a finite state automa-ton. The efficacy and accuracy of our proposed method is evaluated by a large number of English-Chinese and Chinese-English machine translation experi-ments.
Deformable Convolutional Networks Tracker

Object tracking is a fundamental topic in computer vision. It is an interdisciplinary scientific filed involving machine learning, pattern recognition etc, and has a wide applicability. Although, convolutional neural networks (CNNs) have achieved significant success for visual recognition tasks. Deformation and scale variation of targets are huge challenges in object tracking. They cannot address these challenges for relying on massive amounts of data to build deep models. They are inherently limited to model geometric transformations due to the fixed geometry in the building blocks. In short, CNNs are inherently limited to model large and unknown transformation. In this paper, we introduced a deformable convolution module to construct a novel deformable convolutional networks tracker(DCT).The tracker illustrates outstanding performance in the Visual Tracker Benchmark (OTB)100[7] benchmark with scale variation and deformation attributes.
Public Libraries in Multicultural Environment: Main Directions of Activities

The article highlights the directions of library activities in multicultural environment. The author presents definition of multicultural environment and notes that public libraries become cultural and educational centres. The article considers the main tasks and directions of work of libraries in the multicultural environment. Among the tasks facing the libraries are the following: creation of conditions for intercultural and interconfessional dialogue, education of tolerant thinking among the younger generation, socio-cultural mediation between migrants and the local community, the promotion of social cohesion of Russian society. The main goal of the activities of libraries in multicultural environment is their involvement in the implementation of the state cultural and national policy. Therefore, the libraries consider their main task in preservation and development of ethnic cultures and languages of all peoples living in our country. The most common areas of work of libraries are organization of ethno-cultural mass events, development of multilingual collections, creation of multilingual electronic resources, cooperation with local authorities and government agencies, educational institutions, national and cultural associations and various public organizations, assistance in the process of adaptation of migrants and refugees to the conditions of new social environment, creation of language educational centres in libraries for all members of the local community, participation in sociological research, methodological support of library activities in multicultural environment. Annual analytical reports of public libraries over the last three years demonstrate the significant increase of their activities in multicultural environment. The article presents the results of survey of the Gasprinsky Republican Crimean Tatar Library on the topic: “Do you know the traditions of your people?” The author concludes that the activities of library in multicultural environment contributes to its development as a cultural and educational centre. Cooperation with local authorities, educational institutions, national cultural associations, public organizations testifies to the importance of libraries and their recognition as active participants in the process of social cohesion of Russian society.
Sentiment Analysis of Regional Head Candidate’s Electability from the National Mass Media Perspective Using the Text Mining Algorithm

Mass media plays an important role in leading public opinion, including in the election of regional head candidates.The tendency of mass media coverage can be used as a parameter to measure the strength of each regional head candidate.To analyze the tendency of media opinion, sentiment analysis is needed.In this study, text mining techniques were used to analyze opinion sentiments of a regional head election in East Java from the national media perspective.The researcher used the Support Vector Machine algorithm to build a sentiment analysis model.News documents about candidates for the regional head in East Java 2018 were taken from national mass media samples, namely JPNN, Kompas, Detik and Republika.From the test results, the model built on Khoffifah's data as a candidate for regional head number one has a value of precision, recall and AUC of 0.927, 0.931 and 0.902, respectively.Furthermore, the model built on Gus Ipul's data as a candidate for regional head number two has a value of precision, recall, and AUC of 0.940, 0.948 and 0.890 respectively.The models built on both data shows good performance with accurate estimation results.Based on the data obtained, the national media tends to have alignments to the regional head candidate number two namely Gus Ipul.
Handwritten capital letter recognition based on OpenCV

Handwriting capitalization recognition is a function of distinguishing handwritten capital letters by means of machine or computer intelligence, which is classified into the field of optical character recognition. Given that capital letters are widely used around the world, identification and analysis are often used as the main components of some control systems. Therefore, the research on handwritten capital letter recognition is also very practical and has important practical significance. The key part of the research contained in this paper is the image preprocessing and the optimal selection of feature vectors, and finally completes the design of handwritten digit recognition system. In this paper, the Fourier and Bayesian commonly used are compared, and eventually the Fourier transform feature is applied to the system classification identification. After completing the test on the relevant experimental data, the results show that the handwritten capital recognition system established in this paper has a high recognition accuracy for handwritten capital letters after repeated training.
Low-latency semi-systolic architecture for multiplication over finite fields

In this letter, we propose a low-latency semi-systolic architecture for multiplication based on the shifted polynomial basis over finite fields. The proposed multiplier saves at least 49.9% time complexity and 23.7% area-time complexity as compared to the related multipliers. The proposed multiplier can be used as a core circuit for various applications.
Testing of MAES analyzers with BLPP-2000 and BLPP-4000 photodetector linear arrays in a “GRAND-POTOK” spectral system

For the development of “Grand-Potok” spectral systems and rapid high-sensitivity scintillation atomic emission spectrometry, the “VMK-Optoelektronika” company created a new BLPP-2000 photodetector linear array. Testing of the array as part of “Grand-Potok” spectral system had shown its advantages over a BLPP-369М1 array in recording scintillations of the gold Au 267.595 nm analytical spectral line. Further studies of the BLPP-2000 detector revealed the need to increase the spectral resolution of the system. For this, a new BLPP-4000 photodetector linear array has been developed. It was expected that its use would improve the resolution of the Grand spectrometer over the entire wavelength range, but a reduction in the sensitivity of the spectrometer could be possible. The objectives of this study were to experimentally compare the resolution and signal-to-noise ratio of the “Grand-Potok” spectral system using BLPP-2000, BLPP-4000, and BLPP-369М1 photodetector linear arrays and contrast the obtained results with the characteristics of the higher-resolution Grand-1500 spectrometer with BLPP-2000, which had shown good performance in determination of noble metals in geological samples with complex matrix. The data on the intensities and widths of the spectral lines were obtained from the spectra of the standard samples of various compositions and used to compare the signal-to-noise ratio and spectral resolution of the systems. The study showed that the use of the new MAES analyzers based on BLPP-4000 linear photodetector arrays in the Grand spectrometer increased the resolution of the instrument by a factor of two, while the signal-to-noise ratio of the instrument decreased by a factor of 4-6, leading to the deterioration of the detection limits in the scintillation arc atomic-emission spectrometry. Nevertheless, Grand spectrometers based on BLPP-4000 could be used instead of higher-resolution Grand-1500 spectrometers without deterioration of the detection limits as its aperture is 5–20 times higher. In addition, the signal-to-noise ratio and the resolution in Grand spectrometers with BLPP-369M1 detector arrays used in analytical laboratories could be increased by replacing the detectors with BLPP-4000 arrays. Keywords: Grand-Potok spectral system, MAES high-speed analyzer, spectral resolution, geological samples, scintillation atomic emission spectrometry (Russian) DOI: http://dx.doi.org/10.15826/analitika.2019.23.1.005 A.A. Dzyuba 1,2 , V.A. Labusov 1,2,3 , and S.A. Babin 1,2 1 Institute of Automation and Electrometry, Siberian Branch, Russian Academy of Sciences, pr. Akademika Koptyuga, 1, Novosibirsk, 630090, Russian Federation 2 VMK-Optoelektronika, pr. Akademika Koptyuga, 1, Novosibirsk, 630090, Russian Federation 3 Novosibirsk State Technical University, pr. K. Marksa, 20, Novosibirsk, 630073, Russian Federation
Spatial Data Modeling on GIS for Classification of Measles-prone Region Using Multiple Attribute Decision Making

Indonesia is a country that has a tropical climate, so that many typical tropical climate diseases emerge.This disease is caused by viruses and parasites that breed during the dry season or the rainy season.One typical tropical disease is measles.This paper discusses the geographical information system (GIS) technology by analyzing spatial data modeling to determine the classification of measles-prone areas based on immunization status coverage using the Simple Additive Weighting (SAW) and Weight Product Model (WPM) method.Some parameters are used consist of immunization status data for multiple attribute decision making (MADM), diseases preventable by immunization (PD3I), epidemic and nutritional status of infants.The SAW and WPM method in modeling spatial data analysis processes data according to the parameters to determine the scale in comparing all alternative data on the scope of classification of immunization status areas, namely: good, average, fair and poor.The test results with the Cohen's Kappa Method Consistency Test (MCT) is obtained an average coefficient of 0.41 for consistent measurements for the chosen method.It can be concluded that the two measurements using the SAW and WPM methods have a moderate for the strength of agreement category, for using in spatial data modeling on the GIS for classification of measles prone regions using MADM.
Color information correction of images using lightweight camera systems

The paper is about the idea of a method, with which lightweight camera systems can be extended to get more accurate color meta-information for still images and for frames gained from streamed videos.This meta-information can give more information about the lighting conditions and about the colors of objects in the picture.By having more accurate colors in the picture, many typical in situ and post process visual tasks can be done with greater reliability.This extension could enhance color identification of images taken by low budget camera systems to measurement devices.
The Communicative Approach in English Language Teaching

Today, communities are increasingly facing rapid and profound changes and tensions that affect the social, economic, and political aspects of life. The role of education has also become questionable in the millennial era. A matter of fact, 21st century education requires a gradual shift in curriculum construction focusing on the transferable competencies that learners need to develop in instructional settings. In today’s knowledge–based, types of skills and competencies that students need to gain are different from in the past. Emphasizing the communicative competence is one of the most influential developments in language education. The implementation of communicative activities in EFL/ESL classroom prepares learners to use English in the world beyond based on their own needs, interests and opportunities.
Teaching Analytical Textual Activity of Children for Skills Formation in Creating Their Own Texts

The article, based on data from a survey conducted among primary school teachers and language teachers, analyzes the problem of ensuring continuity in teaching analytical textual activity of schoolchildren. Mastering the skills of analytical work with text by schoolchildren is considered as the most important condition for their ability to create their own texts. The author suggests approaches to the content of text-based learning, characterizes the stages of organizing the work of a teacher in developing the skills of independent creation of written statements by younger&#x0D; schoolchildren.
Predictive value of short-term forecasts of DNI for solar energy systems operation

Solar power forecasting plays a critical role in power-system management, scheduling, and dispatch operations. Accurate forecasts of direct normal irradiance (DNI) are essential for an optimized operation strategy of concentrating solar thermal (CST) systems, particularly during partly cloudy days, due to solar intermittency. In this work, short-term forecasts from the radiative scheme McRad (Cycle 41R2) included in the Integrated Forecasting System (IFS), the global numerical weather prediction model of the European Centre for Medium-Range Weather Forecasts (ECMWF), together with in-situ ground-based measurements, are used in a simulated linear focus parabolic-trough power system through the System Advisor Model (SAM). Results are part of a preliminary analysis concerning the value of DNI predictions from the IFS for operation improvement of a CST system with similar configurations as the Andasol 3 CST power plant. For a 365-day period, the present results show high correlations between predictions of energy to grid based on measurements and IFS forecasts mainly for daily values (≈0.94), while lower correlations are obtained for hourly values (≈0.88), due to cloud representation of the IFS during overcast periods, leading to small deviations with respect to those from measurements. Moreover, to measure the forecasting skill of the IFS, daily and hourly skill scores based on local measurements and a persistence model are obtained (≈0.66 and ≈0.51, respectively), demonstrating that the IFS has a good overall performance. These aspects show the value that forecasted DNI has in the operation management of CST power systems, and, consequently, in the electricity market.
TRENDS IN THE M-LEARNING SUBJECT AREA OVER A 15-YEAR PERIOD (2002-2017) USING SCOPUS

The current social dynamics perceive education as an impeller of social and economic change. However, there are problems of coverage, relevance and methodology in the educational process, mainly in Higher Education Institutions (HEIs). Recently, tools have emerged that adopt and appropriate ICTS in learning processes, such as mobile learning, which seeks to meet the requirements of mobility, accessibility and interactivity that traditional teaching mechanisms have not covered satisfactorily. Based on the necessity to identify the factors that drive the adoption of mobile learning by different HEIs, this research identifies the factors that encourage the adoption of mobile learning in the institutions. For this, results of an exercise of technological surveillance in indexed database (Scopus) were analyzed by means of scientometric indicators. Some of the most significant factors detected are: preparation of the professor, perceptions and attitudes of students, technological culture, and technological environment that leverages new learning models. Keywords: bibliometric analysis, high education, mobile learning, research trends.
XY, MS, and First-Order Ambisonics

This chapter describes first-order Ambisonic technologies starting from classical coincident audio recording and playback principles from the 1930s until the invention of first-order Ambisonics in the 1970s. Coincident recording is based on arrangements of directional microphones at the smallest-possible spacings in between. Hereby incident sound approximately arrives with equal delay at all microphones. Intensity-based coincident stereophonic recording such as XY and MS typically yields stable directional playback on a stereophonic loudspeaker pair. While the stereo width is adjustable by MS processing, the directional mapping of first-order Ambisonics is a bit more rigid: the omnidirectional and figure-of-eight recording pickup patterns are reproduced unaltered by equivalent patterns in playback. In perfect appreciation of the benefits of coincident first-order Ambisonic recording technologies in VR and field recording, the chapter gives practical examples for encoding, headphone- and loudspeaker-based decoding. It concludes with a desire for a higher-order Ambisonics format to get a larger sweet area and accommodate first-order resolution-enhancement algorithms, the embedding of alternative, channel-based recordings, etc.
Intelligent System Stability using Type-2 Fuzzy Controller

To avoid mathematical complexity, Interval T2FSs (IT2FSs) have been pertained in majority of the fields.Type-2 fuzzy sets (T2FSs) handle a greater modeling and uncertainties that exist in the real world applications especially in control systems.One of the important components that influence the fuzzy controller is the triangular norm, which is the aggregation operator.For getting the stability of a control system T-norm operator can be preferred.Gaussian Interval Type-2 Membership Function (GIT2MF) has been used in this research.Mathematical properties of aggregation operator also proved using Gaussian Interval Type-2 Weighted Arithmetic (GIT2WA) operator.The aim of this research is analyzing the stability of an inverted pendulum using Interval Type-2 Fuzzy Logic Controller (IT2FLC) and the results are compared with traditional Proportional Integrated Derivative (PID) controller.It is observed that IT2FL controller gives better stability under imprecise condition.
Wargaming the cyber resilience of structurally and technologically different networks

&lt;i&gt;Based on a review of different analytical frameworks, it is suggested to run a table top cyber wargame when trying to analyse the effects of closed national networks being imposed in the near future. The scope of the wargame is to extract results to show how the resilience of an open national network differs from a closed national network. It is self-evident that the formation process of resilience is different between the diverse systems. The proposed wargame is a two-sided cyber table top wargame. The wargame is based on at least two blue teams, at least one red team and a control team (namely a white team). One blue team is located in the closed national networks and its system relies on closed national network infrastructure. The other blue team operates its system within open network society. By designing, constructing and executing the proposed cyber wargame we argue it is possible to find these diff erences and similarities as well. Current research improves cyber situation awareness and proposes a direction to be followed when trying to understand the changing circumstances of the cyber space. It also suggests how the research resources could be directed when trying to improve the situation awareness of the closing process.&lt;/i&gt;
Analysis of the Consumption of Household Appliances for the Detection of Anomalies in the Behaviour of Older People

Nowadays, modern societies are facing the important problem of ageing of their population. On many occasions, older people must leave their homes to be cared for by their relatives or to enter specialised centres for the elderly. On the other hand, something similar happens with disabled people who need the support of other people for their daily activity. This phenomenon brings with it important social and economic consequences. In the activities of the daily life of the elderly it is necessary to have the monitoring of different aspects of their physical activity, such as the detection of critical situations (such as falls) or dangerous situations (such as flooding or gas leaks). The aim of this paper is to analyse the consumption of the different household appliances in order to model a normal behaviour within the daily activities of a house. By means of the consumption of the electrical appliances the aim is to detect anomalous behaviours that induce the appearance of possible problems due to the change in the consumption pattern.
Reversible Watermarking Based on Adaptive Prediction Error Expansion

In traditional prediction error expansion (PEE) based reversible watermarking (RW),Li, Qi the watermark bits are embedded into the two peaks of the global prediction error histogram.Yan, Bin This scheme ignores some bins in local histogram. To improve the utilization of prediction error, a method based on locally adaptive PEE is proposed. The original image is divided into two regions. In the first region, the image is divided into several blocks and the local prediction error histogram of each block is obtained after checkerboard prediction. Then, the two peaks in the local histogram of each block are used for watermark embedding.Li, Hui In the second region, the least significant bit (LSB) replacement is used to embed the auxiliary information and compressed positioning map.Pan, Jeng-Shyang It is verified that, under the same image distortion, this method provides higher embedding capacity.