Reviewerly/exHarmony huggingface dataset:
Large-Scale Font Identification from Document Images

Identification of font in document images has many applications in modern character recognition systems. Visual font recognition task is a challenging yet popular problem in pattern recognition as many designers try to identify a font for their designs from available images. However, the identification problem is particularly difficult because of the large number of probable fonts that can be used for a particular design. Moreover, there can be multiple fonts in a database which contain similar visual features; therefore, it is difficult to identify the exact font class. In this paper, we explore the font recognition problem for a database of 10,000 fonts using convolutional neural network (CNN) architecture. To the best of our knowledge, no previous approach has explored the font identification problem with these many classes. We performed extensive experiments to quantify our results for synthetic document images as well as natural document images. We have achieved 63.45% top-1 accuracy and 70.76% top-3 accuracy in character level, in addition we also observed 57.18% top-1 accuracy and 62.11% top-3 accuracy in word level even in the presence of rotation and scaling, which demonstrate the effectiveness of the proposed method.
Balancing Cost and Benefit with Tied-Multi Transformers

We propose and evaluate a novel procedure for training multiple Transformers with tied parameters which compresses multiple models into one enabling the dynamic choice of the number of encoder and decoder layers during decoding. In sequence-to-sequence modeling, typically, the output of the last layer of the N-layer encoder is fed to the M-layer decoder, and the output of the last decoder layer is used to compute loss. Instead, our method computes a single loss consisting of NxM losses, where each loss is computed from the output of one of the M decoder layers connected to one of the N encoder layers. Such a model subsumes NxM models with different number of encoder and decoder layers, and can be used for decoding with fewer than the maximum number of encoder and decoder layers. We then propose a mechanism to choose a priori the number of encoder and decoder layers for faster decoding, and also explore recurrent stacking of layers and knowledge distillation for model compression. We present a cost-benefit analysis of applying the proposed approaches for neural machine translation and show that they reduce decoding costs while preserving translation quality.
Improving the Ability in Academic Writing of Student’s English Education Department Through Self Directed E-Learning

The aim of this study is to collaborate on the Self Directed Learning model through the use of moodle technology media in which the learning model can enhance the quality and effectiveness of student learning independently so that students can use technology devices in a correct and proper way. This study utilizes a quantitative approach to the design of OneGroup Pretest-Posttest Design with a pre-experimental research technique. The researcher used cluster samples in the process of collecting samples. The data collected from this study was further analyzed and conclusions were reached using the Prerequisite Test of Analysis and the Paired T-Test Test for hypotheses. The findings of the study with the descriptive statistical analysis showed that the pre-test average value was lower than the post-test average, in description there were differences in the average learning outcomes between the pre-test and post-test. Based on the results of the Paired T-Test statistics, Ha is accepted as having t-count value (13,691) greater than T-table (2,131). The results of the pre-testand post-testing are differenced on average so there is a significant effect of self-directed learning using moodle to improve student learning achievement in academic writing skills. The average value of the experimental class was included in a sufficient category, according to calculated results from Gain-scores. It means learning through self-directed e-learning is quite effective in order to improve students ' academic writing abilities. Self-directed learning through Moodle and learning resources are quite effective and efficient in improving student learning and can encourage students to learn on-campus as well as at home, train students to be ready for learning, allow students to participate actively during face to face teaching and learning activities so that students can enhance learning outcomes.
FR-Train: A Mutual Information-Based Approach to Fair and Robust Training

Trustworthy AI is a critical issue in machine learning where, in addition to training a model that is accurate, one must consider both fair and robust training in the presence of data bias and poisoning. However, the existing model fairness techniques mistakenly view poisoned data as an additional bias to be fixed, resulting in severe performance degradation. To address this problem, we propose FR-Train, which holistically performs fair and robust model training. We provide a mutual information-based interpretation of an existing adversarial training-based fairness-only method, and apply this idea to architect an additional discriminator that can identify poisoned data using a clean validation set and reduce its influence. In our experiments, FR-Train shows almost no decrease in fairness and accuracy in the presence of data poisoning by both mitigating the bias and defending against poisoning. We also demonstrate how to construct clean validation sets using crowdsourcing, and release new benchmark datasets.
Mineralogy, geochemistry and genesis of Mollaahmad Pass bentonite deposit, Naein, Isfahan Province, Iran

The Mollaahmad pass bentonite deposit occurs within an area of about 10 km 2 with Oligo-Miocene age (Isfahan-Iran).This bentonite deposit with two general lenticular and layered forms has extended in the tuff, conglomerates and sandstones (including volcanic fragments).XRD studies are demonstrating that montmorillonite, montmorillonite-illite, nontronite, albite, anorthite and quartz are major and clinoptilolite, heulandite, sanidine, orthoclase, calcite, microcline and actinolite are minor constituent minerals in studied bentonite deposit.Moreover, mineral chemistry indicates that Mollaahmad pass bentonite deposit has intermediate to di-octahedral smectites, so it can be classified as Wyoming bentonite type.Based on geochemical studies, transform process of parent rocks into bentonite was accompanied by enrichment of Cr, Sb, Se and REEs, and also enrichment or depletion of other major and trace elements.More geochemical studies have shown positive to negative Eu and Ce anomalies.This can be related to change in rate of oxidation and alteration intensity in altered system.In addition, study of rare earth elements indicates high differentiation of LREEs from HREEs that related to egress of HREEs from environment in form of carbonate complexes.It seems that six factors including discrepancy in rate of alteration intensity of the source materials, incorporation in crystal lattice, complex-forming ligands, surface adsorption and difference in stability of primary minerals are able to control mobilization, differentiation and distribution of elements in studied bentonites.This bentonite deposits has formed in margin of lacustrine environment.
The Dignity of Indonesian Language in Information Technology

The attitude of language is illustrated in the use of language in public spaces. The use of Indonesian language is required in submission of information to the public. Submission of information using the Indonesian language in information technology is a dignity forms of Indonesian language. This study is aimed to describe the use of Indonesian language in information technology. The research method used is descriptive method with a qualitative approach. The source of research data is the website of cluster one tertiary institutions in Indonesia. The data used are menu and submenu which is on the main website in the college website. The results showed that there are still menu and submenu that use foreign languages/terms. Therefore, the dignity of Indonesian language in information technology has not yet been reached maximally. The solution to these problems is the making of policies related to the use of Indonesian language in targeted information technology.
The Encounter with the Real: What Can Complicite’s Theatre Performance &lt;i&gt;The Encounter&lt;/i&gt; Teach Us about the Future of VR Narratives?

The most recent emergence of relatively inexpensive VR technologies has received an enthusiastic attention from the entertainment industry, visual and multimedia artists, and academia. The world of computer gaming is thriving with the new VR platforms and the number of VR games is multiplying exponentially. Similarly, quite a few research projects have been funded in order to explore the potential of the immersive technologies in disciplines as wide and different as health care, nuclear decommissioning and nonfiction immersive documentaries. Similar to the advent of its various digital predecessors at the end of the last century, the encounter with this highly interactive and immersive technology has stirred up the discussion about the nature of the medium and its relation to its predecessors. A particular interest seems to be placed in the narrative possibilities of the medium. Parallel to this shared enthusiasm, however, one can also easily sense equally shared disappointment with the current state of affairs when it comes to the artistic climaxes delivered in the VR medium. The voices from both the entertainment industry and creative academia are clearly dissatisfied with the rather rudimentary narratives presented in the most of VR games, as well as more artistically ambitious immersive experiences. The medium which claims the highest technological level of immersion still struggles to keep its audience truly immersed in its fictional realities. In this article I argue that the answer to this challenge might come outside of the world of immersive interactive gaming, and that the key for understanding the nature of immersion might come from the realm of theatre. My study of Complicite’s performance The Encounter demonstrates that this work manages to achieve the level of immersion unconceivable for any existing VR experience. The key elements for this success are the profoundly relevant subject matter (the narrative based on Petru Popescu’s Amazon Beaming), ingenious use of binaural immersive sound, and extraordinary story-telling performance delivered by Simon McBurney. In other words, it is the combination of the performance’s intertextuality, the multimediality of its means of expression and the intense presence of its narrator/protagonist that accounts for extraordinarily immersive viewers’ experience. If the medium of VR is ever to achieve a comparable level of narrative and formal complexity, it needs to break away from the vacuum of the games-logic based interactivity and shift towards a more intertextual, multimedial and narratorial aesthetic.
Beyond Dropout: Feature Map Distortion to Regularize Deep Neural Networks

Deep neural networks often consist of a great number of trainable parameters for extracting powerful features from given datasets. On one hand, massive trainable parameters significantly enhance the performance of these deep networks. On the other hand, they bring the problem of over-fitting. To this end, dropout based methods disable some elements in the output feature maps during the training phase for reducing the co-adaptation of neurons. Although the generalization ability of the resulting models can be enhanced by these approaches, the conventional binary dropout is not the optimal solution. Therefore, we investigate the empirical Rademacher complexity related to intermediate layers of deep neural networks and propose a feature distortion method (Disout) for addressing the aforementioned problem. In the training period, randomly selected elements in the feature maps will be replaced with specific values by exploiting the generalization error bound. The superiority of the proposed feature map distortion for producing deep neural network with higher testing performance is analyzed and demonstrated on several benchmark image datasets.
Strategy of professional interaction in training professionals in the library and information sphere

Training of library professionals in the circumstances of transforming modern society is examined. The reasons for deteriorating librarian image are discussed, along the ways to preserve and prospects for the profession. The resources for library profession and libraries modernization within the context of developing library higher school based on sciences convergence, interdisciplinarity and transdisciplinarity are specified. The relevance and prospects for library profession, social and economic efficiency of library activities are examined with consideration of triad functional relations between libraries — higher professional schools — science. The transition to the new educational paradigm in the library and information sphere is examined against the background of the developing library innovative activity and the National Project “The culture” (2019–2024). The focus is also made on educating bachelors and masters in the discipline “Library and information work” (federal education standard FGOS 3++). The project activities are seen as a means of sociocultural design with the library and information instruments. The professional interaction in education is developing within the subject scope reflection contradictions between the sociocultural paradigm of the higher education and the pragmatic intellectual labor market, and between the higher school’s assessment scale and the market.
TRAINING FOR THE INNOVATIVE TEACHING AS A DETERMINANT OF THE PROFESSIONAL MOBILITY OF THE FUTURE TECHNOLOGY TEACHERS

The article deals with the professional mobility and readiness for the innovative teaching of future technology teachers as interdependent components. The purpose of the article is to study the organizational and methodological aspects of forming the professional mobility of future technology teachers in the context of preparation for innovation activities at Ukrainian Teacher Training Universities. Using the complex of theoretical and empirical research methods, the main organizational and methodical aspects of training were determined: the construction of the individual trajectory of study based on selected disciplines; the acquisition of new branches of activity; the forming of the complete conception of technological education and future innovative teaching; the introduction of innovative technologies (interactive discussions, motivational trainings, group forms of work, a problem-solving training, design and research activities, mixed learning, etc.); implementation of Information and communications technology (ICT), distance, Smart and hybrid education systems (e-learning resources, electronic educational and methodical complexes, Web services, individual and group projects based on Web quests and Blog quests); the monitoring of the readiness level for professional mobility; the strengthening of the consultative and coordinating function of teachers. The implementation of certain aspects expands the possibilities of optimizing the educational process not only at the level of formation of the readiness for professional mobility, but also at the level of the entire system of training future technology teachers to innovative teaching. It requires: creating conditions for continuous learning; the orientation of the final stages of pedagogical education to the formation of students’ academic mobility; the rapid expansion of vertical and horizontal professional mobility ranges; the forming of future technology teachers’ readiness and the ability to change the specialization, the place of work and even the profession, if necessary, or to master several specialties or training profiles at the same time.
Utilización de herramientas didácticas en el sector educativo como factor clave para la enseñanza

Education is a means to develop the capabilities of a person from different areas such as intellectual and moral. In this sense, there are two interested parties in the realization of this activity, the student and the teacher, who perform learning and teaching functions. From the teaching point of view, there are problems in the teaching process such as the lack of attention and the use of less innovative or outdated teaching methods, which negatively influences the teaching process. Thus, the teaching method becomes an important piece in the process because it directly determines the success or failure of teaching, which is why different teaching tools have been proposed to approach teaching from innovative points of view. Taking into account the above, the objective of this research was to demonstrate the usefulness of teaching tools as a key tool for teaching. In this way, the research was of a qualitative nature because non-measured data were analyzed, which were represented by words. As a result, a fictional story was obtained consisting of stories narrated by the students and the teacher assuming the point of view of the assigned role.
An Evaluation of Knowledge Graph Embeddings for Autonomous Driving Data: Experience and Practice

The autonomous driving (AD) industry is exploring the use of knowledge graphs (KGs) to manage the vast amount of heterogeneous data generated from vehicular sensors. The various types of equipped sensors include video, LIDAR and RADAR. Scene understanding is an important topic in AD which requires consideration of various aspects of a scene, such as detected objects, events, time and location. Recent work on knowledge graph embeddings (KGEs) - an approach that facilitates neuro-symbolic fusion - has shown to improve the predictive performance of machine learning models. With the expectation that neuro-symbolic fusion through KGEs will improve scene understanding, this research explores the generation and evaluation of KGEs for autonomous driving data. We also present an investigation of the relationship between the level of informational detail in a KG and the quality of its derivative embeddings. By systematically evaluating KGEs along four dimensions -- i.e. quality metrics, KG informational detail, algorithms, and datasets -- we show that (1) higher levels of informational detail in KGs lead to higher quality embeddings, (2) type and relation semantics are better captured by the semantic transitional distance-based TransE algorithm, and (3) some metrics, such as coherence measure, may not be suitable for intrinsically evaluating KGEs in this domain. Additionally, we also present an (early) investigation of the usefulness of KGEs for two use-cases in the AD domain.
Correction: Osman, M., et al. A Novel Online Approach for Drift Covariance Estimation of Odometries Used in Intelligent Vehicle Localization. Sensors 2019, 19, 5178

The authors wish to make the following corrections to this paper [...]
Game localization pitfalls: Translation and multitextuality

From the translator’s perspective multitextuality is one of the major challenges of video games localization. The translator needs to cope with texts spanning from the most standard, such as error messages, to the most creative, for example poems. Although every game is unique, it is possible to observe some commonalities with respect to textual genres and text types in video games. Various text types play diverse functions, their content is outstandingly multifarious and they include both standard and creative style and terminology. All of this leads to an assertion that they call for different translation approaches: a standard approach, a creative approach or a mixed approach.
Penentuan Solusi Numerik Pada Model Mangsa-Pemangsa Dengan Pemanenan Pada Mangsa Menggunakan Metode Runge-Kutta-Fehlberg

Predator prey model with harvesting of prey is an update of the Lotka-Volterra model.In this model there are harvest parameters as population control solving predator prey model analitically can be used to predict the population at certain time, but cannot predict in detail the number of exist populations.Therefore numerical method is proposed as alternative in solving the problem of predator prey model with harvesting of prey.This method is an alternative of the Taylor method because it does not require also has high accuracy.The result obtained that the Runge-Kutta-Fehlberg method was a meticulous method with very small error.
A novel watermarking algorithm based on characteristics model of local fragmentary images

Watermarking is a popular technology to protect the copyright of digital image from illegal infringement. Traditional watermarking algorithms cannot better resist the illegal tampering attacks, causing serious security issues. This paper aims to propose an image watermarking algorithm with ability against illegal tampering attacks. The original image should be firstly pre-processed, and its fragmentary characteristic function of local image block is used to generate watermark locations randomly. When the watermark is illegally tampered and damaged, the generated fragmentary characteristic factor can be used to re-construct the original image. Finally, the forensics of original image is realised. The experimental results show that the proposed algorithm can effectively embed a watermark into image. Besides, the original image can be restored even if the watermark is damaged. It is also robust to the typical attacks and has ability against tampering over a large area of the image.
Pembuatan Film Pendek IT In Millennial Daily Life dengan Teknik Handheld dan Continuity Cutting

Making a work through a short film is a pride to make a better experience for thefuture. With the short film can put wisdom or a lesson in it and draw the attention ofthe audience to learn to make short films, for hobbies and to work in the field ofvideography. In making a short film, it certainly requires technical requirements init. So that people who see, make and understand the contents in the short film so theycan know the techniques used. One of them is to make a short film entitled IT inMillennial Daily Life by using handheld techniques and continuity cutting in it. Theexistence of making a short film with the title IT in Millennial Daily Life, has theaim to provide information that today many people who in their daily lives are verydependent on technology. The use of technology that can be done anytime andanywhere or commonly called IT for life. In making the short film, using the twotechniques already mentioned, namely the handheld technique and continuitycutting, which aims to produce videos that do not shake or shake, and the continuitycutting technique in the video editing process produces a video transfer that is nottoo flashy. This film was made to channel a hobby in videography by taking part inthe INDOCORIS COMPETITION 2019 Short Movies category
Intuitionistic Fuzzy Sugeno Integral for Face Recognition

In this paper, an extension of the Sugeno integral using the operators of the intuitionistic fuzzy sets is presented. The proposed method consists of using the Sugeno integral as an integration method of multiple information sources using the degrees of membership and non-membership through the application of the operators of the intuitionistic fuzzy sets. The proposed method is used to combine the modules output of a modular neural network for face recognition. In this paper, the focus is on aggregation operator that use measures with intuitionistic fuzzy sets, in particular the Sugeno integral. The performance of the proposed method is compared with the traditional Sugeno integral using the Cropped Yale database.