Reviewerly/exHarmony huggingface dataset:
Second-Order Finite Automata

Abstract Traditionally, finite automata theory has been used as a framework for the representation of possibly infinite sets of strings. In this work, we introduce the notion of second-order finite automata, a formalism that combines finite automata with ordered decision diagrams, with the aim of representing possibly infinite sets of sets of strings. Our main result states that second-order finite automata can be canonized with respect to the second-order languages they represent. Using this canonization result, we show that sets of sets of strings represented by second-order finite automata are closed under the usual Boolean operations, such as union, intersection, difference and even under a suitable notion of complementation. Additionally, emptiness of intersection and inclusion are decidable. We provide two algorithmic applications for second-order automata. First, we show that several width/size minimization problems for deterministic and nondeterministic ODDs are solvable in fixed-parameter tractable time when parameterized by the width of the input ODD. In particular, our results imply FPT algorithms for corresponding width/size minimization problems for ordered binary decision diagrams (OBDDs) with a fixed variable ordering. Previously, only algorithms that take exponential time in the size of the input OBDD were known for width minimization, even for OBDDs of constant width. Second, we show that for each k and w one can count the number of distinct functions computable by ODDs of width at most w and length k in time h (|Σ|, w ) ⋅ k O (1) , for a suitable $h:\mathbb {N}\times \mathbb {N}\rightarrow \mathbb {N}$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>h</mml:mi> <mml:mo>:</mml:mo> <mml:mi>ℕ</mml:mi> <mml:mo>×</mml:mo> <mml:mi>ℕ</mml:mi> <mml:mo>→</mml:mo> <mml:mi>ℕ</mml:mi> </mml:math> . This improves exponentially on the time necessary to explicitly enumerate all such functions, which is exponential in both the width parameter w and in the length k of the ODDs.
Meeting сhallenges of modern information technologies in Ukraine

International scientific conference «History, political science, philosophy and sociology: European development direction» : conference proceedings, July 16–17, 2021. Riga, Latvia : «Baltija Publishing», 2021. 145 pages.
AN ANALYSIS ON ENGLISH LANGUAGE LEARNING STRATEGIES USED BY SECOND YEAR STUDENTS OF ENGLISH DEPARTMENT AT UNIVERSITAS MARITIM RAJA ALI HAJI TANJUNGPINANG

The purpose of this research is to describe English language learning strategies preference used by students of English Department students Universitas Maritim Raja Ali Haji. The method that is used qualitative method which the data is served by descriptive data. The research design is descriptive analysis design involves 34 students in G.02. This research used data collection techniques such as questionnaires and interview. The questionnaire was arranged based on a Likert scale. Data collection techniques in this research was the interview. This research investigated the English language learning strategies in speaking skill. The data analyzed using Microsoft Excel, Based on the analysis English language leaning strategies, the researcher found the mean 545.33, median 535.00, modus 509.00, and standard deviation 77.85. The result indicates that total score questionnaires respondents for memory strategies 636, cognitive strategies 625, compensation strategies 509, metacognitive strategies 432, affective strategies 509, and social strategies 561. From total score of questionnaires, it is said that the highest strategy used by third semester of English Department is memory strategy. From the interview the most frequently used of learning strategy is cognitive strategy 49, followed social strategy 20, metacognitive strategy 16, memory 9, compensation 6, and last is affective 3.Cognitive strategy that indicates the higher of the data from interview. Therefore, thereare 2 strategies used by the students, namely memory strategies and cognitive strategies
복문으로 나타나는 일본어 「知る」문과 한국어 「알다」문의 통사구조와 재구조화현상

This study examines the syntactic structures and restructuring phenomena of the “siru” sentences in Japanese and the corresponding “alda” sentences in Korean that appear in complex sentences. More specifically, the study shows that although the “siru” sentences in Japanese and the corresponding “alda” sentences in Korean are formed as complex sentences in the deep structure due to the semantic role of the predicates, such syntactic structures can be divided into control structures or raising structures depending on the syntactic roles they perform. In a nutshell, the “siru” sentences in Japanese that take the complementizer of “koto” and the “alda” sentences in Korean that take the complementizer of “il” are of an raising structure, whereas the “siru” sentences that take the complementizer of “no” and “alda” sentences that take the complementizer of “geot” are of a control structure. To present such syntactic structures, this study focuses on the semantic phenomenon related to how idiomatic expressions are interpreted in such syntactic structures. In addition, this study shows that restructuring is observed in these syntactic structures, by demonstrating, through the incidences of cleft sentences, the fact that both the “siru” sentence in Japanese and the “alda” sentence in Korean show in their surface structure such syntactic phenomena as are found in simple-sentence structures.
ANALYSIS OF INFORMATION TECHNOLOGY RISK MANAGEMENT IN RAJA COMPUTER BALIKPAPAN BRANCH USING ISO 31000 FRAMEWORK

Raja Computer Balikpapan Branch is a store that is engaged in selling computers, the store already uses IS/IT in supporting every business activity it carries out. The store uses the Ipost application which is used to support computer sales, record stock of goods, and can be used to record daily contests needed by the store. However, in the world of management, there is always the possibility of risks that may occur and can interfere with business activities in using the system. Thus, an analysis is needed of the IS/IT resources contained in the computer shop. Therefore, it is hoped that using ISO 31000 can help minimize every risk contained in the Ipost application. The results of this risk analysis are in the form of an analysis of possible risks, can group possible risks based on applications that can generate offers and risks that exist in Ipost, so the computer shop can treat existing risks according to the priority level of risk and be able to prevent and minimize disrupting business activities at Raja Computer store Balikpapan branch.
A case study analysis of the teacher management system of foreign institutes for the dissemination of the national language

This study aimed to analyze the current teacher management systems at foreign institutes engaged in the dissemination of their national language, and to draw overarching policy implications. The paper considers the cases of the Confucius Institute, the Goethe Institute, the Alliance Française, the British Council, and the Japan Foundation. The teacher-training programs organized by the US-based TESOL are also considered. Data were gathered between October and December 2020, and the data collection focused on teacher training, professional development, recruitment, types and roles, qualifications, remuneration, benefits, and evaluation. Data were collected by different methods, such as written interviews, real-time online interviews, document analysis, and other materials obtained through requests to the institutions. The policy implications of this analysis concern language teacher typology, the necessity of training, the systematization of training and professional development programs, and teacher welfare. The results can serve as basic reference materials for teacher management at institutes for the dissemination of the Korean language, such as the Sejong Institute.
Aerobics Image Classification Algorithm Based on Modal Symmetry Algorithm

There exist large numbers of methods/algorithms which can be used for the classification of aerobic images. While the current method is used to classify the aerobics image, it cannot effectively remove the noise in the aerobics image. The classification time is long, and there are problems of poor denoising effect and low classification efficiency. Therefore, the aerobics image classification algorithm based on the modal symmetry algorithm is proposed. The method of nonlocal mean filtering based on structural features is used to denoise the aerobics image, and the pyramid structure of the image is introduced to decompose the aerobics image. According to the denoising and decomposition results, the enhancement of aerobics image is realized by the logarithmic image processing (LIP) model and gradient sharpening method. Finally, the aerobics image after the enhancement is classified by a modal symmetry algorithm. Experimental results show that the proposed method has a good denoising effect and high classification efficiency, which shows that the algorithm has significant effectiveness and high application performance.
Maximum of exponential random variables, Hurwitz's zeta function, and the partition function

A natural problem in the context of the coupon collector’s problem is the behavior of the maximum of independent geometrically distributed random variables (with distinct parameters). This question has been addressed by Brennan et al. [British J. Math
Automatic evaluation of discursive answers short based on three linguistic dimensions / Avaliação automática de respostas discursivas curtas com base em três dimensões linguísticas

As the use of virtual environments grows, there is a need for a system of automatic evaluation of discursive answers. This paper proposes a method for automatic evaluation of discursive short answers based on a machine learning architecture. The predictive method is based on the collection of features (140) of similarity between texts in a taxonomy of three linguistic dimensions: lexical, syntactic and semantic. As a result, we obtained quadratic kappa 0.72 human x system (SxH) against 0.94 human x human (HxH) for the proof of biology and an accuracy 0.76 SxH against 0.58 HxH for the proof of geography.
Color, Caption and Emoji – Using Instagram as a Screening Tool for Depression in Teenagers and Adults

Instagram, the largest growing social network site today, has grown exponentially since its launch in 2010. Mental health challenges, particularly anxiety and major depressive disorder in those aged 16 to 30 have been associated with Instagram’s popularity. Depression is of particular interest to health care providers within the public health sector: it affects 264 million people globally; suicide is the second most common cause of death in 18 to 29-year-olds. This age group also constitutes the main demographic group of Instagram users. A narrative review was conducted on peer-reviewed articles between January 2019-July 2020 to analyze Instagram use and its association with depression, and using it as a tool to diagnose depression. PubMed, EBSCO, NCBI, NIH, and Google Scholar were used to source articles published between 2015-2020. The narrative review focused on four primary papers. The first study looked at the social comparison theory, while the second and third studies used screening questionnaires in conjunction with analyzing an individual’s Instagram content into text-based scores. The fourth study analyzed the content of photos which were posted to give insight into an individual’s status regarding depressive states. Accounting for 18 to 30 year olds’ Instagram usage into how they engaged with content can accurately screen for, and diagnose depression.
Investigating Softmax Tempering for Training Neural Machine Translation Models

Neural machine translation (NMT) models are typically trained using a softmax cross-entropy loss where the softmax distribution is compared against the gold labels. In low-resource scenarios and NMT models tend to perform poorly because the model training quickly converges to a point where the softmax distribution computed using logits approaches the gold label distribution. Although label smoothing is a well-known solution to address this issue and we further propose to divide the logits by a temperature coefficient greater than one and forcing the softmax distribution to be smoother during training. This makes it harder for the model to quickly over-fit. In our experiments on 11 language pairs in the low-resource Asian Language Treebank dataset and we observed significant improvements in translation quality. Our analysis focuses on finding the right balance of label smoothing and softmax tempering which indicates that they are orthogonal methods. Finally and a study of softmax entropies and gradients reveal the impact of our method on the internal behavior of our NMT models.
Post-Processing of Schlieren Images

In general, the Schlieren visualization method is used to qualitatively describe phenomena. However, recent studies have attempted to convert the classical Schlieren system into a quantitative method to describe certain flow parameters. This paper aims at analysing pictures from a qualitative and a quantitative point of view. The post-processing of images for both situations is described based on different applications. Real examples are used and both methodologies and logical schemes are explained. The article focuses on image processing, and not on the studied phenomena.
Relevant Independent Variables on MOBA Video Games to Train Machine Learning Algorithms

Popularity of Multiplayer Online Battle Arena (MOBA) video games has grown considerably, its popularity as well as the complexity of their playability, have attracted the attention in recent years of researchers from various areas of knowledge and in particular how they have resorted to different machine learning techniques. The papers reviewed mainly look for patterns in multidimensional data sets. Furthermore, these previous researches do not present a way to select the independent variables (predictors) to train the models. For this reason, this paper proposes a list of variables based on the techniques used and the objectives of the research. It allows to provide a set of variables to find patterns applied in MOBA videogames. In order to get the mentioned list, the consulted works were grouped by the used machine learning techniques, ranging from rule-based systems to complex neural network architectures. Also, a grouping technique is applied based on the objective of each research proposed.
The Optimal Real-Time Video Encoding Scheme for Multi-Camera Panoramic System Using NVENC

Today, modern, powerful, and relatively available computer technology allows the proposal of real-time camera systems working with several video streams. There is also a permanent tendency to increase image resolution, what can be useful for example in some image processing methods used in surveillance systems. Given this, an important part of a multi-camera real-time system proposal is optimal and efficient video compression. The modern encoding standards support 4K or 8K video content. One of these standards is H.264 or HEVC (High Efficiency Video Coding) and the popular available encoding technology using GPU (Graphics Processing Unit) acceleration is NVENC (Nvidia Encoding) provided by Nvidia. Many papers deal with the comparison of encoding standards in terms of quality or bitrate savings on testing video sequences [1], [2]. However, this paper is aimed primarily at a comparison of several practical implementations of NVENC technology using different presets of H.264 and HEVC standards. The experiments are mainly focused on testing the encoder’s real-time ability to deal with single video input obtained from the industrial camera using different settings. To do that, some system performance parameters for the continuous monitoring during the NVENC encoding process were chosen. Results in tables I and II are compared, discussed and the best NVENC implementation with encoding scheme is chosen in the context of our briefly introduced novel panoramic system. Finally, the system is fully loaded by the 7 cameras, all streams are encoded using an optimal encoding scheme and a performance limit is established for our hardware configuration.
Learning of Pseudoword-Movement Association is Accompanied by Enhanced Beta Synchronization

This article presents the case for, and against, using the term crash versus accident to describe unintended events that involve motor vehicles in transport on a trafficway and which result in damage to property or injury to involved persons. The history of the preference for crash versus accident among safety practitioners goes back to the 1960s. The change is not yet universal for a variety of reasons; however, it is gaining acceptance both within and outside the traffic safety field. The case for crash relies mainly on the observation that these events, while unintended, are not unavoidable and the causes and contributing factors are known. Moreover, we can apply effective countermeasures and measure the impact of those countermeasures in reducing the frequency and severity of these events. The counterargument, that the term accident is best, relies mostly on historic precedent and parallel terminology in industrial safety. The preference for crash is strongest among safety practitioners who focus on implementing countermeasures (behavior change, vehicle systems, and the roadway environment) and among those harmed in crashes and their families. We must also recognize the special case of intentionally harmful events that clearly are not accidental under any accepted definition. Those who argue in favor of using the word accident have some difficulty classifying which of the crash contributing factors point to intentional behaviors about which they must agree the term accident is a poor choice. Evidence suggests that media outlets are starting to adopt the changed word choice as well. In the United States, some states are resistant because their laws include the term accident, but classification guidance and standards from the National Highway Traffic Safety Administration (NHTSA) and the American National Standards Institute (ANSI) have made the change a permanent part of the safety lexicon, and some states are following this guidance as well. Note that the majority of this article presents discussions that are taking place in and about the situation in the United States. I have included some information about the situation in the rest of the world regarding terminology and mind-sets and for that input I thank my international colleagues.
Towards a Comprehensive Understanding of Agile Teamwork: A literature-based Thematic Network

Agile Software Development (ASD) has become the mainstream software development method of choice.Its core fundamentals are based on Teamwork factors and the higher value it gives to individuals and their interactions over processes and tools.Teamwork and human factors have been addressed as essential topics in the literature, and researchers have stated the importance of measuring it to increase the chances of success of ASD projects.However, there is no common understanding regarding the factors that should be considered for defining an ASD Teamwork construct.Driven by this problem, this paper presents a thematic network that defines the themes (i.e., factors) that should be considered when addressing ASD Teamwork.The ASD Teamwork thematic network is the result of a process that consisted of (i) defining the studies used as a data source through a literature review; (ii) extracting data from these studies; (iii) translating this data into codes; (iv) translating the codes into themes; (v) creating the model of higher-order themes; and, (vi) assessing the trustworthiness of the synthesis.The resulting thematic network comprises four higher-level themes: Cohesion, Orientation, Shared Leadership, and Autonomy.We believe that the constructed thematic network can be generalized to ASD and used as the basis by researchers who intend to explore ASD Teamwork.Further, practitioners can use our results to understand agile teams' dynamics better and improve their efficiency.
INCREASING TEACHERS' CAPABILITIES IN ONLINE LEARNING BY USING WHATSAPP DURING THE PANDEMIC AT SDN 18 BENGKALIS

Organizing online learning for each educational unit and developing or determining how to provide learning to students could be done by using social media. Choosing social media in carrying out learning is necessary because social media did not recognize space and time, it made it easier to communicate with people who were far apart. Thus, it was necessary to train teachers in using WhatsApp as an alternative to learning by using action research methods or often school action research. This research involved 8 teachers at SDN 18 Bengkalis. The results of the study found that the teachers’ understanding in online learning in Cycle I was 51.13 with sufficient category. After making improvements and seeing reflections from learning, it was continued with cycle II with the results obtained an average of 73.13 with good category while the teacher's ability in learning in cycle I got sufficient category. In cycle II, out of 8 teachers, 2 teachers got very good category and 6 people got good category. In the learning carried out by the teacher using WhatsApp, there was an increase compared to cycle I. In cycle II, the teachers were already able to use WhatsApp in explaining, providing guidance, and also providing tasks that would be done by the teacher.
Perancangan Dan Pengembangan Sıstem Poınt Of Sale Pada Toko Aılısa Collectıon

Business activities can be controlled by the rapid advancement of technology. Therefore with correct information system implementation can help business competitive. This practical project is implemented on Ailisa Collection which is a micro, small, medium enterprise which engages in women’s cosmetics and accessories. The existing problem is Ailisa Collection still use manual recording for sale and purchase transactions and no recording for inventory supply which made the owner have difficulties in finding out the profit or loss and exact amount of stock in inventory which determines decision making. The output from this job training is a web based point of sales system which will help the development of the business. The point of sales system is developed using Sublime Text 3, XAMPP, and Google Chrome with HTML, CSS, PHP as the programming language
Metode Forward Chaining dalam Menganalisis Penyakit Kucing Akibat Infeksi Virus

Cats are pets that are very popular today, their cute behavior and cute body shapes make people from all walks of life love them. We, especially those who like and keep cats, must pay attention to the cat's health condition, because it is possible that viral infections suffered by the cat can be contagious. At this time, the public does not have enough knowledge about education about cat diseases due to viral infections, resulting in cats being often late in getting treatment. This study aims to analyze cat diseases due to viral infections using the Forward Chaining method based on symptoms and to design an Expert System to measure the accuracy of analyzing cat diseases due to viral infections. The data needed in this study are cat data, symptom data and solution or treatment data needed to make decisions that are sourced from veterinarians from Paw's Vet Padang. Sourced form data analysis provided by the expert, the expert has a decision-making mode, which is to collect facts first to reach a conclusion or decision, so the Forward Chaining method can be used to conduct this research. The stages of data processing include preparing input data, expert decision tables, determining rules, conducting tracking processes, making decision trees and tracking results. The results obtained are successful in analyzing the symptoms and can determine diseases related to viral infectious diseases in cats so that solutions and initial steps can be determined for handling them. The results of trials conducted by comparing the data with the system that has been designed have a very good level of accuracy.