Reviewerly/exHarmony huggingface dataset:
On Finite Subgroups in the General Linear Groups over an Algebraic Number Field

Abstract As is well-known, there are only finitely many isomorphic classes of finite subgroups in a given general linear group over the field of rational numbers. This result can be generalized to any algebraic number field. While the case of field of rational numbers is relatively well-studied, we still do not know much for general algebraic number field cases. In this article, we discuss the finiteness of isomorphic classes of finite subgroups of general linear groups over an algebraic number field. We give a method to calculate a multiplicative bound for the orders of finite subgroups and to classify finite cyclic subgroups.
Generalizing Reinforcement Learning through Fusing Self-Supervised Learning into Intrinsic Motivation

Despite the great potential of reinforcement learning (RL) in solving complex decision-making problems, generalization remains one of its key challenges, leading to difficulty in deploying learned RL policies to new environments. In this paper, we propose to improve the generalization of RL algorithms through fusing Self-supervised learning into Intrinsic Motivation (SIM). Specifically, SIM boosts representation learning through driving the cross-correlation matrix between the embeddings of augmented and non-augmented samples close to the identity matrix. This aims to increase the similarity between the embedding vectors of a sample and its augmented version while minimizing the redundancy between the components of these vectors. Meanwhile, the redundancy reduction based self-supervised loss is converted to an intrinsic reward to further improve generalization in RL via an auxiliary objective. As a general paradigm, SIM can be implemented on top of any RL algorithm. Extensive evaluations have been performed on a diversity of tasks. Experimental results demonstrate that SIM consistently outperforms the state-of-the-art methods and exhibits superior generalization capability and sample efficiency.
Artificial Intelligence Approaches to Build Ticket to Ride Maps

Fun, as a game trait, is challenging to evaluate. Previous research explores game arc and game refinement to improve the quality of games. Fun, for some players, is having an even chance to win while executing their strategy. To explore this, we build boards for the game Ticket to Ride while optimizing for a given win rate between four AI agents. These agents execute popular strategies human players use: one-step thinking, long route exploitation, route focus, and destination hungry strategies. We create the underlying graph of a map by connecting several planar bipartite graphs. To build the map, we use a multiple phase design, with each phase implementing several simplified Monte Carlo Tree Search components. Within a phase, the components communicate with each other passively. The experiments show that the proposed approach results in improvements over randomly generated graphs and maps.
A* Search and Bound-Sensitive Heuristics for Oversubscription Planning

Oversubscription planning (OSP) is the problem of finding plans that maximize the utility value of their end state while staying within a specified cost bound. Recently, it has been shown that OSP problems can be reformulated as classical planning problems with multiple cost functions but no utilities. Here we take advantage of this reformulation to show that OSP problems can be solved optimally using the A* search algorithm, in contrast to previous approaches that have used variations on branch-and-bound search. This allows many powerful techniques developed for classical planning to be applied to OSP problems. We also introduce novel bound-sensitive heuristics, which are able to reason about the primary cost of a solution while taking into account secondary cost functions and bounds, to provide superior guidance compared to heuristics that do not take these bounds into account. We propose two such bound-sensitive variants of existing classical planning heuristics, and show experimentally that the resulting search is significantly more informed than with comparable heuristics that do not consider bounds.
Inconsistent Planning: When in Doubt, Toss a Coin!

One of the most widespread human behavioral biases is the present bias -- the tendency to overestimate current costs by a bias factor. Kleinberg and Oren (2014) introduced an elegant graph-theoretical model of inconsistent planning capturing the behavior of a present-biased agent accomplishing a set of actions. The essential measure of the system introduced by Kleinberg and Oren is the cost of irrationality -- the ratio of the total cost of the actions performed by the present-biased agent to the optimal cost. This measure is vital for a task designer to estimate the aftermaths of human behavior related to time-inconsistent planning, including procrastination and abandonment. As we prove in this paper, the cost of irrationality is highly susceptible to the agent's choices when faced with a few possible actions of equal estimated costs. To address this issue, we propose a modification of Kleinberg-Oren's model of inconsistent planning. In our model, when an agent selects from several options of minimum prescribed cost, he uses a randomized procedure. We explore the algorithmic complexity of computing and estimating the cost of irrationality in the new model.
Design and Use of Quickappninja-Based Android Games in Mathematics Learning Through Google Meet

One of the platforms that can be used for online learning is Google Meet, which is a product made by Google. Google Meet can replace the conventional form of class into an interactive virtual class. The use of quickappninja-based android games in learning mathematics through Google Meet is a medium that can make learning more varied and interesting. Quickappninja is a device in the form of web pages that can be accessed online to create android games using HTML language. Using Quickappninja is easy because it does not require a programming language. In making android games through quickappninja, teachers will be more flexible in developing games according to their needs and subject matter. Apart from being delivered classically through Google Meet, this android game can also be used independently for students as a medium of learning at home, as well as repetition of material for students so that they can better understand math subject matter.
Mahasiswa Dan Realitas Kuliah Online (Analisis Persepsi Mahasiswa di Ruang Teks Opini Media)

Abstract. Since the Covid-19 pandemic broke out in March 2019, online lectures or online learning modes have been established by the government through the Directorate General of Higher Education Circular Number 1 of 2020 concerning Prevention of the Spread of Covid-19 as a learning system that must be used at all levels of education units, including universities. The implementation of online lectures at universities not only raises positive opinions, but also negative perceptions of students, as reflected in student opinions whose opinions are presented in the online media news portal room. This study aims to analyze the negative views of students whose sources are extracted from opinion texts on the sample online media news portal page. This qualitative study with descriptive-interpretative analysis method seeks to analyze student opinion texts at the level of their perception, attention, interpretation, and response to the online lectures they have been attending. The results of the study show: This study aims to analyze the negative views of students whose sources are extracted from opinion texts on the sample online media news portal page
Learning Modular Structures That Generalize Out-of-Distribution (Student Abstract)

Out-of-distribution (O.O.D.) generalization remains to be a key challenge for real-world machine learning systems. We describe a method for O.O.D. generalization that, through training, encourages models to only preserve features in the network that are well reused across multiple training domains. Our method combines two complementary neuron-level regularizers with a probabilistic differentiable binary mask over the network, to extract a modular sub-network that achieves better O.O.D. performance than the original network. Preliminary evaluation on two benchmark datasets corroborates the promise of our method.
Robust Reversible Watermarking Using Binary Xored

Invertible or lossless watermarking is the similar to reversible watermarking maintaining and inserting data at sender in encrypted way and decrypting it on receiver side. Digital watermarking in general application domains includes broadcast monitoring, owner recognition, tracking of transactions, authentication of data, etc. Trending works in the global reach of the internet have contributed to widespread use of high data on the internet. Development allows different areas of industry to reach more people but also increases the risk of illegality. The basic requirement of the reverse watermarking technique is that after secret information is removed, the device must be able to recover the cover function. Proposed technique of robust reversible watermarking uses least significant bit (LSB). It is used to preserve ownership and to maintain data quality which is being degraded due to watermark embedding. The system uses pseudorandom number generator for secret key generation which in turn maintains ownership rights and secret data embedded in image that is sent through e-mail. No such method exists which provides service through e-mail in a secure way while preserving ownership rights and recovery of original data with higher number of bits.
STUDENTS' RESPONSE TOWARD TEACHING ONLINE IN ENGLISH READING CLASS.

Pandemic COVID-19 is not over yet, however as an educator we should be more creative and innovative to motivate our students in teaching and learning processes. One of the important aspects of learning The English language is increasing reading comprehension. It is challenging for the educator to make it happen when doing online teaching and learning processes. To evaluate and analyze the problem the writer makes this research. The purpose of this study is to find out teacher strategies in teaching online reading classes during pandemics. The subjects are the third-semester students of The English Department, Language and Culture Faculty, Universitas 17 Agustus 1945 Semarang. The research was held during the even semester of the academic year 2020/2021. This study uses a descriptive qualitative method. The instruments of the data used in this study are questionnaires filled by the students. The objective of this study is to know some problems that happened during online teaching and learning process in reading class that give an impact in improving their reading comprehension skill. In this research, the writer collected students’ responses and did evaluations to make them more effective and interested in the teaching process. The research indicated that there are some problems faced by the students dealing with learning processes such as teaching strategies, technical problems during online teaching and learning process and they also need extra motivation to improve their reading comprehension. The findings suggested that educators can use diverse teaching strategies in reading class such as scaffolding, QARs (Question and answer relationship), and other strategies to stimulate them being active in online learning processes, the other problem is a technical problem as a signal when they are joining in a class by virtual meeting application. The learners also stated that they need motivation and guidance to use various methods in reading a text. Thus, the process of teaching online doesn’t have a big impact on improving reading comprehension but there are other problems should be noticed.
Interpretable Privacy Preservation of Text Representations Using Vector Steganography

Contextual word representations generated by language models learn spurious associations present in the training corpora. Adversaries can exploit these associations to reverse-engineer the private attributes of entities mentioned in the training corpora. These findings have led to efforts towards minimizing the privacy risks of language models. However, existing approaches lack interpretability, compromise on data utility and fail to provide privacy guarantees. Thus, the goal of my doctoral research is to develop interpretable approaches towards privacy preservation of text representations that maximize data utility retention and guarantee privacy. To this end, I aim to study and develop methods to incorporate steganographic modifications within the vector geometry to obfuscate underlying spurious associations and retain the distributional semantic properties learnt during training.
How to Reduce Action Space for Planning Domains? (Student Abstract)

While AI planning and Reinforcement Learning (RL) solve sequential decision-making problems, they are based on different formalisms, which leads to a significant difference in their action spaces. When solving planning problems using RL algorithms, we have observed that a naive translation of the planning action space incurs severe degradation in sample complexity. In practice, those action spaces are often engineered manually in a domain-specific manner. In this abstract, we present a method that reduces the parameters of operators in AI planning domains by introducing a parameter seed set problem and casting it as a classical planning task. Our experiment shows that our proposed method significantly reduces the number of actions in the RL environments originating from AI planning domains.
Relationship between personal and professional self-determination among high school students

Introduction. Many international organizations are increasingly raising the issue of developing state vocational guidance programs. An intensive study of the labor market, its changes and the evolution of skills needs is being carried out. An important aspect was the possibility of choosing a profession in accordance with the abilities and interests of not only everyone, but also taking into account the needs of society. Now it is not necessary to follow the principles of profitability or prestige of the profession. Now you can choose a business to your liking. The most significant group of the population in this area are schoolchildren who are just starting their career path. It became possible to choose a job due to one’s liking. So, a natural question arises about the features of students’ professional and personal self-awareness. The research aims to study the relationship between students’ professional self-determination and personal self-awareness. Materials and methods. The sample consisted of 60 students from the secondary school "Eureka-Development №96" and the Specialized educational and scientific center of the Southern Federal District, whose average age was 17 years. The respondents completed socio-demographic survey as well as psychological assessment of personal and professional identity. To assess personal self-awareness, the authors used Pantileeva’s self-attitude test, and to indicate the level of professional self-determination, we used A.A. Azbel - A.G. Gretsovas’ questionnaire of students’ self-determination. For data analysis, we used Spearman's Rank-Order Correlation and the Friedman test, processed in the software of RStudio and STATISTICA 13.3. Results. There was significant correlation between such variables as status of imposedon professional identity and openness (r = 0.37; p &lt; 0.05), uncertain professional identity and internal conflict (r = 0.39; p &lt; 0.05), moratorium and self-blame (r = -0.44; p &lt; 0.05), also between formed status of professional identity and self-guidance (r = 0.3; p &lt; 0.05). Results show that almost 40% of respondents are in a state of crisis in choosing a profession. At the same time only 20 % of students are ready to make a conscious and independent choice in their further professional development. Conclusion. High school students are in a difficult period when self-confidence, faith in the surmountability of obstacles collides with inner experiences for their qualities and actions. The study showed that for self-determination, schoolchildren need to see their gaps and shortcomings, but at the same time consider themselves the main source of personal development, a regulator of achievements and success and accept responsibility for their professional choices.
Practical Skills of Business English Correspondence Writing Based on Data Mining Algorithm

English correspondence writing has become a necessary skill for every scientific researcher and high-tech talents. An English correspondence writing auxiliary writing system can help nonnative English speakers make up for the lack of professional expression. The key factor of business English correspondence writing system is the construction of knowledge base. To improve the business English correspondence writing knowledge base, we need to mine frequent patterns of sentences in each category. The purpose of this topic is to improve and supplement the knowledge base for the business English correspondence writing system and propose frequent pattern mining for sentences in each category, so as to improve the writing knowledge base for the business English correspondence writing system. Firstly, we crawl a large number of business English letters and telegrams from the Internet, extract the relevant summary information, then store it, and preliminarily construct a corpus based on sentences. Then, we do some research on the structure of business English correspondence abstracts, mark the sentences in the corpus and count the relevant information, and have a certain understanding of their writing methods. Finally, we mine frequent patterns for sentences in each category, so as to improve the knowledge base of summary writing for the business English correspondence writing system. In the experiment, we use the classical FP growth algorithm as the mining method. The experiment shows that the frequent patterns between 3 and 6 words have been mined to a certain extent. By gradually improving the mining strategy, the quality of mining results has been improved and the writing effect of business English correspondence of scientific researchers has been improved.
On the Complexity of Inductively Learning Guarded Clauses

We investigate the computational complexity of mining guarded clauses from clausal datasets through the framework of inductive logic programming (ILP). We show that learning guarded clauses is NP-complete and thus one step below the Sigma2-complete task of learning Horn clauses on the polynomial hierarchy. Motivated by practical applications on large datasets we identify a natural tractable fragment of the problem. Finally, we also generalise all of our results to k-guarded clauses for constant k.
Discussion on Continuing Education of College Accountants under the Background of Big Data Era

In recent years, big data technology has gradually entered people's lives. All walks of life use big data technology to break the traditional data management method. The scale of data and the type of data processing are more diversified. The application makes the work of accountants more convenient, and also provides a broad space for the reform of accounting education. This paper takes the new characteristics of college accounting continuing education under the background of big data technology as the breakthrough point, expounds the problems existing in accounting continuing education under the background of big data, and puts forward specific measures to strengthen accounting continuing education, aiming to provide continuing education and development assistance for college accountants.
PENINGKATAN KEMAMPUAN BERBICARA BERBASIS PRODUKTIVITAS MELALUI SCHEDULE TEXT PADA MAHASISWA FBP UNIVERSITAS TRIATMA MULYA BALI

This research take on focus the Speaking ability on producing sentences with schedule text as the basic material on first semester students on hospitality program. Research showed that effort to improve students’ speaking skill which is based on productivity can be used schedule text as the trigger. The steps can be divided into 3 such as introducing relevant vocabulary where vocabulary showed in matching column in similar number, inserting small text which support the topic and the core activity is producing sentences. The sentences produced are classified into 3 groups according to how tight the dependency to the text provided. The research found out that (a) all students produce minimal 5 sentences and even far more. No students left in achieve this type of sentences. The sentences are produces by linked information on a certain line. (b) A number of students faced it difficult to produce sentences type 2 since it needs more focus in comparing data from the schedule text. Only 85% student got it easy while the others need more time to produce one. The sentences here produced by doing comparison or linking between lines information. (c) For group 3 where sentences need knowledge background to support it is achieved by 55% students. Here, sentences produced by implementing intratext which means another text must be there so the sentences become larger or deeper than the data on schedule text itself. It seemed that not each student has enough knowledge about airlines or small text which is provided before the core activity is neglected. Lack of knowledge or effort made it difficult for some students, but still very essay for others. They can produce many sentences in this group in a minute. From the results, it is suggested for students to do reading activity on interesting topic or article supporting the learning process.
Implementation of Prototype Method in School Payment Information System of SMP AL- Mushlis Karawang

The development of technology in the field of information systems is currently experiencing a very rapid development, with the presence of an information system, many things can be done easier and faster. For the implementation of tuition payments at Al-Mushlih Junior High School, a web-based information system is needed, which is used for the process of SPP payment services. Currently, the management of school fees payments is still done in the traditional way by entering them in the general ledger, which is very time consuming, especially in the days of school fees payments. Errors often occur when recalling data, and it takes a long time because of the need to check the payment archive in the general ledger. By using a web-based information system, retrieving payment data when needed becomes easier and very fast. The prototype method is used as a reference for system design and development, and it is expected that the new system will facilitate the work of staff and the information produced will be more accurate and precise when reports are generated. Supporting software such as web server, PHp, and Mysql is needed to create a website. The results of the information system created can later process student data, payment data, and transaction data for report generation over a period of time.