Reviewerly/exHarmony huggingface dataset:
Abstraction in Data-Sparse Task Transfer (Extended Abstract)

When a robot adapts a learned task for a novel environment, any changes to objects in the novel environment have an unknown effect on its task execution. For example, replacing an object in a pick-and-place task affects where the robot should target its actions, but does not necessarily affect the underlying action model. In contrast, replacing a tool that the robot will use to complete a task will effectively alter its end-effector pose with respect to the robot's base coordinate system, and thus the robot's motion must be replanned accordingly. These examples highlight the relationship among (i) differences between the source and target environments, (ii) the level of abstraction at which a robot's task model should be represented to enable transfer to the target environment, and (iii) the information needed to ground the abstracted task representation in the target environment. In this abstract, summarizing our full article [Fitzgerald et al., 2021], we present our taxonomy of transfer problems based on this relationship. We also describe a knowledge representation called the Tiered Task Abstraction (TTA) and demonstrate its applicability to a variety of transfer problems in the taxonomy. Our experimental results indicate a trade-off between the generality and data requirements of a task representation, and reinforce the need for multiple transfer methods that operate at different levels of abstraction.
Logically Consistent Adversarial Attacks for Soft Theorem Provers

Recent efforts within the AI community have yielded impressive results towards “soft theorem proving” over natural language sentences using language models. We propose a novel, generative adversarial framework for probing and improving these models’ reasoning capabilities. Adversarial attacks in this domain suffer from the logical inconsistency problem, whereby perturbations to the input may alter the label. Our Logically consistent AdVersarial Attacker, LAVA, addresses this by combining a structured generative process with a symbolic solver, guaranteeing logical consistency. Our framework successfully generates adversarial attacks and identifies global weaknesses common across multiple target models. Our analyses reveal naive heuristics and vulnerabilities in these models’ reasoning capabilities, exposing an incomplete grasp of logical deduction under logic programs. Finally, in addition to effective probing of these models, we show that training on the generated samples improves the target model’s performance.
Research on the Characteristics of Meal-kit using Big Data Analysis Method

This study was conducted to find out the characteristics of Meal-kit products that have recently grown rapidly in Korea. To this end, Topic Modeling and PageRank analysis were conducted on online news articles. It is an easy analysis to identify the main topics surrounding the Meal-kit using Topic Modeling, and the PageRank shows the influence relationship well, so it is easy to identify various characteristics surrounding the Meal-kit product. As a result of the study, delivery, online, and cooking can be cited as characteristics of Meal-kit products. This study can be used as useful data for corporate marketing and can also be used as data to predict new industries.
Developing the individual teaching style in foreign language teacher training universities

The present study is of relevance due to the necessity to develop an individual style of professional activity of intending teachers or their individual teaching style (ITS). This necessity is determined by the social and cultural significance of the phenomenon under study and by the rapid pace of changes happening in the educational context today. The purpose of the study is theoretical interpretation of the concept of ITS of intending foreign language (FL) teachers and of its social and cultural significance in the context of teacher training case study. The author hypothesizes that to a large extent the ITS of intending teachers is formed within the framework of the professional courses in the first three years of the university studies. An important condition that contributes to the effective ITS development is the use of practical training, quasi-professional activities, analysis of professional tasks and case-study in the educational process, creation of the digital environment to support students’ individual professional growth. The prevailing design of the study is of a qualitative nature. However, the applied methods of observation and statistical analysis are implemented, too. The research methods include theoretical justification of the key concept of the work through comparative analysis, interpretation, classification and specification, case study and experience analysis of the ways a FL teacher training programme is implemented. The case study is based on the survey results. The survey was carried out on a sample of the 3rd- and 4th-year students of the Faculty of Foreign Languages and Linguodidactics of Saratov State University (methodology by A. M. Markova and A. Ya. Nikonova was implemented, the sample size was n = 126 people). As a result, the article specifies the concept of ITS for the context of FL teacher training, identifies the components of the ITS hierarchical structure, and singles out particular factors and methods of ITS development at the Faculty of Foreign Languages and Linguodidactics. Our results cast a new light on the phenomenon under study in the context of FL teacher training. The initial hypothesis was confirmed, since the research revealed no strong correction of the ITS of the 4th-year students in correlation to the data collected for the 3rd-year students.
Communities of children and adult in a village school

There are several factors that justify the relevance of creating communities of children and adults in rural areas. Thus, it is determined by the necessity to ensure the continuity between older and younger generations, successful socialization of rural children, development of students’ experience in building up relationships with adults based on partnership, dialogue and cooperation. The purpose of the study is to identify the functions and peculiar activities of communities of children and adults in rural schools. The study proposes the definition of the concept of ‘communities of children and adults’. On the basis of a number of features, a comparison of this concept with the category of a ‘collective body’ is given. The author considers the classification of communities of children and adults grounded on various approaches. Distinctive characteristics of communities of children and adults and their functions are determined. Based on the analysis of the experience of rural schools, especially those with a small number of students, the study determines some requirements for the pedagogical staff to use as their guide. It is necessary when school collectives organize the activities of children’s and adult’s communities in order to ensure the realization of the above-mentioned functions. The author makes the conclusions: various child-adult communities are formed in rural areas; a school can become a community of interacting subjects of different ages, where everyone can realize themselves and achieve success. Communities of children and adults in rural educational organizations are the most important mechanism for the personal development process, a means of solving pedagogical tasks and social problems of the countryside. The success of community activities depends on the proficiency of teachers, on their position in the interaction with all the subjects of educational relations, on the possibility to have an authoritative leader.
The Management of Examination Malpractice Using Blockchain Technology

The recent increase in post-examination malpractice at the grade twelve (12) level at marking centers has sparked widespread concern among education stakeholders. The management process at a marking center involves scoring, transfer of grades from hardcopy scripts onto the softcopy system provided by the Examination Council of Zambia and conducted by examiners from various subject panels. However, pockets of post-examination malpractice have been recorded, which include the change of grades initially assigned to a particular candidate’s script at the data entry point. The research is based on finding measures to combat examination malpractice through the use of Blockchain Technology, to stop the post modification of entered results on the Electronic Results Management System of grade 12 results. A baseline study was conducted using purposive sampling of different respondents, i.e., Chief-Examiners, Team Leaders, and Markers, and a prototype using Blockhcain Technology was developed to address this need by the current ERMS. The technology would employ the SHA-256 hashing technique. The final hash document would be shared from a marking center to a central point at the examination council for the verification process before publication of the results. The proposed system showed improved service delivery at marking centers through making it impossible to experience grade modification.
Enhancing Low-Resource Languages Question Answering with Syntactic Graph

Multilingual pre-trained language models (PLMs) facilitate zero-shot cross-lingual transfer from rich-resource languages to low-resource languages in extractive question answering (QA) tasks. However, during fine-tuning on the QA task, the syntactic information of languages in multilingual PLMs is not always preserved or even is forgotten, which may influence the detection of answer spans for low-resource languages. In this paper, we propose an auxiliary task to predict syntactic graphs to enhance syntax information in the fine-tuning stage of the QA task to improve the answer span detection of low-resource. The syntactic graph includes Part-of-Speech (POS) information and syntax tree information without dependency parse label. We convert the syntactic graph prediction task into two subtasks to adapt the sequence input of PLMs: POS tags prediction task and syntax tree prediction task (including depth prediction of a word and distance prediction of two words). Moreover, to improve the alignment between languages, we parallel train the source language and target languages syntactic graph prediction task. Extensive experiments on three multilingual QA datasets show the effectiveness of our proposed approach.
The Influence of the Use of Information Technology on the Literacy Interest of Students at the Amuntai College of Al-Quran Science

Information technology is the processing, processing, and dissemination as well as by a combination of computers and telecommunications. The use of information technology improves student literacy in several ways: first, the existence of information technology can be used in our spare time with a variety of information that we can read and write, it is hoped that it can improve students' critical thinking patterns. Second, the use of Information Technology can improve students' cognitive abilities which are expected to have a positive impact on student academic performance.. The purpose of this study was to determine the effect of the use of information technology on literacy interest. The method used in this study is descriptive analysis method and simple linear regression analysis with a quantitative approach and the collection technique using a population questionnaire in this study was 30 respondents and used saturated sampling so that the sample was the entire population who were students of the Amuntai Al-Quran Science College. The results of this study indicate that there is an influence of information technology on the literacy interest of Amuntai High School of Al-Quran Science (STIQ) students. From the results of descriptive analysis in the use of information technology an average of 39.33 with the number of respondents 15 people or 50.0% and the literacy interest of the Amuntai College of Al-Quran Science students an average of 36.6 with 25 respondents and a linear regression analysis test A simple regression that can be seen is that the regression of 24.9 means that the use of information technology has a positive effect on the literacy interest of high school students of Al-Qur'an. investigated in research.
Penerapan Taksonomi Bloom pada Pembelajaran Bahasa Di Kelas 2 SD Bali Kiddy

This research was conducted with the aim of knowing the operational verbs used in language learning in 2nd grade at Bali Kiddy Primary School, knowing and describing verb learning strategies in language learning in 2nd grade at Bali Kiddy Primary School and knowing the relationship of using the operational verbs with Bloom’s Taxonomy in language learning in 2nd grade at Bali Kiddy Primary School. This research is a qualitative research using observation and interview methods in data collection. Research findings and analysis results show that there are 51 operational verbs used in language learning in grade 2 at Bali Kiddy Primary School which are categorized into two categories of verb according to Shopen Theory; 46 verbs classified as action verb and 5 verbs classified as process verb, as well as the verb learning strategies which are used in language learning in 2nd grade at Bali Kiddy Primary School varies greatly. In addition, this study also found the relationship between the used of operational verbs in language learning in 2nd grade at Bali Kiddy Primary School with Bloom’s Taxonomy. Overall, it was found that operational verbs in language learning was classified three cognitive categories namely C1 (remember) with examples of operational verbs menulis and membaca, C2 (understand) with examples of operational verbs memahami and menginterpretasi and also C3 (apply) with the example of operational verbs menggunakan and menyelesaikan.
The Use of Cohesive Devices in the Narrative Texts of the 11th Graders

Writing is one of the skills learned by 11th graders. It makes the students consider to make their text communicative to the readers. To recognize whether the students can communicate the text or not, one can analyze its cohesive devices. This study aimed to find out the use of cohesive devices in narrative texts written by 11th graders of Pelita Bangsa School. Qualitative method was used in this study. Five texts were chosen by the researcher from 11th graders of Pelita Bangsa School Cirebon. The analysis focused on studentsâ€™ texts analyzed by the theories of Halliday and Hasan (1976) and Thornbury (2005). The findings showed that reference, conjunction, substitution, ellipsis, and lexical cohesion were used by the students. However, both substitution and ellipsis were infrequently used by the students. Meanwhile, reference and conjunction were frequently used by the students. In addition, the relationship of the devices in achieving text coherence was important. Cohesive devices create a text that makes sense to read. In conclusion, some cohesive devices were familiar to the students, only substitution and ellipsis were rarely used by them. Moreover, the relationship of cohesive devices in achieving text coherence was the direct involvement of all cohesive devices in making text coherence.
Masked Face Recognition Attendance System Using A Modified Convolutional Neural Network

In this paper, a masked face recognition based attendance system is developed by modifying a version of convolutional neural network (CNN). In this regard, a Support Vector Machine is integrated in the CNN to replace its original Softmax classifier to perform the task. The performance of the modified CNN in recognizing masked faces in a 5-fold cross validation was compared that of other CNNs. The experimental results show high effectiveness of the proposed CNN (i.e. 98.92%) in recognizing masked faces for recording attendance.
AN EFFICIENT DATA IMPUTATION TECHNIQUE FOR HUMAN ACTIVITY RECOGNITION

The tremendous applications of human activity recognition are surging its span from health monitoring systems to virtual reality applications.Thus, the automatic recognition of daily life activities has become significant for numerous applications.In recent years, many datasets have been proposed to train the machine learning models for efficient monitoring and recognition of human daily living activities.However, the performance of machine learning models in activity recognition is crucially affected when there are incomplete activities in a dataset, i.e., having missing samples in dataset captures.Therefore, in this work, we propose a methodology for extrapolating the missing samples of a dataset to better recognize the human daily living activities.The proposed method efficiently pre-processes the data captures and utilizes the k-Nearest Neighbors (KNN) imputation technique to extrapolate the missing samples in dataset captures.The proposed methodology elegantly extrapolated a similar pattern of activities as they were in the real dataset.
Deep Clustering Self-Organizing Maps with Relevance Learning

Nowadays, with the advance of technology, there is an increasing amount of unstructured data being generated every day. However, it is a painful job to label and organize it. Labeling is an expensive, time-consuming, and difficult task. It is usually done manually, which collaborates with the incorporation of noise and errors to the data. Hence, it is of great importance to developing intelligent models that can benefit from both labeled and unlabeled data. Currently, works on unsupervised and semi-supervised learning are still being overshadowed by the successes of purely supervised learning. However, it is expected that they become far more important in the longer term. This article presents a semi-supervised model, called Batch SemiSupervised Self-Organizing Map (Batch SS-SOM), which is an extension of a SOM incorporating some advances that came with the rise of Deep Learning, such as batch training. The results show that Batch SS-SOM is a good option for semisupervised classification and clustering. It performs well in terms of accuracy and clustering error, even with a small number of labeled samples, as well as when presented to unsupervised data, and shows competitive results in transfer learning scenarios in traditional image classification benchmark datasets.
Penerapan Sistem Accurate Dalam Penyusunan Laporan Keuangan

In this era of increasingly transparent and open globalization, it has brought all the activities of human life into tight competition in the field of technology.The impact of technological developments on work activities is that many people from all walks of life use computers.Incorrect use of computerized technology is in accounting information system in a company. The role of accounting information systems helps enterprise leaders make management decisions by organizing documents and notes, resulting in precise and accurate financial report information to facilitate the management of corporate activities.&#x0D; This research aims to determine the application of accurate systems can assist in the preparation of financial statements and analyze whether there is weakness of the system that is running.The author conducts research at Afifa Laundry, Jl. Raya Laladon Indah No.7 Bogor. This research uses qualitative methods of descriptive. The Data used in this research was obtained through interviews, observations, and documentation conducted at Afifa Laundry.&#x0D; Based on the results of the implementation of a new computer-based accounting information system at Afifa Laundry has made a very positive impact for the company, starting with a neat customer number, the existence of a sales invoice, and the absence of a feedstock in the registration of invoices and companies can control the finances of costs and revenues, and can easily generate financial statements.&#x0D; &#x0D; Key Words: Accounting information System and Accurate Accounting Software version 5
Penerapan Sistem Informasi Akuntansi Berbasis Accurate Terhadap Penyusuanan Laporan Keuangan

Small and Medium Enterprises have increased, but few MSMEs have implemented accounting systems. Accounting Information System is increasingly increasing in the field of accounting certainly makes it easier for companies to produce financial reports in addition to facilitate the recording and can find out the company's financial condition. Financial statements that contain financial statements, company performance, and changes in financial position, inventory, and profits obtained which can help the company's internal parties in making decisions.&#x0D; Almuhajir Tugujaya Convection is a manufacturing company where the company produces clothing and shoes. The recording applied by the Almuhajir Tugujaya Convection is still done manually with the excel program, and only records cash receipts and disbursements, so that the owner does not know for sure the inventory, profits and losses obtained. Manual recording results in recording errors and the risk of data loss. The method used by the author in this study is qualitative with the type of case study. The data obtained is processed and then implemented into Accurate 4.0 Software. From this study, it can be concluded that the application of Accurate Software in the Almuhajir Tugujaya Convection can produce Financial Statements in accordance with current standards, and company profits or losses.&#x0D; Research results, after using Accurate at Almuhajir Tugujaya Convection, computerized sales and purchases transactions make it easy to input transactions. Making different formulas for each production can make it easier to find out the inventory stock, and know the production costs of each product. The resulting financial statements are precise and accurate in accordance with current standards, and can help internal parties know the company's condition in making decisions. The risk of data loss and errors in recording can be prevented.&#x0D; &#x0D; Keywords:Financial Statement, Manufacture, Software Accurate Enterprise 4.0
Faculty Select

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