Reviewerly/exHarmony huggingface dataset:
THE CONCEPTUAL MODEL OF TRAINING OF FUTURE DOCTORS OF PHILOSOPHY FOR THE RESEARCH AND INNOVATION ACTIVITY

The article presents a conceptual model of training of a future doctor of pilosophy for the research and innovation activity. The relevance of the problem is related to the establishment and development of the third level of higher education in Ukraine, which requires the study of foreign experience and its implementation in the practice of domestic higher education institutions. The proposed model consists of five blocks (the target, informative, organizational, operational and diagnostic) and reflects the three steps of this process. At the theoretical and methodological stage represented in the target block, there have been determined the purpose of the research, normative and methodological frameworks for the process of training a future doctor of philosophy. The substantive-practical stage is featured by the informative, organizational and operational blocks of the model. The informative block reveals the content of the training of postgraduate students for the research and innovation activity, which is formed on the basis of the analysis of modern requirements for scientific-pedagogical employees and the constructed profile of a Ph.D., which has been reflected in educational-scientific programs, curricula and individual work plan of a postgraduate student. The organizational block describes the structure, tasks and functions of the innovative educational and scientific environment of the university; the operational block describes the two-component system of training of a Ph.D., where the educational component, along with the traditional-organized learning, includes project-organized learning, as well as additional learning outside the education process. Besides the obligatory work on the thesis research, the scientific component includes other forms and methods of the research and innovation activity at the university as a component of quasi-professional activity of future Ph.Ds. containing measures for the professional development of young scientists. The diagnostic block, which reflects the analytical and productive stage of the research, outlines the criteria, indicators and levels of readiness of the future Ph.D. for the research and innovation activity, outlining methods and tools for their determination. The result of the considered model is the disposition of future Ph.Ds. for the research and innovation activity. A further prospect of the research consists in its testing and experimental verification.
TRANSLATING MATHEMATIC TEXT ABILITY OF FIFTH SEMESTER STUDENTS IN MATH AND SCIENCE DEPARTMENT STKIP YPM BANGKO

The aimed of this research is to describe about students’ ability in translating mathematic text as a material in English for Teaching Math Course at fifth semester in Math Education Program, Math and Sciece Department of STKIP YPM Bangko in academic year 2019/2020. This ability to provide students to be bilingual teacher in math subject. This reasearch is descriptive quantitave research. It will be conducted in Math Education Program of STKIP YPM Bangko. The population is fifth semester students consists of 18 students. It uses total sampling, the researcher will use written test as the instruments of collecting data, it consists about translating mathematics operation, translating mathematic problem, and passage about mathematics. The students are asked to translate from target language to sourse language and source language to target language. In analyzing the data, the researcher will use the procedure reduce the data, classify the data, describe the data, and data display. To know about students’ ability in translating mathematics english text, the researcher will use three indicatorss; accuracy, readability and acceptability. It also categories into 4 level mastery; excellent, good, fair, and poor. The result of this research found that Students’ ability in translating mathematic text was excellent. Based on the aspect of mathematic text, mathematic passage was difficult to translate for them, and accuracy indicator was lowest score, they tend to omitted word and change the spelling. It can be suggested to train students to practice more the interaction to the text and use the effective strategy in translation.
ERLP: Ensembles of Reinforcement Learning Policies (Student Abstract)

Reinforcement learning algorithms are sensitive to hyper-parameters and require tuning and tweaking for specific environments for improving performance. Ensembles of reinforcement learning models on the other hand are known to be much more robust and stable. However, training multiple models independently on an environment suffers from high sample complexity. We present here a methodology to create multiple models from a single training instance that can be used in an ensemble through directed perturbation of the model parameters at regular intervals. This allows training a single model that converges to several local minima during the optimization process as a result of the perturbation. By saving the model parameters at each such instance, we obtain multiple policies during training that are ensembled during evaluation. We evaluate our approach on challenging discrete and continuous control tasks and also discuss various ensembling strategies. Our framework is substantially sample efficient, computationally inexpensive and is seen to outperform state of the art (SOTA) approaches
THE USE OF INFORMATION SOURCES AT CARRYING OUT A FORENSIC EXAMINATION OF THE OLD PRINTED EDITIONS OF THE CYRILLIC ALPHABET

In forensic science is used a full and objective investigation of a crime or the settlement of a civil claim that requires the use of specialized knowledge, in particular, when examining an expert in the printed editions of Cyrillic. The methodological approaches of eminent scholars on the attribution and cultural evaluation of old printed books are still relevant in the study of book publications by forensic experts dealing with art. The compilation and description of Slavic editions is of great importance both in terms of cultural studies, history, linguistics, engraving, and in terms of the accumulation of some basis for the comparative study of ancient books in forensic studies of ancient printed matter. Therefore, for completeness, comprehensiveness and objectivity of expert research in forensic and expert examination of ancient printed editions of Cyrillic printing, the use of the didactic, cultural and bibliographic material of several generations of leading scientists is of great importance.
Semantically Enriching the Knowledge Payload of Knowledge Objects Through the Utilization of Knowledge Object Wrappers

Aim/Purpose: In this research the authors present the designs of three different knowledge object meta-data wrapper models as a supportive technology to assist the knowledge intensive operations of a network of knowledge, such as a living lab. Background: Within any knowledge driven network environment there is a need to increase the corporate knowledge capacity of the network. The role of experts and knowledge brokers are emphasized, and the exchange of knowledge based on prior experiences informing corporate memories of the members, is the departure point of this research. Methodology: The primary research method applied is that of the design science research methodology supported by experience and application research and the literature. Contribution: Three different metadata models are presented that will when implemented support the informing process within the network of knowledge. The models are grounded on the utilization of metadata elements composing of various key descriptors as found in activity theory and normal means of heuristic enquiry which entail common questions. The elements are annotated and fur-ther enriched using standard JSON-LD IRI pairs. The presented models expand on the extant knowledge of the use of metadata annotations and present a novel way in encapsulating the corporate memories of knowledge workers in the form of knowledge object wrappers. Findings: The results of the evaluation process of the design science research methodolo-gy applied, showed that there is a consensus that the use of knowledge object wrappers as additional metadata, containers could enhance the knowledge ca-pacity and efficiency of a LL and in particular the knowledge brokers.
Hierarchical Average Reward Policy Gradient Algorithms (Student Abstract)

Option-critic learning is a general-purpose reinforcement learning (RL) framework that aims to address the issue of long term credit assignment by leveraging temporal abstractions. However, when dealing with extended timescales, discounting future rewards can lead to incorrect credit assignments. In this work, we address this issue by extending the hierarchical option-critic policy gradient theorem for the average reward criterion. Our proposed framework aims to maximize the long-term reward obtained in the steady-state of the Markov chain defined by the agent's policy. Furthermore, we use an ordinary differential equation based approach for our convergence analysis and prove that the parameters of the intra-option policies, termination functions, and value functions, converge to their corresponding optimal values, with probability one. Finally, we illustrate the competitive advantage of learning options, in the average reward setting, on a grid-world environment with sparse rewards.
Incremental Sense Weight Training for In-Depth Interpretation of Contextualized Word Embeddings (Student Abstract)

We present a novel online algorithm that learns the essence of each dimension in word embeddings. We first mask dimensions determined unessential by our algorithm, apply the masked word embeddings to a word sense disambiguation task (WSD), and compare its performance against the one achieved by the original embeddings. Our results show that the masked word embeddings do not hurt the performance and can improve it by 3%.
Improved RSA security using Chinese Remainder Theorem and Multiple Keys

Now a days, have a great dependence on computer and network and the security of computer related to the whole world and everybody. Cryptography is the art and science of achieving security by encoding message to make them non readable, to secure data information transmits over the network, In this paper introduced modified RSA approach based on multi keys and Chinese remainder theorem (CRT), which RSA algorithm is asymmetric key encryption technique. The objective of this Technique is to provide secure transmission of data between any networks. Which is the Network security is an activity which is designed to provide the usage protection and integrity of the Network and data. So that only the user allowed can read and process it, the objective of this paper Enhancement the performance of RSA and increase the security. In proposed model RSA will be implemented using java.
APLIKASI PENCARIAN RUTE TERPENDEK LOKASI KULINER KHAS PALEMBANG MENGGUNAKAN ALGORITMA EUCLIDEAN DISTANCE DAN A*(STAR)

Palembang is one of the regions in Indonesia which is known for having culinary which has a distinctive and delicious taste. Besides having a distinctive taste, Palembang cuisine also has its own story related to the history of Palembang City and the development of people's lives there. The many types of culinary and culinary tourist attractions in the city of Palembang provide its own obstacles for tourists and local residents in choosing a culinary meal and the route to the culinary location. The solution to the problem proposed is to make the application for the shortest route search for culinary locations typical of Palembang using the Euclidean Distance and A * algorithm. Euclidean Distance algorithm which is a calculation of the distance from two points as a basis in finding the shortest route and gives the user information about the location that is around the user by comparing the distances and applying the A * algorithm as a basis in finding the shortest route using the smallest estimated cost to achieve the goals to be achieved, and has a heuristic value that is used as a basis for consideration. The final results of the study showed that the algorithm performed had a high degree of accuracy in determining the shortest culinary route location in Palembang, namely the Mean Mean percentage error (MAPE) of 4.4%.
A Multi-Task Learning Machine Reading Comprehension Model for Noisy Document (Student Abstract)

Current neural models for Machine Reading Comprehension (MRC) have achieved successful performance in recent years. However, the model is too fragile and lack robustness to tackle the imperceptible adversarial perturbations to the input. In this work, we propose a multi-task learning MRC model with a hierarchical knowledge enrichment to further improve the robustness for noisy document. Our model follows a typical encode-align-decode framework. Additionally, we apply a hierarchical method of adding background knowledge into the model from coarse-to-fine to enhance the language representations. Besides, we optimize our model by jointly training the answer span and unanswerability prediction, aiming to improve the robustness to noise. Experiment results on benchmark datasets confirm the superiority of our method, and our method can achieve competitive performance compared with other strong baselines.
Social-Humanitarian Training of Future Masters of Natural Specialties by Means of Digital Technologies

The article outlines the difference between master’s degree programs, which is their deep focus on fundamental knowledge, focus on innovation, including the scientific field. It has been found that the training of masters of natural specialties is a multifactorial process that requires the integration of scientific approaches, including systematic, synergistic, axiological, competence and acmeology. Principles (problem, systematic, fundamentalization, variativity, following) characteristics, forms, methods, means of master’s training of students are distinguished. The results of the study “Competencies of higher school teachers in the age of change”, which were obtained by scientists of the Borys Grinchenko Kyiv University during the implementation of the international project of the Visegrad Fund, are presented. Positive foreign experience of master’s training is presented. The examples of the positive experience of the Borys Grinchenko Kyiv University in raising the level of digital competences of teachers and students as a guarantee of the use of digital technologies in the educational process are given. The digital resources that should be used in the context of socio-humanitarian training of future masters of natural specialties are highlighted: means for creating joint documents, means for data collection and rapid analysis, means of graphical interpretation of information, means for creating presentation materials, means for chronological presentation of materials, means for presenting classification, ideas, structures.
REPRESENTING THE INCUMBENT AND THE CONTENDER IN THE 2019 INDONESIAN PRESIDENTIAL DEBATES

Background and Purpose: The 2019 Indonesian presidential debates were an important part of the presidential election because it drew public interest, enabling the candidates to persuade the electorate. The debates reunited Joko Widodo, the incumbent and Prabowo Subianto, his former contender.&#x0D; &#x0D; Methodology: The article selected the five debates during the 2019 presidential debates. The debates were analyzed with Transitivity from Systemic Functional Linguistics (SFL), studying how process, participant and circumstance represent the presidential candidates.&#x0D; &#x0D; Findings: The incumbent and contender, although from different parties, share similarities in their Transitivity patterns. Joko Widodo and Prabowo Subianto frequently employ Material, Relational and Mental processes to state their actions for governing Indonesia, describe present or future plans, and share their thoughts and hopes for the country. Being politicians, the incumbent and contender use language to construe themselves as the most suitable person to be president. The two candidates employ the pronoun ‘we’ to depict themselves as part of a group, be it a political party or the electorate. They also employ the pronoun ‘I’ to showcase their personal capability. The two candidates share patterns of Transitivity because their representation tries to persuade the electorate to vote for them.&#x0D; &#x0D; Contributions: The present article extends research on political discourse because it studies data from Indonesia and data in the Indonesian language. The findings can serve to educate the electorate on how politicians employ language in persuasion.&#x0D; &#x0D; Keywords: Debates, elections, Indonesia, president, transitivity.&#x0D; &#x0D; Cite as: Fidyati, L., &amp; Rajandran, K. (2020). Representing the incumbent and the contender in the 2019 Indonesian presidential debates. Journal of Nusantara Studies, 5(2), 215-238. http://dx.doi.org/10.24200/jonus.vol5iss2pp215-238
Explainable and Contextual Preferences based Decision Making with Assumption-based Argumentation for Diagnostics and Prognostics of Alzheimer's Disease

We present an argumentation-based approach to decision making that can support context-based defeasible preferences and offer dialogical explanations for the decisions made. The proposed approach makes and explains a decision as follows: (1) construct a Contextual Preference Decision Framework (CPDF) to model the problem, (2) use Assumption-based Argumentation as a sound and complete computational mechanism for identifying most-contextual-preferred decisions in the CPDF, and (3) construct explaining dialogues to provide dialogical explanations for identified decisions. We have implemented our approach for two tasks, diagnostics and prognostics of Alzheimer's Disease (AD), and evaluated the performance of our models on the two tasks with real-world datasets.
The Interconnection and Interdependence of Students' Independent Work and the Potential of Society

The article describes the components of future specialists' readiness for professional activity (cognitive, practical and personal), which are the structural components of the system of professional training of students of higher education; the essence of independent (extra-auditory) work of students is determined, which contains educational-research, scientific-research work of students with the purpose of mastering basic knowledge, professional abilities and skills of activity on a profile, experience of creative, research activity and promotes the development of independence, responsibility to address educational and professional issues as well as an organized process. Characterization of the potential of the society, which is a collection of social phenomena internally individual, interindividual and metaindividual, is given. It is proved that: student's independent work is a kind of social activity, which is aimed at assimilation of social experience, although it is individual in nature, but is social in content, as it creates for social activity a meaningful result; the difference between the student's and society's independent work is that it is only an element of society, the purpose of which is to increase the level of knowledge, skills and abilities based on the use of diverse social experience, and in general - to use the potential of society to solve their own problems. On the basis of the activity of all subjects of the organization of independent work of the student (teacher, tutor, representatives of social institutions and the student), it is determined that it can be considered as a social factor of constituents of society and development of opportunities of the student.
On the Hierarchical Information in a Single Contextualised Word Representation (Student Abstract)

Contextual word embeddings produced by neural language models, such as BERT or ELMo, have seen widespread application and performance gains across many Natural Language Processing tasks, suggesting rich linguistic features encoded in their representations. This work aims to investigate to what extent any linguistic hierarchical information is encoded into a single contextual embedding. Using labelled constituency trees, we train simple linear classifiers on top of single contextualised word representations for ancestor sentiment analysis tasks at multiple constituency levels of a sentence. To assess the presence of hierarchical information throughout the networks, the linear classifiers are trained using representations produced by each intermediate layer of BERT and ELMo variants. We show that with no fine-tuning, a single contextualised representation encodes enough syntactic and semantic sentence-level information to significantly outperform a non-contextual baseline for classifying 5-class sentiment of its ancestor constituents at multiple levels of the constituency tree. Additionally, we show that both LSTM and transformer architectures trained on similarly sized datasets achieve similar levels of performance on these tasks. Future work looks to expand the analysis to a wider range of NLP tasks and contextualisers.
Search Tree Pruning for Progressive Neural Architecture Search (Student Abstract)

Our neural architecture search algorithm progressively searches a tree of neural network architectures. Child nodes are created by inserting new layers determined by a transition graph into a parent network up to a maximum depth and pruned when performance is worse than its parent. This increases efficiency but makes the algorithm greedy. Simpler networks are successfully found before more complex ones that can achieve benchmark performance similar to other top-performing networks.
Shadow Detection for Ultrasound Images Using Unlabeled Data and Synthetic Shadows

Medical ultrasound is widely used technique for diagnosing internal organs. As common artifacts, shadows often appear in ultrasound images. Detecting such shadows is curious because they prevent accurate diagnosis. In this paper, we propose a novel shadow detection method based on auto-encoding structure. It once separates an input image into a shadow image and a content image using two decoders and combines them to reconstruct the input. To lead the network into separating the input, we inject synthetic shadows into the input and make the network to predict them as the shadow image. Since we know the rough shape of shadows as basic domain knowledge, we can generate plausible shadows. These processes are achieved by using only unlabeled data. Experiments on ultrasound images for fetal heart diagnosis shows the effectiveness of the method.
Implementation of Digital Archives for Teachers and Administrators at State Vocational School 16 Jakarta

The purpose of this community service is training and workshop to guide and assist teachers, employees and students in introducing and understanding and implementing digital archive management with Windows Explorer, Microsoft Office Excel, Microsoft Office Word and PHP MYSQL.. The resulting output is a digital archive book that will be useful in guiding teachers and as one of the teaching materials in carrying out education and teaching in vocational high schools. The methodology used in the implementation of this community service activity is action research activities consisting of Planning, Preparation, Implementation (actions), Observation and Evaluation and Reflection. The conclusion of community service is the implementation of community service activities through guidance and assistance with the results of increased knowledge about digital archives, skills in managing digital archives, expertise in using digital information technology and being able to apply digital archives management and support for the course of an organization.