Reviewerly/exHarmony huggingface dataset:
Design and Implementation of Database Prototype for A Portable Electronic Transaction Device

In recent times, electronic money (e-money) has gained significant popularity in the form of smartphone applications, barcodes, and smart card systems. In previous research, we have developed a smartcard-based device equipped with a dual interface to facilitate electronic transactions using contact or contactless technology. These methods involve initiating a connection with a cloud server, where all transaction data are recorded with full encryption. This device also supports payment activities, as well as checking or topping up account balances by utilizing contact and contactless smart cards, which are produced in Indonesia by PT. Xirka Silicon Technology. The aforementioned research did not explain the significance of a database which actually plays a vital role in the system’s data storage. Therefore, this research aims to provide detailed information on the design of this database. Furthermore, five web pages are designed including, token generator, token list, partner list, payments, and transactions to provide specific services requested by users via a web URL through the database that stores transaction activities carried out by the device.
Peningkatan Kualitas Manajemen Tutorial Tatap Muka Berbasis Webinar

Every management of tutorial activities, the Open University has equipped it with a set of systematic control tools to ensure course competencies can be achieved, including Tutorial Activity Design � Tutorial Activity Unit (RAT SAT), Tutorial Meeting Notes (CPT), and Attendance List of tutors and students. In the CPT document, the tutor must inform at each tutorial meeting about the lecture material based on RATSAT, the obstacles faced by students in mastering the lecture material, and follow-up to overcome related obstacles. However, CPT information still does not function optimally, such as the achievement of RAT SAT which is not clearly conveyed, or the constraints / difficulties of students in mastering certain sub-subjects. The research aims to minimize the weaknesses of tutorial control tools by utilizing software that can be accessed from tutor and student gadgets. All logging will be done in real time which can also be used in tutorial regions that have difficulty accessing internet signals. This research method is descriptive qualitative research. Thus, the University as a tutorial organizer can quickly and easily monitor and correct the weaknesses of tutorial management in its work area.�
How Students Seek Information When Studying at Home? A Case Study in Pekalongan High Schools

&#x0D; &#x0D; &#x0D; &#x0D; The Covid-19 has hampered students’ activities to visit the library. Thus, it changes students’ behavior in accessing information once studying at home. This paper studied the information seeking behavior of high school students in Pekalongan during the pandemic. This study used descriptive quantitative methods that collect research data using online questionnaires to research respondents. The research sample used the simple random sampling technique. The data was then analyzed by using descriptive statistical analysis of SPSS version 26th edition. The results showed that the information seeking behavior of high school students in Pekalongan during school from home occurs due to the Context of Information Needs (2, 88); Activating Mechanism (2.69) and risk/reward (3.07); Intervening variables in Psychological (3.08), Role-related or Interpersonal (3.37), Environmental (2.98), and Source Characteristics (2.68). Additionally, indicating the level of information seeking, Passive Search (3.07), Active Search (2.79), Ongoing Search (3.04), and Information processing and use (2.74).&#x0D; &#x0D; &#x0D; &#x0D;
IT-PMF: A Novel Community E-Commerce Recommendation Method Based on Implicit Trust

It is well-known that data sparsity and cold start are two of the open problems in recommendation system research. Numerous studies have been dedicated to dealing with those two problems. Among these, a method of introducing user context information could effectively solve the problem of data sparsity and improve the accuracy of recommendation algorithms. This study proposed a novel approach called IT-PMF (Implicit Trust-Probabilistic Matrix Factorization) based on implicit trust, which consists of local implicit trust relationships and in-group membership. The study started from generating the user commodity rating matrix based on the cumulative purchases for items according to their historical purchase records to find the similarity of purchase behaviors and the number of successful interactions between users, which represent the local implicit trust relationship between users. The user group attribute value was calculated through a fuzzy c-means clustering algorithm to obtain the user’s in-group membership. The local implicit trust relationship and the user’s in-group membership were adjusted by the adaptive weight to determine the degree of each part’s influence. Then, the author integrated the user’s score of items and the user’s implicit trust relationship into the probabilistic matrix factorization algorithm to form a trusted recommendation model based on implicit trust relationships and in-group membership. The extensive experiments were conducted using a real dataset collected from a community E-commerce platform, and the IT-PMF method had a better performance in both MAE (Mean Absolute Error) and RMSE (Root Mean Square Error) indices compared with well-known existing algorithms, such as PMF (Probabilistic Matrix Factorization) and SVD (Single Value Decomposition). The results of the experiments indicated that the introduction of implicit trust into PMF could improve the quality of recommendations.
Hubungan Persepsi dalam Pembelajaran Online dengan Kemandirian Belajar dan Prestasi Belajar Matematika Siswa SMP Negeri 17 Mataram

This correlation study aims to describe students' perceptions in online learning, learning independence, and student achievement and to determine the relationship between student perceptions in online learning and learning independence and student achievement. The population is all eighth grade students at SMP Negeri 17 Mataram for the 2020/2021 academic year. The sampling technique used purposive sampling technique and the samples obtained were students of class VIIIC. The data collection technique uses a questionnaire on student perceptions in online learning, student learning independence questionnaire, documentation, and interviews. Data analysis technique using Pearson correlation test. The results of data analysis show that: (1) students' perceptions in online learning are mostly in the sufficient category, students' learning independence is mostly in the good category and student achievement is mostly in the bad category; (2) There is a relationship between students' perceptions and learning independence and includes a positive correlation. (3) There is a correlation between students' perceptions of online learning and student achievement, including a negative correlation; (4) there is a correlation between learning independence and student achievement including a negative correlation. For this reason, apart from perceptions, learning independence and learning achievement, it is also a good idea to look at the motivation, talent and interest in student learning.
The first academic library in Krasnoyarsk (65th anniversary of the library of the Kirensky Institute of Physics of SB RAS)

The publication presents some details to the portrait of the library of the Kirensky Institute of Physics SB RAS, which has its deserved place in the row of libraries, founded in the period of active development of academic science in Siberia, accumulating acceptable practices and creating its own experience.
A Rule-based Spelling Checker for Correcting Punctuation Errors in Indonesia Text using KEBI 1.0 Checker

Punctuation errors in Indonesian often occur in Indonesian scientific writing. This error was caused intentionally and unintentionally by the author. The factor of intentional is because the author does not have time to make independent improvements after writing, while unintentional occurs because of the authors ignorance of the appropriate form of punctuation. Therefore, the punctuation error detection system in Indonesian writing was developed to overcome them. The name of the application is KEBI 1.0 Checker which was a web-based application and provided three features, namely punctuation detection, typo detection, and standard words detection. The research proposed to evaluate the performance of application based on punctuation errors using a rule-based spelling checker that can be detected were in the form of comma punctuation, hyphens in repeat words, and writing of pre-, post-, and inter- particles, as well as writing prefixes with additional English verbs. After the application was tested on ten scientific papers, KEBI 1.0 Checker showed accuracy for correcting punctuation errors reached an accuracy of 76.67%, precision of 100%, and recall of 76.67%.
Analysis of natural language processing technology: modern problems and approaches

Introduction . The article presents an overview of modern neural network models for natural language processing. Research into natural language processing is of interest as the need to process large amounts of audio and text information accumulated in recent decades has increased. The most discussed in foreign literature are the features of the processing of spoken language. The aim of the work is to present modern models of neural networks in the field of oral speech processing. Materials and Methods . Applied research on understanding spoken language is an important and far-reaching topic in the natural language processing. Listening comprehension is central to practice and presents a challenge. This study meets a method of hearing detection based on deep learning. The article briefly outlines the substantive aspects of various neural networks for speech recognition, using the main terms associated with this theory. A brief description of the main points of the transformation of neural networks into a natural language is given. Results . A retrospective analysis of foreign and domestic literary sources was carried out alongside with a description of new methods for oral speech processing, in which neural networks were used. Information about neural networks, methods of speech recognition and synthesis is provided. The work includes the results of diverse experimental works of recent years. The article elucidates the main approaches to natural language processing and their changes over time, as well as the emergence of new technologies. The major problems currently existing in this area are considered. Discussion and Conclusions . The analysis of the main aspects of speech recognition systems has shown that there is currently no universal system that would be self-learning, noise-resistant, recognizing continuous speech, capable of working with large dictionaries and at the same time having a low error rate.
I. I. Betsky’s collection in the stock of the Scientific Library of the Russian Academy of Arts

The Scientific Library of the Russian Academyof Arts is one of the most important specialized art libraries in Russia. The formation of its library collections began almost immediately after the decree of the Senate on the creation of the Academy of Arts in St. Petersburg. One of the first collections transferred to the Academy of Arts, along with the famous collection of I. I. Shuvalov, was the collection of books of the first presidentof the Academy of Arts, Ivan Ivanovich Betsky. According to the “Catalogue of books of the Imperial Academy of Arts”, compiled by the artist, academic inspector K. I. Golovachevsky in 1773, on behalf of Betsky in 1765, 69 titles of publications in 85 volumes were transferred to the Academy. The inventory was compiled entirelyin Russian, including the names of authors and titles of foreign publications, which greatly hampered the process of identifying books.Working with archival sources, online resources of foreign libraries and library catalogs madeit possible to compile an extended inventory of books with original titles and library codes.To date, the study of the collection of I. I. Betskyis at the stage of reconciliation with the inventory.The purpose of this article is to raise the issueof a comprehensive study of personal collections in the stock of the Scientific Library of the Russian Academy of Arts, and, on the example of the collection of I. I. Betsky, of the need to develop this field of library research. The published materials represent one from the methods of work on identifying individual collections: to compile according to the documents the historical reconstruction, being the base of the search for publications in the stock, carried out further, and give the general component characteristics of the collection under analysis.
Lifecycle Optimization of Smart Contract for Flexibility

&lt;div&gt;Smart contract-based methods are used to implement the blockchain applications. While smart contracts have separate pre-deployed steps, which are suitable for applications that are deployed once and invoked many times. However, there are smart contracts that are used only one time (the disposable smart contract) or few times. Pre-deployment requires an additional step and additional transactions, which bring burdens (such as longer waiting time and more transaction fees) to users. In this paper, we propose a new Lifecycle model of smart contracts, which allows combining the pre-deployment with function invocations. This facilitates the usage of the disposable smart contract, as users are only required to send one transaction to perform both the pre-deployment and the function invocation. Together with the smart contract separation, it also allows participants to customize their special smart contracts at the request time. At last, we verify the proposed model and it shows the potential to save additional burden and to facilitate the usage of the smart contract.&lt;/div&gt;
Desain Pembelajaran Pendekatan Discovery Learning dengan Menerapkan Pembelajaran dari Finlandia

This study aims to provide alternative solutions from learning using discovery learning approach learning design by applying learning from Finland. A learning design is used to create a learning model in this piece of literature. Students' requirements are taken into consideration throughout the development process. Discussed in depth, learning outcomes are tailored to the instructional goals. As a consequence of the findings of this research, educators who want to teach statistics using group data may consider adopting a method inspired by Finnish research and practice. This lesson is divided into small parts and starts from the basic understanding of statistics that students need.&#x0D;
Benefits of Pod dimensioning with best-effort resources in bare metal cloud native deployments

&lt;p&gt;Existing container orchestration platforms provide frameworks capable of automatically scaling resources to evolving traffic conditions based on resource usage. Service providers rely on these automatic scaling capabilities to improve the traffic adaptability of their cloud native applications while reducing costs. However, this may lead to service degradation related to the delayed response to the traffic changes. Traditionally, Pod dimensioning has been performed considering guaranteed (or request) resources. Recently, container orchestration platforms included the possibility to allow Pods to use idle resources that can be withheld for a short period of time in a best-effort fashion (known as limit resources). This paper analyzes the potential of limit resources as a way to mitigate degradation while reducing the amount of request resources. Results for a sample case show that a strategy relying on limit resources achieves the same level of degradation as a conventional strategy that uses only request resources, while reducing requested CPU by 25%.&lt;/p&gt;
Building Process-Oriented Data Science Solutions for Real-World Healthcare

The COVID-19 pandemic has highlighted some of the opportunities, problems and barriers facing the application of Artificial Intelligence to the medical domain. It is becoming increasingly important to determine how Artificial Intelligence will help healthcare providers understand and improve the daily practice of medicine. As a part of the Artificial Intelligence research field, the Process-Oriented Data Science community has been active in the analysis of this situation and in identifying current challenges and available solutions. We have identified a need to integrate the best efforts made by the community to ensure that promised improvements to care processes can be achieved in real healthcare. In this paper, we argue that it is necessary to provide appropriate tools to support medical experts and that frequent, interactive communication between medical experts and data miners is needed to co-create solutions. Process-Oriented Data Science, and specifically concrete techniques such as Process Mining, can offer an easy to manage set of tools for developing understandable and explainable Artificial Intelligence solutions. Process Mining offers tools, methods and a data driven approach that can involve medical experts in the process of co-discovering real-world evidence in an interactive way. It is time for Process-Oriented Data scientists to collaborate more closely with healthcare professionals to provide and build useful, understandable solutions that answer practical questions in daily practice. With a shared vision, we should be better prepared to meet the complex challenges that will shape the future of healthcare.
New lower bounds for the number of ACG codes over F_4

In this paper we consider additive circulant graph (ACG) codes over F_4 of length n &gt;= 34 and we present some new results for the number of these codes. The most important result is that there exists a unique ACG code over F_4 of length 36 and minimum weight 11.
Readiness Analysis of Structure Smart City in Wonogiri Regency

Digital transformation is happening at a rapid pace. Local governments are forced to adapt to the fast-changing technology. however, not all local governments are able to adapt to the changing digital environment. then there needs to be preparation for the implementation of digital-based local governance or often called a smart city.This paper focuses on analyzing the readiness of Wonogiri Regency in implementing a smart city, especially structural readiness. Researchers collected data by interviewing informants and secondary data. The results of the study show based on the structure, Wonogiri Regency is quite ready to organize a smart city.
Non-Adaptive and Adaptive Two-Sided Search with Fast Objects

In 1946, Koopman introduced a two-sided search model. In this model, a searched object is active and can move, at most, one step after each test. We analyze the model of a combinatorial two-sided search by allowing more moves of the searched object after each test. We give strategies and show that they are optimal. We consider adaptive and non-adaptive strategies. We show the surprising result that with the combinatorial two-sided search on a path graph, the optimal non-adaptive search needs the same number of tests as the corresponding adaptive strategy does. The strategy obtained can also be used as a encoding strategy to sent the position of a moving element through a transmission channel.
A Study on Emotions Expressed in the Aesthetics of the Mind

This study is to examine whether the feelings of joy, anger, sadness, and joy were expressed as the aesthetics of the mind by approaching Wang Yangming's aesthetics as a category of art education. To this end, art classes were applied to art majors at universities, and through the analysis criteria for works, students' understanding of the aesthetics of the mind and whether originality, the core of the aesthetics of the mind, was expressed as a level of painting. As a result, it was confirmed that various elements of action originated from the intuitive mind, and aesthetic objects and aesthetic interests interact to diagnose the inner world and to be self-sufficient by the action of the body of the mind, resulting in original and unique aesthetics, that is, strange aesthetics. In addition, it is possible to confirm the establishment of subjectivity, practical, reflective, and self-reflection that one realizes and obtains through internal awareness according to the main body of the mind. The aesthetics of the mind can be said to be the most basic major concept to be recognized in art education. The aesthetic value of the mind is moral, practical, and self-sufficient education, and it can be confirmed that their mutual relationship can be linked to the emotion of art education. Therefore, Wang Yangming's aesthetic of mind can be said to be an educational philosophy suitable for basic education in the present era, which is being transitioned to a value-respecting society. In addition, all emotions expressed from the heart are a source of creativity, suggesting the possibility that they can be linked to the orientation of basic education in art and to liberal arts or aesthetic education.
Sports Video Motion Direction Detection and Target Tracking Algorithm Based on Convolutional Neural Network

In order to effectively detect and monitor athletes and record various motion data of targets, the study suggests a study of target tracking algorithms to detect the direction of motion video sports movement based on the neural network. A class of feedforward neural networks with convolutional computation and deep structure is one of the representative algorithms of deep learning. Firstly, the athlete image is obtained from the video frame; combined with the nonathlete image to construct the training set, use the bootstrapping algorithm to train the convolutional neural network classifier. In the case of input picture frames, pyramids of different scales are then constructed by subsampling, and the location of many candidate athletes is detected by a neural network of disruption. Finally, these centers calculate the center of gravity of the athletes, find the athlete to represent the candidate, and determine the location of the final athlete through a local search process. The results of the experiment show that the proposed scheme of 6000 frames in the two game videos is compared with the AdaBoost scheme, and the detection rate of the proposed scheme is 75.41% to calculate the average detection accuracy and false alarm speed of all players. The detection rate is higher than the AdaBoost scheme. Therefore, this scheme has a high detection rate and low false positives.
False Negative Reduction in Semantic Segmentation under Domain Shift using Depth Estimation

State-of-the-art deep neural networks demonstrate outstanding performance in semantic segmentation. However, their performance is tied to the domain represented by the training data. Open world scenarios cause inaccurate predictions which is hazardous in safety relevant applications like automated driving. In this work, we enhance semantic segmentation predictions using monocular depth estimation to improve segmentation by reducing the occurrence of non-detected objects in presence of domain shift. To this end, we infer a depth heatmap via a modified segmentation network which generates foreground-background masks, operating in parallel to a given semantic segmentation network. Both segmentation masks are aggregated with a focus on foreground classes (here road users) to reduce false negatives. To also reduce the occurrence of false positives, we apply a pruning based on uncertainty estimates. Our approach is modular in a sense that it post-processes the output of any semantic segmentation network. In our experiments, we observe less non-detected objects of most important classes and an enhanced generalization to other domains compared to the basic semantic segmentation prediction.