Reviewerly/exHarmony huggingface dataset:
IT Implementation Processes in Libraries: Adopting Foreign Experience

Objective. The purpose of the article is to study the problems of implementing IT technologies in university libraries of Ukraine in the context of foreign experience. The article examines the retrospective of development of library information systems, their effectiveness and problematic issues related to the transition of library staff to work with them. Methods. When writing the article, the review, comparative, and historical methods were used to summarize the research on the development of library information systems and to choose a sufficiently effective and convenient system among ILS (Integrated Library System), LSP (Library Service Platform), LMS (Library Management System) or LIMS (Library Information Management System) for domestic university libraries. Results. The article provides a periodization of the development of library systems from 1931 till 2022. Problematic issues for Ukrainian university libraries related to the replacement of software tools with modern software products are identified. Specialists of higher education libraries are suggested to use the web-resource “Library Technology Guides” to select the latest innovative automated library systems with their subsequent configuration. Conclusions. As a result, the ILS Koha is proposed as more adapted system in terms of financial costs and possibility of its further maintenance by existing specialists.
Comparison among Additive Time Series, Multiplicative Time Series, Holt Winter Additive and Holt Winter Multiplicative Methods in Forecasting the Number of Foreign Tourists Visit to Riau Islands Province

Comparison among Additive Time Series, Multiplicative Time Series, Holt Winter Additive and Holt Winter Multiplicative Methods in Forecasting the Number of Foreign Tourists Visit to Riau Islands Province
Implementasi Support Vector Machine Pada Alat Monitoring Kecelakaan Dengan Intelligent Transport System

The implementation of intelligent transportation systems will produce a large amount of data. The resulting data is critical in the design and implementation of ITS in the transportation system. This study discusses the performance of the Support Vector Machine algorithm on an accident monitoring tool by utilizing the Intelligent Transportation System that works in real-time using an Android-based application. This experiment simulates accident monitoring with a multisensor accident monitoring device. Multisensor technology consists of MPU 6050 sensor, sound sensor, vibration sensor, and camera. In an experiment, the measured variables are location, slope, accuracy, and time of the traffic accident monitoring system. The results of monitoring traffic accidents in testing using the Support Vector Machine algorithm can work well by classifying data based on the type of accident.
POS Tagger Improvisation with the Addition of Foreign Word Labels on Telkom University News

News is a medium of daily information usually obtained by the public. The news consists of a lot of information in it and is composed of sentence structures. Each language is unique with its own sentence structure, like Indonesian and other foreign languages. But nowadays, many media mix Indonesian with foreign languages, making the sentence structure different from Bahasa Indonesia. To classify these words, Part Of Speech Tagging needed to determine the class of words composed of sentences by learning from the Corpus of each language. With the new sentence structure, POS Tagger requires a larger Corpus to learn. The language structure can determine the results of tagging from the POS Tagger. If there are words that are not in the Corpus, it can reduce the accuracy of the POS Tagger. We conducted to enhance the research results by adding data with a different sentence structure from the Indonesian Language Corpus using sentences from online media. Added about 242 sentences with 7,043 tokens on Corpus focused on Foreign Word tags, which total 3819 tags. After doing some testing and scenarios, the results of the accuracy of POS Tagger show an accuracy of 94.7% using the Hidden Markov Model method with the F1-Score tag FW 78%.
Perancangan Aplikasi Android pada Alat Monitoring Kecelakaan dengan Intellegent Transport System

The increasing number of transportation also increases the number of traffic accidents. It can happen not only in the open road but also in the quiet road so that the bad things can happen to the accident victims. The delays of handling the accidents often occur due to the delay information that received by the police or the nearest hospital. This is due to the information that obtained by local people and forwarded to the authorities is slow. Therefore a system that can monitor the vehicle remotely will be needed nowdays. By building an accident monitoring system using the Intelligent Transport System (ITS), it is hoped that it can monitor the vehicle and through Android can directly check the coordinates of the vehicle and the condition of the vehicle. In the design of the accident monitoring system tool using the SVM (Support Vector Machine) method. Testing this tool uses hardware consisting of Rasberry PI 3, Arduino Uno, Sensor FC04, Accelerometer 6050, Vibration Shock Sensor, Camera Pi Noir, panic button, GPS and Android Application as an interface with the user. The results of this research show that the tool made has a percentage of delays between 1 to 5 seconds, all data from the accident monitoring system tool is directly sent to the Android application in real time based on the internet network speed connection
Nomadic Schools in the System of the State National Policy in the Russian North: Advantages and Limitations

One of the main tasks of the state national policy in the Russian Federation is to ensure ethno-cultural and linguistic diversity through the improvement of the education system.At the same time, the strategic priorities for the development of the northern territories of the country are focused on increasing the availability of quality general education.Nomadic schools for indigenous small-numbered peoples of the North, leading a nomadic or semi-nomadic lifestyle, perform educational, socio-pedagogical, and sociocultural functions.The article presents the results of a qualitative content analysis of scientific literature (n=54) concerning functioning and description of the nomadic schools experience in the northern regions of Russia.Nomadic schools are characterized as ungraded schools with socio-cultural and national-regional components in education, and the flexibility of the educational process.Among the advantages of this form of education are the availability of education, and a differentiated approach to students.The cost of creation and functioning of nomadic schools, the lack of a regulatory framework for regulating their activities at the federal level, undeveloped organizational and scientific and methodological issues of nomadic education, as well as the shortage of teaching staff for this form of educational institution can be considered as disadvantages.Conclusions about the need to develop a unified approach to the testing and implementation of different types of nomadic schools are formulated.
Mission-Aware Value of Information Censoring for Distributed Filtering

In this paper, we study the problem of distributed estimation with an emphasis on communication-efficiency. The proposed algorithm is based on a windowed maximum a posteriori (MAP) estimation problem, wherein each agent in the network locally computes a Kalman-like filter estimate that approximates the centralized MAP solution. Information sharing among agents is restricted to their neighbors only, with guarantees on overall estimate consistency provided via logarithmic opinion pooling. The problem is efficiently distributed using the alternating direction method of multipliers (ADMM), whose overall communication usage is further reduced by a value of information (VoI) censoring mechanism, wherein agents only transmit their primal-dual iterates when deemed valuable to do so. The proposed censoring mechanism is mission-aware, enabling a globally efficient use of communication resources while guaranteeing possibly different local estimation requirements. To illustrate the validity of the approach we perform simulations in a target tracking scenario.
Back Cover: Generation and Structuring of Multipartite Entanglement in a Josephson Parametric System (Adv. Quantum Technol. 1/2023)

Highly entangled multimode states in continuous variables are a valuable resource in quantum information. The cover illustrates the 4-partite correlations of microwave modes generated from electromagnetic vacuum via three-wave mixing process in a Josephson parametric amplifier by using three pumps. As shown in article number 2200031 by Kirill Viktorovich Petrovnin, Pertti Juhani Hakonen, and co-workers, this results in genuine multipartite entanglement. A fully controllable pump scheme can provide a comprehensive manipulation of the structure of the generated entangled states.
The Genesis of GENDY3. The Creative Process that Led to Xenakis' Opus Summum

Gendy 3 (1991) by Iannis Xenakis is the culmination of his lifelong quest for an automated (i.e. algorithmic) music. About 20 minutes of digital sound are computed directto- disk and presented more or less as such to the public. Therefore, Gendy 3 demonstrates the machine computability of a work of art. Officially, there is only one Gendy 3 in Xenakis' catalogue of works. However, before the world premiere of Gendy 3 on 11/17/1991 in Metz, France, Xenakis presented a proto version called GENDY301 at ICMC Montreal on 10/18/1991, which is a similar but completely different piece. Moreover, an uncut “raw” version (I call it “GENDY3”) can be obtained by re-executing Xenakis' own algorithm. It contains 75 seconds more music than Gendy 3. And finally, Xenakis' algorithm also allows creating a 16-track version by generating all of its 16 layers of sound separately. These 4 versions (2 by Xenakis, 2 by the author), taken together, help to retrace the creative process that led to one of the most remarkable pieces of electroacoustic music to date.
Sign Language Recognition

Abstract: People communicate using sign language by visually conveying sign patterns to portray purpose. One method of communicating with deaf-mute people is to use sign language mechanisms. One of the nonverbal communication strategies used in sign language is the hand gesture. Many manufacturers all over the world have created various sign language systems, but they are neither adaptable nor cost-effective for end users. We present a design that can recognize various American sign language static hand motions in real-time using transfer learning, Python, and OpenCV in this paper. “Hello, Yes, No, Thank You, and I Love You" are all prevalent sign language terms that our system correctly acknowledges. The following are the key steps in system design; we created our own dataset taking prominent gestures of the American Sign Language, captured images with OpenCV and webcam, the images were then labelled for object detection, training and testing of dataset was done with transfer learning using SSD MobileNet, and eventually the gestures were successfully determined in real-time.
Tool for the selection of software development methodologies for small projects and small equipment

There is no single, universal software development methodology that applies to all cases. However, there is one that is better adapted to each type of project, the particularity of each of them requires a detailed arrangement of the activities, whether they are associated with traditional, agile or hybrid methodologies. Considering that small projects and small teams are the ones that mostly lack a methodological framework to guide them, the article presents a methodological tool that helps the project manager of small groups of developers to visualize which methodology to apply. to better face the software project and reduce its risks. Our preliminary results demonstrate the effectiveness of the tool, being well evaluated in the projects involved in the test cases. In addition, it can be affirmed that the need to guide the development methodology was resolved by automating a previously developed framework.
Preliminary results with BERT for human activity recognition using skeleton sequences features

The use of artificial intelligence techniques for the recognition of human activity has been an important area of research. Several approaches have been proposed and a large part of them address this problem through vision with conventional RGB cameras. Some of the most significant problems in human activity recognition systems are privacy, the limitations of the operating devices and the comparison of machine learning and deep learning techniques for the prediction of said activity. The present document presents an activity recognition system by means of a recurrent neural network BERT, based on camera vision, using image sequences containing the information of the detection of the pose of the human skeleton for the extraction of characteristics. The proposed method is evaluated with the UP-Fall data-set, outperforming the results of other activity recognition systems that use deep learning techniques and the same data-set. This method achieves an accuracy of 99.14% and a F1-Score of 80.95%.
Alat Monitoring Kecelakaan Dengan Intelligent Transport System Berbasis Internet of Things

Accidents are one of the problems that are always faced in big cities. This is evident from the indications that traffic accident numbers are always increasing. Delays in handling accidents often occur due to delays in information received by the police and nearby hospitals. Therefore, a remote monitoring system is needed to control vehicles that are operating in real time using monitoring tools that are able to detect traffic accidents and emergency events on the way In this study, the Internet of Things-based Intelligent Transport System was applied using the Support Vector Machine method whose design was carried out using accelerometer sensors, vibrating sensors and sound sensors with the addition of NEO 6M GPS as a coordinate point information provider and a PI NoIR Camera to capture images of surrounding conditions when an accident occurred. The way this tool works is that when there is an accident in a vehicle (car) this tool has been installed with various sensors and components that are able to analyze the surrounding situation if this car has an accident, it will send data that will be displayed in the Android application in the form of time data, coordinates, vibration, sound and images.
Sistem Pendukung Keputusan Penerimaan Bantuan Dana Desa BLT dengan Metode SAW Berbasis WEB

The object of research that will be made is to determine the receipt of village funds in the village of Kampung Melayu, namely Direct Cash Assistance (BLT) according to system rules. The purpose of previous research regarding research on determining recipients of rice social assistance to the poor in Kampung Melayu village with the Simple Additive Weighting (SAW) method aims to determine prospective recipients of poor rice to complete practical decision making and have alternative choices for decision making in order to determine poor people who are entitled to receive rice social assistance for the poor (Raskin) in the village. Based on the criteria used to determine the decision to receive rice social assistance for the poor, namely the amount of income, marital status, number of dependents and age. The results of this study are shown for the village government to be able to determine the people who are entitled to receive social assistance for poor rice (Raskin)
Preliminary results on anomaly detection and recognition in spacecraft telemetry

Space missions are critical systems that must cope with extreme conditions such as temperature changes, radiation and vibration. Due to the complexity of their structure and operation, these systems are designed in such a way that they can mitigate errors and handle critical situations. The only available communication link and way by which the ground station can monitor the health of the satellite and act upon possible failures is status telemetry. This paper presents the implementation of a machine learning-based anomaly detection system for satellite telemetry; the data used corresponds to a NASA public database of telemetry channels from the Soil Moisture Active Passive (SMAP) mission. In order to get all the possible information from the signals, a feature extraction phase was carried out defining three detectors based on recurrent neural networks (RNN), moving average (MA) and Fourier transform, respectively. An AdaBoost algorithm was trained to perform anomaly classification. The proposed system was evaluated using data partitioning into training and test sets. The results show that we can achieve performance comparable to the original anomaly detection method under the same dataset using a supervised method which incorporates knowledge about the frequency, magnitude and waveform of known anomalies.
COMPARATIVE ANALYSIS OF DIMENSIONAL CHARACTERISTICS FOR PARTICLES OF HYBRID AND MINERAL ADSORBENTS FOR WATER PURIFICATION PROCESSES

n the work, a comparative morphometric analysis of various types of domestic adsorbents intended for use in water purification technologies is performed. Four types of adsorbents were investigated: «Möbius» carbon adsorbent, P1T1KA clay powder of the montmorillonite type, DG-100 carbon black, C-1 colloidal graphite preparation.Morphometric analysis of adsorbent particles was carried out by the method of optical polarization microscopy («Bi-olam» brand microscope). Photomicrographs of particles pre-dispersed in the immersion liquid were obtained using a digital camera with a high-resolution matrix. Quantitative assessment of the sizes of adsorbent particles was carried out by the method of digital image analysis (ImageJ software package). The area and perimeter of individual particles were determined and their equivalent diameter and shape index were calculated. Statistical processing of experimental data was carried out using the «Statistica» software package.It was established that the nature of the distribution of particles of the investigated types of adsorbents in terms of equiv-alent diameter depends on the type of sample, and may be complicated by the processes of particle aggregation.It is shown that a similar nature of distribution is observed for all investigated carbon adsorbents according to the shape index. The pronounced and largest fraction (27-37%) corresponds to particles with a shape close to round. The most acceptable adsorbents for water purification processes can be considered a colloidal graphite preparation and clay powder of the mont-morillonite type, for which there is a higher homogeneity of the distribution of particles according to the shape indicator. This, in turn, can provide higher sorption efficiency in water treatment technologies.The application of the method of optical polarization microscopy in combination with the morphometric analysis of particles makes it possible to reasonably approach the selection of the brand of adsorbents for their use in water purification technologies. Further research in this direction can be directed to the processes of surface modification of adsorbent particles to increase their specific capacity and selective ability.
Providing Membership Privacy to the Asynchronous Ratcheting Trees Protocol without losing Scalability

A secure messaging protocol, such as the Signal protocol, provides end-to-end encrypted asynchronous communication. This paper focuses on a secure group messaging (SGM) protocol, and proposes a method capable of hiding membership information from the viewpoint of non group members, which we call “membership privacy”. In this work, we add membership privacy to the Asynchronous Ratcheting Trees (ART) protocol (proposed by Cohn-Gordon et al., (ACM CCS 2018)). For hiding membership-related values in the setup phase, we employ a key-private and robust publickey encryption (Abdalla et al., TCC2010/JoC2018). Moreover, we introduce a group common key to encrypt membership information in the key update phase. Our modification achieves asymptotically the same efficiency of the ART protocol in the setup phase. Any additional cost for key update does not depend on the number of group members. Therefore, the proposed protocol can add membership privacy to the ART protocol with a quite small overhead. Specifically, one encryption and decryption of a symmetric-key encryption scheme and one execution of a key-derivation function for each key update are employed. Finally, we discuss how to extend our protocol to provide sender-specific authentication, dynamic groups, group-size hiding, and how to adopt our technique to the Messaging Layer Security (MLS) protocol. We note that, although Chase et al. (ACM CCS 2020) have considered the same notion, their proposal is an extension of Signal so called “Pairwise Signal” where a group message is repeatedly sent over individual Signal channels. Thus their protocol is not scalable.
The Mind set of a Beauty Learner The Effect of Learning Immersion and Intention on Learning Continuity

This study attempted to unveil structural relationships among learners’ mindset, learning flow and intention to continue learning and help beauty service learners have a desirable perception. For this, a self-administered questionnaire survey was performed against a total of 320 adult beauty service learners in their 20-50s in Busan from July 18 to 25, 2022. They voluntarily participated in the survey with an understanding of its purposes. Effective samples were collected and analyzed by SPSS 25.0, and the results found the followings: First, no significant learning flow was found in beauty service learners with a fixed mindset while high learning flow was observed in those with a growth mindset. Second, an intention to continue learning wasn’t found in beauty service learners with a fixed mindset while an intention to continue learning was observed among those with a growth mindset. Third, both cognitive commitment and affective commitment revealed an intention to continue learning. The above results show that those with a growth mindset are committed to learning for their continuous growth and development and disclose their will to continue learning. In contrast, those with a fixed mindset are aware of their limit and reveal passive learning commitment, losing their intention to continue learning. It is anticipated that the study results provide an implication which is needed to help beauty service learners find a way to improve a growth mindset.
Research on Intelligent Analysis and Processing Technology of Financial Big Data Education Based on DM Algorithm

Aiming at the problem of account risk discrimination and prediction in financial system, an intelligent analysis and processing technology based on K-means clustering algorithm study the analysis and processing technology of financial data in detail, this paper fully analyzes various management requirements of the financial system, and completes the automatic execution of a large number of standardized financial work and the identification, prediction and analysis of account risk by using process automation technology and neural network algorithm. In addition, by introducing k-means algorithm, this paper studies and classifies, so as to realize the comprehensive analysis and evaluation of various abilities such as debt repayment, development, operation and profitability of financial accounts, so as to avoid the one sidedness and subjectivity of artificial risk evaluation to a great extent.