Reviewerly/exHarmony huggingface dataset:
Modern technologies of adult education

The motivation to constant knowledge update is due to the dynamic scientific and technological progress, which affects the change of all spheres of human activity. Employees of many organizations are in need of both professional development as well as obtaining a new specialty in order to maintain and improve their own competitiveness. In these conditions, higher educational institutions focused on adults training, are looking for new ways that will improve the formation of adult students competence. The purpose of the article is to analyze the experience of modern technologies implementation in the process of adult education. The article reveals the possibilities of innovative educational technologies, their essence and role in modern professional education. The role of continuous adult students education is emphasized, their functions are highlighted. The authors have identified the features on which the teacher relies in the process of adults training, which helps to make the training more effective. The implementation of modern adult education is based on the following principles: problematical character (the teacher should remember that adult students may feel uncomfortable in a group, they may be unaccustomed to feel like students again, for this it is necessary to "immerse" them in favorable conditions of communication. Role-playing, "brain storm" (which is more often referred to as discussion technologies, but in gaming it also takes place), blitz games contribute to the removal of emotional tension and the formation of effective cognitive motivation; the principle of dialogical communication.The study conducted among students of professional development courses from the age of 32 to 45 showed the need for further introduction of modern educational technologies in adult education. Their capabilities make the learning process more intense, active, and at the same time contribute to the rapid achievement of positive results.
Mapping Land Suitability for Sugar Cane Production Using K-means Algorithm with Leaflets Library to Support Food Sovereignty in Central Java

Indonesia is the largest sugar importer country in the world, this is contrary to the government's desire to realize sugar self-sufficiency. To overcome the dependence on sugar imports in order to support national food sovereignty, geographic information system technology (GIS) can be used to present information as material for consideration by the government in determining policies on the management of sugar cane land resources. The K-means algorithm is used to group regions according to production level, while the Matching method is for evaluating the suitability of sugarcane land. Presentation of data in the form of map visualization on the web using a new model in processing land data, where this model processes production grouping data, and land suitability class data in the form of GeoJSON then mapped with the help of Leaflets. This new model enables dynamic land data processing and visualization in the form of interactive maps. The results of the EUCS test for GIS mapping of Land Suitability and Cane Production are 3.23 (Satisfied) of the total score of 4, so this system can be accepted by the user.
ID Photo Verification by Face Recognition

These days the important documents are said to be shown as proofs for verification, most of the documents consist of photo. The problem is to compare the face from ID card to real face. So that we are in need for face comparison with the real face and photo, which is done by biometrics, using the face recognition method. There are some initial problems like based on light intensity and etc. These can be overcome by the transformation of the face, which is done by illumination invariant method proposed in Viola and Jones algorithm, classification of images done and continued with principal component analysis, all such methodologies are included in the image pre-processing. After the transformation, the recognition process is done by the use of Eigen faces for cross comparing with the real time faces to ID photo.
A New Limit Theorem for Quantum Walk in Terms of Quantum Bernoulli Noises

In this paper, we consider limit probability distributions of the quantum walk recently introduced by Wang and Ye (C.S. Wang and X.J. Ye, Quantum walk in terms of quantum Bernoulli noises, Quantum Inf. Process. 15 (2016), no. 5, 1897–1908). We first establish several technical theorems, which themselves are also interesting. Then, by using these theorems, we prove that, for a wide range of choices of the initial state, the above-mentioned quantum walk has a limit probability distribution of standard Gauss type, which actually gives a new limit theorem for the walk.
Reporting, recording, and communication of COVID-19 cases in workplace: data protection as a moving target

In response to concerns related to privacy in the context of coronavirus disease 2019 (COVID-19), recently European and national Data Protection Authorities (DPAs) issued guidelines and recommendations addressing a variety of issues related to the processing of personal data for preventive purposes. One of the recurring questions in these guidelines is related to the rights and responsibilities of employers and employees in reporting, recording, and communicating COVID-19 cases in workplace. National DPAs in some cases adopted different approaches regarding duties in reporting and communicating the COVID-19 cases; however, they unanimously stressed the importance of adopting privacy-preserving approaches to avoid raising concerns about surveillance and stigmatization. We stress that in view of the increasing use of new data collection and sharing tools such as 'tracing and warning' apps, the associated privacy-related risks should be evaluated on an ongoing manner. In addition, the intricacies of different settings where such apps may be used should be taken into consideration when assessing the associated risks and benefits.
Learning Logic Gate through 7-Gates Game

This game is based on Logic Gates that invented by Walther Bothe in 1924 and improvised by Konrad Zuse (from 1935 – 1938). This game is a simple method for a student that try to learn in Logic Gates, an educational game with futuristic adventure. The only way for the player to save the digital world in this game by using Logic Gates, with Logic Gates formulas the player can make the power connection on the circuit to the digital world engine. Without knowing how Logic Gates functional will make the player losing the power for the engine to the digital world. 7 Gates Digital World is a complex genre game. The main genre for this game absolutely is an Educational Game. Although, the game developer made a complex genre for this educational game. Puzzle include in this game combined with platforms games style the player must collect all the switches in confusion platform map to go through the next portal to the next level. Educational genre in this game giving the content level completely based on the level of understanding and give the player to memorize every gates formula.
Nonlinear effects on the dynamics of quantum harmonic modes coupled through angular momentum

Abstract We investigate nonlinear effects on the dynamics of entanglement and other quantum observables in a system of two harmonic modes coupled through angular momentum. The nonlinearity arises from a Kerr-type anharmonic term in each mode. The emergence and evolution of entanglement, non-Gaussianity, photon number, photon antibunching and squeezing are examined for different initial coherent product states and couplings, through exact diagonalization in a truncated basis. It is shown that the anharmonic terms, even if weak, can lead to very significant effects for such initial states, considerably enhancing and stabilizing entanglement and leading to a non negligible non-Gaussianity of the evolved states. They also affect other observables, stabilizing the dynamics after an initial transient regime, for not too small initial average populations of each mode. Analytic short-time approximate expressions are also provided.
COMPARISON OF DATA MINING CLASSIFICATION ALGORITHM FOR PREDICTING THE PERFORMANCE OF HIGH SCHOOL STUDENTS

Data Mining is a series of processes to explore added value in the form of unknown information manually from the database. In the world of data mining education can be used to obtain information about student performance. In this study the researchers took research samples from class XI (eleven) students at SMAN 3 Ambon by classifying student performance based on thirteen attributes, namely: age, sex, school organization, extracurricular activities, pocket money, duration of study at home, duration of social media, online game duration, attendance, illness, permits, semester 1 and semester 2 grades. Using the KDD (Knowledge Discovery Database) method and classification algorithm that will be used, namely, decision tree, Naïve Bayes and K-Nearest Neighbor. And then do the test using k-fold cross validation.
On the Use of Federal Scientific Telecommunication Infrastructure for High Performance Computing

The article is devoted to the prospects for the development of scientific telecommunications infrastructure based on the new generation national research computer network (NRCN), formed by the integration of departmental scientific and educational networks RUNNet and RASNet. The new network\prime capabilities for combining supercomputer resources and providing barrier-free access to them are shown. Based on the generalized world experience, it has been shown that supercomputer infrastructures have special requirements for a telecommunication network for data transmission and the presence of a number of additional services. These requirements go far beyond the services of commercial telecom providers and, as a rule, can only be satisfied by the combined efforts of national scientific and educational networks. The key elements of the federal telecommunications infrastructure necessary for combining high-performance computing resources are considered: high-performance communication channels with a specified quality of service, their automatic allocation on demand and on schedule, trusted network environment, federated authentication and authorization, reliability and security, end-to-end monitoring of the data transmission path between end users. Based on the analysis of the life cycle of the supercomputer job migrating at the distributed network, the requirements for the NRCN telecommunications infrastructure and services based on it are formulated.
Learning Logic Gates Using Augmented Reality

Augmented reality (AR) is a new form as integration of technologies that overlays computer-generated information on real world believed would help students in learning process. Hence, educators have begun to seek technologies that have the potential to be integrated in education in order to help students learn actively and improve their understanding. The focus of this research is on development of mobile application on logic gates topic with three inputs by using augmented reality technology for Computer Architecture and Organization Subject in University Pendidikan Sultan Idris (UPSI). Students have difficulty to understand logic gates besides less usage of mobile application on augmented reality in logic gates topic, this application could help them understand logic gates easily and effectively. By using ADDIE model, evaluation phase included pre-test and post-test have been carried out on target user as to see the improvement when using this mobile application. The result of finding show that the improvement percentage is 56%. Hence, this mobile Apps of AR technology could enhance the traditional forms of teaching and learning in order to improve student knowledge and interest about Logic Gates and also encourage students to think critically and creatively which improves their understanding and experiences using technology while learn.
Constructions and Attacks on Hash Functions

This paper presents a study about the construction models that are used to build hash functions. The study covers Merkle-Damgård, Sponge, HAIFA, Wide-Pipe, and Parallel-Tree constructions. Moreover, attacks on hash functions are also discussed in this paper. The major attacks on hash functions are presented with counter-attack methodology from the literature. This work helps the researchers in the area of cryptography hash functions to avoid any possibility of security threats in future designs.
A novel routing verification approach based on blockchain for inter-domain routing in smart metropolitan area networks

In recent years, with the continuous expansion of metropolitan area networks, the routing security problem has become more and more serious. In particular, promise-violating attack to inter-domain routing protocol is one of the most difficult attacks to defend, which always leads to serious consequences, such as maliciously attracting traffic and disrupting the network. To deal with such attack, current research generally adopts routing verification. However, it can only detect attacks violating a specific routing policy triggered by one malicious node, and no research has yet solved the problem caused by multiple collusion nodes. In this paper, we propose BRVM, a blockchain-based routing verification model, to address the issue that violating the shortest AS Path policy. The main idea of BRVM is to construct a route proof chain to verify whether a route violates the policy with the help of the blockchain technology. The precondition that avoiding the collusion attack is that the proportion of the malicious verification nodes is lower than the fault tolerance rate of the consensus algorithm. Then, we prove the correctness of BRVM in theory, and implement a prototype based on Quagga and Hyperledger Fabric. Some experiments on this prototype show that BRVM can indeed solve the promise-violating problem caused by multiple collusion nodes, and about 15.5% faster in performance compared with SPIDeR.
Knowledge Decentralization in the Age of Blockchain: Developing a Knowledge-Transfer System Using Digital Assets

Disruptive technologies have reshaped the way governance, regulations and businesses plan their medium- to long-term development strategies, affecting our socio-economic and cultural environments in a number of ways. Blockchain in general, and its applications in corporations, medical services, archiving or investment, in particular, is a phenomenon whose significance is yet to be fully explored. Big corporations like Microsoft and Walmart are already integrating blockchain for cloud services, smart contracts or food chain databases. As the adoption of the blockchain is increasing, we will witness the discovery of more ways to make organizational processes run even more smoothly. The aim of our chapter is to challenge the traditional ways to perceive organizational knowledge by creating a model that allows the application of private Blockchains to knowledge evolution, ownership and transfer. Socio-economic and cultural aspects of integrating blockchain in the knowledge transfer systems would be discussed and our focus will be to explore the effectiveness of such a system and its impact on intellectual capital.
State Estimation for Linear Dynamic System With Multiple-Step Random Delays Using High-Order Markov Chain

To cope with the large state estimation error due to sensor delay, a novel flexible model is explored to describe a linear dynamic system with multiple-step random delays in this paper. Compared with existing models, this model is more consistent with the actual situation. Based on the new model, the main difficulty, which is to determine the probability of any number of steps delayed, is overcome by applying techniques of high-order Markov chain. Then, the Kalman filtering problem with measurement delays is converted to random parameter matrices Kalman filtering(RKF), the new approximate state estimators are proposed. For a n-step random delay model, we prove that it can be treated as a (2n-1)th-order Markov chain, making it theoretically feasible to apply the method in this paper to deal with any multiple-step delay model. Some illustrative numerical examples are presented to demonstrate the efficiency of the new model and superiority over existing algorithms.
Ruang kelas virtual: pembelajaran dengan pemanfaatan permainan online Hago

Game users today have a lot, ranging from children to adults. Even parents are now starting to play the game as free time to get rid of boredom. Online games are now a favorite for users. The Hago application not only presents a number of game options, but the application can be used in the world of education, such as the use of chat rooms with several menu choices in it. With the chat room feature, users can communicate remotely, especially students and teachers in terms of learning. The purpose of this study is to describe the use of Hago chat Room as a virtal classroom for students. The type of research is descriptive qualitative. The data in the form of recorded chat room user conversations, while the data source in this study is the chat room menus in Hago. Data collection techniques are done by recording several menus in the chat room and data analysis techniques, namely analyzing the menus in the chat room into a virtual classroom. The results showed that the chat room has benefits in the world of education, namely virtual classrooms by utilizing the menus in the chat room.
Retrospective Analysis of Emergency Medical Services (EMS) Physician Medical Control Calls

Introduction: Although emergency medical services (EMS) standing-order protocols provide more efficient and accurate on-scene management by paramedics, online medical direction (OLMD) has not been eliminated from practice. In this modern era of OLMD, no studies exist to describe the prevalence of reasons for contacting OLMD.Objectives: The primary goal of this study was to describe the quantity of and reasons for calls for medical direction. We also sought to determine time diverted from emergency physicians due to OLMD. Finally, we hoped to identify any areas for potential improvement or additional training opportunities for EMS providers.Methods: This was a descriptive study with retrospective data analysis of recorded OLMD calls from January 1, 2016, to December 31, 2016. Data were extracted by research personnel listening to audio recordings and were entered into a database for descriptive analysis. We abstracted the date and length of call, patient demographic information (age and gender), category of call (trauma, medical, cardiac, or obstetrics), reason for call, and origin of call (prehospital, interhospital, nursing home, or discharge).Results: The total number of recordings analyzed was 519. Calls were divided into four categories pertaining to their nature: 353 (68.5%) medical; 70 (13.6%) trauma; 83 (16.1%) cardiac; and 9 (8%) were obstetrics related. Repeat calls regarding the same patient encounter comprised 48 (9.4%) of the calls. Patient refusal of transport was the most common reason for a call medical direction (32.3% of calls). The total time for medical direction calls for the year was 26.6 hours. The maximum number of calls in a single day was seven, with a mean of 2.04 calls per day (standard deviation [SD] ± 1.18). The mean call length was 3.06 minutes (SD ± 2.51).Conclusion: Our analysis shows that the use of OLMD frequently involves complex decision-making such as determination of the medical decision-making capacity of patients to refuse treatment and transport, and evaluation of the appropriate level of care for interfacility transfers. Further investigation into the effect of EMS physician-driven medical direction on both the quality and time required for OLMD could allow for better identification of areas of potential improvement and training.
E-Learning Feasibility Analysis: Dwi Sejahtera Vocational High School Pekanbaru Context

Abstract The digital age has an important role along with the rapid development of technology, the need for concepts and mechanisms of information technology-based teaching and learning is inevitable. One of the learning concepts is E-Learning or electronic based learning. But there are an important thing that must considered by the stakeholders of a school that even though the learning system that developed by many parties is very good, if the institutions in the service field cannot see the opportunity or the difficulty of making decisions in analyzing to establish an electronic-based learning system, it will result in slow planning and implementation of the learning concept. The purpose of this research is to determine how feasible is the object studied in the design of electronic learning or E-Learning media in improving learning independence of the students so that it will also produce any content and feature needed in the e-learning system to designed. The main result to be achieved from the data analysis and processing in this study is to find out the factors that still need improvement and the factors that are considered good in the implementation of e-learning in the learning process at the Dwi Sejahtera Vocational School
An Efficient v-Minimum Absolute Deviation Distribution Regression Machine

Support Vector Regression (SVR) and its variants are widely used regression algorithms, and they have demonstrated high generalization ability. This research proposes a new SVR-based regressor: v-minimum absolute deviation distribution regression (v-MADR) machine. Instead of merely minimizing structural risk, as with v-SVR, v-MADR aims to achieve better generalization performance by minimizing both the absolute regression deviation mean and the absolute regression deviation variance, which takes into account the positive and negative values of the regression deviation of sample points. For optimization, we propose a dual coordinate descent (DCD) algorithm for small sample problems, and we also propose an averaged stochastic gradient descent (ASGD) algorithm for large-scale problems. Furthermore, we study the statistical property of v-MADR that leads to a bound on the expectation of error. The experimental results on both artificial and real datasets indicate that our v-MADR has significant improvement in generalization performance with less training time compared to the widely used v-SVR, LS-SVR, ε-TSVR, and linear ε-SVR. Finally, we open source the code of v-MADR at https://github.com/AsunaYY/v-MADR for wider dissemination.
Intra-Pulse Modulation Recognition for Fractional Bandlimited Signals Based on a Modified MWC-Based Digital Receiver

In this paper, we present a modified modulated wideband converter (MWC)-based digital receiver for fractional bandlimited signals, and further propose an intra-pulse modulation recognition method in discrete time fractional Fourier domain (DTFrFD) for the intercepted signals.The proposed digital receiver can move the cross-channel signal to the baseband and since the nonzero part of its available spectrum is narrower in DTFrFD than in discrete time Fourier domain (DTFD), so a better separation can be achieved by the proposed digital receiver than by original MWC-based receiver.Then, with the data acquired from the digital receiver, we propose an intra-pulse modulation recognition method based on the optimal transformation order and the spectral kurtosis (SK) in DTFrFD for the six types of fractional bandlimited signals.In this algorithm, the optimal transformation order is tested to distinguish the encoded signals from the non-encoded signals, and then the SK is tested to determine the intra-pulse modulation type specially.The computational complexity of the proposed method is much lower than search-based methods.Meanwhile, since the SK of Gaussian signals is zero in DTFrFD, the proposed method shows better robustness than the original MWC discrete compressive sampling structure against SNR variation.Simulation results confirm the obtained analytical results.