Reviewerly/exHarmony huggingface dataset:
Evaluasi Pembelajaran Daring Dengan Menggunakan Aplikasi Zoom di Masa Pendemi Covid-19 Pada Mata Kuliah Pengantar Asuhan Kebidanan

Covid-19 pandemic which is currently affecting almost all countries in the world including Indonesia has an impact on the world of education. An online home study policy was adopted to protect students from Covid-19 exposure. The purpose of this study was to determine students' perceptions of online learning by using the Zoom application in the introductory of midwifery care course, and to determine the effectiveness of learners in terms of student achievement. The research is a descriptive study with a mixed method. The population is all STIKes Karsa Husada Garut students who take introductory of midwifery care courses. The quantitative sample was taken by students in grade 1A. The qualitative sample was taken by 4 students who actively participated in all lecture and communicative activities. Retrieval of data using the final semester exam documentation, and interviews. Data analysis is a qualitative approach with interactive analysis of Miles and Huberman, and a quantitative approach with one sample t test. The results showed that students' perceptions were not good towards learning in introductory of midwifery care courses with the Zoom application during the Covid-19 pandemic, because: 1) the Zoom application requires a large internet quota; 2) There is noise due to microphone quality problems and / or noise interference from the student environment that does not turn off the microphone; 3) students are less focused because learning is done from their homes, because the connection is lost due to bad signals, and there is no direct supervision from the lecturer. Learning in midwifery introductory courses with the Zoom application is not effective when viewed from learning achievements
Construction of local Lyapunov functions around non-hyperbolic equilibria by verified numerics for two dimensional cases

Numerical verification methods are proposed in order to construct local Lyapunov functions around non-hyperbolic equilibria of dynamical systems described by ODEs in two dimensional space.The normal form theory in dynamical systems gives basic ideas of these methods.To prove negative definiteness of polynomials of higher degree than two, a new theorem on interval arithmetic is also proposed.
A Proposed Fully Homomorphic for Securing Cloud Banking Data at Rest

Fully homomorphic encryption (FHE) reaped the importance and amazement of most researchers and followers in data encryption issues, as programs are allowed to perform arithmetic operations on encrypted data without decrypting it and obtain results similar to the effects of arithmetic operations on unencrypted data. The first (FHE) model was introduced by Craig Gentry in 2009, and it was just theoretical research, but later significant progress was made on it, this research offers FHE system based on directly of factoring big prime numbers which consider open problem now, The proposed scheme offers a fully homomorphic system for data encryption and stores it in encrypted form on the cloud based on a new algorithm that has been tried on a local cloud and compared with two previous encryption systems (RSA and Paillier) and shows us that this algorithm reduces the time of encryption and decryption by 5 times compared to other systems.
A Study of Impact of Cashless Transaction on Society Using Statistical Methods

A cashless society describes an economic state whereby financial transaction are not conduced with money in the form of physical banknotes or coins but rather though the transfer of digital information (usually an electronic representation of money) between the transacting parties. Cashless society have existed based on barter and other methods of exchange, and cashless transactions have also become possible using digital currencies such as bit coins. Cashless India is a mission launched by the government of India led by prime minister Narendramodi to reduce dependency of Indian economy on cash and to bring hoards of stashed black money lying unused into the banking system. The country embarked upon this transition to a cashless economy when the government took the revolutionary step of demonetization of old currency notes such as Rs.500 and Rs.1000 on November 8, 2016. Different activities needed to be planned in all the point of view for migration to cashless society and digital India to achieve the aim of payment and settlement system of India: Vision 2018.
Spanish-Turkish Low-Resource Machine Translation: Unsupervised Learning vs Round-Tripping

The quality of data-driven Machine Translation (MT) strongly depends on the quantity as well as the quality of the training dataset.However, collecting a large set of training parallel texts is not easy in practice.Although various approaches have already been proposed to overcome this issue, the lack of large parallel corpora still poses a major practical problem for many language pairs.Since monolingual data plays an important role in boosting fluency for Neural MT (NMT) models, this paper investigates and compares the performance of two learning-based translation approaches for Spanish-Turkish translation as a low-resource setting in case we only have access to large sets of monolingual data in each language; 1) Unsupervised Learning approach, and 2) Round-Tripping approach.Either approach completely removes the need for bilingual data or enables us to train the NMT system relying on monolingual data only.We utilize an Attention-based NMT (Attentional NMT) model, which leverages a careful initialization of the parameters, the denoising effect of language models, and the automatic generation of bilingual data.Our experimental results demonstrate that the Unsupervised Learning approach outperforms the Round-Tripping approach in Spanish-Turkish translation and vice versa.These results confirm that the Unsupervised Learning approach is still a reliable learning-based translation technique for Spanish-Turkish low-resource NMT.
Security Enhancement in Cloud Environment using Secure Secret Key Sharing

Securing the data in distributed cloud system is considered one of the major concern for the cloud customers who faces security risks. The data leakage or data tampering are widely used by attackers to extract the private information of other users who shares the confidential data through virtualization. This paper presents Secure Secret Sharing (SSS) technique which is being recognized as one of the leading method to secure the sensitive data. It shares encrypted data over cloud and generated secret key is split into different parts distributed to qualified participants (Qn) only which is analyzed by malicious checkers. It verifies the clients based on their previous performances, whether these users proved to be authorized participant or not. The key computation is evaluated by the Key handler (KH) called trusted party which manages authorized control list, encryption/decryption and reconstruction of key shares. The Lagrange’s interpolation method is used to reconstruct the secret from shares. The experimental results shows that the proposed secure data sharing algorithm not only provides excellent security and performance, but also achieves better key management and data confidentiality than previous countermeasures. It improves the security by using secure VM placement and evaluated based on time consumption and probability computation to prove the efficacy of our algorithm. Experiments are performed on cloudsim based on following parameters i.e. time computation of key generation; response time and encryption/decryption. The experimental results demonstrate that this method can effectively reduce the risks and improves the security and time consumption upto 27.81% and 43.61% over existing algorithms.
Wave–Particle–Entanglement–Ignorance Complementarity for General Bipartite Systems

Wave-particle duality as the defining characteristic of quantum objects is a typical example of the principle of complementarity. The wave-particle-entanglement (WPE) complementarity, initially developed for two-qubit systems, is an extended form of complementarity that combines wave-particle duality with a previously missing ingredient, quantum entanglement. For two-qubit systems in mixed states, the WPE complementarity was further completed by adding yet another piece that characterizes ignorance, forming the wave-particle-entanglement-ignorance (WPEI) complementarity. A general formulation of the WPEI complementarity can not only shed new light on fundamental problems in quantum mechanics, but can also have a wide range of experimental and practical applications in quantum-mechanical settings. The purpose of this study is to establish the WPEI complementarity for general multi-dimensional bipartite systems in pure or mixed states, and extend its range of applications to incorporate hierarchical and infinite-dimensional bipartite systems. The general formulation is facilitated by well-motivated generalizations of the relevant quantities. When faced with different directions of extensions to take, our guiding principle is that the formulated complementarity should be as simple and powerful as possible. We find that the generalized form of the WPEI complementarity contains unequal-weight averages reflecting the difference in the subsystem dimensions, and that the tangle, instead of the squared concurrence, serves as a more suitable entanglement measure in the general scenario. Two examples, a finite-dimensional bipartite system in mixed states and an infinite-dimensional bipartite system in pure states, are studied in detail to illustrate the general formalism. We also discuss our results in connection with some previous work. The WPEI complementarity for general finite-dimensional bipartite systems may be tested in multi-beam interference experiments, while the second example we studied may facilitate future experimental investigations on complementarity in infinite-dimensional bipartite systems.
Spectral estimation from simulations via sketching

Sketching is a stochastic dimension reduction method that preserves geometric structures of data and has applications in high-dimensional regression, low rank approximation and graph sparsification. In this work, we show that sketching can be used to compress simulation data and still accurately estimate time autocorrelation and power spectral density. For a given compression ratio, the accuracy is much higher than using previously known methods. In addition to providing theoretical guarantees, we apply sketching to a molecular dynamics simulation of methanol and find that the estimate of spectral density is 90% accurate using only 10% of the data.
Chaos-based Digital Image Encryption Using Unique Iris Features

As the use of the Internet increases the exchange of private data as well, therefore the development of faster and novel algorithms is essential.This paper presents an algorithm for encrypting images based on the natural, unique and complex patterns present in the Iris and the use of Non-Linear Systems that present a chaotic behavior suitable for an encryption system.It has been proven that the developed algorithm produces optimal security values and can be used for encryption processes in real communications.
Verification of graph states in an untrusted network

Graph states are a large class of multipartite entangled quantum states that form the basis of schemes for quantum computation, communication, error correction, metrology, and more. In this work, we consider verification of graph states generated by an untrusted source and shared between a network of possibly dishonest parties. This has implications in certifying the application of graph states for various distributed tasks. We present a protocol which is globally efficient for a large family of useful graph states, including cluster states, GHZ states, cycle graph states, and more. For general graph states, efficiency with respect to the security parameter is maintained, though there is a cost increase with the size of the graph state. The protocols are practical, requiring only multiple copies of the graph state, local measurements, and classical communication.
Influence of Motivational Factors on Employee Retention among the Sales Managers in the Private Sector Insurance companies in Chennai City

The study's purpose is to measure the influence of motivational factors on Employee Retention among the Sales Managers in Private sector life insurance companies in Chennai city.The sample for this study consisted of 300 sales managers drawn based ona simple random sampling method from private sector life insurance companies in Chennai city.The study found that the sales managers are satisfied with the motivational factors,namely Compensation, Work Environment, Leadership, Training and Development, and Fringe benefits, which offered by the private sector life insurers.The study also makesknown that there is a significant association between motivational factors and employee retention practices in the private sector life insurers in Chennai city.The study also creates that there is a significant impact of motivational factors on employee retention.
Digital literacy of schoolchildren and teachers: A comparative analysis

The article considers digital literacy as a fundamental component of the media competence development. The study of the history of the issue and analysis of the existing theories showed that the research focus on the digital literacy of the adult population and do not take into account minors who demonstrate the highest interest in media technologies. The authors develop a theory of the deep mediation of the social space and argue that the indicators of digital literacy of schoolchildren should correlate with the data on teachers, who, according to the contemporary educational strategy, are responsible for increasing the media competence of society - starting from the media-oriented courses in school. In 2019, the authors conducted a survey Media competence of schoolchildren and teachers (N=500+500) in 10 cities of the Volga Federal District with the lowest digital literacy index. Based on the results of the comparative analysis, the article identifies a number of challenges in the field of media literacy, in particular digital literacy, and the main one is the digital divide between two generations (schoolchildren and teachers), which indicates a communication barrier that hinders interaction not only in education, but also in the social space. While schoolchildren demonstrate high interest in media technologies, their teachers seem not to be interested in media technologies not only in professional activities but also in everyday life. The authors believe that the inverse correlation of the digital literacy levels of schoolchildren and teachers prevents the harmonious development of the media competence in the Russian society.
Data Mining and Exploration: A Comparison Study among Data Mining Techniques on Iris Data Set

This work aims at investigating the efficiency of diverse methods of classification through the use of WEKA software for the well-known Iris data set. For the assessment of the classification algorithm performance, this paper adopted the use of Receiver Operating Characteristic (ROC) curves. The different classification algorithm techniques used for this work include neural networks, naive Bayes and decision trees. The data set used in our investigation, Iris data, is one of the oldest and widely used data sets in data mining. For the three techniques of classification used in this study, a comparison of the ROC curves used in this study indicate that the Neural Network (NN) is the most appropriate method of evaluation investigated in this work. The other two methods, Bayes network classifier and decision trees, have their classical procedures for classification that might need to improve significantly.
Video-based Tancho Koi Fish Tracking System Using CSK, DFT, and LOT

Abstract In this paper, a comparison of Circulant Structure of Tracking-by-detection with Kernels (CSK), Distribution Fields for Tracking (DFT) and Locally Orderless Tracking (LOT) methods is proposed for the process of video-based object tracking. The object in question is the tancho koi fish and its variants, in the form of video recordings. All three methods are applied to trace the red roundabout in the head of the koi fish. The purpose of this study is to provide the best tracking process recommendations for this case. From the experimental results, it is found that the average sample accuracy of the DFT tracking method is more recommended than the other two methods, even though it has an average frame rate that is no better than the CSK method.
Mixing deep learning with classical vision for object recognition

Nowadays, when one needs a system for image recognition, it is mostly a matter of finding pre-trained CNN and, sometimes, adding additional training based on transferred knowledge.Accurate 6-DOF object localization in the image is a more laborious task and requires more complex training data to be available.On the other hand, if we know the model of the object, it is straightforward to acquire its pose from the image (RGB or RGB-D).In this paper, we try to show the advantages of mixing deep learning object recognition/detection with classical 6-DOF pose estimation algorithms, with a focus on applications in service robotics.
Quantum Risk Assessment Model Based on Two Three-Qubit GHZ States

With the acceleration of the construction of quantum communication networks, scholars have proposed different quantum communication protocols for different application scenarios. However, few scholars pay attention to the risk assessment process before communication. In this paper, we propose a novel quantum risk assessment model based on quantum teleportation technology with two three-qubit GHZ states. Only by using Bell states measurements (BSMs) and two-qubit projective measurements (PJMs), the communicators can recovery any arbitrary two-qubit state. This protocol can transmit two-dimension risk assessment factors with better security performance. On the one hand, more sufficient evaluation factors allow the two communicating parties to more objectively evaluate the risk level of communication with the other party, and on the other hand, it also improves the qubit efficiency of the protocol. Moreover, we introduce the third party in this scheme can be semi-trusted, which must be full-trusted in our previous work. This change can reduce the dependence of the communication parties on the third-party organization and improve the privacy of communication. The security analysis shows that this scheme can resist internal and external attacks, and the quantum circuit diagrams also prove that our protocol is physically easier to implement.
INVESTIGATIVE TECHNIQUES IN THE DIGITAL AGE: CYBERCRIME AND CRIMINAL PROFILING

&lt;p&gt;The advent of the Internet and social networks has reduced human and empathic relationships, consequently increasing virtual ones. Cyberspace offers the possibility of carrying out illegal acts with the perception of remaining unpunished. In this article we discussed the differences between crime and cybercrime which takes different forms within cyberspace such as cyberstalking, cyberbullying, online sexual offences and property crimes such as white-collar crimes. Furthermore, the evolution of criminal profiling in the digital age has been described and the profile of the cyber-criminal has been defined as outlined by the Italian State Police. The multiplication of criminal activities perpetrated through the web has led the Legislator to wonder about the most effective repressive methods to repress and try to ward off the numerous dangers that are wandering within cyberspace. The Italian legislator, through various legislative interventions, has introduced changes to the Penal Code as in article 612-bis, introducing in paragraph 2 an increase in punishment for the case in which the crime is committed through IT tools such as e-mail, SMS, chat malware and, above all, social networks. Also, the legislator included article 612-ter in the Penal Code to prosecute the illegal dissemination of sexually explicit images and videos. Finally, criminological research must consider that cybercrime has different variables than traditional crime and the evaluation of criminal behaviour should take into account the influence of the virtual dimension on the cognitive processes of the subjects.&lt;/p&gt;&lt;p&gt; &lt;/p&gt;&lt;p&gt;&lt;strong&gt; Article visualizations:&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;img src="/-counters-/soc/0548/a.php" alt="Hit counter" /&gt;&lt;/p&gt;&lt;a href="https://doi.org/10.5281/zenodo.3877668"&gt;&lt;img src="https://zenodo.org/badge/DOI/10.5281/zenodo.3877668.svg" alt="DOI" /&gt;&lt;/a&gt;
Student-Centered Teaching Design and Practice of Database Course

This paper elaborates the design and practice of database course teaching based on student-centered ideas for non-computer-major students in South China University of Technology, which have weak foundation in computer science.The practical results show that the proposed teaching methods effectively stimulate students' interest, enthusiasm and potential in learning, meanwhile better achieve teaching objectives and improve teaching quality.
THE APPLICATION OF MATCHING GAME TO IMPROVE STUDENTS’ ENGLISH VOCABULARY MASTERY

Based on the problem found in the classroom, mastering English vocabulary is one of the weekness for the student. It seemed difficult for them to understand some words which are unfamiliar with them or even memorizing them. The use of learning media can be more effective and interesting way in learning.Therefore the researcher decided to solve these problems by applying a matching game which can be used as an alternative learning medium in learning Vocabulary. The participanst of this research were 20 Students of English Depatment. Tihis game was conducted in two cycles. Each cycle consisted of four meetings; three meetings for teaching the vocabulary by using this media, and one of them was for the test. The research findings showed that matching game could improve the students’ vocabulary mastery. It could be seen from the improvement of the students score in test. The average score of students in cycle 1 was 63 and in cycle 2 was 66. In conclusion, the implementation of matching game could improve the students’ Vocabulary mastery at first year Students of English Department at State Polytechnic of Bengkalis.
Deteksi Kendaraan secara Real Time menggunakan Metode YOLO Berbasis Android

The Activities on the highway that involve vehicles often have congestion problems due to the tightening of the quantity of vehicles on the highway. In addition, there are also problems of order and violations, the use of improper routes, such as vehicles entering the lane that are not intended for the vehicle. Therefore, researchers designed a vehicle detection application in real time based on Android using the YOLO method (You Only Look Once). The analysis carried out using 200 datasets, 4 classes, 10 batches, and 200 epochs. The training process was carried out up to 4000 steps, and the storage of checkpoints to the form of file protob was done at steps 800, 1000, 1200, 1400, 1600, 1800, 2000, 3000, and 4000. Bounding boxes successfully detected and classified objects correctly. This test is done using a Xiaomi Redmi 4X smartphone with a video resolution measuring 768x432 pixels.