Reviewerly/exHarmony huggingface dataset:
BLOOD COAGULATION MONITORING SYSTEM

This article describes the creation of a communication system between smartphones and various medical devices, also there is an analysis of different approaches to data transfer between devices, such as manual data entry, screen scanning using a seven-segment display recognition system, and Bluetooth low energy.The practical part demonstrates a developed communication system using Bluetooth technology.There is also implemented an automatic communication between devices that requires no user actions.
Functional Encryption for Set Intersection in the Multi-Client Setting.

Functional encryption for set intersection (FE-SI) in the multi-client environment is that each client i encrypts a set $$X_i$$ associated with time T by using its own encryption key and uploads it to a cloud server, and then the cloud server which receives a function key of the client indexes i, j from a trusted center can compute the intersection $$X_i \cap X_j$$ of the two client ciphertexts. In this paper, we first newly define the concept of FE-SI suitable for the multi-client setting. Then, we propose an efficient FE-SI scheme in asymmetric bilinear groups and prove the static security of our scheme under newly introduced assumptions. In our FE-SI scheme, a ciphertext consists of $$O(\ell )$$ group elements, a function key consists of a single group element, and the decryption algorithm has $$O(\ell ^2)$$ complexity where $$\ell $$ is the size of a set in the ciphertext. Next, we propose another FE-SI scheme with time-constrained keys that limits the ability of function keys to be valid only for a specified time period T, and proves the static security of our scheme. Finally, we prove that the two assumptions hold in the general group model to provide confidence in the two newly introduced assumptions.
МОДЕЛЮВАННЯ СИСТЕМИ УПРАВЛІННЯ ОСВІТНІМ ПРОЦЕСОМ ЯК ОСНОВА ПІДВИЩЕННЯ ЯКОСТІ МАТЕМАТИЧНО-ПРИРОДНИЧОЇ ОСВІТИ У ЗАКЛАДАХ СЕРЕДНЬОЇ ОСВІТИ

The author researches the management of educational processes. Author's developments on management of these processes are presented, as well as the model of “Conflict-free education” which give positive results in practice.
Penggunaan Model Contextual Teaching and Learning dalam Peningkatan Hasil Belajar Siswa SMP Kelas VIII Pada Mata Pelajaran Bahasa Indonesia

Abstract Learning Model is a learning technique that is used by teachers in teaching a particular subject and in the selection of a model must be adjusted in advance with the subject matter. The level of cognitive development of students and the facilities or facilities available in accordance with the learning objectives so that the expected learning model can be achieved. Implementation of learning about the delivery of stories by applying the Contextual Teaching And Learning (CTL) model. CTL is a learning concept that helps teachers relate to students' real-world situations and encourages students to make connections between the knowledge they have and their application in their daily lives. The CTL model runs in accordance with the scenarios in the Learning Implementation Plan (RPP), and has succeeded in creating a conducive learning situation where students are directly involved in the learning process, can also improve student learning outcomes for learning Indonesian which was initially considered boring. The level of students' understanding of the delivery of stories after learning to use the CTL learning model can increase well, this can be seen from the results of the evaluation that in cycle 1, the average score of 67 categories was sufficient and in the second cycle it obtained an average score of 80 with a good category. After being given an action by using the application of the model of conventional teaching and learning (CTL) in cyle 1 students learning completeness is 74% or 20 Students. While in cycle 2 the classical learning achievement to 93% or 25 Students.
Improving Pointing Direction Estimation by Considering Hand- and Ocular-Dominance

This paper introduces a user study regarding the effects of hand- and ocular-dominances to pointing gestures. The result of this study is applicable for designing new gesture interfaces which are close to a user's cognition, intuitive, and easy to use. The user study investigates the relationship between the participant's dominances and pointing gestures. Four participant groups—right-handed right-eye dominant, right-handed left-eye dominant, left-handed right-eye dominant and left-handed left-eye dominant—were prepared, and participants were asked to point at the targets on a screen by their left and right hands. The pointing errors among the different participant groups are calculated and compared. The result of this user study shows that using dominant eyes produces better results than using non-dominant eyes and the accuracy increases when the targets are located at the same side of dominant eye. Based on these interesting properties, a method to find the dominant eye for pointing gestures is proposed. This method can find the dominant eye of an individual with more than 90% accuracy.
Computable steering criterion for bipartite quantum systems

Quantum steering describes the ability of one observer to nonlocally affect the other observer's state through local measurements, which represents a new form of quantum nonlocal correlation and has potential applications in quantum information and quantum communication. In this paper, we propose a computable steering criterion that is applicable to bipartite quantum systems of arbitrary dimensions. The criterion can be used to verify a wide range of steerable states directly from a given density matrix without constructing measurement settings. Compared with the existing steering criteria, it is readily computable and testable in experiment, which can also be used to verify entanglement as all steerable quantum states are entangled.
Training A Day with English

Education is an activity that is common to every human being on this earth. Education cannot be separated from all forms of human activities. The teaching and learning process is certainly a core activity in the whole process of education in school or formal education. English is a language that is commonly used in several countries, therefore knowledge and learning of English is very important for the development of children's knowledge. Introduction, and learning things in the child's environment can initiate children's interest in learning English. This activity aims to provide knowledge to children about the use of English in everyday life, when children communicate in English, children become easier to know the meaning of words and their meanings because the material is learned based on the science of direct practice. Because the concentration of children at an early age is still very minimal and uncontrollable, the most appropriate method is by learning and playing where children can understand the material well because of the learning and teaching process that attracts children's interest. With this method, the interest of children is no longer only interested in how to play or just give rewards, but children will be happy with the repetition of the things he had learned before. So, children's interest in learning will increase with regard to things he already knows.
Council of Europe Recommendation CM/Rec(2017)5 and e-Voting Protocol Design

The Corona pandemic has created a push towards digitization in a number of fields, not least in the public sector including democratic processes. This of course includes an increased interest in e-voting via the Internet. The Council of Europe has a long-standing history of work in the field including two Recommendations – (2004)11 and (2017)5 – which have become the de facto yardstick against which every e-voting system is measured. Rec(2017)5 builds on a decade of experience with e-voting and particularly strengthens two concepts important in any electronic voting system: Voting secrecy and auditability/verifiability. This has distinct implications for the design of e-voting protocols. The aim of this paper is to analyse the impact on what arguably are the most popular voting protocol families, envelope and token protocols. How does the modified Recommendation impact on the viability of protocols and protocol design? The paper first presents the Council of Europe Recommendation and the technical issues it addresses. Then a model is introduced to assess a voting protocol against the Recommendation; a typical envelope and a token protocol are assessed in view of the model and finally the two assessments are compared including policy recommendations for a path to e-voting implementation.
The Road to Quantum Computational Supremacy

The main purpose of this paper is to examine some (potential) applications of quantum computation in AI and to review the interplay between quantum theory and AI. For the readers who are not familiar with quantum computation, a brief introduction to it is provided, and a famous but simple quantum algorithm is introduced so that they can appreciate the power of quantum computation. Also, a (quite personal) survey of quantum computation is presented in order to give the readers a (unbalanced) panorama of the field. The author hopes that this paper will be a useful map for AI researchers who are going to explore further and deeper connections between AI and quantum computation as well as quantum theory although some parts of the map are very rough and other parts are empty, and waiting for the readers to fill in.
Cinematherapy Meningkatkan Kendali Diri Mahasiswa

The purpose of this study was to determine the effectiveness of cinematherapy in improving student self-control. This research uses a descriptive method with a quantitative approach. The sample of this study were 21 Unindra students. The self control instrument used is a Likert scale model. The results showed the percentage of Pre Test and post test showed that there were 4 students who had self-control in the excellent category of 19%. Furthermore, there are 17 students who have a good category by 81%. Next, if seen from the t test results show that the value of the Pre Test obtained an average of self-control or a mean of 218.9. While the Post Full Self Test value was 222.9. So with that it means descriptively there is a difference in the average of self control between the Pre Test and the Post Test results. However, it is not significant. Based on the value of the correlation coefficient (correlation) of 0.350 with a significance value (sig.) Of 0,000 because the value of Sig. 0,000 &lt;probability 0.05, it can be said that there is a relationship between the Pre Test variable and the Post Test variable. However, it is not significant. So it can be concluded that there is no significant difference in average between Pre-Test and Post-Test self-control, which means that cinematherapy has proven ineffective in increasing the self-control of UNINDRA students.
Comparison and Research on Diversified Portfolios with Several Entropy Measures Based on Different Psychological States

In previous studies, there were few portfolio models involving investors' psychological states, market ambiguity and entropy. Some entropy can make the model have the effect of diversifying investment, which is very important. This paper mainly studies four kinds of entropy. First, we obtained four definitions of entropy from the literature, and gave the function of fuzzy entropy in different psychological states through strict mathematical proof. Then, we construct a fuzzy portfolio entropy decision model based on the investor's psychological states, and compared it with the possibilistic mean-variance model. Then we presented a numerical example and compared the five different models established. By comparing the results, we find that: (a) The possibilistic mean-Shannon entropy model solves the problem of the possibility of excessive concentration in the possibilistic mean-variance model, but the dispersion is not enough. Conversely, the possibilistic mean-Yager entropy is over-emphasized due to the definition of its own function, such that it gave an investment pattern of equal weight distribution or approximate average distribution. (b) The results of possibilistic mean-proportional entropy can be said to be the middle status of the portfolios of possibilistic mean-Shannon entropy and possibilistic mean-Yager entropy. This portfolio not only achieves a certain rate of return, but also disperses the risk to some extent. (c) The lines of satisfaction for portfolios derived from different models are approximately U-shaped with the increase in return preference. (d) The possibilistic mean-Shannon entropy model tends to have the highest portfolio satisfaction with the same psychological state of the investor.
ANALISIS KEMAMPUAN WEBRATIO UNTUK PENGEMBANGAN APLIKASI WEB MENGGUNAKAN INTERACTION FLOW MODELING LANGUAGE (IFML)

The model-driven development (MDD) method is a method that can accelerate the application development process. With this method, the model can be immediately transformed into an executable application. Model-driven architecture is one kind of MDD approaches. MDA has a standard modeling language that is used to facilitate the transformation process. One of the modeling languages in MDA is Interaction Flow Management Language (IFML). IFML models an application based on the interaction flow and interface of the application. This paper explains the capabilities of WebRatio in developing Web applications and their effectiveness. The effectiveness is calculated from the effort required for the development. On the other side, the effort is calculated from the line of code (LOC) generated from the model. The experiment's case study is a simple web-shop application, with some functional and non-functional requirements. The measurement results show that to develop a web-shop, the effort required is quite efficient, only 13% of the total application. However, another study still needs to be done because many variables affect the productivity of application development.
Students' perception towered autonomy in foreign language learning and instructions

In the current day, especially in the field of curriculum, designers are progressively concentrating their efforts on learning quality and student improvement in L2 instruction. Learner-centered approach is their target and has led to an emphasis on learner autonomy and its value in stimulating the development of the learner.&#x0D; The current paper aims to examine two hundred university students' perception regarding their autonomy in writing and their teachers' perceptions of the writing skill of the curriculum in promoting students' autonomy and this investigation provided a comprehensive analysis of the instructional processes in promoting autonomy in writing skills and shed light upon the subjects that are be reviewed in the writing skill area of the curriculum.
A CRYPT ANALYSIS OF THE TINY ENCRYPTION ALGORITHM IN KEY GENERATION

Encryption algorithms are used for security over wireless communications, but securing data also consumes resources. Major important factors to consider when designing a cryptographic system are performance, speed, size, and security. Tiny Encryption Algorithm (TEA), and the Extension of TEA (XTEA) are examples of cryptographic algorithms. There is a requirement to specify cryptographic strength in an objective manner rather than describing it using subjective descriptors such as weak, strong, acceptable etc. This paper proposes the Study on a Tiny Encryption Algorithm. The Tiny Encryption Algorithm (TEA) is a cryptographic algorithm designed to minimize memory footprint and maximize speed. It is a Feistel type cipher that uses operations from mixed (orthogonal) algebraic groups. In this Paper, we propose Tiny Encryption Algorithm (TEA) to some standard for random number generator tests.
Authentication of Choice on Mobile Devices: A Preliminary Investigation

Authentication is a security measure designed to allow authorized users to use the system securely with minimum interference on the usability of the system. Although numerous user studies had examined various authentication methods such as traditional alphanumeric password, graphical password, and biometrics, very limited research investigated users’ performance and preference when they were allowed to choose the authentication method(s) of their choice for a specific application. This study was conducted as an initial attempt to fill in that gap. We developed a mobile application called the ‘Event manager’ that offers calendar and file management functions. Regarding the authentication, the ‘Event manager’ app provides users the freedom to choose their preferred authentication method(s) among five commonly adopted authentication mechanisms. We conducted an empirical user study with a ‘within-group’ design to investigate users’ initial interaction with three different types of authentication processes: alphanumeric passwords, one-factor authentication of choice, and two-factor authentication of choice. 75 participants completed the study. The result of the study will help understand users’ general perception regarding the ‘authentication of choice’ approach as well as their preferred authentication method or combination of methods in the context of mobile devices.
Financing Inventory Through Initial Coin Offerings (ICOs)

Initial Coin Offerings (ICOs) are an emerging form of fundraising for Blockchain-based startups. We propose a simple model of matching supply with demand with ICOs by companies involved in production of physical products. We examine how ICOs should be designedâ€”including optimal token floating and pricing of utility tokensâ€”in the presence of product risk and demand uncertainty, make predictions on ICO failure, and discuss the implications on firm operational decisions and profits. We show that in the current unregulated environment, ICOs lead to risk-shifting incentives (moral hazard), and hence to underproduction, agency costs, and loss of firm value. These inefficiencies, however, fade as product margin increases and market conditions improve.
aSNAQ: An adaptive stochastic Nesterov's accelerated quasi-Newton method for training RNNs

Recurrent Neural Networks (RNNs) are powerful sequence models that are particularly difficult to train. This paper proposes an adaptive stochastic Nesterov's accelerated quasi-Newton (aSNAQ) method for training RNNs. Several algorithms have been proposed earlier for training RNNs. However, due to high computational complexity, very few methods use second-order curvature information despite its ability to improve convergence. The proposed method is an accelerated second-order method that attempts to incorporate curvature information while maintaining a low per iteration cost. Furthermore, direction normalization has been introduced to solve the vanishing and/or exploding gradient problem that is prominent in training RNNs. The performance of the proposed method is evaluated in Tensorflow on benchmark sequence modeling problems. The results show that the proposed aSNAQ method is effective in training RNNs with a low per-iteration cost and improved performance compared to the second-order adaQN and first-order Adagrad and Adam methods.
Phone Conversation Analytics

The paper reviews the results of research of possibilities of well-known speech recognition systems, considers the importance of speech recognition technology in various telephone systems for the analysis process of voice records or current phone calls.This technology provides searching of useful information from the content of a call and improving the customer service quality of call centre.The use of analytics of speech in real-time makes it possible to the call centre operator to make certain conclusions based on the analysis of past calls and thus to determine the proposed answers.The paper also analyses those challenges that are in the field of real-time speech analytics.The article deals with a multifunctional application developed in the call centre of emergency response, which recognizes Georgian speech and presents received data in a form convenient for further analysis.It describes the software technologies used for this application as well.
Multi-turn Response Selection using Dialogue Dependency Relations

Multi-turn response selection is a task designed for developing dialogue agents. The performance on this task has a remarkable improvement with pre-trained language models. However, these models simply concatenate the turns in dialogue history as the input and largely ignore the dependencies between the turns. In this paper, we propose a dialogue extraction algorithm to transform a dialogue history into threads based on their dependency relations. Each thread can be regarded as a self-contained sub-dialogue. We also propose Thread-Encoder model to encode threads and candidates into compact representations by pre-trained Transformers and finally get the matching score through an attention layer. The experiments show that dependency relations are helpful for dialogue context understanding, and our model outperforms the state-of-the-art baselines on both DSTC7 and DSTC8*, with competitive results on UbuntuV2.
A method to suppress local minima for symmetrical DOPO networks

Coherent Ising machine (CIM) implemented by degenerate optical parametric oscillator (DOPO) networks can solve some combinatorial optimization problems. However, when the network structure has a certain type of symmetry, optimal solutions are not always detected since the search process may be trapped by local minima. In addition, a uniform pump rate for DOPOs in the conventional operation cannot overcome this problem. In this paper proposes a method to avoid trapping of the local minima by applying a control input in a pump rate of an appropriate node. This controller breaks the symmetrical property and causes to change the bifurcation structure temporarily, then it guides transient responses into the global minima. We show several numerical simulation results.
Cervical Cell Cytoplasm Extraction Algorithm

Cervical cancer is one of the most common malignancies among women. According to world health organization, an estimated one million women worldwide are currently living with cervical cancer. With no symptoms at all in its pre-cancerous stage, it is hard to detect, and when the symptoms are visible, it is unresponsive to treatment. Fortunately, it is possible to detect it in pre-cancerous stage using Pap smear test, so it could be treated. Human-based smear analysis is tedious, time consuming, and error prone. Therefore, machine-assisted automated screening brings significant benefits in the field. The screening of cervical cell requires detection of any morphological and structural change. An effective segmentation algorithm is needed to detect the contours of cytoplasm and nucleus, and then input is fed into an automated system to diagnosis any unpropitious condition. The author in this paper proposed an automated algorithm for segmentation of cytoplasm from a cell image containing cell of interest accommodating with other undesired substances. The algorithm intended to segment the available cervical cell image into sub image, which will contain the extracted cytoplasm. The extracted image of cytoplasm shall then be subjected to further analysis to determine the malignancies in the cervical cell.