Reviewerly/exHarmony huggingface dataset:
Time-bin multiplexed differential phase shift quantum key distribution (Conference Presentation)

We present an experimental demonstration of the 4-state differential-phase-shift quantum key distribution (4S-DPS-QKD) over a 30 km quantum channel with two different approaches, namely path superposition and time-bin superposition. 4S-DPS-QKD offers enhanced security compared to the pulse-train DPS-QKD against individual attacks. We show that the key generation efficiency, and security, improve with an increase in the number of path delays or time bin superpositions. Our implementation establishes an ease in implementation of the time-bin superposition approach, over the path superposition approach. The sender (Alice) uses a photon in a superposition state, corresponding to either 3 spatial paths or temporal bins. In the temporal case, Alice uses a weak coherent source (WCS) with a pulse width of 3 ns, that we interpret as a single wave packet comprising of three time-bins of 1 ns each.. Alice encodes her random key bit [0,1] as a random phase [0,pi] between |a&gt; and |b&gt;, and |b&gt; and |c&gt;, i.e. successive paths or time bins of the WCS, with mean photon number &lt; n&gt;=0.1, and pulse widths of 0.5 ns. The phase encoded bits are then transmitted over a single mode optical fibre. Both path and timb-bin implementations follow similar setups beyond the transmitter. At the receiver, a delay line interferometer (DLI) introduces a delay of 1 ns, measures &lt; a|b&gt; and&lt; b|c&gt;, and recovers the phase introduced by Alice as a detection at one of the 2 output ports of the DLI with a time resolution of 50 ps using a time-to-digital convertor (TDC). Our experiments have yielded a QBER of 21% for path superposition and 17% for time-bin superposition. We thus establish the equivalence of the two approaches, and note that the time-bin approach is easily extended to more than 3 time-bins, and an increased secure key rate.
Дилетантизм и экономическая жизнь в условиях современности

The article considers the issues of dynamics of economic behavior of the parties to social relations related to changes in the technological (instrumental) environment of our existence, typical for the beginning of the 21st century – digitalization, Internet technologies, development of the search algorithms, social media. Possible changes in self-identification of the participant of economic activity in his interaction with the information field formed by the Internet technologies are being revealed. A new understanding of the dilettante phenomenon and his role in modern social and economic relations is offered. The subject is considered in the light of the K. Popper’s [three worlds] concept, provisions of the M. McLuhan’s instrumental evolution theory, A. Giddens’ postmodernity theory and T. Friedman’s ‘flat world’ ideas.
Genetic Action Sequence for Integration of Agent Actions

Reinforcement learning has remarkable achievements in areas such as GO, Game, and autonomous vehicles, and is attracting attention as the most promising future technology among neural network-based technique. In spite of its capability, Reinforcement learning suffers from its greedy nature that causes selective behaviors. This is because the agent learns in such a way that each action seeks an optimal reward. However, the pursuit of maximum rewards by each action does not guarantee the maximization of the total reward. This is an obstacle to improving the overall performance of reinforcement learning. This paper introduces a concise illustration of Action Sequence, a method that encourages the trained model to seek grander strategies generating more desirable results. Especially aiming at highly complexed problems where plain actions can hardly handle any tasks. The model was tested under a video game environment to verify its improved proficiency in choosing suitable actions.
Correction to: Hybrid image of three contents

In the original publication of this article [1], the Figs. 3 and 4 are not clear enough. They are adjusted the size and showed as below.
Flexi-Lexicon Learning Using Krill Herd Algorithm for Sentiment Analysis

The process of sentiment analysis has the theme of extracting a semantic structure from a given text. This can be achieved using optimization algorithm is lexicon learning where the lexicon learning structure can be tuned using an optimization algorithm for effective extraction of semantic level structure. In this paper, Krill Herd (KH) algorithm is used for optimizing lexicon learning where an effective sentiment analysis can be popped out. The algorithm has been tested with standard six different datasets, and the results are compared with the recent developed literature algorithms. The output shows that the proposed algorithm outperforms existing algorithms for all the six datasets with a confidence interval of 0.95.
Expanding the Horizons of Primary School Children in the Process of Playing the Game "Gastronomic travel"

The article proposes to consider a cycle of lessons for younger students, the purpose of which is to familiarize themselves with the culinary traditions of different countries. The concept developed with the active participation of the author and implemented in the course "Gastronomic travel" is intended to complement the educational subject "The World Around Us": during the lessons, the preparation of national dishes by students is accompanied by a complete "regional immersion". Based on the research of reputable psychologists and teachers, the significance of the role-playing game for the child as a means of understanding the world and preparing for further serious activity is revealed. Its relevance is emphasized not only for preschoolers, but also for children of primary school age. Particular attention is paid to the practice of using educational and play techniques in the educational process of primary school, which allows you to avoid routine, stimulates the child's cognitive interest, creates conditions for his free self-expression and development.
Block-Based Data Security Storage Scheme

Blockchain technology is now a frontier field of high value with its unique technological advantages, innovative value concepts and wide application scenarios. The blockchain guarantees the integrity and anti-tamper modification of the stored transaction data through the hash algorithm. In the face of the hash algorithm, the centralized attack method, namely the brute force cracking method, the dictionary cracking method and the rainbow table attack method, is realized by using the collision principle. Based on the traditional method of salt-adding hashing, this paper proposes to use the commonly used Miller-Rabin prime number detection algorithm to generate random large prime salt to resist the attack of rainbow table. The test time comparison proves that this method plays an important role in the secure storage of blockchain data.
Recommender System Combining Popularity and Novelty Based on One-mode Projection of Weighted Bipartite Network

Personalized recommendation algorithms, which are effective means to solve information overload, are popular topics in current research. In this paper, a recommender system combining popularity and novelty (RSCPN) based on one-mode projection of weighted bipartite network is proposed. The edge between a user and item is weighted with the item’s rating, and we consider the difference in the ratings of different users for an item to obtain a reasonable method of measuring the similarity between users. RSCPN can be used in the same model for popularity and novelty recommendation by setting different parameter values and analyzing how a change in parameters affects the popularity and novelty of the recommender system. We verify and compare the accuracy, diversity and novelty of the proposed model with those of other models, and results show that RSCPN is feasible.
An investigation on the impact of sampling techniques for t-SNE

The main topic of this article concerns t-SNE, a dimensionality reduction technique that has gained much popularity for its increased capability of creating low-dimensional embeddings that preserve ...
Pengaruh Media Pembelajaran, Lingkungan Sekolah Dan Kompetensi Pedagogik Terhadap Motivasi Belajar Siswa

This study aims to determine (i) the effect of learning media partially on student motivation in SDN 245 Batutompo, Rilau Ale Subdistrict, Bulukumba District (ii) partially influence the school environment on student motivation in SDN 245 Batutompo, Rilau Ale Subdistrict, Bulukumba District (iii) partial influence of pedagogical competence on student motivation in SDN 245 Batutompo, Rilau Ale Subdistrict, Bulukumba District (iv) the influence of learning media, school environment, and pedagogic competence simultaneously on student motivation in SDN 245 Batutompo Subdistrict, Rilau Ale, Bulukumba District. This study uses a quantitative approach that examines the relationship between learning media, the school environment and pedagogical competence on student motivation. Data analysis techniques using quantitative techniques with inferential statistical approaches, namely multiple linear regression analysis. The results showed that simultaneous learning media, school environment, and pedagogical competencies had a positive and significant effect on student motivation in SDN 245 Batutompo, Rilau Ale District, Bulukumba Regency. While the partial test results show that the learning media, school environment and pedagogical competence each have a positive and significant effect on student motivation in SDN 245 Batutompo, Rilau Ale District, Bulukumba Regency.
TOLERANCE TO STRESS IN EXTREME WORK CONDITIONS

The article presents the theoretical and empirical study on tolerance to stress of people working in extreme working conditions (patrol officers). The main discussed question is: what characteristics should be develop, so that an individual can adequately respond without painful personality destruction in stressful situations, when known ways of social behavior do not work? The built theoretical-conceptual platform of the studied problem allowed us to put forward the study purpose: to determine and explore personality traits that can be useful in extreme working conditions. The article present the results of the following study tasks: to analyze theoretically the problem and&nbsp; generalize the basic personal traits useful in extreme work situations; to investigate empirically with corresponding test indicators the emotional and cognitive characteristics of patrol officers’ stress tolerance; to analyze discovered correlations. The empirical study was carried out on the basis the author’s “Personality Stress Resistance Model” developed with the aim of using by psychologists at their practical work with stressed clients. The model includes the following components of tolerance to stress: psychophysiological, emotional, cognitive, and integrative. The author, on the basis of a systematic approach, revealed important aspects of tolerance to stress that must be taken into account during selection of patrol officers for the National Police. The performed empirical study showed importance of “job satisfaction” as an emotional component of stress tolerance. The relationships of emotional and cognitive components were also determined: as a combination of motivation for work, communicative competence, self-regulation and the chosen coping strategies for interactions with citizens. Communicative competence, which means knowledge of communicative norms and rules, corresponding techniques, is a component of socio-psychological competence. Communicative competence determines the quality of an individual’s communication and includes such components as the communicative person qualities, characterizing need for communication, attitudes to communicative methods and communicative abilities - to accept an initiative in communication, be active, respond emotionally to communicative partners’ states, formulate and implement individual communicative program. Therefore, the author concluded that it is important at the stage of selection officers, who will work at extreme conditions, to choose such specialists who can be emotionally satisfied from the labor process; the necessary conditions should also be created to improve work motivation; and only then, we can develop patrol officers’ tolerance to stress. Self-regulation is determined as an important personal quality that must be developed at people having extreme professions. As for patrol officers, self-regulation means changes taking place within the framework of existing rules, norms, stereotypes. &nbsp
Multi-stage Attack and Proactive Defense for CBTC

CBTC is one of the most advanced signal systems at present. The security of the CBTC systems are crucial for its close relation with people’s livelihood, thus the defense methods study is necessary. The information attacks in the CBTC systems have two main attributes: multi-stage and cyber-physical fusion which makes the consequence of failed defense enormous, and more importantly, the traditional passive defense that only statically defense against network domain attacks that can hardly achieve effective defense anymore. Therefore, we adopt proactive defense to solve this problem. In this paper, an in-depth analysis of the multi-stage feature of attacks in the CBTC systems has been made, based on which, we propose a multi-stage game model framework to describe the attack–defense interaction in each stage and obtain the optimal defense strategies by calculating the game equilibrium. Finally, the result reveals the effectiveness and superiority of the proposed method.
ON STUDY OF SOME ASYMMETRIC KEY CRYPTOGRAPHY ALGORITHMS

The cryptography uses different method by encrypting data at sender side and decrypted at receiver side .For securing the data there are two main types of cryptography algorithm, one is called symmetric and other is called asymmetric algorithms.In this paper I discuss about some asymmetric key algorithms with its advantages and disadvantages. In particular RSA, DSA, Diffie-Hellman,Elgamal, Elliptic curve cryptography and XTR for asymmetric encryption algorithms.Asymmetric key algorithms use different keys for encryption and decryption. The keys arePrivate Key and Public Key. . Public key for encrypt (conversion form data or information to code) and private key for decrypt (reciprocal of encryption or reverse process of encryption) a message.Public key is very efficient for authentication as well as for encryption. The decryption key cannot be derived from the encryption key. Asymmetric key algorithms used for transmitting encryption keys or other data securely even when the parties have no opportunity to agree on a secret key in private.
Research on Equipment Support Evaluation Method Based on Wavelet Neural Network

To evaluate the equipment support level scientifically and reasonablely, a Wavelet Neural Network (WNN) evaluation method of equipment support is proposed. In the method, firstly, on the basis of system analysis, the evaluation index system of equipment support is constructed. Then WNN model is established, and the equipment support is evaluated by built model. The simulation result verifies its feasibility and effectiveness.
The Effect of Employee Wage on Business Performance of Lodging Companies

The purpose of this study is to verify the effect of the average wage per employee on business performance of lodging companies. Human resource is one of the most important core competencies of the companies, and human resource management of lodging companies, which is a labor intensive service industry, will be more important. This paper focuses on wage, which is a representative item related to human resource. Analysis of 2,515 firm-year from 2000 to 2017 showed that the relationship between the average wage per employee and business performance appeared to be positive. All analyses, such as correlation, univariate, and regression reported consistent results. It appears that high wage served as a motivation for employees of low-paying lodging companies, and therefore, performance has improved. Despite the importance of the study of employees, which constitutes a large part of the companies, only a fragmentary study of a particular hotel company has been made while little research on the entire lodging business has been conducted due to the limitations of data collection. This study is meaningful in that it has verified the relationship between the average wage per employee on business performance for the externally audited lodging companies. Lodging companies will need to make efforts to improve their performance through appropriate compensation to their employees.
Do It KWIC(er) (and Better)

This chapter expands upon the previous chapter in order to build an interactive and reusable Keyword in Context (KWIC) application that allows for quick and intuitive KWIC list building. Readers are introduced to interactive R functions including readline and functions for data type conversion.
JOY OF LEARNING OF MALAY VOCABULARY USING UNIQUE VOCABULARY APP: SINGAPORE EXPEREINCE

In the 21st Century, students are more enthuse to explore and enhane their learning using Information and Communication Technology (ICT). Learning aproaches that utilise ICT usually motivate learners to participate actively is learning amongst students. This paper explains the experience of Singapore leveraging on ICT in Malay language (ML) teaching and learning in particular in the learning of ML vocabulary. Students like the element of games in learning. For this purposes, Malay Language Centre of Singapore (MLCS) developed Bitara Kata or Unique Vocabulary App to motivate learners in the learning of ML vocabulary. Five schoools and 89 students were involved in the trialling of the App to investigae the effectiveness of the App in enhancing the learning of ML vocabulary among students. The findings of the trialling showed that students’ vocabulary increased. Students could learn and assess the App anytime and anywhere according to students’ pace of learning and comforts. This App be accessed and downloaded for free by students, teachers, parents and anyone. Thus far, the App has been downloaded more than 15,500 users from all over the world.
Efficient Pairing-Free Provably Secure Scalable Revocable Identity-Based Signature Scheme

Revocation functionality is essential for the practical deployment of identity-based cryptosystems because a user’s private key may be corrupted by hacking or the period of a contract expires. Many researchers are focusing on revocable identity-based encryption scheme, while revocable identity-based signature scheme has received limited concentration. Recently, several revocable identity-based signature schemes have been proposed. However, these schemes are not scalable and are vulnerable to signing key exposure attack. In this paper, we first refine the security model of revocable identity-based signature scheme by considering the signing key exposure attack. Then, we propose a pairing-free revocable identity-based signature scheme with signing key exposure resistance. The proposed scheme is more efficient and practical than existing schemes in terms of update cost, sign cost, verification cost and scalability. Finally, we prove the proposed scheme is existentially unforgeable against adaptively chosen message and identity attacks under the standard discrete logarithm assumption in the random oracle model.
Multi-subpopulation Algorithm with Ensemble Mutation Strategies for Protein Structure Prediction

One of the most challenging problems in protein structure prediction (PSP) is the ability of the sampling low energy conformations. In this paper, a multi-subpopulation algorithm with ensemble mutation strategies (MSEMS) is proposed, based on the framework of differential evolution (DE). In proposed MSEMS, multiple subpopulations with different mutation strategy pools are applied to balance the exploitation and exploration capability. One of the subpopulations is utilized to reward the one with the best performance in the other three subpopulations. Meanwhile, a distance-based fitness score is designed to alleviate inaccuracy of low-resolution energy model. The experimental results indicate that MSEMS has the potential to improve the accuracy of protein structure prediction.
GPU Based Acceleration of Intelligent Grid Forecasting

With the rapid development of the Internet, the era of big data is coming. The weather forecast operation also is faced more challenges and opportunities. At present, the intelligent grid forecasting operation being carried out by the China Meteorological Administration will be based on meteorological big data, artificial intelligence methods and high-performance computing. This study uses the high-frequency grid multi-source observed fusion product generated by the HRCLDAS operational system of the National Meteorological Information Center as the grid observation data. The Sliding Two-Predictor regression correction method is used to test the full-grid point correction of the China’s regional ECMWF model direct output products of. And three different parallel computing schemes were compared with each other. The results show that the STPRC method can correct the ECMWF mode direct output product (DMO), and the grid MAE of 2-m temperature and 10-m wind speed can be greatly reduced. At the same time, the parallel computing scheme of GPU can greatly improve the efficiency of grid modeling. The combination of the two technologies finally produces high-accuracy, high-temporal and resolution grid forecasting products in a timely and efficient manner.
Sistem Pakar Mendiagnosa Penyakit Polio Menerapkan Metode Hybrid Case Based

Expert system of a computer system designed to be able to do reasoning like an expert or expert in a particular field. It should be noted, however, that this expert system is not a substitute for an expert or physician but is only for limited equipment, since this expert system is consultative and also has no such properties as a physician who is able to identify in detail the illness experienced by the patient with his or her thoughts . This expert system is made using Hybrid Case Based method. This method is a combination of the system that is Rule Based Reasoning (RBR) and Case Based Reasoning (CBR), this method has a better accuracy than the method running alone. This method will process a symptom so that can be detected disease suffered by the patient.
Code Readability Management of High-level Programming Languages: A Comparative Study

Quality can never be an accident and therefore, software engineers are paying immense attention to produce quality software product.Source code readability is one of those important factors that play a vital role in producing quality software.The code readability is an internal quality attribute that directly affects the future maintenance of the software and reusability of same code in similar other projects.Literature shows that readability does not just rely on programmer's ability to write tidy code but it also depends on programming language's syntax.Syntax is the most visible part of any programming language that directly influence the readability of its code.If readability is a major factor for a given project, the programmers should know about the language that they shall choose to achieve the required level of quality.For this we compare the readability of three most popular high-level programming languages; Java, C#, and C++.We propose a comprehensive framework for readability comparison among these languages.The comparison has been performed on the basis of certain readability parameters that are referenced in the literature.We have also implemented an analysis tool and performed extensive experiments that produced interesting results.Furthermore, to judge the effectiveness of these results, we have performed statistical analysis using SPSS (Statistical Package for Social Sciences) tool.We have chosen the Spearman's correlation ad Mann Whitney's T-test for the same.The results show that among all three languages, Java has the most readable code.Programmers should use Java in the projects that have code readability as a significant quality requirement.