Reviewerly/exHarmony huggingface dataset:
Multimedia Motion of Picking Robot Based on Cooperative Relationship of Matching Gradient Algorithm

With the continuous development of social economy, robots gradually replace human beings in many aspects of auxiliary work, but it is worth noting that orderly, accurate, and safe operation is the reasonable form of robot movement. In view of the existing limitations, this study combines the gradient matching algorithm, by using a high-precision motion matching for the visual system, improves the automation precision, and, at the same time, picking fruit image smoothing and enhancement, achieves fruit edge feature extraction; the simulation experiments proved that matching the gradient algorithm is effective and can realize the visual and actions match together and support picking robot movement.
Improving the Performance of Continuous-Variable Measurement-Device-Independent Quantum Key Distribution via a Noiseless Linear Amplifier

In the continuous variable measurement-device-independent quantum key distribution (CV-MDI-QKD) protocol, both Alice and Bob send quantum states to an untrusted third party, Charlie, for detection through the quantum channel. In this paper, we mainly study the performance of the CV-MDI-QKD system using the noiseless linear amplifier (NLA). The NLA is added to the output of the detector at Charlie's side. The research results show that NLA can increase the communication distance and secret key rate of the CV-MDI-QKD protocol. Moreover, we find that the more powerful the improvement of the performance with the longer gain of NLA and the optimum gain is given under different conditions.
The Relationship Between Reading Interest and Figurative Language Mastery With Short Story Writing Skills

This study aims to (1) prove a significant relationship between short story writing skills and reading interest. (2) proves a significant relationship between short story writing skills and mastery of figurative language. This type of research is quantitative research and the research design used is an expost facto correlational design. The data of this research are numerical data/nominal scores of interest in reading, mastery of figurative language and short story writing skills. Data collection techniques, namely questionnaire data to collect information on reading interest, multiple choice test data, and data on the assignment of writing short stories. The data analysis technique uses statistics that aim to determine the relationship between variables. The results obtained indicate that the results of the questionnaire analysis of students' reading interest get the category level with the highest frequency, which is in the high category. The results of the analysis of students' mastery of figurative language got the category level with the highest frequency, which was in the medium category. The results of the analysis of students' short story writing skills got the category level with the highest frequency, which was in the high category. There is a significant relationship between the variable of reading interest and short story writing skills with a significance value of 0.002 with a correlation coefficient of 0.437, therefore the value of sig. &lt;0.05 indicates a moderate positive relationship between reading interest and short story writing skills. There is a significant relationship between the variable mastery of figurative language and short story writing skills with a significance value of 0.002 with a correlation coefficient of 0.437, therefore the value of sig. &lt;0.05 indicates a moderate positive relationship between mastery of figurative language and short story writing skills
Phishing URL Detection: A novel hybrid Approach using Long Short-Term Memory and Gated Recurrent Units

Phishing is one of the oldest types of cyber-attack, which mostly comes in the form of camouflaged URLs to delude the users to disclose their personal information for malevolent purposes of the attacker.It is one of the easiest ways of inducing people into revealing their personal credentials including credit card details.Usually, most phishing attacks come up as fake websites pretending to mimic a trustworthy website, and the attackers use these malicious website URLs for successful data breaches.Therefore, it is a necessity to filter up which URLs are benign, and which are malicious.This study proposes three non-hybrid deep learning models, namely CNN (1D), LSTM, GRU, and four hybrid deep learning models, namely GRU-LSTM, LSTM-LSTM, BI (GRU)-LSTM, and BI (LSTM)-LSTM.Based on the results obtained, it was found that BI (GRU)-LSTM model was the best performing model with an accuracy of 93.91%, precision of 93.94 %, recall of 93.38 %, and F1-Score of 93.66 %.Thus, the primary objective of this paper is to provide an insight into the hybrid deep learning approaches in phishing URL detection by evaluating their accuracy, precision, recall, and f1 score.
Future Preschool Teachers’ Search and Research Skills Formation During Professional Training

Based on the established essential characteristics and the structure of professional training of students, taking into account the results of the observational experiment, the levels of future preschools’ teachers search and research skills formation of preschool institutions were determined. The methods of scientific research were the analysis of scientific and methodological literature, educational documentation on pedagogical practice, questionnaires of future educators, as well as observation of research activities of students of higher education institutions. Analysis of psychological and pedagogical research, conducting a statement experiment made it possible to establish the features of the structural elements of research activities. The research experiment made it possible to check the level of formation of research skills in students – future educators of preschool education, as well as how they master the motivational-value, content-procedural, research components of professional training, acquire knowledge and research skills. The results of the inspection were carried out in accordance with the developed criteria, indicators and levels of research skills of future educators of preschool educational institutions.
Variable Selection Using aModified Gibbs Sampler Algorithm with Application on Rock Strength Dataset

Variable selection is an essential and necessary task in the statistical modeling field. Several studies have triedto develop and standardize the process of variable selection, but it isdifficultto do so. The first question a researcher needs to ask himself/herself what are the most significant variables that should be used to describe a given dataset’s response. In thispaper, a new method for variable selection using Gibbs sampler techniqueshas beendeveloped.First, the model is defined, and the posterior distributions for all the parameters are derived.The new variable selection methodis tested usingfour simulation datasets. The new approachiscompared with some existingtechniques: Ordinary Least Squared (OLS), Least Absolute Shrinkage and Selection Operator (Lasso), and Tikhonov Regularization (Ridge). The simulation studiesshow that the performance of our method is better than the othersaccording to the error and the time complexity. Thesemethodsare applied to a real dataset, which is called Rock StrengthDataset.The new approach implemented using the Gibbs sampler is more powerful and effective than other approaches.All the statistical computations conducted for this paper are done using R version 4.0.3 on a single processor computer.
Evaluation of Computational Approaches of Short Weierstrass Elliptic Curves for Cryptography

Abstract The survey presents the evolution of Short Weierstrass elliptic curves after their introduction in cryptography. Subsequently, this evolution resulted in the establishment of present elliptic curve computational standards. We discuss the chronology of attacks on Elliptic Curve Discrete Logarithm Problem (ECDLP) and investigate their countermeasures to highlight the evolved selection criteria of cryptographically safe elliptic curves. Further, two popular deterministic and random approaches for selection of Short Weierstrass elliptic curve for cryptography are evaluated from computational, security and trust perspectives and a trend in existent computational standards is demonstrated. Finally, standard and non-standard elliptic curves are analysed to add a new insight into their usability. There is no such survey conducted in past to the best of our knowledge.
SPETS: Secure and Privacy-Preserving Energy Trading System in Microgrid

Recently, the development of distributed renewable energy resources, smart devices, and smart grids empowers the emergence of peer-to-peer energy trading via local energy markets. However, due to security and privacy concerns in energy trading, sensitive information of energy traders could be leaked to an adversary. In addition, malicious users could perform attacks against the energy market, such as collusion, double spending, and repudiation attacks. Moreover, network attacks could be executed by external attackers against energy networks, such as eavesdropping, data spoofing, and tampering attacks. To tackle the abovementioned attacks, we propose a secure and privacy-preserving energy trading system (SPETS). First, a permissioned energy blockchain is presented to perform secure energy transactions between energy sellers and buyers. Second, a discrete-time double auction is proposed for energy allocation and pricing. Third, the concept of reputation scores is adopted to guarantee market reliability and trust. The proposed energy system is implemented using Hyperledger Fabric (HF) where the chaincode is utilized to control the energy market. Theoretical analysis proves that SPETS is resilient to several security attacks. Simulation results demonstrate the increase in sellers’ and buyers’ welfare by approximately 76.5% and 26%, respectively. The proposed system ensures trustfulness and guarantees efficient energy allocation. The benchmark analysis proves that SPETS consumes few resources in terms of memory and disk usage, CPU, and network utilization.
Review of the theoretical approaches regarding the legal protection of objects generated by artificial intelligence systems in the field of copyright and related rights

Keywords: artificial intelligence, copyright, related rights, sui generis&#x0D; The publication provides a descriptive review of existingtheoretical approaches regarding the legal protection of objects generated byartificial intelligence systems in the field of copyright and related rights, namely.1) The inexpediency of legal protection of computer-generated objects. It is concludedthat the absence of legal regulation and free circulation of generated objects isconsidered the easiest option. Still, hardly fair and justified, as the creation of artificialintelligence systems requires large and significant investments in their development.2) The possibility of protecting computer-generated objects by copyright as originalworks. It has been established that extending the concept of «originality» to computergeneratedobjects seems unjustifiable.3) The introduction of the latest iteration of the fiction theory and establishing aspecial legal status for artificial intelligence systems. It is noted that such an approachseems premature because the existing artificial intelligence systems are amanifestation of «narrow» or «weak» artificial intelligence and not artificial generalintelligence.4) Protection of specific generated objects through related rights. It is concludedthat the objects generated by AI systems may be protected in Ukraine through theprism of related rights, under the condition that the relevant object can be attributedto a phonogram, videogram, or broadcast (program) of broadcasters respectively.5) Protection of generated objects through a special legal regime under copyrightlaw. It is described that this approach cannot be considered a universal example forimitating the legal protection of objects generated by computer programs because itsapplication leaves more questions and inconsistencies than solving the problem onthe merits.6) Protection of generated objects through sui generis law. It is assumed that applyingsuch an approach to the protection of objects generated by computer programswill not lead to significant changes in copyright and will protect the interests and investmentsof developers of artificial intelligence systems.
Creative Social Potential of Digital Society

In the article, the authors consider the phenomenon of creativity, creativity as a demanded competence in contemporary society. Artists, poets, composers, musicians, carriers of the so-called fine art creativity, have always been in demand. In the “fast” digital world, creativity takes on new characteristics, turns into a mass-market productive force. The public demand for creativity and the supply for this characteristic are undergoing noticeable changes now. Creativity has now become a demanded competence that can bring high income to its owners. The authors analyze the influence of common social institutions of socialization on the development of creativity. The article provides a definition of individual and social creativity , structuring the sociological approaches available in world science to the study of creativity and its nature. The authors introduce a new term — paracreativity and reveal its features. The authors come to the conclusion that society, by creating and maintaining social norms, aimed at developing inner freedom and creativity, contributes to the formation of happier social groups and thus individuals, where each individual has created conditions for the disclosure and realization of his creative potential for the benefit of himself and a large or small society, depending on the scale of the activity. Meanwhile, in the digital world, the creator himself regulates the scale of his activities, using/neglecting social networks.
A Relative Investigation of Various Algorithms for Online Financial Fraud Detection Techniques

Online financial transactions play a crucial role in today’s economy. It becomes an unavoidable part of the business and global activities. Transaction fraud executes thoughtful intimidations to e-commerce spending. Now-a-days, the online contract or business is fetching additional sound by knowing the types of online transaction frauds associated with, these are raising which disturbs the currency accompanying business. It has the capability to confine and encumber the contract accomplished by the intruder from an honest consumer’s credit card information. In order to avoid such a problem, the proposed system is established transaction limit for the customers. Efficient data is only considered for detecting fraudulent user action and it happens only at the time of registration. Transaction which is happening for any individual is not at all known to any FDS (Fraud Detection System) consecutively at the bank which mainly issues credit cards to customers. To speak out this problem, BLA (Behaviour and Location Analysis) is executed. The FDS tracks at a credit card provided by bank. All the inbound business is directed to the FDS aimed at confirmation, authentication and verification. FDS catches the card particulars and matter to confirm that the operation is fake or genuine. The pick-up merchandises are unknown to Fraud Detection System. If the transaction is assumed to be fraud, then the corresponding bank declines it. In order to verify the individuality, uniqueness or originality, it uses spending patterns and geographical area. In case, if any suspicious pattern is identified or detected, the FDS system needs verification. The information which is already registered by the user, the system identifies infrequent outlines in the disbursement method. After three invalid attempts, the system will hinder the user. In this proposed system, most of the algorithms are checked and investigated for online financial fraud detection techniques.
FIRST STEPS BEFORE THE JUMP: UKRAINIAN UNIVERSITY LIBRARIANS SURVEY ABOUT OER

Objective. The authors study: 1) the level of awareness of librarians of Ukrainian universities about Open Educational Resources (OER); 2) the ability of librarians to provide support services for the development, creation and use of OER in teaching, learning, research. Methods. The study was conducted by methods of analysis of professional literature, online survey (questionnaires) and analysis of the results. The questionnaires “Library of Higher Education Institution in Support of Distance Learning: Open Educational Resources” was distributed from 20.04. until 20.05.2021 among 137 directors of libraries of higher education institutions of Ukraine. Responses came from 77 libraries. The questionnaire consisted of 9 open-ended and closed-ended questions to allow researchers to get a holistic picture of the research process. Results. The analysis of 77 questionnaires showed that the vast majority of free HEI libraries in Ukraine have extensive experience in working with electronic educational resources. Ranking by resource type prove that 95.89% of library collections are the own generation resources (HEI authors): databases, incl. repositories. The concept of "Open Educational Resources" (OERs) is familiar and understandable to 84.42% of respondents. At the same time, 75.32% are already involved in supporting the OER. Librarians may catalog them (21.92%) or not catalog (32.88%). Among the OER types supported by librarians, educational materials (77.05%) and textbooks (55.74%) predominate. The closest partnership of librarians in OER support (except for teachers) is with the specialists of IT services (66.13%). Conclusions. Despite the still spontaneous, chaotic and little-studied nature of the library movement towards OER, librarians are well aware of this issue. At the same time, 96.1% of respondents want to improve their competencies in the direction of supporting open educational resources. This is very important, because it is the understanding and acceptance of OER that is crucial for a long-term vision of this movement. That is why specific aspects, such as organizational, economic, personnel and motivational, need urgent further study.
Modularity in FOLIO: principles, techniques and tools

From its earliest inception, FOLIO was conceived not as an ILS (Integrated Library System), but as a true Services Platform, composed of many independent but interdependent modules, and forming a foundation on which an ILS or other library software could be built out of relevant modules. This vision of modularity is crucial to FOLIO’s appeal to the library community, because it lowers the bar to participation: individual libraries may create modules that meet their needs, or hire developers to do so, or contribute to funding modules that will be of use to a broader community — all without needing “permission” from a central authority. The technical design of FOLIO is deeply influenced by the requirements of modularity, with the establishment of standard specifications and an emphasis on machine-readable API descriptions. While FOLIO’s modular design has proved advantageous, it also introduces difficulties, including cross-module searching and data consistency. Some conventions have been established to address these difficulties, and others are in the process of crystallizing. As the ILS built on FOLIO’s platform grows and matures, and as other application suites are built on it, it remains crucial to resist the shortcuts that monolithic systems can benefit from, and retain the vision of modularity that has so successfully brought FOLIO this far.
The Effectiveness of Online Learning Model Implementation

The study from home policy was implemented to reduce crowds as an effort to suppress the spread of Covid-19. All levels of education were asked to learn from home, guided and facilitated by educators and educational institutions. Ideally, the learning process should run smoothly even though learning activities are carried out online. However, the shift in learning modes from face-to-face to online has created many learning problems. This study aimed to assess the effectiveness of the implemention of online learning models in Indonesia. This was a descriptive study and a quantitative approach was used. Data were collected online using a questionnaire. Data were analyzed interactively through three components of analysis, namely data reduction, data presentation, and drawing conclusions or verification. Based on the results, it was found that the implementation of online learning was effective. 100% of the lecturers implemented online learning using LMS, of which 86.67% were skilled at using the LMS platform in carrying out online learning. The lecturers used various strategies to organize learning, including integrating cognitive materials in core activities to improve student preparation, involvement and independence in online learning activities. In addition, 50% of the lecturers have conducted student satisfaction surveys on online learning.&#x0D; Keywords: effectiveness, learning model, online learning
DESIGN FRAMEWORK FOR ABLUTION SPACES OF ICONIC MOSQUES IN MALAYSIA

Mosques are places where Muslims perform prayers and other social activities. Those are built as a place for humans to worship the Almighty Allah at all times, as well as to provide an environment that responds to the needs of devotees and educates the future generation by the Quranic verses and the Prophet's teachings. Derived from the Holy Quran and the Prophet, purity is compulsory at all times for Muslims, and has many meanings that are applicable during prayers and the day. The ablution room is integrated into all mosque designs because it is an unseparated element. However, Malaysian mosques have been questioned in their application of some Islamic regulations to uniform a hygienically clean space that can respond the needs of Muslims. The design of the ablution rooms in Malaysian mosques is encountering a serious issue regarding the spaces' cleanliness. Although the ablution room has been designed to respond the Muslim's need to conduct the ablution practice and to cleanse a person spiritually and physically, several problems related to its design aspects were revealed. This research investigates the cleanliness of the Malaysian ablution space. It examines how the design aspects of the ablution rooms of the Iconic Malaysian Mosques impact the area's cleanliness and its users. Five case studies were selected for this study. Three methods of study were utilized: physical observation, architectural drawing analysis, and interviews. Aspects of design form, ventilation, cleaning status, and user experience were discussed. This research suggested that the larger mosques in Malaysia were suffering from serious hygiene issues that resulted from many aspects, including poor design, ventilation systems, and users' abuse. The research suggested some design guidelines for future and existing ablution areas that will improve the cleanliness.
Morphological Analysis of Japanese Hiragana Sentences using the BI-LSTM CRF Model

This study proposes a method to develop neural models of the morphological analyzer for Japanese Hiragana sentences using the Bi-LSTM CRF model. Morphological analysis is a technique that divides text data into words and assigns information such as parts of speech. This technique plays an essential role in downstream applications in Japanese natural language processing systems because the Japanese language does not have word delimiters between words. Hiragana is a type of Japanese phonogramic characters, which is used for texts for children or people who cannot read Chinese characters. Morphological analysis of Hiragana sentences is more difficult than that of ordinary Japanese sentences because there is less information for dividing. For morphological analysis of Hiragana sentences, we demonstrated the effectiveness of fine-tuning using a model based on ordinary Japanese text and examined the influence of training data on texts of various genres.