Reviewerly/exHarmony huggingface dataset:
Security Enhancement of an Automated Teller Machine Using Fingerprint and Password

This paper focuses on how to enhanced security of Transactions in Automatic Teller Machine system using a multi-factor authentication system (Password and Fingerprint). In order to achieve security and to overcome illegal activities, shortcoming of piracy in money transactions, we propose the idea of using fingerprints of customers and password instead of traditional use of PIN number. After authorized verification, the customer will be able to proceed for transaction else after four successive wrong attempts, the ATM card will be ejected automatically and a message will be sent to the registered mobile number. The proposed system is developed to provide better security to the ATMs. Keywords— ATM, Fingerprint, PIN, Biometric.
EQ: An Eigen Image Quality Assessment based on the Complement Feature

An Eigen formulation is proposed for image quality assessment IQA.Each block is represented by an array composed of feature vectors (intensity/color at this stage).After attaching the complement feature(s), the autocorrelation matrix is computed for each block.The proposed full reference FR-IQA is simply the deviation of the Eigen values of the degraded image from that of the original image.Interestingly, the second largest Eigen value was sufficient to perform this comparison.Results and comparisons with SSIM and GMSD schemes on different types of degradation are demonstrated to show the effectiveness of the proposed schemes.Using TID2013 database, the proposed scheme outperforms SSIM.In addition, the proposed schemes is closer to the MOS score compared to GMSD; however, the correlation with MOS is inferior as illustrated in the tables.These results are concluded from the average behaviour on all the images using all degradations (with 5 levels) on the database.
Syntactische tolerantie: hoe voorzetselvoorwerpen bij intransitieve werkwoorden ook in een passieve zin kunnen voorkomen?

The aim of this article is to answer the question whether it is possible to form a passive voice of intransitive verbs with prepositional objects. First, I present the information concerning prepositional objects and subsequently provide a brief discussion of the passive voice in Dutch. I also present conditions under which an intransitive verb with a prepositional object is allowed to undergo passivisation.
Mengatasi Kesulitan dalam Berbahasa Inggris

Learning English is still quite difficult, especially among junior high school students. Learning difficulties due to the lack of motivation to learn, infrastructure, learning materials and environment. The difficulty often faced by students is about pronunciation or speaking ability. The atmosphere of the Covid-19 pandemic is a major problem in the implementation of teaching because learning is carried out online and this is a new challenge for students and educators, therefore to increase learning interest for students, learning is still designed as well as possible so that students are able to participate in learning. Based on the phenomenon, the Master of linguistics at Warmadewa University takes part through community service activities by holding training programs in the form of online learning about how to speak English so that students have high motivation even in a pandemic situation. This is done with the aim of assisting students in improving their English language skills of Swastika students located in Badung District which is not far from the Warmadewa University. The four language skills that help students learn a language are writing, reading, listening and speaking. This study was designed using qualitative research with the FGD method. This study aims to explain the difficulty of English among junior high school level students.
The Python language: Adopt a snake!

Python is a versatile and easy-to-learn programming language. It has been in existence for almost 30 years, but it remained quite confidential for many years and is now a big success—to the point of being one of the most widely taught programming languages today. In this chapter, we will quickly introduce the basics of the Python language and its syntax.
Tourism Information System To Facilitate Tourists in Determining Travel Routes in a Web-Based City of Pagar Alam

This study aims to create a Web-based Tourism Information System. In conveying about tourism, promotion is still carried out through the mass media of television, newspapers, banners and baleho. The impact is that tourists still find it difficult to determine the planning of a tour in the city of Pagar Alam. The system development method used is the Web Engineering method with five stages of Customer Communication, Planning, Modeling, Construction and Deployment. Therefore, the researcher will create a web-based tourism information system in order to make it easier for tourists to find information such as tourist attraction data, hotel data and restaurant data as well as places that are connected to the google map. With the existence of a web-based information system can help spread promotions to tourists widely to increase tourist visits to the City of Pagar Alam.
The recurrence formula for the number of solutions of a equation in finite field

The main purpose of this paper is using analytic methods to give a recurrence formula of the number of solutions of an equation over finite field. We use analytic methods to give a recurrence formula for the number of solutions of the above equation. And our method is based on the properties of the Gauss sum. It is worth noting that we used a novel method to simplify the steps and avoid complicated calculations.
Pattern Morphing for Efficient Graph Mining

Graph mining applications analyze the structural properties of large graphs, and they do so by finding subgraph isomorphisms, which makes them computationally intensive. Existing graph mining techniques including both custom graph mining applications and general-purpose graph mining systems, develop efficient execution plans to speed up the exploration of the given query patterns that represent subgraph structures of interest. In this paper, we step beyond the traditional philosophy of optimizing the execution plans for a given set of patterns, and exploit the sub-structural similarities across different query patterns. We propose Pattern Morphing, a technique that enables structure-aware algebra over patterns to accurately infer the results for a given set of patterns using the results of a completely different set of patterns that are less expensive to compute. Pattern morphing "morphs" (or converts) a given set of query patterns into alternative patterns, while retaining full equivalency. It is a general technique that supports various operations over matches of a pattern beyond just counting (e.g., support calculation, enumeration, etc.), making it widely applicable to various graph mining applications like Motif Counting and Frequent Subgraph Mining. Since pattern morphing mainly transforms query patterns before their exploration starts, it can be easily incorporated in existing general-purpose graph mining systems. We evaluate the effectiveness of pattern morphing by incorporating it in Peregrine, a recent state-of-the-art graph mining system, and show that pattern morphing significantly improves the performance of different graph mining applications.
Intrinsic Image Captioning Evaluation

The image captioning task is about to generate suitable descriptions from images. For this task there can be several challenges such as accuracy, fluency and diversity. However there are few metrics that can cover all these properties while evaluating results of captioning models.In this paper we first conduct a comprehensive investigation on contemporary metrics. Motivated by the auto-encoder mechanism and the research advances of word embeddings we propose a learning based metrics for image captioning, which we call Intrinsic Image Captioning Evaluation(I2CE). We select several state-of-the-art image captioning models and test their performances on MS COCO dataset with respects to both contemporary metrics and the proposed I2CE. Experiment results show that our proposed method can keep robust performance and give more flexible scores to candidate captions when encountered with semantic similar expression or less aligned semantics. On this concern the proposed metric could serve as a novel indicator on the intrinsic information between captions, which may be complementary to the existing ones.
DSM Refinement with Deep Encoder-Decoder Networks

3D city models can be generated from aerial images. However, the calculated DSMs suffer from noise, artefacts, and data holes that have to be manually cleaned up in a time-consuming process. This work presents an approach that automatically refines such DSMs. The key idea is to teach a neural network the characteristics of urban area from reference data. In order to achieve this goal, a loss function consisting of an L1 norm and a feature loss is proposed. These features are constructed using a pre-trained image classification network. To learn to update the height maps, the network architecture is set up based on the concept of deep residual learning and an encoder-decoder structure. The results show that this combination is highly effective in preserving the relevant geometric structures while removing the undesired artefacts and noise.
Review and Test of Steganography Techniques

Steganography is the art of concealing a secret message within an appropriate-multimedia carrier such as images, audio, video files, and even network packets. Steganographic techniques have been used since ancient times to hide the message from third-parties deemed to be enemies. On one hand, Steganography is a useful technique that has been applied in various useful applications. On the other hand, however, the same technique has been applied and used for the wrong purposes by people who have ill intentions. The increase in computational power and increase in security-awareness over the past few years have propelled the application of steganography in computational security-techniques. Being robust, undetectable, and having a good capacity of hidden-data, steganography has been preferred for hiding data than watermarking and cryptographic-techniques. This paper clarifies the application of steganography on different multimedia-carriers by using various potential tools, methods, and principles to either apply or detect steganography techniques.
The relationship of cultural intelligence with self-government of future teachers in the educational environment of a multi-ethnic region (on the example of the Khabarovsk Territory)

The paper presents the results of a study on the study of the relationship between self-government and the cultural intelligence of teachers in the educational environment of the multi-ethnic Khabarovsk Territory. The presented pedagogical system of interconnection based on the principles of using the cluster approach in the interaction of institutions of preschool, general, secondary vocational and higher education in the exchange of experience and the dissemination of best practices.
Bisa ng Filtech Web Apps bilang kagamitang panturo sa asignaturang Filipino ng Lungsod ng Pasig

This study aims to measure the effectiveness of Filtech Web Apps in teaching narrative and persuasive text in Filipino subject to Grade 11 senior high school students of Buting Senior High School.A quasi-experimental research design was employed, where student-respondents were divided into two groups -the experimental group and the comparison group.The comparison group was subjected to traditional teaching method while the experimental group used the Filtech Web Apps.The scores obtained by each group of students in pretest, posttest, formative and summative examination were computed and used as the basis to determine the effectiveness of the Filtech Web Apps.As a result of the pretesting, no significant difference was noted in the persuasive text and significant difference appeared in narrative text.Whereas the experimental group obtained higher score compared to comparison group.The academic performance of the experimental group subjected to Filtech Web Apps performed better in terms of their average scores in formative, summative and post-test evaluation, than the comparison group who underwent the traditional method of teaching.The research study was significant as it confirmed the effectiveness of using Filtech Web Apps toward the objective of improving the performance of Grade 11 students in understanding narrative and persuasive text.The study, therefore, strongly recommends the adaptation of Filtech Web Apps and the use of other appropriate modern teaching technology, particularly in teaching Filipino subject.This is to enhance the understanding, the content evaluation skill and to further motivate students to study Filipino language.Similarly, Filipino teachers are encouraged to introduce innovation in their teaching methodology, so that these groups of millennial students would find the subject and topics interesting.This would also promote and stimulate interaction, collaboration, and active participation among students.
Development of an algorithm for selecting the optimal set of tools and techniques for Agile project management in industry and engineering

Continuous development and the increase of the safety requirements in the field of engineering and industry, as well as the need to comply with the planned timing and costs of the projects require the use of modern approaches to the management of complex engineering systems and their interaction. To achieve the optimal balance between the deadlines and the resources expended, a project approach is used in world practice. One of the new methods of the project approach is Agile management. The use of Agile project management in industry and engineering requires a systematic adaptation of implementation approaches, taking into account internal requirements, risks and organizational characteristics, and is due to the high complexity of decision-making. The paper considers an approach to the formation of a generalized algorithm for the optimal set of tools selection for Agile project management in industry and engineering based on system analysis methods. This algorithm is designed to provide decision support for the selection of the most suitable tools and techniques for Agile project management with a view to their successful implementation.
A Zero-Trust Federated Identity and Access Management Framework for Cloud and Cloud-based Computing Environments

Identity and Access Management (IAM) is an important aspect of information security. The deployment of cloud computing (CC) and cloud-based computing (CbC) creates a complex information security scenario involving multiple global stakeholders and geographically dispersed infrastructures. Therefore, implementing IAM in CC/CbC requires the consideration and consolidation of multiple factors. A trust-based approach towards information security may not be a credible option for the CC/CbC environment as trust-based relationships among different architectural elements and including human beings may pose an additional security threat to the cloud space. In this paper, we propose a zero-trust framework for federated IAM in CC/CbC. The proposed framework deploys a decentralised approach towards IAM that aims to minimize any single entity’s controlling power over the digital assets in the CC/CbC space. The critical component of the proposed framework is the decentralised audit log.
A Novel Survey Platform in the Age of COVID-19 to Increase Accuracy and Adoptability While Reducing Selection Bias

Abstract Given the ongoing COVID-19 pandemic, secure and distanced data collection platforms are critical for reaching vulnerable populations. Commonly used electronic data collection systems lack a myriad of critical features, including a modern technology stack, new data encryption and security standards, study workflows, and reporting algorithms. Moreover, these systems do not have multilingual mapping functionalities of survey and consent forms. All of these components ultimately increase selection bias while simultaneously reducing the security and quality of the response data. In order to directly address the aforementioned issues, we have developed a multilingual and highly secure data management platform. Our application is built using stable, tested, and modular programming frameworks and design patterns targeted at accommodating intricately complex structures of polyglot mapping, large volume of data, encryption and granular user authorization. The statistical accuracy along with the multilingual mapping are the core highlights of this system. The multilingual function of this platform has the ability to eliminate selection biases while creating a well-balanced cross-section of society. Modern survey design workflows and validation checks ultimately prevent data loss and help reduce data collection errors. The platform design was initiated in April 1, 2020 and has been pilot tested for use in multilingual populations. The currently active application version of the system is capable of supporting in-person and telephone interviews, emailing survey links to every registered participant, building family tree architecture, and online consent management. This platform also has built-in report functionality. Additional features are being explored to improve study coordination and monitoring.
KNN Classification with One-step Computation

KNN classification is a query triggered yet improvisational learning mode, in which they are carried out only when a test data is predicted that set a suitable K value and search the K nearest neighbors from the whole training sample space, referred them to the lazy part of KNN classification. This lazy part has been the bottleneck problem of applying KNN classification. In this paper, a one-step computation is proposed to replace the lazy part of KNN classification. The one-step computation actually transforms the lazy part to a matrix computation as follows. Given a test data, training samples are first applied to fit the test data with the least squares loss function. And then, a relationship matrix is generated by weighting all training samples according to their influence on the test data. Finally, a group lasso is employed to perform sparse learning of the relationship matrix. In this way, setting K value and searching K nearest neighbors are both integrated to a unified computation. In addition, a new classification rule is proposed for improving the performance of one-step KNN classification. The proposed approach is experimentally evaluated, and demonstrated that the one-step KNN classification is efficient and promising.
EFFICACY OF COMPETENCY-BASED APPROACH IN TEACHING PROCESS OF PHYSICAL EDUCATION IN A UNIVERSITY

The study addresses the efficacy of the competency-based approach in physical education on the basis of the developed model of universal competency (UC-7) formation. The experimental work at the informational stage involved a questionnaire survey, a physical performance test, studies of morphological and functional indicators and psychophysical state. The organizational-activity stage included a program of methodological-practical and educational-training sessions, based on the personality-oriented approach to physical culture and sports activity and aimed at the formation of special knowledge, abilities and skills that contribute to maintaining the proper level of physical fitness and to ensure full-fledged social and professional activity. The control stage included a questionnaire survey and tests aimed at determining the psycho-emotional state, which allowed determining the level of competency formation in students according to the developed assessment system. The competency-based approach was introduced to the physical educational process based on the universal competency formation model. The educational process was reorganized pursuant to new pedagogical conditions. The results were the improvement of students’ physical activity, fitness and performance; the indicators of pulmonary function improved; and the level of personal and situational anxiety and depression in students decreased.
Innovations in teacher training based on partnership with employers from the field of additional education

This article is devoted to the study of innovations in the training of teachers in modern world and domestic experience on the basis of partnership with employers. The article considers the concept of "partnership" in the field of additional education. Particular emphasis is placed on the characterization of the modern situation, which changes the traditional models of higher education. Models of partnership with employers are considered, using the example of institutions of additional education. Foreign and domestic experience of organizing partnerships with employers for training and professional development of pedagogical personnel is analyzed in detail.
Modelling CLV in the Insurance Industry Using Deep Learning Methods

This paper presents a master’s thesis project in which deep learning methods are used to both calculate and subsequently attempt to maximize Customer Lifetime Value (CLV) for an insurance provider’ ...
Completely Regular Codes in Johnson and Grassmann Graphs with Small Covering Radii

Let ${\cal L}$ be a Desarguesian 2-spread in the Grassmann graph $J_q(n,2)$. We prove that the collection of the $4$-subspaces, which do not contain subspaces from ${\cal L}$ is a completely regular code in $J_q(n,4)$. Similarly, we construct a completely regular code in the Johnson graph $J(n,6)$ from the Steiner quadruple system of the extended Hamming code. We obtain several new completely regular codes with covering radius $1$ in the Grassmann graph $J_2(6,3)$ using binary linear programming.
AutoEncoder Guided Bootstrapping of Semantic Lexicon

Mutual bootstrapping is a commonly used technique for many natural language processing tasks, including semantic lexicon induction. Among many bootstrapping methods, the Basilisk algorithm has led to successful applications through two key iterative steps: scoring context patterns and candidate instances. In this work, we improve Basilisk by modifying its two scoring functions. By incorporating AutoEncoder in the scoring functions of patterns and candidates, we can reduce the bias problems and obtain more balanced results. The experimental results demonstrate that our proposed methods for guiding the bootstrapping of a semantic lexicon with AutoEncoder can boost overall performance.
Ternary classification for image aesthetic assessment using deep learning

As the number of digital photos increases, the need for image aesthetic assessment is increasing in various applications to provide improved user satisfaction. Most existing studies have considered binary classification to determine whether an image has a high- or low-level of aesthetic quality. However, the binary classification has a limitation in that when an image is classified incorrectly, users experience a large gap between their perception and the predicted result. To reduce the gap, we propose ternary classification-based image aesthetic assessment. Through experiments using popular classification deep learning models, we show the advantages of the ternary classification over the binary classification.