Reviewerly/exHarmony huggingface dataset:
Offline Signature Verification based on Ensemble of Features using Support Vector Machine

In this paper, we propose a novel feature representation technique namely Edge Histogram and 4 Directional Histogram for offline signature verification system.Edge is a curve or point where the intensity of an image changes rapidly.Edges represent the boundary of object of an image.Edge detection is a process of detecting edges of an image.Several algorithms are available to detect edges effectively from an image.Canny, Roberts, Prewitt and Sobel are several popular available edge detectors.In our approach we used Sobel operator for edge detection.We also applied radon transform on signature samples and obtained fractal properties with the help of box-counting method.Finally fusion of these features forms a feature vector.We employed Support vector machine for classification.Experiments are conducted on bench mark dataset namely CEDAR and GPDS.The obtained experimental results exhibit the performance of the proposed method.
Point-Counterpoint Strategy for Better Reading Comprehension on EFL Junior High School Students

Point-Counterpoint is one of the strategies that can be used to stimulate students and make them free in reading. This study is conducted to reveal the significant difference in reading ability under Point-Counterpoint strategy and conventional technique in class seven students at SMP Negeri 1 Batauga, South Buton regency. The design of this study was a quasi-experimental method. The sample was taken using cluster sampling, in which took class VII-F was selected as an experimental group and class VII-E was a control group. The instruments used were a pretest and a posttest. The results revealed that the average score for the pretest in the experimental group was 47.83, while the average score in the control group was 34.77. The average score for the posttest in the experimental group was 71.13, while it was 58.62 in the control group. Those scores indicated that the students had good reading ability in the experimental group, while the students in the control group had moderate comprehension in reading. The requirement testing outcome informed that the data had a normal distribution and were homogeneous. The hypothesis testing indicated that the tcount was 4.489 and the significant score was 0.000. Both results meant that the Point-Counterpoint strategy was significantly different from a conventional method toward students’ reading comprehension.
Iran’s Cyber Capabilities and Assessing Security Standards for Popular Iranian Websites

The security of online users depends on various factors. One of the most important factors are to follow security standards and use of reliable and updated technology as well as the standards and technologies that have been created in recent years specifically to increase data and communication security on websites and various internet services. However numerous studies show that the current state of global web security is not desirable yet, and these standards and technologies are not being applied as fast as they are developed. Our research in CERTFA Lab on popular Iranian websites (414 websites) show that the security of Iranian websites is not different from the global level, and very few websites are fully utilizing the security standards and modern technologies. According to our investigation, only 7 websites from our assessed sites have been used CSP2 configuration, which the implementation of Cafebazaar.ir and Virgool.io have more detail and other 5 websites just use the upgrade-insecure-requests option as a default setting for CSP. In other cases, popular websites, not only did not use the CSP header, they have also forgotten to use the basic security header. Also, the results of modern standards analysis in this study (such as DNSSEC, CAA, DMARC, SPF, and Expect-CT), which is mandatory for most Internet businesses, indicate that just Eligasht.com, one of the Iranian popular websites, has properly used these standard configurations. Since these security standards and modern technologies are easy to use and cheap to implement, we could say that the reason for this undesirable situation might be the negligence of admins and service providers.
SECURED AND PRIVACY PRESERVING E-KYC SYSTEM USING BLOCKCHAIN

A Blockchain technology guarantees to be highly trending and empowering in financial domain computing programs.The virtual economic system is becoming an fundamental a part of present day life.in order the use of the digital global increases there are more probabilities of lower is the safety stage.So greater using digitization more the frauds and less the safety.In a few cases of personal information, leakage has brought back into the focus the security troubles with the extraordinary identification sharing mechanisms.A client is predicted to provide his identification for authentication by means of unique agencies.So the KYC process offers with the identity of the user.And in flip, provides the desired security.The KYC strategies which are used by the banks are absolutely dependent on the encryption that's sluggish and it is able to result in the lack of patron info to other their birthday celebration economic establishments.This device can be efficient by means of using Blockchain technology, which has the ability to automate numerous manual approaches and it's also proof against hacks of any type.The immutable blockchain block and its distributed ledger is the best complement to the system of KYC.With the addition of clever contacts, fraud detection may be computerized.For KYC identification info garage, we are able to employ any types of KYC.So, the banks can develop a shared non-public blockchain within the financial institution premise and the equal can be used for verifying the documents.This permits the user to get control in their touchy files and also makes it easier for banks to reap the documents they want for compliance.
Modern information and innovative technologies in teaching Ukrainian as a foreign language

International scientific conference «Information technologies and management in higher education and sciences» : conference proceedings (November 28, 2022. Fergana, the Republic of Uzbekistan). Part 1. Riga, Latvia : Baltija Publishing, 2022. 392 pages.
An Efficient Probabilistic Methodology to Evaluate Web Sources as Data Source for Warehousing

Internet is the largest source of data and the requirement of data analytics have fueled the data warehouse to switch from structured conventional Data Warehouse to complex Web Data Warehouse.The dynamic and complex nature of web poses various types of complexities during synthesis of web data into a conventional warehouse.Multi-Criteria-Decision Making (MCDM) is a prominent mechanism to select the best data for storing into the data-warehouse.In this article, a method, based on the probabilistic analysis of SAW and TOPSIS methods, has been proposed to select web data sources as data sources for web data warehouse.This method deals more efficiently with the dynamic and complex nature of web.Here, the result of the selection employs the analysis of both the methods (SAW and TOPSIS) to evaluate the probability of selection of respective score (1-9) for each feature.With these probability values, the probability of selection of the next web sources has been be determined.Moreover, using the same probability values, mean score and standard deviation of the scores of respective features of selected web sources have been deduced, which are further used to fix the standard score of each feature for selection of web sources.The standard score is a parameter of the proposed Mean-Standard-Deviation (MSD) method to check the suitability of web sources individually, whereas others do the same on comparative basis.The proposed method cuts down the cost of the repetitive comparison operation, once after computation of the Standard score using Mean and Standard deviation of each individual feature.Here, the respective value of the standard score of each feature is only compared with the score of each respective feature of the next web sources, so it reduces the cost of computation and selects the web sources faster as well.
Cartoon Film Media in Improving Narrative Writing Ability Of 11th Grade Science Students Of SMAN Situraja

The objectives of the research are: (1) to find out whether the students’ skill in writing narrative texts can be improved by using cartoon films. (2) to find out the effectiveness of the teaching and learning process when cartoon films are used in teaching writing narrative texts. The researcher collected the data using qualitative and quantitative data. The improvement of students’ writing skill includes: (1) having an abundance of vocabulary; (2) using correct capitalizations and spelling; (3) making sentences grammatically; (4) developing their ideas into coherent paragraphs. The effectiveness of using cartoon films shown in: (1) motivating students to write; (2) making the lesson more clearly (3) increasing their interest; (4) increasing their attention. The students’ score in pre-test was 61.77, post-test 1 in cycle 1 was 70.6, and post-test 2 in cycle 2 was 74.90. It can be concluded that the use of cartoon films can improve students’ skill in writing narrative text.
Software Framework for Implementing User Interface Interaction in IOS Applications Based on Oculography

Usage of gaze tracking technologies for the purpose of user interface interaction in iOS applications is significantly hampered by the absence of a unified approach to their integration. Current solutions are either strictly limited to their own use-case or made solely for research purposes and thus inapplicable to real-world problems. The focus of this article is the development of a software framework that performs gaze tracking using native technologies and suggests a unified approach to the development of gaze-driven iOS applications.
Characteristics of mastering the basics of digital literacy by private school students

International scientific conference «Information technologies and management in higher education and sciences» : conference proceedings (November 28, 2022. Fergana, the Republic of Uzbekistan). Part 1. Riga, Latvia : Baltija Publishing, 2022. 392 pages.
Analisis Performa Algoritma K-Nearest Neighbor dan Reduksi Dimensi Menggunakan Principal Component Analysis

This paper discusses the performance of the K-Nearest Neighbor Algorithm with dimension reduction using Principal Component Analysis (PCA) in the case of diabetes disease classification. A large number of variables and data on the diabetes dataset requires a relatively long computation time, so dimensional reduction is needed to speed up the computational process. The dimension reduction method used in this study is PCA. After dimension reduction is done, it is continued with classification using the K-Nearest Neighbor Algorithm. The results on diabetes case studies show that dimension reduction using PCA produces 3 main components of the 8 variables in the original data, namely PC1, PC2, and PC3. Then classification result using K-Nearest Neighbor shows that by choosing 3 closest neighbor parameters (K), for K = 3, K = 5, and K = 7. The result for K = 3 has an accuracy of 67,53%, for K = 5 had an accuracy is 72,72%, and for K=7 had an accuracy of 77,92%. Thus, it was concluded that the best accuracy performance for the classification of diabetes was achieved at K=7 with an accuracy of 77.92%.
Kajian Fonetik Bunyi Vokal Tunggal Bahasa Mandarin

This study aimed at describing the characteristics and differences in the Mandarin vowel sounds. This study involved a Chinese lecturer and two students of Mandarin Language Education FKIP Untan as research samples. The research data was in forms of Mandarin vocabulary which contains a single vowel. The PRAAT application was used to calculate the time, frequency, and intensity of the research object when uttering single vowel words. This study used experimental phonetics as a research method and presented the data in forms of tables and spectrogram images. The data retrieval method is through the PRAAT program with audio files (MP3). The study results show that pronunciation of a single vowel sound /o/ with the longest duration value from students and native speakers. The highest pitch value for native speakers is 315 Hz in single vowel /i/ and the highest pitch value for students when pronouncing words with single vowel /o/, with a voice frequency of 279.5 Hz. The highest native intensity value is for single vowel /ε/ with a value of 79.92 dB, single vowel /o/ is 79.96 dB for student speakers. The influence of tone errors is one factor that affects the resulting duration, pitch, and intensity values.
Analysis of the Degree of Satisfaction with Life Before and During the COVID-19 Pandemic in University Teachers

This paper focuses on analyzing the degree of satisfaction with the life of university teachers before and during the COVID-19 pandemic in the context of social isolation. The present study adopts a quantitative and cross-sectional approach. The sample included 129 university professors, between 18 and 74 years, from the Faculty of Physical Culture Sciences of the Autonomous University of Chihuahua. Satisfaction with Life Scale (SWLS) was obtained to measure the degree of teacher satisfaction (Atienza et al., 2000; Diener et al., 1985; Pons et al., 2002). The results globally showed significant differences between life satisfaction before and during the pandemic according to the means comparison test, using the T-test for related samples, with values ​​of 4.06 before and 3.6 during the pandemic. When categorizing the results according to the escalation, it was shown that 55.7% of the teachers perceived themselves as satisfied before the pandemic, while the opposite happened during the isolation, decreasing, with only 45.5% feeling satisfied. Only 27% felt very satisfied before, and this percentage decreased to only 14.5% during isolation. The COVID-19 not only wreaked havoc on health, but it also had a negative effects on people's psychological, emotional, and social spheres, thereby modifying healthy lifestyles and leaving possible effects on physical and mental health as a consequence.
Research on “Internet+” Secondary School English Teachers’ Professional Development Strategy Based on SWOT Analysis

In the era of “Internet +”, the rapid development of information technology has also promoted the continuous innovation in the field of education. In recent years, scholars have begun to pay attention to the use of the Internet to promote teacher professional development, which provides a new path for teacher professional development, but at the same time, secondary school English teachers also face new challenges. Therefore, through SWOT analysis, this paper accurately grasps the strengths and weaknesses then provides relevant strategies for the professional development of English teachers based on opportunities and challenges of “Internet+” secondary school English teachers’ professional development.
Development of Augmented Reality Media to Improve Student Understanding of Optical Eyes System Materials

Optical material is material that is quite difficult for students because it has abstract concepts. Media that is considered an alternative solution is augmented reality. AR provides an effective learning experience because it displays 3D images so that it is easily accepted by students and makes students interested in learning. This study aims to develop augmented reality media to increase students' understanding of the eye optical system material. The type of research to be carried out in Research and Development, with the chosen development model being ADDIE. Product evaluation is carried out based on test results and product implementation. The population of this research is students of the Physics Education Study Program, FKIP UT, who are enrolled in the 2021.2-semester lectures and tutors for the Physics Education Study Program, FKIP UT. The research sample was students of the UT FKIP Physics Education Study Program who attended several 18 people (from UPBJJ UT Bogor, Jakarta, and Serang and tuweb tutors for the optics course). The data collection method consisted of administering a questionnaire. To determine the level of understanding of student material on system material eye optics, test results given to students were analyzed descriptively. Questionnaire analysis from tutors and students regarding the need for AR media was analyzed descriptively and quantitatively. The sampling technique used was random sampling, in which the entire population has the same rights and opportunities to be involved in research Based on the results of the needs analysis, it shows that 81% of students agree and need AR media to study the optical system of the eye, 72% of students agree that the material for the optical system of the watch has the potential to cause misconceptions if studied without using media. Based on the results of the needs analysis, consists of 3 main topics, namely regarding the structure of the eye, the process of seeing in the eye, and eye defects. The results of the trial analysis using AR media used a paired sample t-test to see the effectiveness of AR media. The results of the analysis of the paired sample t-test showed a Sig.2 tailed value &gt; 0.05 so it can be concluded that there was a significant difference between before and after using AR media. In other words, it is easier for students to understand the material after being treated in the form of AR media on the concept of eye optics.
Design of an automotive platform for computer vision research

The goal of our work is to design an automotive platform for AD/ADAS data acquisition in view of subsequent application to behaviour analysis of vulnerable road users.We present a novel data capture platform mounted on a Mercedes GLC vehicle.The car is equipped with an array of sensors and recording hardware including multiple RGB cameras, Lidar, GPS and IMU.For future research on human behaviour analysis in traffic scenes, we compile two kinds of data recordings.Firstly, we design a range of artificial test cases which we then record on a safety regulated proving ground with stunt persons to capture rare events in traffic scenes in a predictable and structured way.Secondly, we record data on public streets of Vienna, Austria, showing unconstrained pedestrian behaviour in an urban setting, while also considering European General Data Protection Regulation (GDPR) requirements.We describe the overall framework including the planning phase, data acquisition and ground truth annotation.
Geometrical Tolerances Android Application Developed for Student for a Better Understanding of Orientation Tolerances According to the Latest ISO Standards

In the year 2021, a virtual reality training application has been developed, specifically for the Oculus Quest 2 headset, in order to allow the users to view and analyse 3D models for a wide variety of geometrical tolerances, tolerance zones and even the conformity condition and the datum features. This application allows the students to better understand the geometrical tolerances in accordance with the latest ISO GPS standards by using different 3D interactive models in order to highlight different types of geometrical tolerances and tolerance zones. In order to try to make the virtual reality training application more mobile and accessible for students, a mobile application, designed for the android operating system smartphones, has been developed. This application can facilitate better learning outcomes within the teaching-learning process by enabling the students to visualize a wide variety of 3D models representing different types of geometrical tolerances. Due to the dramatic evolution of technology in the past 20 years and the need to constantly keep up with it, the learning and teaching process suffered a massive change. The Covid pandemic has closed Universities all over the world and so, for the teaching process to continue, a sudden shift from traditional teaching to a more modern one involving the digital world was needed. Thanks for the fact that, nowadays, students are more inclined to use different types of mobile devices, the shift to the new learning paradigm has not left a great “scar” on student and teachers.
Differentially Private Feature Selection Based on Dynamic Relevance for Correlated Data

&lt;p&gt;Traditional feature selection methods are only concerned with high relevance between selected features and classes and low redundancy among features, ignoring their interrelations which partly weak classification performance. This paper developed a dynamic relevance strategy to measure the dependency among them, where the relevance of each candidate feature is updated dynamically when a new feature is selected. Protecting sensitive information has become an important issue when executing feature selection. However, existing differentially private machine learning algorithms have seldom considered the impact of data correlation, which may cause more privacy leakage than expected. Therefore, the paper proposed a differentially private feature selection based on dynamic relevance measure, namely DPFSDR. Firstly, as a correlation analysis technique, the weighted undirected graph model is constructed via the correlated degree, which can reduce the dataset&amp;rsquo;s dimension and correlated sensitivity. Secondly, as a feature selection criterion, F-score with differential privacy is adopted to measure the feature importance of each feature. Finally, to evaluate the effectiveness of feature selection, differentially private SVM combined with dynamic relevance measure is utilized to choose features. Experimental results show that the proposed DPFSDR algorithm can effectively obtain the optimal feature subset, and improve data utility while preserving data privacy.&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;
Face Age Feature Analysis Based on Improved Conditional Adversarial Auto-encoder (I-CAAE)

&lt;p&gt;In recent years, the research of face age features has achieved rapid development driven by deep learning. The faces generated by the Conditional Adversarial Auto-encoder (CAAE) model are not only highly credible, but also closer to the target age. However, there are many problems, such as low resolution of human face image generation and poor local feature retention effect of human face features. To this end, this paper improves on the CAAE network. Firstly, referring to the LSGAN network structure, the 4 convolution layers of the encoder are added to 5 layers and the 4 convolution layers of the generator are added to 7 layers. Secondly, on the basis of the original loss function, the image gradient difference loss function is added to ensure the output face image quality. Meanwhile, the data set were preprocessed for face correction. Finally, this paper performs face similarity analysis on the Eye-key platform and contrasts the generated image quality using structural similarity and peak signal to noise ratio metrics. In addition, the generated results were tested for their robustness. The experimental results show that the average similarity of faces generated by the Improved Conditional Adversarial Auto-encoder (I-CAAE) network was increased by 3.9. And the average peak signal to noise ratio of the generated pictures was reduced by 1.8. Confirming the superiority of the proposed method.&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;