Reviewerly/exHarmony huggingface dataset:
Virtual Drawing Board (Drawing and Writing Using Hand Gestures)

Abstract: A virtual Drawing Board which is a computer- based vision system which is used to draw on screen by detecting the motion of index finger with the camera. The idea of making a software using AI in python, useful in online teaching, presenting presentations and in various other industries. In present condition online teaching has become an alternate mode of teaching via online meets, without using any external devices for drawing or writing on screen one can use Virtual Drawing Board just by opening their camera and using index finger with its motion they can draw or write.
E-Commerce Fraud Detection Using Support Vector Machine and Naïve Bayes Algorithm

The prevalence of online fraud cases, including e-commerce fraud, is rising as a result of technological advancements and the speed with which cybercriminals can change their methods of operation.Scams are nothing new, but as the frequency of transactions without currency rises, so does the trend of online fraud.People are purchasing more goods online as a result of the COVID-19 quarantine because they want to be safe or because the items, they require are hard to get in the shuttered local stores.The best course of action in this circumstance is to implement a fraud prevention service that automatically identifies fraudulent behaviour patterns, associated with the time, place, and device name associated with the login or transaction.This will prevent fraudsters from using the data they stole.You can halt fraudsters before they start a transaction by spotting suspicious activity on an account.Through relevant historical data from databases and machine learning techniques, this study aims to identify fraud patterns in e-commerce transactions.Based on email, payment methods, payment method providers, and transaction volume, this research will train a computer or system that can predict fraud patterns.Machine learning must be used to improve fraud protection in e-commerce since it allows machines to be analysed using learning algorithms.Support vector machine and naive Bayes will be the algorithms employ.
New Informed Non-Blind Medical Image Watermarking Based on Local Binary Pattern

Medical image watermarking represents a promising alternative tool regarding many security aspects such: digital rights, authenticity and integrity and content protection issues. Achieving a successful watermarking should be achieved by choosing the most significant and important patterns describing the image. This strategy should also ensure a tradeoff between the robustness of the watermark against attacks and the computational time both for watermark embedding and extracting processes. In this paper, an informed medical image watermarking scheme is proposed based on local binary pattern LBP. Local Binary Pattern (LBP) is an effective texture descriptor for images by providing the texture regions of interests concerned by watermarking. A watermark is built based on the significant information extracted from the host image by through the LBP descriptor. LBP image will be addressed to be embedded using a linear interpolation. Scenarios of geometric and non-geometric attacks have been realized on the watermarked images to evaluate the robustness of the embedded watermark in the extraction process. Furthermore, the obtained experiment results show the effectiveness of the proposed approach regarding the watermark imperceptibility and robustness.
Driver Identification System Using Finger Vein and YOLO Object Detection

Biometrics used to identify people is one of the safest and most convenient identification methods. The hypoxic hemoglobin method can present a human finger vein image for driver identification through infrared ray irradiation. The finger vein image is captured system; with the finger vein image processed using contrast-limited adaptive histogram equalization (CLAHE) and the Gabor filter to obtain a clearer image. The YOLO object detection technology is used to drive identification. The proposed system can be divided into two parts. The first part is the training part, which processes images. A database generates the weight files for external testing. The second part is the testing system. When the driver's finger is placed in the designated photo area a photo will be taken. The photo will be processed and run on Raspberry Pi 4 together with the weight file to identify the driver. The experimental results show that when the database has a large amount of data, the yolov4-tiny-hy recognition rate is comparable to that of YOLOv4. The training time is greatly shortened.
A Traffic Parameter Detection Algorithm Based on Double Coils

This paper designs a detection method for real-time acquisition of traffic intersection parameters based on image processing. Firstly, two virtual coils were drawn at the beginning and the end on the acquired video stream image. Next, the presence of the vehicle was judged based on the change of the gray value in the two virtual coils. The background difference algorithm was adopted to detect and obtain various traffic parameters. The experimental video samples were collected in the actual road environment. Our algorithm relies on the first and last two coils for information processing, and completes vehicle detection, speed detection, and important parameter information acquisition of body color. Experiments show that, compared with the traditional machine vision-based traffic information detection algorithm, our traffic parameter detection method, which is based on double virtual coils, has high detection accuracy, and can detect more parameter information, while satisfying real-time performance.
Non-Fungible Token (NFT) Prices, Cryptocurrencies, Interest Rate and Gold: An Econometric Analysis (Jan. 2019-Aug. 2022)

In May 2014, the animation &amp;ldquo;Quantum&amp;rdquo; was the first work to be associated with a non-fungible token (NFT) type certificate. As of 2020, the market has evolved considerably, with the millionaire figures and exponential growth typical of new disruptive technologies. Considering the recent rise of the NFT market, it is important to understand how it works and, above all, the determinants of the prices of NFTs are highlighted. Based on a detailed analysis of this new market, a GARCH multivariate econometric model is applied in order to assess whether it is possible to identify the price determinants of NFTs, based on the behavior of the prices of cryptocurrencies (Bitcoin and Ethereum), the US interest rate and the price of gold. The research is based on the study by Dowling (2022a), which sought to analyze relations between the prices of NFTs and cryptocurrencies. The results found coincide with the prices of NFTs that are similar and independent of cryptocurrencies, the interest rate and the price of gold, some specific differences to identify a determined period.
NETWORKING AND SECURITY

With the secure network and growing of cyber attacks computer networks are now have a need of all organizations.The security threats are increasing day by day.These cyber attacks increasing beyond the imagination.Cyber security experts and researchers working for long period of time for unauthorized access networks to maintain privacy and security to prevent cyber attacks.Today numerous companies and governments are taking many measures but cyber security is still a big concern.
Yolov4 in White Blood Cell Classification

White blood cell (WBC) counting is vital for the diagnostic of many diseases. However, the manual counting method operated in hospitals and centers is time-consuming and inefficient. Many automatic processes in classifying WBC types were proposed using deep learning (DL) models. YOLOv4 is an emerging model for detecting objects with promising results in many applications including the medical field. In this paper, YOLOv4’s performance would be tested on classifying four types of WBC: monocyte, lymphocyte, neutrophil, and eosinophil. A mixed database of WBC microscopic images from an online dataset BCCD and a hospital dataset collected from the Vietnamese National Institute of Hematology and Blood Transfusion, comprising of 10,275 images in total after the augmentation, was used for training and testing the model. The results showed that the trained YOLOv4 was able to classify equivalently well all 4 WBC types with the average accuracy of 97.8%, ranking the second-best option when compared to other contemporary studies.
Camera Calibration Using Robust Intrinsic and Extrinsic Parameters

Camera-related factors like the position, orientation, focal length, and others affect the image. These factors can be divided into two types: internal and external (intrinsic and extrinsic). Internal or intrinsic parameters include focal length and distortion by lens whereas external or extrinsic parameters include rotation and translation vectors. Now the procedure for determining these camera parameters is called calibrating the camera. Camera calibration is essential for applications like removing distortion from an image, for photogrammetric or finding the location of the camera in a scene. This chapter intends to explain the process and mathematics behind calibration of a digital camera using OpenCV in Python.
Convergence of Blockchain Technology and Artificial Intelligence

It is beyond doubt that both blockchain technology and artificial intelligence (AI) are two emerging technologies in the field of science. Both of them have been highly unexplored in terms of their respective fields. Blockchain technology is defined as a decentralized, distributed ledger that records the provenance of a digital asset whereas AI assists computers and machines to mimic the problem-solving and decision-making capabilities of the human mind. In this chapter, we discuss the role of blockchain technology in the domains of data monetization, resource optimization, improving AI user experience, and data protection. The quality of intelligent service has been optimized through the integration of blockchain technology and AI. The aim of this chapter is to showcase how AI and blockchain can be clubbed together for opening new avenues in different domains. Block chain enables secure storage whereas AI offers new methods to analyze and generate new solutions. These two technologies have been in boom recently because all the datasets are necessary to be updated with the latest data to ensure its safe and effective usage. Together with the use of blockchain, we can create a model that can ensure optimum usage in different aspects related to the computing world.
Social media as the fifth estate

Social media are also called the fifth estate that form a new control body and may thus fulfil democratic functions. On the other hand, social media have enabled the proliferation of hateful debates in which, with reference to freedom of speech, previously tabooed contents and language are becoming de-tabooed and accepted. As an answer to fake news, direct and indirect hate speech also forms of organised counterspeech have been developing in social media to counter the normalisation of aggressive and hateful speech. To influence the discourse in comment columns of social media in terms of the fifth estate, counterspeech has to be visible also quantitatively. In this contrastive study, I analyse the activities of the German and Finnish Facebook groups of the network #iamhere international. Special focus is on how the groups organise their activities strategically and in how far the conventionalisation of digital genres influences the intensity and continuity of their activities.
Pengembangan Weather Station Online Berbasis Android dengan Menggunakan Database Firebase

The weather station app provides weather information to users in realtime from the database. After the development of the application, further testing is carried out to assess the quality of the application based on ISO 25010. Based on the results of the study, an application was generated that can be used in monitoring cauca changes in real time. Based on the test results using the ISO 25010 standard, the weather station application has met the standards where: a). Testing aspects of fungtional suitability using the black box testing method, which is carried out by two system experts where the test results are worth 1 with a very decent category, b). compatibility aspect testing using co-existence and no errors were found during testing, c). Testing aspects of performance efficiency is carried out using an application called AppTim and the test results are in the good category, d). Portability aspect testing is carried out by testingtheapplication, on devices with different androids, and from the test results no errors and errors were found in the application, so the application was declared suitable for use based on the results of ISO25010 testing.
RANCANG BANGUN GAME EDUKASI PENGENALAN HEWAN ENDEMIK INDONESIA MENGGUNAKAN CONSTRUCT 2 BERBASIS ANDROID

Indonesia has a very wide archipelago from the mainland to the mountains. The territory in the Indonesian archipelago contains various kinds of flora and fauna as well as microbes. Games are games. The game in this case refers to the notion of intellectual agility (Intellectual Playability Game) which can also be interpreted as an arena for decisions and actions of players, usually in a non-serious context or with the aim of refreshing. Educational Game is one type of media that is used to provide teaching, increase the knowledge of its users through a unique and interesting media. Puzzle games generally involve shapes, symbols or colors, and the player must arrange them into the correct pattern.&#x0D; Keyword : Flora, Fauna, Game, Puzzle game
APLIKASI LAPORAN KEUANGAN TOKO BERKAH AQUATIC BERBASIS WEB

The development and use of information technology has grown rapidly at this time. Especially in store performance efficiency where most of the processes are computerized and certain documents are documented and stored in digital form. One of them is the process for recapitulating the store's financial statements. The results of the business process will become one of the foundations for high-level departments to make decisions. The business process for recapitulating store financial reports that is done manually can certainly cause several problems, including the potential for data loss, or human errors during calculations and daily input documentation and so on. To overcome these problems, of course, a financial application model that focuses on the processing of financial statements can be used. Based on this, this research will build a web-based financial report application that can include financial reports, processing income and expenditure data. This system is made using CodeIgniter while for system development using the waterfall method. Furthermore, the website model will be built with a front-end and back-end equipped with a data base.
PERANCANGAN SISTEM INFORMASI PENJUALAN PADA ZENIS PETSHOP BERBASIS WEB

Zenis Petshop is a business in the field of providing needs and services for pets. In its business, Zenis Petshop sells various pet needs ranging from cat food, dogs, hamsters, cages, etc. In addition to selling a variety of food and accessories, Zenis Petshop also offers grooming services or an animal salon specifically for cats, such as grooming, bathing, and cutting nails. The problems faced by Zenis Petshop include problems in processing goods data that are still not computerized, there is no evidence of transactions such as proof of sales. Another problem that exists at Zenis Petshop is that they often have difficulty checking stock of goods, there is no sales report and they only use a recap of notes for reports. To be able to overcome these problems, we need an information system that can help processing data items, sales and profit reports by combining components that have not been computerized into one system. with the creation of a web-based sales information system using the waterfall method so that later it can be used in its business processes to be more effective and fast.
GAME EDUKATIF PENGENALAN BENDERA DAN IBUKOTA NEGARA DIASIA DAN EROPA MENGGUNAKAN CONSTRUCT2

Games (Games) on mobile phones have now become an inseparable part, especially on the Android operating system. Most people, including students, spend a lot of time with cellphones for about 5-6 hours in front of cellphones just for applications and opening website addresses. The current digital era learning model has differences compared to conventional learning models. The PJJ model according to Azis (2019: 309) states that the digital era learning model consists of 3 models, first, the teacher provides online learning materials to students and then downloads and learns them manually (offline), both teachers provide online learning materials and participants students learn online too, and collaboration between learning that takes place between online and offline. The learning that has been carried out will end with an evaluation of both daily assessments, mid-semester assessments, and end-of-semester assessments. Based on the background above, the researchers intend to design applications that can be run via mobile phones with the Android operating system.
THE ORGANIZATION OF THE EDUCATIONAL PROCESS IN INSTITUTIONS OF GENERAL SECONDARY EDUCATION IN THE CONDITIONS OF MARTIAL LAW BASED ON THE EXAMPLE OF PRACTICE OF LVIV REGION TEACHERS

The organization of the educational process in institutions of general secondary education in the conditions of martial law based on the example of practice of Lviv region teachersSummary.The article examines the peculiarities of the organization of distance education and the role of the Ukrainian teacher in the conditions of martial law from February 24, 2022.Important questions regarding the creation of a single effective eenvironment for high-quality distance education in Lviv Oblast and Ukraine, in particular, were described.Attention was focused on the creation of the first volunteer project of the Ukrainian Distance School (UDS) in Ukraine for pupils of grades 5-11 who found themselves in the war zone, moved to another region of Ukraine or abroad and cannot continue their studies at their native school.The expediency of using the LMS Moodle educational platform for pupils and teachers of general secondary education has been analyzed and substantiated.Features of lesson organization using various Moodle resources and activities were demonstrated.
The Analysis Of Parental Participation In Improving Children's Learning Motivation During The Covid-19 Pandemic

&lt;span&gt;Covid-19 has hit many countries in the world, including Indonesia. This epidemic has affected many sectors of life, including the education sector. The government's rules regarding the Implementation of Learning from Home is one of their effort to reduce the spread of Covid-19. In this regard, teachers and parents have involvement in increasing the children's learning motivation. This research raised parental participation in providing learning motivation to students during Distance Learning. The method used in this research is the literature review and survey method. The researcher used several reference books and questionnaires with the type of scale being differential semantic that had the highest score is five and the lowest score is one. The result of this research is the participation of parents in providing learning motivation to students during distance learning consists of three aspects: facilities, time, and child psychology. The percentage of the role of parents in motivating children in the aspect of facilities is 94.78%; in time aspect is 97.68%, and in the psychology of children aspect is 94.78%. So, most parents in grades V and VI have tried to increase learning motivation in distance learning during a pandemic. &lt;/span&gt;
Naïve Bayes dan Support Vector Machine Berbasis PSO untuk Seleksi Fitur pada Sentiment Analysis

Sentiment analysis is a process that aims to determine the content of the dataset in the form of positive, negative and neutral text. Currently the opinion of the general public is an important source of decision making. Social media is a place to express public opinion on an object, problem or event. Such as the government's policy regarding the relocation of the capital city of Indonesia, which was originally in Jakarta to Kalimantan, did not escape the attention of the public, especially Twitter users. One of the problems in sentiment analysis is the high number of attributes and dimensions in the dataset. In this study, sentiment analysis was carried out on the relocation of the national capital using the Naïve Bayes method, and the Support Vector Machine based on Particle Swarm Optimization (PSO). The advantages of the Support Vector Machine are High dimensional space and Vector document space. Feature selection greatly affects the performance of the classification, the use of PSO as feature selection to improve accuracy. The results of this study obtained the best accuracy value of 96.45% and the AUC value of 0.920 from the application of PSO on the Support Vector Machine. This result has increased when compared to the experimental results using Naïve Bayes and Support Vector Machine without PSO. The application of PSO on the Support Vector Machine is proven to get better accuracy results in predicting sentiment analysis on the dataset of moving the State Capital.
PROBLEMS OF FORMING INFORMATION COMPETENCE IN LIBRARIES OF HIGHER EDUCATIONAL INSTITUTIONS: ON THE RESEARCH MATERIALS

The article is devoted to the results and conclusions of the first stage of the All-Russian study "Formation of information competence of students in the digital environment" (June-July 2021). The task of this stage is to study the state of affairs in the formation of information competencies of students in several areas: content, forms, features, problems. At the stage of questionnaire analysis, five technologies and trends were formed that can influence the formation of information competencies. Based on the results of the study, a modular exemplary program was formed, which elements can be used in the preparation of curricula and programs in libraries.
Using deep learning and reinforcement learning combination in automatic vehicle application of allee effect

Convolutional Neural Network (CNN) can detect images from cameras installed on self-driving cars.First, we drove a car on a simulator and recorded frames from three cameras: left, right, and center.These frames were recorded at the rate of 30 frames per second.Additional data recorded were the distribution of steering angles, average velocity, etc. were passed through a CNN to train a self-driving system.CNN is like the eyes and visual area in the brain, so CNN's achievements in autonomous vehicle control are somewhat limited.Therefore, this paper proposes the use of algorithms based on Deep Learning (DL) combined with reinforcement learning (RL) in the control of autonomous vehicles.We call this algorithm Deep Reinforcement Learning (DRL) which can send control commands to the vehicle to navigate properly and efficiently along a defined route.CNN tracks multiple objects while RL predicts the environment or assesses the current condition of the vehicle to make the safest decision.DRL-based algorithms have been used to solve Markov Decision Processes (MDPs), where the scope of the algorithm is to compute the optimal policy of an autonomous vehicle for choosing actions in a environment with the goal of maximizing a reward function.