Reviewerly/exHarmony huggingface dataset:
Medical face mask detection using modified MobileNetV2

In this paper, a simple and computationally efficient approach as per the complexity has been presented for Face mask detection using a Deep Learning architecture called MobileNetV2 including some additional specifications for the improvisation of the results. The secondary objective is to keep the pre/post-processing of the images minimal. The presented model is trained on images from the RMFD dataset which includes masked and non-masked people images. The aim is to achieve an accuracy above 95% with a minimum number of parameters after evaluation.
Does AI need symbols?

Abstract Inspired by the brain, artificial neural networks are core to modern artificial intelligence. Grace Lindsay, author of Models of the Mind, explains concerns over the cognitive limits of these systems.
Histopathological Image Analysis and Classification Techniques for Breast Cancer Detection

Breast malignant growth is one of the most incessant reasons for death in women around the world. The early detection of breast cancer growth can improve the endurance rate. Cancer grading of the histopathological image depends upon the histological structures, like tumors, cell membranes, or nuclei, data size, shape, etc., which are very important prerequisites for disease prediction, analysis, and classification. Histopathological images exhibit a lot of variability in the structure, which creates diagnosis uncertainty and error. The automatic breast cancer detection system can help pathologists in the diagnosis of this problem more efficiently. Image processing algorithms for the automated examination of histopathological images have become progressively famous in the most recent decade with the exceptional development in computational power. The development of high-throughput measuring devices takes into account the computer-aided assessment of microscopic images, bringing about a snappy and unbiased image elucidation that encourages the clinical decision-making process. This chapter will explore different techniques for image acquisition, followed by image pre-processing, image segmentation to find the region of interest (ROI), feature extraction of the segmented image, and classification techniques. The chapter is divided into two sections. The first section is analysis, particularly segmentation, in which test images are partitioned for identification of ROI for feature extraction. This part will investigate various feature extraction methods to classify cells or regions into normal and abnormal categories. The next section covers the image classification process with histopathological image analysis. This research will provide a more versatile classification system with discriminating class-specific dictionaries, which automatically identifies the feature based on which the symptom can be easily classified. The machine learning algorithms are used to decide the presence of abnormalities at the pixel location. Support vector machine (SVM) classifier, minimum distance classifier, and convolutional neural network classifier are also employed for classification. The proposed computer-aided diagnostic system reduces subjectivity and makes an accurate, quick, and more precise diagnostic decision. It will help practitioners in increasing the diagnosis accuracy, sensitivity, and specificity of the pathological test.
A novel approach for product cipher encryption algorithm using circular queues

This paper aims to introduce a circular queue-based product cipher encryption algorithm in which the message or the plaintext is inserted into a series of circular queues where the letters in the circular queues are first replaced by some other letters including alphabets, numbers, or special characters and then the letters shift in a particular direction within the queue. Each circular queue may or may not have a distinct shifting offset and direction. In this way, the plaintext is altered into an unintelligent text. The concept of the shifting of letters in a circular queue is driven from the real-life safe lock systems where multiple rotator locks are rotated in such a way that only a particular position of every rotator lock unlocks the safe. As the size of plaintext increases, the number of queues and the size of queues will increase which will consequently increase the randomization of letters.
Novel Review in Sentiment Analysis and Its Approaches

Sentiment Analysis is becoming an important concept these days. Not only the customers but also the companies also analysis the reviews other customers in order to either buy or to improve the quality of the products. This paper is an attempt to review the concepts of the sentiment analysis, its methods etc.
Sensemaking in Cybersecurity Incident Response: The interplay of Organizations, Technology, and Individuals

Sensemaking is a critical activity in organizations. It is a process through which individuals ascribe meanings to events which forms the basis to facilitate collective action. However, the role of organizations, technology and individuals and their interaction in the process of sensemaking has not been sufficiently explored. This novel study seeks to address this gap by proposing a framework that explains how the interplay among organizations, technology and individuals enables sensemaking in the process of cybersecurity incident response. We propose that Organizations, Technology, and Individuals are the key components that interact in various ways to facilitate enactment, selection and retention activities (Sensemaking activities) in Incident Response. We argue that sensemaking in Incident Response is the outcome of this interaction. This interaction allows organizations to respond to cybersecurity incidents in a comprehensive manner.
Fault-Tolerant Syndrome Extraction and Cat State Preparation with Fewer Qubits

We reduce the extra qubits needed for two fault-tolerant quantum computing protocols: error correction, specifically syndrome bit measurement, and cat state preparation. For fault-tolerant syndrome extraction, we show an exponential reduction in qubit overhead over the previous best protocol. For a weight-w stabilizer, we demonstrate that stabilizer measurement tolerating one fault (distance-three) needs at most ⌈ log₂ w ⌉ + 1 ancillas. If qubits reset quickly, four ancillas suffice. We also study the preparation of cat states, simple yet versatile entangled states. We prove that the overhead needed for distance-three fault tolerance is only logarithmic in the cat state size. These results could be useful both for near-term experiments with a few qubits, and for the general study of the asymptotic resource requirements of syndrome measurement and state preparation.For 'a' measured flag bits, there are 2^a possible flag patterns that can identify faults. Hence our results come from solving a combinatorial problem: the construction of maximal-length paths in the a-dimensional hypercube, corresponding to maximal-weight stabilizers or maximal-weight cat states.
An Approach for Secure Data Exchange in Medical Field Using Block Chain

Block chain technology in the medical management sector is the focus of this project. This project will showcase a block chain application for secure conversation and secure data in real time to various nodes/ computers/ people and everything will be recorded, secured and hosted on an immutable block chain data structure. Our block chain also implements a light-weight chain validation algorithm and POW which validates the added block itself, to prevent someone from creating a fake block. The block chain network can embody numerous functionalities as well as plus transfer between simulated nodes running in parallel, along side a Block human which is able to act as a face to trace numerous group action, addresses and therefore the block chain itself. It will additionally create use of varied science algorithms like SHA256, Mining Hybrid chain validation (consensus-longest chain) to supply secure transacting surroundings. In addition to the current it'll additionally embody Associate in Nursing API (built from scratch) exploitation NODE.js Express.js to make a server within which the block chains are going to be hosted.
THE HUMANITIES FACING THE CHALLENGE OF THE COVID-19

The Covid-19 pandemic has shocked the ways of organizing the nations and has put enormous pressure on the knowledge systems. In these circumstances, the humanities offer a perspective that allows us to understand this event in its real complexity and, likewise, alert us to the potential risks faced by societies built around democratic and humanistic values. (English) [ABSTRACT FROM AUTHOR] La pandemia de covid-19 ha conmocionado las formas de organizar a las naciones y ha ejercido una enorme presion sobre los sistemas del conocimiento. En estas circunstancias, las humanidades ofrecen una perspectiva que permite comprender este fenomeno en su real complejidad y, asimismo, nos alertan sobre los riesgos que corren las sociedades constituidas segun valores democraticos y humanistas. (Spanish) [ABSTRACT FROM AUTHOR] Copyright of Estudios: Filosofia, Historia, Letras is the property of Instituto Tecnologico Autonomo de Mexico and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
DETERMINATION FOR CONSUMER PATTERNS IN BEVERAGE PRODUCT SALES USING THE FREQUENT PATTERN GROWTH ALGORITHM

The culinary business is now increasingly developing and competition is increasing, so it requires a strategy to market the products to be sold. In the business sector, the results of the implementation of FP-Growth algorithm data mining can help business people find opportunities from consumption trends so that culinary business people can find out what types of products currently have the highest rating in the community so that managers can provide menu recommendations so they can increase sales turnover. The data required is a certain period of transaction data which is analyzed to produce product recommendations by the association rules. The design of this application uses HTML as the base system used in making websites, PHP as a means to develop websites, and SQL as a medium for data storage and processing. The testing process begins with the login process, then determines the support and confidence parameters, and determines the transaction time period. From the conclusion, managers can determine marketing strategies by increasing the stock of raw materials in beverage products that have the highest itemset value. Then the product with the lowest itemset value can provide promos or discounts on the purchase of goods to attract consumer buying interest.
PID Sensor Controlled Automatic Wheelchair for Physically Disabled People

Automation in medical mechatronics for physically disabled people has been researched in many institutes and various medical fields, and many scientists and researchers have developed a various prototype which is controlled by a gesture, RC, accelerometer, automatic control with the joystick in the functioning of a wheelchair for physically disabled people, but the control of the equipment using only PID (Passive Infrared Detector) sensor has yet to be developed. In this paper, we have mainly focused on the cost effective factor of developing a cheap automatic wheelchair for low-income families. This wheelchair works on the simple principle of a PID SENSOR as the Title suggests that the wheelchair is controlled using a PID SENSOR using hand obstruction so that the reflected infrared light falling on the PID sensor will give the received information to the Arduino board to give a signal to the motor to move the wheelchair as per the person’s desire to the desired direction. We have mounted PID sensors for left, right, and reverse direction also. So, when the Infrared sensor module receives a reflected infrared ray to the IR RECIEVER then the reflected ray is initiated to give the signal from the obstruction of the OBJECT(in our case – HAND/FINGER) and thus the wheelchair starts to move. And for stopping the wheelchair simply take the obstruction made by the OBJECT (HAND) above the PID sensor then no infrared ray will be received by the IR RECIEVER then it will stop giving a signal to the motors to move any further and thus bring the wheelchair to a stationary position. So, this wheelchair design allows self-control using Infrared Sensors and a microcontroller (Arduino Uno) based circuitry. This design is to bring support for the physically disabled people with very low income who cannot afford to buy a fully functional automatic wheelchair at a high cost. The entire setup is done through a normal wheelchair with DC motors and a control unit consisting of IR sensors, Arduino Uno, beeper, motor driver modules, a switch, and a battery.
One-Click Marketing Solution for Mobile Videos

In this paper, we propose a simple one-click marketing solution for mobile devices which can advertise a product which is embedded in a mobile video while watching the video on a smartphone. If a specific product of interest appears in the video to the user, one can simply click on the product in the video and a pop-up window with information about the product is proposed. The implementation of the system is expected to enable users to gain real-time information about the product while watching the video without having to search for the product again after watching the movie, and thereby facilitating more mobile commerce. We use a two-fold system to prevent the failure of tracking which often occurs on a single online tracking system, so that the user cannot always get the commercial product information.
WP1 report: an international review of Social Media Archiving initiatives

This report details the tasks completed during Work Package 1 of the BESOCIAL project; a BELSPOfunded, KBR coordinated, BRAIN research project with the following partners: CENTAL fromUCLouvain; CRIDS from UNamur, and the research entities of MICT, GhentCDH, and IDLab fromGhent University.The aim of this work package was to review existing social media archiving projects and corpora inBelgium and abroad. The following report outlines the existing social media archiving atan international level.
DETECTION OF FAKE PROFILES USING MACHINE LEARNING

Fake profiles in modern era are cause of concern in almost every field of life. Credit card, money laundering and bank fake profiles are common and technology has to play important part in overcoming this issue. This paper provides insight into financial fake profiles leading from malicious users in trading network. To this end several techniques are researched over. To start with price based fake profile detection is discussed and then similarity matrix, linear binary patterns, support vector machine and random forest in the field of fake profile detection are elaborated. This paper highlights pros and cons of each of such techniques. Dataset required determining classification accuracy of these approaches is synthetically driven. Execution time while determining fake profiles is critical entity and similarity matrix approach is fast and accurate as compared to random forest, support vector and linear binary patterns.
Implicit Learning and Deliberate Problem Solving: What is the Connection?

Many theoretical proposals conceptualize the acquisition of deep knowledge as a deliberate, effortful and constructive process. In contrast, research on implicit learning of artificial grammars suggests that learning is a passive, inductive process which is independent of any intention to learn and which creates knowledge not accessible to the learner. Participants are then given a new list of letter strings and are asked to identify those that are similar to the strings previously memorized. Participants perform better than chance in the test phase, implying that an abstract representation is extracted from the training phase and used in the recognition task of the test phase. If what is learned in implicit pattern learning is available for deliberate problem solving, prior implicit learning of the relevant pattern should facilitate performance on sequence extrapolation. The six number strings followed the exact same pattern as the associated letter sequence extrapolation problem.
Formation of spirituality, morality and patriotic feelings in children of primary school age

The article deals with the specific aspects of the formation of spirituality, morality and patriotic feelings in children of primary school age. Spirituality, morality, and patriotic feelings are unchangeable universal values that may sound different, but their semantic content is identical among different peoples. The formation of these values is possible already in primary school age. It is spiritual and moral education that sets the attitudes that affect the essence of human relationships. The personality becomes spiritually richer through the introduction of children of the first stage of education to spiritual and moral values, through the formation of an attitude to themselves and to other people, to the surrounding world as a value, the development of the consciousness of the younger student and his spiritual qualities. The formation of moral qualities in students of primary school age will be more productive when creating a number of pedagogical conditions, since they are the most manageable, aimed at forming a certain kind of relationship. The analysis of theoretical sources gives us a reason to conclude that the problem of the spirituality of the individual occupies one of the central places in the system of knowledge about a person, and has repeatedly become the object of research by philosophers, psychologists and teachers. In order to identify the pedagogical conditions for the formation of spirituality, morality and patriotic feelings in younger schoolchildren by determining the level of formation of these qualities in students, a study was conducted in MBOU Secondary School No. 20 in Mineralnye Vody, Stavropol Territory. The authors identified the criteria of educational work on the formation of patriotic feelings and determine the stages of patriotic education in children of primary school age.
Personal Well-Being Of University Teacher In Professional Activity: Experience Of Empirical Research

The article presents the development of diagnostic tools, which provides an opportunity to assess the state of subjective well-being / ill-being of university teachers in their professional activities.These diagnostic tools were formed on the basis of a model that uses two criteria: 1) significance; 2) time cost.Eight aspects of the professional activity of a University teacher, previously identified by experts, are considered.Pairwise comparison of the respondents of these aspects occurs twice: first, according to the criterion of personal significance, then -according to the criterion of time cost.An indicator of a lecturer's well-being or ill-being is the difference between the frequencies of each component's selection based on these criteria.The assessment uses four States that respondents can be in: the "normal" state, if the difference in the assessment of a component of activity according to two criteria is ≤1, the "at risk" state, if this difference is >1 and ≤3, the "stress zone" state, if the difference is > 3 and ≤ 5, and, finally, the "value-semantic conflict" state, if the difference is > 5. Approbation of the developed methodology showed that for a sample of 117 respondents -teachers of Russian universities, the most conflicting component of activity is "working with documents".Subjective well-being of more than 80% of teachers who participated in the testing is assessed as a state of "tension" (over 37%) and "value-semantic conflict" (over 43%).There were no teachers whose condition could be described as normal.
The Early Days of Synthetic Data

It may appear that synthetic data has become instrumental only very recently, with the rise of modern computer graphics that allows for near-photorealistic imagery. But in fact, synthetic data has been used throughout the history of computer vision, starting from its very inception in the 1960s. In this chapter, we begin with the early days of synthetic data, show some of the earliest models and applications of computer vision, and discuss aspects of computer vision that have always been very hard or even impossible to do without synthetic data.
DEFINING THE INDICATOR OF INNOVATIVE DIDACTIC POTENTIAL ON THE THIRD (EDUCATIONAL AND SCIENTIFIC) LEVEL OF SPECIALTY «011 EDUCATIONAL, PEDAGOGICAL SCIENCES»

The purpose of the study was to reveal the essence of the concept of «innovative didactic potential», its formulation and defining the component composition; substantiation of the diagnostic program for determining the quantitative value of the index of innovative diagnostic potential and selection of conditions for its formation. We understand under the innovative didactic potential an integrated indicator of innovative abilities of an individual, which is revealed in the educational environment in the process of didactic interaction and is displayed in the system of attitudes to the innovative field of activity. To achieve the goal, the following research methods were applied: analysis, synthesis, generalization, systematization − to determine the conceptual apparatus of research, namely, innovative didactic potential, potential index. Methods of comparative analysis, deduction, induction, modeling were applied in the development of a diagnostic program for defining the index of innovative didactic potential. In modern conditions, higher education focuses on the requirements for research and teaching staff in the parameters of innovative educational activities. This implies the ability of research and teaching staff to master and implement innovative methods of teaching and learning. With this aim the curriculum for the training of the third educational and scientific level students provides the course «Innovation in pedagogy, organization and provision of modern classes». Generalization of the results of theoretical developments and empirical findings in the study of the problem of determining and evaluating the index of innovative didactic potential allowed to identify the conditions necessary for its formation: didactic, psychological, organizational, information technology.
Hand written Alphanumeric Recognition

One way that developers are enabling machines to become more intelligent is by diving into machine learning and deep learning techniques. The process of learning how to perform a task is best described as repeating it again and again in order to make it solid in your memory. It is the ability to read the handwritten alphanumeric characters either digit or alphabet, without human assistance. Handwritten characters can be made in many different ways, and that makes it difficult for the machine to decipher them. This application, which utilises both written and image data, helps solve this problem because it allows us to use handwritten alphanumeric characters and alphabet characters both together and for recognising data in images. We follow specific steps in order to build this handwritten alphanumeric recognition. By using deep learning algorithms such as CNN, RNN, we plan to implement face recognition to identify data written.