Reviewerly/exHarmony huggingface dataset:
Joint Blind Reconstruction of the Cyclic Codes and Self-Synchronous Scramblers in a Noisy Environment

Reverse analysis of the intercepted signal to reconstruct the communication scheme used by the transmitter is a key problem in the non-cooperative context. In this paper, we propose a new algorithm for the joint blind reconstruction of the cyclic codes and self-synchronous scramblers directly using soft-decision sequences. First, we derive the conclusion that if the parity polynomial of the factor of the generator polynomial of the cyclic code and the feedback polynomial of the self-synchronous scrambler are multiplied, then the vector corresponding to the inverse polynomial of this product forms a parity-check relation with the row vector of the self-synchronously scrambled cyclic code bit matrix, which is constructed by the sequence of self-synchronously scrambled cyclic codes. To detect this parity-check relation, the concept of average parity-check probability (APCP) is defined, which uses the intercepted soft-decision sequence to measure the reliability of the parity-check relation. An optimal threshold based on the minimum error criterion is then derived. When the APCP is greater than this optimal threshold, the parity-check relation is considered to be detected, i.e., the corresponding irreducible polynomial is a factor of the generator polynomial of the cyclic code and the corresponding candidate feedback polynomial is the feedback polynomial of the self-synchronous scrambler. Therefore, the blind reconstruction problem in this paper is exactly equivalent to the hypothesis-testing problem. Simulation results show that the algorithm is more fault-tolerant than existing algorithms in noisy environments.
Professional Qualities of a Foreign Language Teacher from the Point of Participants in the Educational Process (Профессиональные качества преподавателя иностранного языка – мнение участников образовательного процесса)

The success of the learning process in any type of educational institution is directly related to the involvement of all its participants. The main participants are students, teachers, administration and employers. As part of a scientific study, the task was to find out the opinion of students, teachers and heads of departments about what professional qualities a university foreign language teacher should have.The following methods were used during the study: semantic analysis, semantic field method, questioning, quantitative analysis. To clarify the plan of the content of the term "foreign language teacher", four groups of respondents were interviewed - heads of departments, undergraduate students, teachers of foreign languages, foreign students. A total of 807 respondents took part in the survey. Within the framework of this article, free-form answers were analyzed. Respondents were asked to continue the phrase "A modern teacher of a foreign language is ....". This question was answered by 726 respondents. All survey participants mentioned the terms "specialist" and "professional" in their wording. They also noted the importance of the teacher's personal qualities. The most frequently mentioned were initiative, interest, sociability, responsibility, decency, creative approach to the profession. The role of scientific work for all groups of respondents turned out to be less significant.
Approach to Improving Java Source Code Considering Non-compliance with a Java Style Guide

This work shows the betterment of a typical Java source code application by taking into account its non-compliance with a subset of items of the Google Java Style Guide. To get this, an improving strategy is used. The improving strategy has a set of activities that allow defining non-functional requirements in the form of characteristics, attributes, items, and their relationships, as well as designing and implementing measurements, evaluations, analysis, and code changes. The practical case was carried out in the context of an advanced undergraduate subject in System Engineering as a compulsory integrated exam. The results of evaluating attributes/items for compliance with the above coding style guide and improving non-compliances are illustrated in detail. We argue that this study may be of interest to professors and students of other similar degrees.
Gaining Insights into a Robot Localization Monitor Using Explainable Artificial Intelligence

Monitoring the state of a localization component in robotic systems has received increasing attention in recent years, as navigation behaviors of robots rely on a reliable pose estimation to a large extend. Nowadays, research focuses on the development of new approaches to monitor the localization state of a robot. Many of those approaches use Machine Learning techniques which do not provide direct insight into the decision making process and are thus often handled as a black box. In this work, we aim to open this black box by making use of an Explainable Artificial Intelligence (XAI) framework that allows us to improve the understanding of a machine learning based localization monitor. To gain insights into the machine learning model, we make use of the open-source framework SHapley Additive exPlanations (SHAP). Results show that investigations in the model structure of a localization monitor using XAI helps to improve the model’s transparency. Overall, XAI proves to be useful in understanding the decision-making process of a localization monitor and can even help to improve the model’s design quality.
Just Look: Knowing Peers with Image Representation

We present a novel approach to assess firm similarity by analyzing two million images. We leverage machine learning techniques to identify graphical objects that best represent companies’ operations, forming Image Industry Classifications (IIC). IIC mirrors investor-defined peer groups and, akin to the brain’s visual processing superiority, outperforms SIC, GICS, NAICS, and text-based similarity in delivering the greatest diversification benefits and industry momentum profits. This success is attributed to high investor agreement within IIC, leading to substantial aggregated demand and supply effects on stock prices. IIC excels in industries characterized by expectation-driven value, growth, and intangibility.
Data hiding by using AES Algorithm

Data hiding is the art of hiding data for various purposes such as; to maintain private data, secure confidential data and so on. Securely exchange the data over the internet network is very important issue. So, in order to transfer the data securely to the destination, there are many approaches like cryptography and steganography. In this research we propose an AES algorithm for embedding the data into the images which is implemented through the Microsoft .NET framework using the C#.NET.
Share references by using web pages

During the past recent years, there has been tremendous development reaming the concept of digital libraries-a knowledge base that can be stored and retrieved through online networks. Digital libraries are the most complex form of information systems that support digital document preservation, distributed database management, hypertext, filtering, information retrieval, and selective dissemination of information. This has really overcome geographical barriers offering a wide range of academic, research, and cultural resources with multimedia effects that can be accessed around the world over the distributed networks. The paper examines the concept of Digital library, the technology that has enabled its emergence &amp; architecture of the digital library system. It also highlights the digital library projects undertaken in USA, UK, and India. Here the authors explored the unique feature of digital library and possible challenges ahead for library and information professionals in the digital environment.
Online translated system: DESIGN AND Implementation

In the presence of technology and taking into account the concept of globalization, the application of chat is one of the most important aspects of our daily life to use different purposes that meet the needs of education, business and personal communication where the barrier is the language in most cases. Although we can send text using the chat app but there is still no known chat app where people can chat in different languages with the help of automatic translation system. Here the author decided to develop a mobile application with a chat and translation system in which users can chat in their preferred language for the translation system. Businessmen will help to facilitate communication with their foreign partners and students can talk to their friends abroad. It is useful to learn different languages and is useful to communicate with each other. Users only need to select the language they want to chat from the specified system. The system will use the Microsoft Translator API to translate in different languages.
TRAINING FUTURE TEACHERS OF TECHNOLOGY IN THE ARTISTIC FIELD OF CONDUCTING A MASTER CLASS ON MAKING A KNOT DOLL

Main topic to consider are the issues of artistic features, traditions of making knotted dolls, the potential of national-patriotic and aesthetic education among student youth by means of folk art. Emphasizing on the importance of mastering the technique of making a folk doll among future technology teachers which can be widely used later in their practical pedagogical activities both in technology classes and in extracurricular educational activities with students of primary and basic new Ukrainian schools, in particular during master classes. The main topic of discussion is the need to acquire knowledge about ethnographic research on the creation of a folk doll from various materials and regional features of shaping and decorating toy in order to conduct a high-quality and effective master class on a knotted doll, to achieve the educational, developmental goal and practical significance of such a format in technology classes.The study highlights the structure of the organization and preparation for the master class on knotted dolls in general secondary education institutions. At the preparation stage, it is necessary to select and thematically decorate the room for the master class, think over the structure of the author’s mini-lecture, prepare a multimedia presentation, select illustrative and visual material, organize an exhibition of the author’s creative works of the master class, select and prepare the necessary materials for making a doll by the participants of this master class. It is important to think over the features of the final stage of the master class (posting and reflection). The work describes in detail the technological stages of making a doll: forming the head - a knot, laying out a cross from threads, forming an anthropomorphic figure, decorating the "dressing" of the doll. The research substantiates the importance of studying the traditions of folk art in institutions of higher education by conducting master classes on knotted dolls. The artistic features of the knotted doll and conducting master classes are analyzed. The importance of the introduction of innovative technologies during master classes on knotted dolls in institutions of higher education is emphasized.
Design of a Novel Smartolight-pen and User Interface Screen enabled with URL detection

Air-writing refers to tracking object movement in the air with the interest of writing linguistic characters. The need for graphic pens and tablets in online educative teaching accounts for significant expenses. The proposed framework takes an exception from conventional handwriting systems. Colour detection and morphological segmentation techniques are at ease when compared to gesture-based methods since it employs a simpler model and detects the centre coordinates incessantly based on the contour. A novel low-cost Green LED Pen (GLP) is employed for air-writing. The proposed algorithm transfigures the characters in the frame into text using the strategy of handwriting-to-text conversion with the help of an Optical Character Recognition (OCR) technique. It enables fast processing to extract text from images. If a Uniform Resource Locator (URL) is detected in the User Interface Screen (UIS), the user is directed to the desired webpage. The proposed algorithm is hence unwavering for characters, digits, and special characters. A minimum object area of 500 sq. pixels with an object illumination of 498 lux and distance up to 70 cm at an angle of 55 degrees was found to trace a legible and smooth curve for air-writing. A total of 35 trials for handwritten to digital text conversion yielded an accuracy of 91.43%.
HKCN: A Novel Breast Cancer Identification Scheme using Homomorphic K-Means Clustering Norms

Breast cancer is the most common kind of cancer in women across the world. Furthermore, if the disease is discovered early, therapy can begin sooner and therefore be more effective. Mammograms are the most prevalent means of detecting this illness in its earliest stages. It is possible to detect micro-calcifications, which are specific to breast cancer, with the use of this approach. The goal of computer-aided detection is to help mammography in detecting breast cancer, minimizing the number of false positives and allowing for better diagnosis and treatment. Computer-aided detection systems are the product of a group of algorithms that automatically identify lesions. For this project, the major goal is to automatically enhance and segregate micro-calcifications in mammographic pictures. Homomorphic filter is one of the image enhancing techniques that has been implemented and put to use. The image classification methodology K-means segmentation also was developed and utilized. Different geometrical and spectral approach used to extract contouring and characteristics.
Model using GAN for Text to Image synthesis

Due to its remarkable data-generating capabilities, generative adversarial networks have gained significant relevance in unsupervised learning. Generative adversarial networks are very much useful in generating synthetic images from the given text description. The research work presented in this paper aims at developing a text-image synthesis model to generate high resolution synthetic images based on the scenario description given in input text. The paper proposes a novel model Df-GAN which is derived from VQGAN and CLIP using transfer learning. This model is evaluated on the COCO dataset. the experimental results show that the model can generate high resolution images. The model achieves FID score of 18.26 which is satisfactory.
A Hybrid Approach for Multimedia Summarization

Text summarization is the basic method in NLP (Natural Language Processing) application which makes the text data into a shorter version. All over the world a lot of multimedia data is generating which includes text, audio, video, image, etc., Generating the short summary from entire text will reduce our task of understanding the things. In the proposed work, film reviews data is taken to perform summarization. A film review is an article that reviews and analyses a film and is published in a magazine, newspaper, video, or scholarly journal. As a result, reading through the entire conversation will take a long time to comprehend the reviews and consider the film. To perform text summarization, we need to work on multi-media data to generate the short summary of the entire content. By scanning the images, audio, videos and converting them into text documents, multi-media data will reduce the difficulty for the machine to understand the important information from it. In this project, proposing a Hybrid (combination of Extractive summarization and Abstractive summarization) multi-media summarization method that uses NLP techniques, image processing, speech processing to retrieve the information contained in multimedia model. The proposed work includes the sequence of implementations namely, Multimedia processing, applying NLP techniques, Seq-to-Seq modelling to the text, and performing sentiment analysis using a Naive Bayes classifier.
Supply Chain Management in Pharmaceutical Industry Using IOT

The pharmaceuticals industries are in need of recently developed technology to compete with the worldwide market share to avoid counterfeit of pharmaceutical drugs right from warehouse to customers. Internet of Things (IoT) transforms the current pharmaceutical sector by providing and automating pharmaceutical manufacturing process across various sectors such as supply chain management, discovery of drugs, remote patient access and monitoring. Digitization has tremendous potential to help pharmaceuticals industries in addressing various challenges. Major problems the pharmaceutical industries have come across are supply chain management related to poor coordination between clusters, high dependency on human resources, temperature control in facilities, supply chain visibility, etc. Our paper will present the modus operandi in implementing the IoT to overcome the challenges in supply chain of drugs from warehouse to customers with focus on specific applications such as obtaining accurate information about location across the entire supply chain of drugs and to get real-time updates. This provides visibility of all the activities carried out in the supply chain. Also, this avoids counterfeiting of drugs. Counterfeit drugs are increasing nowadays and affects the risk of many lives in a large. Designing a system which provides solutions to these issues has become inevitable. An IoT based Supply chain management helps in addressing the problems faced by Counterfeit drugs. In addition to avoid counterfeit drugs, delivering the pharmaceutical products to customers at the right time, environmental parameters such as temperature and humidity are also monitored throughout the supply chain to avoid spoilage of pharmaceutical products.
A Large Scale Medical Crowdfunding Platform using Smart Contracts in Blockchain

This paper summarizes about the proposed system used for crowdfunding using blockchain. Crowdfunding with blockchain securely provides crypto-denominated assets for emergency cases with the use of Blockchain Tech. Overcrowding in emergency rooms (ED) has a negative impact on patients' health, accessibility, and high cost of care in community healthcare systems. The goal is to assist users in quickly and safely digitizing the crowdfunding process and organizing the security threat posed by frauds. Smooth transactions are made possible by Ethereum Blockchain's safe encryption of cryptocurrencies utilised for crowdfunding. Through a huge number of little donations, Project Crypto-bute assists in achieving the objective. Additionally, it streamlines and simplifies the process of asking for money. Distributed funding techniques make it possible to raise money rapidly and without incurring debt. The answer described above is the main tenet that will guide you in curating all of the needs. In particular during times of medical emergency, obtaining medical financing ought to be hassle-free, to quickly provide distributed funds. The costs of all necessary medical procedures and critical medical issues can be financed here. If your medical insurance policies do not cover the costs of all necessary medical conditions and treatments, you can obtain financing here. The aim is to reduce the competitive interest rates, low credit scores, and payback plans with the proposed crowdfunding effort. Blockchain technology is used in this case to quickly raise funds, promoting stress-free medical procedures.
Cheat Detection for Credit Cards Using Artificial Intelligence

The volume of web clients is progressively making changes on web-based business increment too. It is noticed that the amount of fraud on web-based exchanges is expanding as well. Credit card fraud is a kind of wholesale fraud where cheats gain or get money from another client's charge card account. This might happen using a client's ongoing records, actual credit card burglary, account number or PINs. The popularity of web-based businesses has resulted in a considerable increase in the frequency of online transactions in recent years. There is a substantial increase in online fraud instances, which result in million dollars in damages every year throughout the world. As a result, it is important to develop and use procedures that can aid in fraud detection. The Credit Card fraud identification project distinguishes the deceitful idea of the new exchange by shaping the credit card exchanges with the information on those which have been fake. To distinguish, in an event exchange is a typical transaction which can be real or fraud. A predictive model is employed for detection of cheat and legitimate exchanges using a popular machine learning algorithm called Random Forest Algorithm. This model is designed to Validate each transaction of the credit card accurately. The algorithm is designed such that it will analyze the data efficiently. The database used is imbalanced. To adjust, it ought to up-sample the database. Later a confusion matrix is built which analyzes random forest algorithms accuracy as 99.88%.
Histopathological Image Analysis Of Uterus Cancer

In this paper a method for examining the malignancy in uterine histopathological pictures is presented. It offers a method for classifying uterine cancer that is based on CNN and using ReduceLROnPlateaue in order to reduce the learning rate. Since there ain't much research on endometrial cancer, some assumptions are made based on previous approaches and Conv2D with sequential model is utilized to choose a preferred method and Relu is an activation function used here to minimize the error rate and for appropriate prediction. Adam is used as an optimization algorithm. This research makes a significant contribution to the field of medicine.
Stop Phishing : Master Anti-Phishing Techniques

Phishing Websites steal confidential material like from digital users. They steal all information possible from an end user. They use different techniques to steal the data. Most of the internet users become victims across the globe due to lack of digital education. Most fake websites look like trusted and real websites. About 2.009 million Phishing websites are detected in 2020; this rises to 26.02 percent in 2021. Identity theft cases have doubled since early 2020. Normal users can't spot phishing sites. Detecting fake sites requires special tools. Detecting phishing websites used black-list/whitelist, knowledge, URL-based, visual-similarity, machine learning, heuristic methods. Models detect URL-analysis, Webpage code, Webpage text data, URL statistical data, website images, and content. This paper studied and reviewed Phishing website detection methods. Comparing models, techniques, and accuracy.
A Simple Convolutional Neural Network for Doodle Classification

Visuals have been an integral part of our lives. The use of hand-drawn doodles is widespread and persistent, enabling people to retain information better and freely communicate thoughts and information. Doodle classification / hand-drawn diagram classification has significant application to communicate with persons who are deaf or hard of hearing that trains them to identify their urgent needs. The objective of this work is to develop a convolutional neural network (CNN) to classify the hand drawn images. This work utilized the Quickdraw dataset to train and evaluate the model. The performance of the customized model is compared with various state-of-the-art deep learning algorithms like MobileNet and DenseNet architectures and proved that proposed model comparatively gives better results on Quickdraw dataset.