Reviewerly/exHarmony huggingface dataset:
Open refine to wikibase

This tutorial aims to help researchers, digital collection librarians and data managers make their datasets available as linked open data. Participants have the option to either bring their own dataset or work with a sample dataset provided by the organizers. They will take part in practical exercises and learn how to use OpenRefine for data transformation and Wikibase for data storage. This pipeline workflow was developed in the context of NFDI4Culture, a German consortium of research and cultural institutions working towards a shared infrastructure for research data that meets the needs of 21st century data creators, maintainers and end users.
Recognition of Handwritten Digits and Characters Using Machine Learning

Handwritten Digits and Characters is that the capa- bility of a device to admit and take written response from various causes like paper forms, images bit show system and so forth Recognition of handwritten digits and chars is an arising space of exploration and finds expansive operations in banks, services and diligence/industries. The most aim is to style knowledgeable system for ”OCR(English) victimisation Neural Network”. Which will effectively fete a specific character of kind format using the machine learning approach. Machine learning is relatively new field, and style factors are. Therefore less well mere than those of alternative infrastructure. Machine learning system apply data community. System are operated in way which is fully separate from the operation of normal computers. System are trained so that given a positive staring state(data input); they whichever categorize the input data into one of the number of modules or the pure information to develop in such a way that a assured helpful property is increased. Handwritten Digits and Character an idea of recognize digits which is used for computers. Object detection technique is employed for detective work the digits and characters in West Germanic language i.e. digits from 0-9 and characters from(A-Z)(a-z) Capital letters and tiny Letters. Object detection is performed by Cascade classifier. Cascade classifier class to detect object in a video stream.
APPLICATION OF DEEP LEARNING-BASED SYSTEM FOR PREDICTING THE DIFFERENTIATION STATUS OF EARLY GASTRIC CANCER

So Young Han: NO financial relationship with a commercial interest | Jie-Hyun Kim: NO financial relationship with a commercial interest | Sang-Il Oh: NO financial relationship with a commercial interest | Ji-Soo Keum: NO financial relationship with a commercial interest | Kyung Nam Kim: NO financial relationship with a commercial interest | Jaeyoung Chun: YES financial relationship with a commercial interest;Eisai:Grant/Research Support | Young Hoon Youn: NO financial relationship with a commercial interest | Hyojin Park: NO financial relationship with a commercial interest
Probability of Data Leakage and Its Impacts on Confidentiality

A multi-channel communication architecture featuring distributed fragments of data is presented as a method for improving security available in a communication architecture. However, measuring security remains challenging. The Quality of Secure Service (QoSS) model defines a manner by which the probability of data leakage and the probability of data corruption may be used to estimate security properties for a given communication network. These two probabilities reflect two of the three aspects of the IT security triad, specifically confidentiality and integrity. The probability of data leakage is directly related to the probability of confidentiality and may be estimated based on the probabilities of data interception, decryption, and decoding. The number of listeners who have access to the communication channels influences these probabilities, and unique to the QoSS model, the ability to fragment and distribute data messages across multiple channels between sender and receiver. To simulate the behaviors of various communication architectures and the possibility of malicious interference, the probability of data leakage and its constituent metrics require a thorough analysis. Even if a listener is aware that multiple channels exist, each intermediate node (if any) simply appears to have one input and one output. There may be one or more listeners, and they may or may not be working cooperatively. Even if the listener(s) gains access to more than one channel, there is still the challenge of decrypting, decoding, or reassembling the fragmented data. The analysis presented herein will explore the probability of confidentiality from both the authorized user’s and the adversary’s perspective.
Hand Gesture Image Drag and Drop

The project ‘Virtual Drag’ (Artificial Intelligence) is a OpenCV based system. This will allow the user to virtually click and drag the pictures and items on the screen to other parts of the screen without use of mouse. The system will detect the hand landmarks on the palm, using those pin points and distance between the fingertips the system will be able to perform the operation. Virtual Drag utilizes the prominent gestures of your hand to drag and drop the images from one place to another. User needs to snap the fingers together to pick the image and then drag to any part of the screen and then drop by moving the fingers away. The system is based on the Mediapipe library provided by Google and the Python language.
Cloud Functions and Serverless Computing

Abstract: Cloud Function in the simplest words is a Function-as-a-Service (FaaS). FaaS is actually a family of the serverless computing category. “Serverless” means that the user can focus on its application logic without dealing with infrastructure at all. Painless development, deployment, and maintenance of a web API is still not a turn-key solution, although modern web application frameworkshave improved dramatically in the last few years. Serverless is without any doubt a game-changer. The event-driven approach combined with a scalable and robust cloud ecosystem offered by the maintop cloud vendors opens endless opportunities. Cloud Functions is Google Cloud’s event-driven serverless compute platform. FaaS is a real NoOpstechnology, it completely abstracts away servers. Cloud Functions are developed with the sole purpose to build event-driven architectures. These can react to events like file changes in storage, messages in the queue, or any HTTP request. Index Terms: Cloud Computing, Serverless Technology, Function as a Service, LambdaFunctions and Functions
Android Application for Image Steganography using Android Studio

Abstract: Image Steganography is mainly used for hiding an image or secret message in a cover image. For data hiding, this technique is being widely used for so many years. Image steganography is being used now by government, individual sender and receiver, in business and in so many fields. Now-a-days, this process has become very popular worldwide. People are doing research on image steganography and inventing new even stronger algorithms for image steganography. Hiding data in cover image by modifying bits of that is now optimized by so many new algorithms. Enthusiastic people are increasing demand of researching on image steganography and developing PC software and mobile application using different developing tools, programming languages and their own invention, algorithms etc. Steganography is the process of hiding a secret message within a larger one, in such a way that someone cannot know the presence or contents of the hidden message. Although related, steganography is not to be confused with Encryption, which is the process of making a message unintelligible. Whereas, steganography attempts to hide the existence of communication. The main advantage of steganography algorithm is because of its simple security mechanism. Because the steganographic message is integrated invisibly and covered inside other harmless sources, it is very difficult to detect the message without knowing the existence and the appropriate encoding scheme. Keywords: steganography, hiding, algorithms
A Technical Note for a Shor’s Algorithm by Phase Estimation

The objective of this paper concerns at first the motivation and the method of Shor’s algorithm including remarks on quantum computing introducing an algorithmic description of the method. The corner stone of the Shor’s algorithm is the modular exponentiation that is the most computational component (in time and space). A linear depth unit based on phase estimation is introduced and a description of a generic version of a modular multiplier based on phases is introduced to build block of a gates to efficient modular exponentiation circuit. Our proposal includes numerical experiments achieved on both the IBM simulator using the Qiskit library and on quantum physical optimizers provided by IBM. The shor’s algorithm based on phase estimation succeeds in factoring integer numbers with more than 35 digits using circuits with about 100 qubits.
Numerical Simulation of Robustness to Large Displacement of Optical Flow Based on Deep Learning

Abstract Traditional optical flow algorithm based on prior is sensitive to large displacement, in order to solve the problems, one optical flow algorithm based on deep learning is introduced to measure the global velocity of fluorescent oil film. The test results of numerical simulation show that the Average Endpoint Error (AEE) of HS, LK and Flownet2 are 2.4604 pixels, 2.3898 pixels and 0.9916 pixels in terms of warping 0.1s respectively, and the error of FlowNet2 is always the lowest under the conditions of large displacement. Therefore, the algorithm is more robust to large displacement than the others that is currently being used, which has certain exploration significance and engineering reference value.
A Comparative Study between Awash Bank S.C and Commercial Bank of Ethiopia the Effect of Corporate Social Responsibility on Brand Equity in Dire Dawa, Ethiopia

The objectives of this study was to examine the effect of CSR on brand Equity in Commercial Banks particularly between Awash Bank and Commercial Bank of Ethiopia in Dire Dawa Multidimensional corporate social responsibility (philanthropic, ethical, legal, and economic) on brand equity (brand awareness, brand association, perceived quality, and brand loyalty)in the banking industry, specifically were investigated the case of Awash Bank branch and Commercial Bank of Ethiopia branch in Dire Dawa Districts.Descriptive and explanatory research design quantitative methods were used and also using non-probability sampling technique.This study was used quantitative data collection tools self-administered structured questionnaires for collecting information.Both primary and secondary data sources were used to satisfy both the general and specific objective of the study.The data collected were analyzed through both descriptive and inferential statistics.Inferential statistics such as such as independent-samples t-test and ordinal logistic (O logit) regression data analysis were used.The survey findings the bank managers should be considered, CSR activities can create a positive impact on a bank's image, as perceived by its customers.Although three CSR components (Legal, Ethical and Economic domains) are found significant, they vary in terms of their importance by the banks' customers.However, Philanthropic domain of CSR is not significantly influence on Brand Equity in commercial banks particularly Awash Bank and Commercial Bank of Ethiopia in Dire Dawa thus, need to realize and incorporate these activities into their corporate strategy if they want to sustain a good level of competitive advantage, it may create a positive influence on society engaging in charitable activities, donating to the society and protecting the environment.
Collaborative annotation and semantic enrichment of 3D media

A new FOSS (free and open source software) toolchain and associated workflow is being developed in the context of NFDI4Culture, a German consortium of research- and cultural heritage institutions working towards a shared infrastructure for research data that meets the needs of 21st century data creators, maintainers and end users across the broad spectrum of the digital libraries and archives field, and the digital humanities. This short paper and demo present how the integrated toolchain connects: 1) OpenRefine - for data reconciliation and batch upload; 2) Wikibase - for linked open data (LOD) storage; and 3) Kompakkt - for rendering and annotating 3D models. The presentation is aimed at librarians, digital curators and data managers interested in learning how to manage research datasets containing 3D media, and how to make them available within an open data environment with 3D-rendering and collaborative annotation features.
Perspectives and commitments of smart education in Russia

The challenges of modern world are not only numerous, but also diverse – from a positive impact on the development of society to clearly unfriendly attacks in the economy, politics, science and education. Positive trends are associated with the smart education development, a new cognitive sphere that involves complex communication of all participants in the educational process in order to continuously improve the methods and technologies of the knowledge economy. In the digital paradigm of social development management, the knowledge sources are not only various formats (digital and paper) of textbooks, manuals and other, but also a close creative union between a teacher and a student, which allows not to get lost in the endless expanses of the Internet. The article highlights the trends in the domestic and foreign authors’ studying problems and prospects for the development of smart education. A mechanism for transforming the established methods of vocational training in Russian universities into a new concept of smart education is proposed. The principles of digital education format are formulated. The article content is determined by the methodology for the knowledge economy development: the basic principles of smart education and conceptually important methods for educational process organising. The studies of professors A.A. Bubenchikov, V.V. Glukhov, M.K. Novikov, V.P. Tikhomirov, etc., facilitated the idea of a prospective smart university concept development. The article is based on scientific research methods such as: comparison, analysis and synthesis, induction and deduction, historical and logical methods, positive and normative analysis, and the method of scientific logic.
DQI: A Dynamic Quantization Method for Efficient Convolutional Neural Network Inference Accelerators

The post-training compression with quantization is a common technology to improve the efficiency of embedded neural network accelerators. In this paper, a Dynamic Quantization in Inference (DQI) method is proposed to solve the severe quantization overflow problem that may occur in CNN inference process. Based on analysis of quantization errors of activation values in convolutional layers, efficient quantization overflow detection and quantization parameters dynamic update are designed and implemented in CNN accelerator. The evaluation result on VGG16 and MobileNetV2 models demonstrates that DQI can improve the inference accuracy of by up to 11.59% in high overflow scenarios, while the overhead in hardware resources and runtime is acceptable.
Mapping the Energy Internet Physical and Cyber System into Complex Networks Model

As a new ecological energy system with renewable energy as the priority, electric energy as the foundation, and multiple energy synergy, the energy Internet integrates technologies such as big data, Internet of Things, cloud computing, mobile Internet, and artificial intelligence to reduce carbon emissions and achieve a powerful solution for carbon neutrality. This paper takes the energy Internet physical and cyber system as the research object, using complex network theory, explores the nodes and links mapping mechanism of energy Internet physical and cyber system, and constructs a complex network model of the energy Internet physical and cyber system. Based on this network model, we could shed a light on understanding the energy Internet physical and cyber system.
Classification Trends Taxonomy of Model-based Testing for Software Product Line: A Systematic Literature Review

Context: Testing is one of the techniques that can assure the quality of software including the domain of Software Product Line (SPL).Various techniques have been deliberated to enhance the quality of SPL including Model-based Testing (MBT).Objective: The objective of this study is to analyze and classify trends of MBT in SPL covering the solutions, issues and evaluation aspects by using taxonomy form.Method: A Systematic Literature Review (SLR) was conducted involving 63 primary studies from different sources.The selected studies were categorized based on their common characteristics.Results: Several findings can guide future research on MBT for SPL.The important finding is that the multiple measurements are still open to improving current metrics to evaluate test cases in MBT for SPL.The multiple types of measurement required a trade-off between maximization and minimization results to ensure the testing method which could satisfy multiple test criteria for example cost and effectiveness at the same time.
Analisis Digital Forensik Keaslian Video Rekaman CCTV Menggunakan Metode Localization Tampering

Video is one the valid evidence if the handling process is in accordance with digital forensic procedures. Closed circuit television is a video sourse that is often used as authentic evidence in court. The authenticity of the video is something that is often doubted by certain parties. For this reason, this discusses how to detect the authenticity of video as digital evidence by comparing the original video files and tampering video files resulting from attack frame addition and attack frame delection. The media info tool is used to analyze the metadata and the localization tampering method is used to detect the frame where manipulation occurs. Localization tampering analyzes frame by frame, calculates as histogram and displays a histogram graph. Based on the results of the metadata analysis of the original video file and the video file tampering, it displays different information, which means that the video has been manipulated. Next, analyze the video with the localization tampering method to display the location on the video frame where manipulation has occurred. From the analysis results provide different information both from the calculation of the RGB value and the histogram graph.
Unreal engine-based photorealistic aerial data generation and unit testing of artificial intelligence algorithms

A number of real-time object detection, tracking, and autonomy artificial intelligence (AI) and machine learning (ML) algorithms are being proposed for unmanned aerial vehicles (UAVs). A big challenge is can we stress test these algorithms, identify their strengths and weaknesses, and assess if the UAV is safe and trustworthy? The process of collecting real-world UAV data is costly, time consuming, and riddled by lack of quality geospatial ground truth and metadata. Herein, we outline a fully automated framework and work ow to address the above challenges using free or low-cost assets, the photorealistic Unreal Engine (UE), and AirSim aerial platform simulator. Specifically, we discuss the rapid prototyping of an outdoor environment combined with the robotic operating system (ROS) for abstracting UAV data collection, control, and processing. Real and accurate ground truth is collected and metrics are presented for individual frame and entire flight collection evaluation. Metrics recorded and analyzed include percentage of scene mapped, 3D mapping accuracy, time to complete task, object detection and tracking statistics, battery usage, altitude (from ground), collisions, and other statistics. These metrics are computed in general and with respect to context, e.g., clutter, view angle, etc. Overall, the proposed work is an automated way to explore UAV operation before real-world testing or deployment. Promising preliminary results are discussed for an outdoor environment with vegetation, short and long range objects, buildings, people, vehicles, and other features for a UAV performing loitering and interrogation.
An Autonomous Approach for Type Categorization of Product Data Based on Numerous Text and Attribute Factorizations

Product categorization or Product classification is an area of Natural Language Processing. This special area happens to have a lot of challenges, especially for e-commerce organizations. Scientists and researchers have actively worked on this area over the years using various machine learning &amp; artificial intelligence techniques. Product categorization is the placement and organization of products into their respective categories.
USE OF INFORMATION AND COMMUNICATION TECHNOLOGY IN TEACHING AND LEARNING IN EMERGENCY SITUATIONS: RELEVANCE, CHALLENGES AND ETHICAL CONCERNS

This study sought to ascertain the relevance of the use of information and communication technology (ICT), its challenges and ethical concerns in teaching and learning in in emergency situations. Some instances of such situations are natural disasters and outbreak of diseases. A case in hand about such diseases is the current Corona Virus Pandemic. Using a qualitative method of conceptual frame and critical analysis, the paper explored the meanings and imports of technology, information technology, communication technology and information and communication technology, in reference to teaching and learning in emergency situations. It was discovered that these concepts, though interrelated, are not exactly the same, and that information and communication technology is better understood in the light or backdrop of technology itself. The components of ICT were discussed, leading to the ascertainment of the relevance of and challenges to ICT in teaching and learning in emergency situations, as well as ethical issues emanating from the use of ICT. In the course of the analytical exploration, the roles of stakeholders such as parents, teachers, students and the government were highlighted. Based on the insight gained from the discourse, the paper came to a conclusion that the relevance of the use of ICT in teaching and learning in emergency situations is indisputable, but not without some challenges. Although ethical issues constitute a challenge of its own in the context of ICT, it is believed that their proper understanding and application by various stakeholders, especially teachers and students, will be of immense help in overcoming other challenges facing the use of ICT in teaching and learning. In the light of the conclusion arrived at, the paper recommended, among others, that teachers at all levels of education be well knowledgeable in the use of ICT in teaching and learning, with its ethical concerns, so as to be able to guide students properly, and students endeavor to be discreet in their use of the internet, while government should legislate and provide enabling environments that will make online teaching and learning thrive in emergency situations.