Reviewerly/exHarmony huggingface dataset:
Case study: a novel system to manage e-healthcare data by using blockchain technology

Changing socio-economic factors, scientific breakthroughs in biomedical research, as well as the emergence of new materials and information technologies are profoundly transforming the healthcare sector. In the last 20 years, a large number of research and development projects and standardization activities have concerned the processing, sharing and presentation of data through reliable, scalable, and economically sustainable systems. In particular, blockchain-based technologies are playing an increasing role in collecting, handling, storing, and updating medical records securely. After the illustration of the current challenges faced by the healthcare organizations in data management, this chapter focuses on a specific use case related to the update of the Patient Summary. This health data document is of fundamental importance for a correct knowledge of the patient&apos;s clinical history. The authors developed a blockchain system to support the general practitioner in the Patient Summary update process, ensuring the integrity of the health data and validating the entire medical process through smart contract programming. The proof-of-concept simulation demonstrates the practicability of the technical approach and its ability in improving the current management of the Patient Summary update process.
Improving Healthcare Record Management System in Indonesia by Using Blockchain Technology

Over time as the growth of IoT and other technology has grown rapidly over the years, so does the usage of blockchain technology, nowadays even many industrial activities use blockchain technology due to the nature of the blockchain itself to be transparent, saleable, decentralized, and secure for transactions and other industrial purposes. Blockchain is referred to as a public ledger consisting of all transactions taking place across a peer-to-peer network. It is a data structure that consists of linked blocks of data that are also stored in different ways depending on the encryption code of the block itself. Blockchain has also proven to have many successful uses and positive feedback when used as a system for EMR (Electronic Medical Record). However, it will be challenging to implement these technologies since many factors need to be addressed, such as the current regulation of the government. Creating a suitable blockchain management system for the healthcare system in growing countries such as Indonesia that needed it the most since healthcare is one of the essential components for a growing nation to thrive.
A comparison of histopathology imaging comprehension algorithms based on multiple instance learning

Whole slide imaging (WSI), also called digital virtual microscopy, is a new imaging modality. It allows for the application of AI and machine learning methods to cancer pathology to help establish a means for the automatic diagnosis of cancer cases. However, designing machine-learning models for WSI is computationally challenging due to its required ultra-high resolution. The current state-of-the-art models use multiple instance learning (MIL). MIL is a weakly-supervised learning method in which the model uses an array of inferences from many smaller instances to make a final classification about the entire set. In the context of WSI, researchers divide the ultra-high-resolution image into many patches. The model then classifies the slide based on an array of inferences from the patches. Among several ways of making the final classification, attention-based mechanisms have resulted in superb accuracy scores. The Transformer, one attention-based algorithm, has reported substantial improvements for WSI comprehension tasks. In this project, we studied and compared several WSI comprehension algorithms. We used the following three datasets: CAMELYON16+17, TCGALung, and TCGA-Kidney. We found that attention-based MIL algorithms performed better than standard MIL algorithms for classifying WSI images, achieving a higher mean accuracy and AUC. However, none of the attention-based algorithms performed significantly better than the others, reporting accuracy scores that varied widely. Presumably, it is due to the limited availability of training samples in the data corpus. Since it is not easy to increase the samples from human subjects, some machine learning techniques like transfer learning could help mitigate this issue.
Category feature reconstruction for pathological image segmentation

In recent works, more and more attention mechanisms have been used for medical image segmentation, however, attention mechanisms are not very good at distinguishing categories in multi-category medical image segmentation tasks. In this paper, we propose a category feature reconstruction module (CFRM) for multi-category pathological image segmentation of pancreatic adenosquamous carcinoma. Compared with the attention mechanism to enhance the features of the region of interest, the proposed CFRM pays more attention to the reconstruction of category features. The CFRM enables the network not only to highlight the features of the region of interest, but also to increase the discrimination of different categories of features. Based on UNet, the proposed CFRM is added at the top of the encoding path. Compared with other state-of-art methods, both the Dice coefficients and the Iou coefficients of the proposed method have reached the best level on our pancreatic adenosquamous carcinoma segmentation dataset.
Resilient EDGE Detection Method for Significant IMPULSE Noise

The present study introduces a novel technique for detecting edges in images by means of the Switching Adaptive Median and Fixed Weighted Mean (SAMFWM) filter, which proves to be highly effective in removing impulse noise compared to conventional denoising filters that are currently available, while preserving edge details, thus ensuring optimal edge detection.The performance of the proposed approach is assessed using a comprehensive analysis of different performance metrics, including Mean Square Error (MSE), Structural Similarity Index (SSIM), and Peak Signal-to-Noise Ratio (PSNR).In addition, the Sobel operator is used to detect the edges and Non-Maximum Suppression is used to track and thin the edges.These techniques are utilized to handle edge discontinuities and detect edges in the presence of high-intensity noise.Furthermore, the proposed approach outperforms other alternative techniques such as the Robert, Prewitt, and Canny edge detectors in effectively removing impulse noise, even at high levels.
Smartphone-Assisted Language Learning: A Breakthrough for English Learning Autonomy

21st-century language learning involves technology as a medium of learning.Over the centuries, various technologies have been created to synchronize the language learning process to the present-day phenomenon that results in flexibility -students can learn a language anywhere, anytime even without a teacher.As the newest information technology, smartphones have now functioned as mini-computers that are used by students for language learning.It promotes autonomous learning, that is the ability to control one's learning and the potential ability to act in learning situations.This research aims to investigate the potential of smartphones in promoting autonomous language learning, focusing on three questions; ( 1) what smartphone applications are used by students for language learning, ( 2) what skills are associated with it, and (3) how they use them for language learning.An interview and smartphone log were used to collect the data.The findings showed that there are 51 applications used by the participants.Those applications are used for different purposes in language learning.
Object Detection and Screen Presence Time Estimation Using Opencv and Yolo Alogrithm

This paper describes about the object detection and object's screen presence time estimating model which will run on any computer easily.Currently there are only models that will only detect the motion of the object alongside estimating screen time.But here we tried to propose a model that will detect the object that is present in the camera view and also estimate the amount of time the object is present in the camera view.For object detection there are many algorithms such as CNN (Convolutional Neural Network), R-CNN, Fast R-CNN, Faster R-CNN, SSD (Single Shot Detector), YOLO (You Only Look Once) etc.In the current model we gave preference to the speed of detecting the object along with the accuracy.So, we preferred using the Yolo algorithm among all the existing algorithms that can be used for the object detection.But yolo is only designed for using in the GPU based computers.So, in order to implement yolo algorithm in our normal CPU based computers we used OpenCV library such that real time object detection is also possible in Non-GPU computers.Our model estimates the time of screen presence of each object using python libraries such as pandas, time etc.As we used yolo as our object detection algorithm our model detects objects with 80-99% confidence.
Cryptocurrency as a Component of the Blockchain in the South African Banking Industry amid 4IR

The paper intended to offer insights on using Cryptocurrency as a Component of Blockchain technology in financial institutions with a focus on South Africa.The study sought: (1) To highlight the economic impact that blockchain and Cryptocurrency have on the finance industry; (2) To learn more about how respondents; perspectives and experiences of blockchain and Cryptocurrency; and finally, (3) To determine what factors are helpful and harmful in the actual context of what would be deemed as a banking environment customers use a new group of e-commerce methods to conduct transactions without involving banks.A questionnaire was used to collect data, followed by interviews on respondents' different views related to blockchain and Cryptocurrency.From the large number of respondents that use financial institutions' services as a target, a sample of 200 participants took place in the study.The study's descriptive measures include variables such as the Mean, standard deviation, and correlation analysis.The SPSS software summarized and analyzed the relevant data collected.Correlation analysis measured the inner relationship between factors and the study data.The study showed that Millennials and Generation Z are much more technology inclined.Most of them were educated and showed interest in blockchain technology and the use of Cryptocurrency.The results also revealed a strong relationship between the possibilities and risks associated with blockchain and Cryptocurrency.Blockchain has become a more efficient way to complete transactions.The study showed that respondents utilize Cryptocurrency and perform different transactions such as cash receipts, deposit corrections, and cross-border payments.
Blockchain Technology for Sustainable Supply Chain Management Systems

This paper explores the applications of blockchain technology for sustainable supply chain management systems with an attempt to address the challenges that are facing the manufacturing industry.The supply chain management systems should be viewed as three components, namely, the strategic component, the tactical component, and the operational component.Therefore, an intervention requires the ability to trace the root cause(s) to ensure that technology-based solutions are tested through the three main components for usability.A systematic review was used for this paper to explore the applications of blockchain technology for sustainable supply chain management systems.This paper advocates for the application of blockchain on the basis that this technology is "the factory of the future" with the capability of creating transparency and traceability through all phases of the value chain from sourcing materials to final production.The findings suggest that blockchain increases auditing and compliance functionality, reduces costs, and creates a reliable ecosystem shipment process to prevent shipping fraud.It should be conceded that there are technical challenges that cannot be overlooked, hence the evidence still suggests that there is a reluctance to adopt blockchain, which is making the industry lag behind.Furthermore, there is the possibility that some industries are still struggling with readiness assessment in order to justify and select the appropriate technologies.
THE USE OF SONG, SOCIAL MEDIA, AND GAMES IN IMPROVING VOCABULARY: STUDENTS’ PERCEPTION

Vocabulary is one of the crucial aspects of learning English. However, knowing and remembering the vocabulary is difficult because there are many words in the language. The goal of this research is to know which platform will help students to improve their vocabulary more quickly. This study also seeks to answer to the research questions: 1. What is students’ perception of improving vocabulary from songs, social media, and games? 2. Which platform do students like and enjoy using to improve their vocabulary? 3. Which gender prefers to use songs, social media, and games to improve their vocabulary? 4. From songs, social media, and games. Which one that students struggle with or do not like using it? The research is designed with interview and questionnaire design. 100 students of grade 10 senior high schools from four island in Indonesia. The questionnaire was distributed online to the students and a followed up interview. The findings of this study indicate that learning through song, games, and social media can help students improve vocabulary.
Interpretable SAM-kNN Regressor for Incremental Learning on High-Dimensional Data Streams

In many real-world scenarios, data are provided as a potentially infinite stream of samples that are subject to changes in the underlying data distribution, a phenomenon often referred to as concept drift. A specific facet of concept drift is feature drift, where the relevance of a feature to the problem at hand changes over time. High-dimensionality of the data poses an additional challenge to learning algorithms operating in such environments. Common scenarios of this nature can for example be found in sensor-based maintenance operations of industrial machines or inside entire networks, such as power grids or water distribution systems. However, since most existing methods for incremental learning focus on classification tasks, efficient online learning for regression is still an underdeveloped area. In this work, we introduce an extension to the SAM-kNN Regressor that incorporates metric learning in order to improve the prediction quality on data streams, gain insights into the relevance of different input features and based on that, transform the input data into a lower dimension in order to improve computational complexity and suitability for high-dimensional data. We evaluate our proposed method on artificial data, to demonstrate its applicability in various scenarios. In addition to that, we apply the method to the real-world problem of water distribution network monitoring. Specifically, we demonstrate that sensor faults in the water distribution network can be detected by monitoring the feature relevances computed by our algorithm.
Image-To-Image Translation for Animation Using Opencv and Gan

The main goal is to produce an output to convert the global real image into supported impressions (Animated Image). The concept of the paper is based on one-of-a-kind photos that are turned into an art shape akin to oil. This project would use an OpenCV package in Python to create the layout and a Deep Convolutional Generative Adversarial Network (DCGAN) to generate realistic-looking photos. The system is made up of three components: (a) a generative adversarial network that has been trained to generate comic characters, (b) a cartoon model that will generate edge animated images using OpenCV, and (c) an edge detects that takes input from portraits and then generates comic characters based on the resulting edge images
The Enlightenment of Swedish Higher Education Characteristics to Our Higher Education

In northern Europe, Sweden has the most advanced technology.Higher education, vocational education, vocational education, vocational education, vocational introduction and vocational training system have formed a special education system.Especially after the long development and reform, higher education has its own characteristics.This paper discusses the characteristics of Swedish universities and its application and enlightenment in Chinese universities. Higher education situation in SwedenLocated in Scandinavia, Sweden is a country of the European Union, with 35 universities and 20 national universities.Swedish institutions of higher learning are divided into five types, namely universities, other colleges, art colleges and other universities.Higher education in Sweden presents a diversified education system, because local universities have a great sense of autonomy and can adjust their curriculum and learning plans according to the professional development plan.In view of the complex situation of Chinese universities, the government agencies will conduct regular review and supervise them to ensure the level of school education.The largest educational administrative units in Sweden are the Education Department and the Science Division.In these institutions, responsible for the administrative control of colleges and universities is the national higher education institutions (Swedish Ministry of Higher Education), its primary task is to use evaluation, certification, audit and other means to conduct administrative supervision of colleges and universities, to ensure that the universities strictly abide by the relevant government regulations, to meet the academic needs of students [1].The evaluation of higher education quality in Sweden, also known as "quality audit", has been a long and lengthy evaluation of teaching quality since Sweden became the European Union in 1995.In the integration of higher education in Europe, Sweden began the European "Bologna Process" in 1999.In the context of the European education system, the Swedish higher education evaluation system, based on the European Quality assurance Standards and Standards of Higher Education (ESG), through the improvement and improvement of its own evaluation system, has made major changes to its higher education quality evaluation system in 2007 and 2011 [1]. The development of higher education in SwedenIn May 1975, Sweden issued a reform of higher education.The goal of higher education is to
How Are You? A Sociological Case Report of the COVID-19 Pandemic from Professionals in Italy

COVID-19 has turned our lives upside down. The first lockdown occurred in Italy in the spring of 2020, drastically disrupting people’s daily schedules, work schedules, socialisation, and relationships with co-workers, family and friends. To overcome physical isolation, collect impressions and keep a record of the period, the “How are you?” online questionnaire has been designed as a potential conversation among friends during home confinement for all but essential reasons. What impact this situation had on people? The study investigates some of the social and relational consequences the first lockdown in Italy had on a group of professionals in terms of similarities and differences regarding changes and limitations on their work and daily routines, primarily focusing on the emotions felt at that time. Text mining techniques have been applied to almost one hundred replies, as well as an unsupervised method of emotion analysis; the latter is used for the entire sample and a subgroup consisting only of female scientists. Our findings show that during the Spring 2020 lockdown, a moment of physical and relational confinement was bear, causing bewilderment due to several factors: in terms of work-life balance, the overlap between public and private space, and the established daily routine to return, while regarding the relational sphere, the lack of physical contacts and interactions - such as support for dependent elderly - that technology has only partly been able to fill. Two primary emotions emerge from the entire sample: acceptance of the virus containment measures imposed and restlessness about the present and future. The group of female scientists appears more optimistic. The experienced situation of deprivation of individual freedoms such as movement and social contact, however, has brought along a new awareness of the frailties of our society, refocusing attention on the importance of scientific research, ecological transition, and, more generally, a reflection on our development model.
HOW BLOCKCHAIN BASED CLOUD COMPUTING BENEFIT RENEWABLE ENERGY INDUSTRY?

Blockchain technology is a distributed ledger with records of data containing all details of the transactions carried out and distributed among the nodes present in the network. All the transactions carried out in the system are confirmed by consensus mechanisms, and the data once stored cannot be altered. Blockchain technology is the necessary technology behind Bitcoin, which is a popular digital Cryptocurrency. ''Cloud computing is a practice of using a network of remote servers hosted on the internet to store, manage, and process data, rather than a local server or a personal computer and high computational power. It is still facing many challenges like data security, data management, compliance, reliability. In this article, we have mentioned some of the significant challenges faced by the cloud and proposed solutions by integrating it with blockchain technology. Many devices connected to grid help in exchange of information with power system using cloud computing. INDEX TERMS Cloud computing, Blockchain Technology, data security, decentralization.
Crime Evidence Over Blockchain

Blockchain is a digital ledger of transactions that is duplicated and spread over the whole network of computer systems on the blockchain, and it is a system of preserving information in a way that makes it difficult or impossible to edit or hack. Collecting, identifying, evaluating, analyzing, preserving, and presenting evidence is a difficult task in existing forensics. That's where the blockchain'sdecentralized nature comes into play, with forensic data being stored in the private network using the blockchain's nodes in a peer-to-peer network. Digitalforensics will also be more secure,and the investigation will be more transparent to those on the other side of the jurisdictional border. In the criminal investigation process, information that frequently changes is stored in the hotblockchain, and unchanging data such as videos are stored in the cold blockchain. In this we are using the Ethereum concepts and implementing smart contracts. Keywords - ledger, chain of custody, Hyperledger fabric, forensic.