Reviewerly/exHarmony huggingface dataset:
Effective Management of Personal Health Records using Blockchain Technology

The goal of this chapter is to present the key challenges for the implementation of blockchain technology (BT) to personal health records (PHRs) as identified in recent publications. Meta-analysis was used and ScienceDirect, EBSCOhost (including Health Source – Consumer Edition and MEDLINE), OECD iLibrary, Open Knowledge Repository, Scopus, and Web of Science databases have been researched. The keywords used in searching were blockchain, PHRs, digital patient records, data protection, security, and trust in various combinations. The chapter is structured as follows: first, the goal of the chapter is presented within the framework of the scheme created by the Strategic Intelligence of the World Economic Forum to show the impact of the Fourth Industrial Revolution in which blockchain is an important component. On completion, the actual methodology is briefly described, followed by a literary review where the main findings are presented. The findings are grouped into three sections: technical developments, legal challenges, and social challenges. Based on these, the future of blockchain in PHRs is sketched and key success factors for the effective implementation of BT in PHR are identified. Conclusions will follow at the end of the chapter.
An Empirical Analysis of the Effects of Population Growth on Economic Growth in Ethiopia Using an Auto Regressive Distributive Lag (ARDL) Model Approach

Abstract Between 1980 and 2020, the study looks at "An Empirical Analysis of the Effects of Population Growth on Economic Growth in Ethiopia Using an Auto Regressive Distributive Lag (ARDL) Model Approach." The appraisal coefficient of population growth (POP) is positive and significant, according to the findings of this study. However, in response to the long-term association between population expansion and economic growth in Ethiopia, the macroeconomic variables were subjected to a limit test and a broader causality test. From the finding of bound test, since the value of F-statics is greater than the upper boundary line then there are long run equilibrium relationships between RGDP, Population size, foreign direct investment, personal remittance, population growth rate, rate of inflation and gross capital formation. According to the findings of the Grander Causality Test, Real Gross Domestic Product can cause Ethiopian population size (POP), but population number (POP) cannot cause Real Gross Domestic Product at the same time. Finally, in order to boost Ethiopia's economic growth, the government should implement policies that would attract foreign investors. The government should also establish a benchmark to ensure that the economy increases faster than the population.
File Search in Employee Archives Using Sequential Search Algorithm

PT. Jaya Nika Permata Group is one of the companies engaged in the Bakery, Café and Restaurant which has been running for 37 years and is still active until now. Currently based in the city of Pekanbaru, and already has branches in Duri, Dumai, Batam. With the total number of employees of PT. Jaya Nika Permata Group has approximately 485 employees, of course, the number of employee files that will be archived is quite large and the file types are varied. In addition, the process of searching for employee files at the time of archived and when files are needed will take a long time considering the large number of employees. Currently, there is no system that can help facilitate the employee's file archiving activities. In this study, field research was conducted to determine the condition of the current file archiving system. Based on the analysis that has been obtained, research is carried out to develop an employee file filing system that is currently running at PT. Jaya Nika Permata. Searching files in employee archives using a sequential search algorithm is expected to facilitate employee file archiving activities and speed up the process of searching for employee files when needed.
Pengaruh Jarak Elektroda dan Tegangan terhadap Efektivitas Pengolahan Air Lindi dengan Metode Elektrokoagulasi-Adsorpsi Zeolit

The problem that has been difficult to overcome until now is the waste problem. Landfilling remains a method that is often used but has a disadvantage in the form of leachate production. Leachate or leachate is defined as wastewater produced from Final Disposal Sites (TPA). The combination of electrocoagulation and adsorption methods can be a promising treatment technology. The electrocoagulation process was carried out for 1 hour using iron electrodes. The variations used are electrode distances consisting of 1 cm, 1.5 cm, and 2 cm while the voltages consist of 10 volts, 20 volts, and 30 volts. In adsorption, zeolite adsorbent was used with a residence time of 2 hours. The research stages started from the preparation of leachate samples, examination of initial characteristics, leachate treatment, and testing of COD, TSS, and pH. The results showed that the optimal variation was obtained at a distance of 1 cm and a voltage of 30 volts with a COD efficiency of 98.84% and TSS of 99.82%. For the pH value, the result is that the greater the distance between the electrodes and the voltage, the higher the pH value obtained.
Socialization of the Making of Learning Comic Media Using the Make Beliefs Comix Website at SDN Bukur

This sosialization aims to optimize limited face-to-face learning by using comic learning media through the Make Beliefs Comix website’s. The core activity is in the form of socialization activities about making learning media that attract students' attention by displaying comics according to the learning theme. This activity was carried out twice in August, prinecisely in the first week. At the beginning meeting the teacher was introduced to the Make Beliefs Comix media and tutorials for its use, while in the last meeting , the teacher presented the comics that had been made. The result of socialization can make teacher to produce commix according to themes how this teach in classroom, and make interactive story in commix strips in according situation in class and learning material.
Home Learning Facilitation of Parents on their Children in the Modular Learning Modality

Home Learning Facilitation of parents refers to the role of the parents in guiding and mentoring their children who are into Modular Learning Modality. While learning at home, this learning modality requires a great extent of support from parents as learning facilitators to ensure students’ learning progress. This study aims to describe home facilitation as experienced by the parents in the selected remote areas in region 12. This is qualitative research employing a descriptive phenomenological approach using Collaizi’s approach on thematic analysis. Themes on Building the character and setting life’s goals; Motivating children to pursue education; learning facilitative pedagogical approaches in mentoring their children, and their shared insights have emerged in understanding the essence of Home Learning Facilitation of Parents on their Children.
Rwin-FPN++: Rwin Transformer with Feature Pyramid Network for Dense Scene Text Spotting

Scene text spotting has made tremendous progress with the in-depth research on deep convolutional neural networks (DCNN). Previous approaches mainly focus on the spotting of arbitrary-shaped scene text, on which it is difficult to achieve satisfactory results on dense scene text containing various instances of bending, occlusion, and lighting. To address this problem, we propose an approach called Rwin-FPN++, which incorporates the long-range dependency merit of the Rwin Transformer into the feature pyramid network (FPN) to effectively enhance the functionality and generalization of FPN. Specifically, we first propose the rotated windows-based Transformer (Rwin) to enhance the rotation-invariant performance of self-attention. Then, we attach the Rwin Transformer to each level on our feature pyramids to extract global self-attention contexts for each feature map produced by the FPN. Thirdly, we fuse these feature pyramids by upsampling to predict the score matrix and keypoints matrix of the text regions. Fourthly, a simple post-processing process is adopted to precisely merge the pixels in the score matrix and keypoints matrix and obtain the final segmentation results. Finally, we use the recurrent neural network to recognize each segmentation region and thus achieve the final spotting results. To evaluate the performance of our Rwin-FPN++ network, we construct a dense scene text dataset with various shapes and occlusion from the wiring of the terminal block of the substation panel cabinet. We train our Rwin-FPN++ network on public datasets and then evaluate the performance on our dense scene text dataset. Experiments demonstrate that our Rwin-FPN++ network can achieve an F-measure of 79% and outperform all other methods in F-measure by at least 2.8%. This is because our proposed method has better rotation invariance and long-range dependency merit.
Cloud Gaming Video Coding Optimization Based on Camera Motion-Guided Reference Frame Enhancement

Recent years have witnessed tremendous advances in clouding gaming. To alleviate the bandwidth pressure due to transmissions of high-quality cloud gaming videos, this paper optimized existing video codecs with deep learning networks to reduce the bitrate consumption of cloud gaming videos. Specifically, a camera motion-guided network, i.e., CMGNet, was proposed for the reference frame enhancement, leveraging the camera motion information of cloud gaming videos and the reconstructed frames in the reference frame list. The obtained high-quality reference frame was then added to the reference frame list to improve the compression efficiency. The decoder side performs the same operation to generate the reconstructed frames using the updated reference frame list. In the CMGNet, camera motions were used as guidance to estimate the frame motion and weight masks to achieve more accurate frame alignment and fusion, respectively. As a result, the quality of the reference frame was significantly enhanced and thus being more suitable as a prediction candidate for the target frame. Experimental results demonstrate the effectiveness of the proposed algorithm, which achieves 4.91% BD-rate reduction on average. Moreover, a cloud gaming video dataset with camera motion data was made available to promote research on game video compression.
Teachers’ strategies to teach writing Explanation texts

The strategy in teaching is very important for the teacher in teaching writing, especially in teaching writing explanation text. The teacher must have a variety in teaching to help the students study successfully. This research was intended to find out the teaching strategies used by the teachers at SMAN 10 Garut. The purposes of this research are to identify some of the teachers' strategies and techniques used in teaching writing explanations. The data needed is gained through a sample consisting of 4 SMAN 10 Garut (Senior High School) teachers. The teachers are provided with 18 questionnaires. The responses are in the form of Yes, Sometimes, and No to the statements given. Then, the result is formulated by using: = f × 100%. This research used the descriptive method and employed qualitative data. The writer observed the teachers in teaching writing explanation text and using teachers' observation form also. Based on the findings, (61. 11%) of the respondents perceive that various teaching strategies were needed for the students. Based on the writer's interpretation, it is suggested that the teachers practice specific strategies for teaching writing explanations.
USING KWL (KNOW, WANT, LEARNED) TECHNIQUE IN TEACHINGREADING COMPREHENSION

The research is entitled “Using KWL (Know, Want, Learned) Technique in Teaching Reading Comprehension”. The aims of the research are to figure out how the teachers implement Know, Want, Learned (KWL) technique in teaching reading comprehension and the problems that raise when applying Know, Want, Learned (KWL) technique in teaching reading comprehension. This research uses descriptive qualitative method. The respondents of this study are two English teachers in one of the Vocational High Schools in Padalarang. The instruments used to collect data are interview and classroom observation. The results of data analysis showed that the teacher implemented all the steps of KWL (Know, Want, Learned) systematically during classroom activities based on what had been listed in the theory including (1) write a chart on the blackboard, (2) give topic about descriptive text and narrative text, (3) ask students to fill what they already know about the topic in column K, (4) asked students to fill what they want to know aboutthe topic in column W, (5) asked students to fill what they have learned about the topic in column L, and (6) make conclusions from the topic. The research finding also showed that the teachers faced some problems in implementing KWL (Know,Want, Learned) technique in teaching reading comprehension including students lack of background knowledge and students lack of vocabularies. This research is held based on the fact that although KWL has been found to help overcome problems encountered by teachers in getting the students to be more active to participate in the process of learning, but a vast amount of research about KWL in Indonesia, especially in vocational high school, has not been conducted, and there is still a great deal that is not known about the implementation of KWL in vocational high schools.
An approach to the design of didactic material for the strengthening of the integral development of the child

The development of children must be an integral part of their educational environment, focusing on strengthening their learning and social skills. The research is framed in the design of didactic material, under the perspective of product design. As a discipline of study, it focuses on the needs andparticularities of the rural educational environment and attempts to support the integral development that Ecuadorian education has been pursued. In this context, with a qualitative approach, the characteristics of the environment are collected, as well as the perspectives of basic general education teachers, inrelation to the integral education and the existing materials in formal education. In a comparative analysis, we analyzed data obtained with similar training projects, which show the importance of working on social skills in children. The results determine parameters and requirements to develop didactic products that complement education, based on concepts of design, pedagogy, and didactics as knowledge-building tools.&#x0D; Keywords: Product Design, Teaching Material, Comprehensive Training, Social Skills.
FINANCIAL DEEPENING AND STOCK MARKET PERFORMANCE IN SELECTED SUB-SAHARA AFRICAN COUNTRIES

Purpose- The study investigates the effect of financial deepening on stock market performance in selected Sub-Saharan African countries by determining the relationship that exist between financial deepening and stock market performance. Expansion in the financial services to reach out to the underbanked or unbanked in our society enables these individuals to assess banking services, thereby boosting economic activities. Methodology- The study considers four selected countries in Sub-Saharan African over the period 2001 to 2019. Multiple regression analysis techniques were used with Seemingly Unrelated Regression (SUR) to analyse the data. SUR used in this analysis provides the lowest standard errors of the estimated parameters. Findings- Ordinary Least Square (OLS) gives consistent results. However, it is not as efficient as the SUR method, which amounts to feasible generalised least squares with a specific form of the variance matrix. It solves the problem of endogeneity. The study conducted Augmented Dicky Fuller (ADF) test, Hausman test, and Bruce Pagan test to avoid any challenges associated with data normality. Conclusion- The research finds out that broad money supply, a proxy for financial deepening, positively and statistically significantly impacted stock market performance in each of the four countries. It was recommended that all countries involved in this study and others implement policies that seek to enhance financial deepening in increasing broad money supply as a percentage of GDP. The increase in overall money supply allows for investment in productive sectors of the economy. Keywords: Sub-Saharan Africa, seemingly unrelated regression, Augmented Dicky Fuller, investigates, ordinary least squares. JEL Codes: E51, F21
Cinematheraphy dalam Islam

Cinematherapy is one of various techniques in therapy, but in this paper the researcher tries to combine cinematherapy techniques and the use of Islamic films in cinematherapy techniques. This study has a purpose, namely, to analyze the development of cinematherapy to help clients, and the lack of specific references that discuss cinematherapy in a religious context. Therefore, this research is here to try to contribute in the academic and social sciences in terms of counseling guidance so that it can contribute to the development of cinematherapy in Islam. The method used in this research is library research from the findings of journals that specifically discuss cinematherapy problems, namely 16 journals obtained through geoogle schoolar, garuda journals, sinta journals, and various searches found. The results of the study found that the cinematherapy technique has a high success rate in terms of general scientific fields but specifically the use of cinematherapy in Islam to overcome client problems has not been found. Therefore, researchers are trying to present Islamic values ​​in cinematherapy techniques as a form of scientific development in the form of cinematherapy as techniques and methods in overcoming client problems Keywords: therapy, film, cinematherapy, islam
DETECTION OF VPNS USING MACHINE LEARNING

The nature of the tools used by criminal actors to hide their identities has made it is very challenging to detect unauthorized users. Network security is any move an association makes to forestall vindictive use or coincidental harm to the organization's private information, its clients, or their gadgets. The objective of organization security is to keep the organization running and valid for every authentic client. Since there are such countless ways that an organization’s security can be compromised, network security includes a wide scope of rehearses. Most of normal assaults against networks are intended to acquire admittance to data, by keeping an eye on the correspondences and information of clients, rather than to harm the actual organization. However, assailants can do more than taking the information. They might have the option to harm clients' gadgets or control frameworks to acquire actual admittance to offices. This leaves the association's property and individuals in danger of damage. Network security extensively comprises of approaches, cycles and practices embraced to forestall, recognize and screen unapproved access, abuse, change, or disavowal of organization available assets. This work presents computational model that can detect the use of virtual private networks to gain unauthorized access
TO IMPLEMENT PARALLEL PERFORMANCE (PROCESSOR) IN DATA WAREHOUSE USING CLOUD COMPUTING SYSTEM

Databases today, irrespective of whether they are data warehouses, functioning data stores, or OLTP systems, enclose a huge volume of statistics. But, outcome and offering the correct statistics in an appropriate manner has to a challenge because of the huge amount of data complicated. Parallel performance is the competence that addresses this challenge. Cloud computing is developing of Parallel Performance (Processor) in Data warehouse. The development of cloud computing has made parallel processor derive into commons lives. Firstly, this paper develops the model of cloud computing and introduces two numerous traditional Parallel performance develops processing, When to Implement Parallel Performance or not and in-Memory Parallel Execution. The implementation of parallel performance has two levels. It has analysed and studied the principles, advantages and disadvantages of parallel performance develop processing. The results of this paper are intended to provide a reference for the development of parallel performance develops processing.
A MULTI-OBJECTIVE GWO BASED CLUSTERING APPROACH FOR EFFICIENT DOCUMENT MINING

Learning and data mining systems often use clustering. Such applications require efficient and fast clustering algorithms. However, clustering a dataset is often a difficult task, especially for complex datasets such as text classification. Clustering is a strategy of grouping data points based on their similarities. Data clustering can be done using any clustering algorithm. However, conventional partitioning clustering algorithms greatly depend on initial points and can drift towards inefficient clustering on improper initialization. Furthermore, these algorithms are less flexible for achieving multiple objectives required for clustering the complex overlapping classes. Therefore, in this work, we proposed a Gray Wolf Optimization (GWO) based multiobjective optimization algorithm for document clustering. GWO is a metaheuristic algorithm that works in the same way that grey wolves do when hunting prey. The proposed algorithm has the advantage of easily modifying clusters based on the objectives. The performance of the proposed algorithm on the Reuters-21578 dataset demonstrates that it outperforms k-means and affinity propagation algorithms.
DETECTION OF SKIN CANCER DISEASE USING DEEP LEARNING ALGORITHM

Early detection of melanoma skin cancer is important for a person effective treatment. Recently, it is well-known that the most dangerous type of skin cancer is other types of skin cancer.Melanoma because it may spread to other are asif you are not diagnosed and treated early. Non-invasive computer vision or medical imaging play an important role in the clinical identification of various diseases. Such techniques that provide an automatic image analysis tool for accurate measurement and quick wound testing. Steps involved in this. The study collects dermos copy image data, preliminary processing, division using threshold, mathematical element domain using Gray Level Cooccurrence Matrix (GLCM), Asymmetry, Border, Color, Scope, (ABCD) etc., feature selection using Principal section (PCA) ), to calculate the value Dermos copy Score then differentiate using Convocation neural network (CNN).the results show that the accuracy of the categories obtained is 92.1
A SURVEY ON SEMANTIC ANNOTATION TOOLS FOR KNOWLEDGE MANAGEMENT

Support for information and knowledge exchange is a key issue in the information society. To reduce the time wasted in searching and to reduce associated user frustration much more selective user access is needed. This is possible by semantic information processing of online documents.Knowledge management in an organisation are used for managing knowledge resources in order to facilitate access and reuse of knowledge.Semantic annotation is about assigning to the entities in the text, links to their semantic descriptions. This sort of metadata provides both class and instance information about the entities. Semantic annotation is applicable for any type of textweb pages, regular documents etc. For semantic annotation, there are various manual, semiautomatic and full automatic tools are developed by various organizations like mindswap.org, ontotext.org etc. In this paper, we are presenting analysis and review of some of these tools according to their applicability for an application domain in knowledge management.Our review and analysis may help the research community in selecting an appropriate tool for extracting the relevent and desired information from huge knowledge base of an organisation.