Reviewerly/exHarmony huggingface dataset:
Understanding the Data Management Plan as a Boundary Object through a Multi-stakeholder perspective

&#x0D; A three-phase Delphi study was used to investigate an emerging community for research data management in Norway and their understanding and application of data management plans (DMPs). The findings reveal visions of what the DMP should be as well as different practice approaches, yet the stakeholders present common goals. This paper discusses the different perspectives on the DMP by applying Star and Griesemerâ€™s theory of boundary objects (Star &amp; Griesemer, 1989). The debate on what the DMP is and the findings presented are relevant to all research communities currently implementing DMP procedures and requirements. The current discussions about DMPs tend to be distant from the active researchers and limited to the needs of funders and institutions rather than to the usefulness for researchers. By analysing the DMP as a boundary object, plastic and adaptable yet with a robust identity (Star &amp; Griesemer, 1989), and by translating between worlds where collaboration on data sharing can take place we expand the perspectives and include all stakeholders. An understanding of the DMP as a boundary object can shift the focus from shaping a DMP which fulfils fundersâ€™ requirements to enabling collaboration on data management and sharing across domains using standardised forms.&#x0D;
Limitations of Blockchain Technology with its Applications.

Block chain is also called as chain of blocks i.e. it is collection of technologies or collection of Technologies or a bit like a block chain sack of Logo From the sack y can collect different bricks and arrange them some particular way/different way to create a chain blocks .It is decentralized i.e. no any central control or authority assigned to it .It is simple. Easy to understand and work the system. New blocks are added at the end of the block chain .It uses data structure-link list-also called as linear data structure, stored at contiguous location in work on concept of pointers. They form a chain in continuous way using array ,doubly link list-pointers are used for fast and speedy execution ,it traverse in forward direction –move ahead, backward direction-move back, operations like addition &amp; deletion of node can be efficiently done
Perbandingan Kinerja Algoritma untuk Prediksi Penyakit Jantung dengan Teknik Data Mining

Heart disease is a disease that contributes to a relatively high mortality rate. The rate of human death caused by disease in the heart is a widespread problem in the world. The main objective of this study is to predict people with heart disease using the publicly available dataset in the UCI Repository with the Heart Disease dataset. To obtain the best classification algorithm is by comparing three Algoritma Naive Bayes, Random Forest, Neural Network algorithms, which are frequently used to predict people with heart disease. Comparison results show that Naive Bayes ' algorithm is a precise and accurate algorithm used to predict people with heart disease with a percentage of 83 %.
Cell Nuclei Detection and Segmentation for Computational Pathology Using Deep Learning

This work presents a deep learning model and image processing based processing flow to detect and segment nuclei from microscopy images. This work aims at isolating each nuclei by segmenting the boundary and detecting the geometric center of the nuclei. The deep learning model employs a multi-layer convolutional neural network based architecture to extract features from both spatial and color information and to generate a gray scaled image mask. Subsequent image processing steps smooth nuclei boundaries, isolate each individual nuclei and calculate the geometric center of the nuclei. The proposed work has been implemented and tested using H&E stained microscopy images containing seven different tissue samples. Experimental results demonstrated an average precision of 0.799, recall of 0.955, F-score of 0.86, and IoU of 0.835.
The Impact of Feature Selection Methods for Classifying Arabic Textual Data

Text classification is a vital process due to the large volume of electronic articles. One of the drawbacks of text classification is the high dimensionality of feature space. Scholars developed several algorithms to choose relevant features from article text such as Chi-square (x2), Information Gain (IG), and Correlation (CFS). These algorithms have been investigated widely for English text, while studies for Arabic text are still limited. In this paper, we investigated four well-known algorithms: Support Vector Machines (SVMs), Naïve Bayes (NB), K-Nearest Neighbors (KNN), and Decision Tree against benchmark Arabic textual datasets, called Saudi Press Agency (SPA) to evaluate the impact of feature selection methods. Using the WEKA tool, we have experimented the application of the four mentioned classification algorithms with and without feature selection algorithms. The results provided clear evidence that the three feature selection methods often improves classification accuracy by eliminating irrelevant features.
Hand Gesture Recognition for Deaf and Mute

Communication is the fundamental channel between individuals to speak with each other. In the world of communication gestures and signals is a great deal and a lot of research work has been done in the course of past decades. With the end goal to enhance the recognition rate of systems, numerous specialists have conveyed strategies, for example, HMM, Artificial Neural Networks, and Kinect stage. Effective algorithms for segmentation, classification, pattern matching, and recognition have evolved. Gesture-based communication is generally utilized by people with hearing disabilities to speak with one another helpfully utilizing hand motions. The system uses image processing technology and neural networking for the capturing and conversion of gestures. A number of python packages are used to process and generate the results. The application uses laptop webcam for capturing gestures and recognize gestures shown by the user. The application uses TensorFlow and Keras to generate the model for datasets. The gestures shown by the user are compared with stored gestures and the corresponding output is generated along with speech output. The application thus eliminates the communication barrier between hearing impaired-mute and normal people.
An Insight on Sentiment Analysis Research from Text using Deep Learning Methods

Nowadays, Deep Learning (DL) is a fast growing and most attractive research field in the area of image processing and natural language processing (NLP), which is being adopted across several sectors like medicine, agriculture, commerce and so many other areas as well. This is mainly because of the greater advantages in using DL like automatic feature extraction, capability to process more number of parameters and capacity to generate more accuracy in results. In this paper, we have examined the research works which have used the DL based Sentiment Analysis (SA) for the social network data. This paper provides the brief explanation about the SA, the necessities of the pre-processing of text, performance metrics and the roles of DL models in SA. The main focus of this paper is to explore how the DL algorithms can enhance the performance of SA than the traditional machine learning algorithms for text based analysis. Since DL models are more effective for NLP research, the text classification can be applied on the complex sentences in which there are two inverse emotions which produces the two different emotions about an event. Through this literature appraisal we conclude that by using the Convolutional Neural Network (CNN) technique we can obtain more accuracy than others. The paper also brings to the light that there is no major focus on mixed emotions by using DL methods, which eventually increases the scope for future researches.
Enhanced Security of Encrypted Text by KDMT: Key-Domain Maximization Technique

Encryption-decryption techniques have been the backbone of network security in the modern era of wireless transmission of data. We present here a more secured encryption-decryption method based on the maximization of key domain in finite field. The proposed technique uses a random primary key to fetch the encryption-decryption key-pair furnished by a unique decomposition. A secondary key taken from a subdomain with specific property is used to add more randomness in the encrypted text structure. A probabilistic comparison of key prediction by hacker is also discussed to justify the added security in the proposed method.
An Efficient AES Algorithm for IoT based Applications

With a massive growth in net communications, there is always a chance of risk to keep the data secret, reliability of data, additionally accessibility of data. An outcome for this is gift cryptographic methodologies which includes the superior Encryption trendy (AES), which might be at gift shield such information, are necessitated to be quick and well protected. In this report, we talk two novel techniques for adapting the foresaid trouble and it is being made potentially through enhancing the design of mix column manipulation of Advance Encryption Standard (AES). An improvement of 1.27 occasions transformed into completed in evaluation to earlier calculations in expressions of pace proficiency [1][2]. As far as hardware structural layout, a space discount of almost thrice change is additionally achieved. AES has input data blocks of 128 bits, with keys length of 128,192 or 256 bits. In this manuscript, a hardware representation of AES algorithm is described using key of length 128 bits. The AES hardware set up is realized using xilinx nexys 4 artix 7 –FPGA board with the help of xilinx ISE design suite. Our work focuses on MAES, a low power AES encryption algorithm which run over the interest [5]. In MAES, a S-Box of one dimension is suggested using new mathematical expression for creating a (n×n) matrix in affine transformation. The percentage efficiency of 18.35% is obtained by MAES than AES, when encrypted packets are transmitted. Thus MAES expends low power compared to that of AES, which is suitable for resource constraint environments.
The Effect of Face-to-Face and non-Face-to-Face Synchronously Collaborative Writing Environment on Student Engagement and Academic Performance

Collaborative Writing (CW) tools such as Google Docs provide an efficient way for students to perform collaborative writing tasks.This research is based on a novel CW tool called Cooperpad, with a group awareness functionality, which continuously gathers group members' writing behaviour, analyzes and visualize their engagement intensity for group members to compare their participation with that of others.The comparative experiment is carried out in two different online learning environments: face-to-face and non-face-to-face, with an experimental group (N = 72) and a control group (N = 48).Through systematic data and post-test design we have examined in which environment the students showed more engagement in the group-writing task.The results showed that Cooperpad writing system is more helpful to enhance the student engagement and improve students' academic performance on certain levels in face-to-face online learning environment compared with non-face-to-face.Moreover, the student engagement was positively correlated to the academic performance.Students have a high degree of the system, which has a positive promoting effect on learning initiative and teamwork ability.
Sentiment Mining of Product Opinion Data

Sentiment Analysis has gotten a focal point of consideration for the retrieving of web information and text corpora. At the point when we talk about sentiment analysis, it investigates the people's criticism or conclusion or audits in the wake of removing those reviews from various stages. While, when we find out about Sentiment Analysis, it recognizes the mining or analysis, which are communicated through content and afterward we investigate it. The fundamental goal of Sentiment Analysis is to reason feelings and ideas. In this paper the research work has done sentiment analysis on Amazon Reviews. The data set used is Amazon Reviews on Unlocked Mobile phones dataset of 413840 records. There are number of columns for the dataset like Product Name, Price, Rating, Brand Review text and the count of people for whom the review was helpful. But the research work has used on the Rating and Reviews columns. The research work has applied bag of words, tf-idf and n-grams techniques. It was found that n-gram with bag of words approach gave a maximum testing accuracy of 97% and AUCROC score of .967. Using deep learning approaches and their comparing with used ones is left as future work.
Unconstrained Handwritten Text Line Segmentation for Kannada Language

Segmentation is division of something into smaller parts and one of the Component of character recognition system. Separation of characters, words and lines are done in Segmentation from text documents. character recognition is a process which allows computers to recognize written or printed characters such as numbers or letters and to change them into a form that the computer can use. the accuracy of OCR system is done by taking the output of an OCR run for an image and comparing it to the original version of the same text. The main aim of this paper is to find out the various text line segmentations are Projection profiles, Weighted Bucket Method. Proposed method is horizontal projection profile and connected component method on Handwritten Kannada language. These methods are used for experimentation and finally comparing their accuracy and results.
Structural Anonymity For Privacy Protection In Social Network

the release of social networks in digital media has verified many benefits in our daily life, but the user privacy breach accompanies this intensification in popularity.Various methods has been used for publishing the social network data, the privacy preservation of the individuals in the data published has become a significant concern.Several works in relational data showed that the degree of privacy preservation does not depend on the size of the equivalence classes on quasi identifier attributes; it is determined by the number and distribution of distinct sensitive values associated with each equivalence class.To overcome the weakness in kanonymity, we will use l-diversity to achieve guarantees more substantial privacy preservation along with structural anonymity.The proposed algorithms use minimum edge addition techniques.The empirical study shows that our algorithm leads significantly to less number of edge modifications for anonymization of the social network data and has an extensively lower running time than the other algorithms previously proposed in the field.We will use more than one dataset in our experiments to declare differential datasets lead to a different result; Every dataset has its properties, which should be analyzed to select the best Anonymization method.
Professional and personal readiness of future teachers to implement inclusive education

This publication provides a detailed analysis of theoretical studies of professional and personal readiness of future teachers to implement inclusive education. Professional and personal readiness is understood as an integrative dynamic new formation of the future teacher, which ensures the development of the image of the Self and a professionally significant attitude to it, manifested in the pedagogical motivation to achieve success in professional positions in the implementation of inclusive education.
Infographic development of Blambangan Kingdom for history learning in senior high school

Teaching materials become an essential component of learning.History learning is often considered synonymous with boring material.The purpose of this study is to develop interesting teaching materials for the historical learning.The development of teaching materials used historical research data.The Blambangan Kingdom (1293-1772) was one of the important ancient kingdoms in East Java that needed to be taught in schools.The method of this study was research and development.The steps of research and development were literature study, product design, product specification, design validation, product manufacturing, initial product testing, product revision, extensive product testing, and dissemination.Infographic teaching materials become a solution for history learning.This study develops an infographic teaching materials with a focus on the discussion about the history of Blambangan Kingdom in senior high school.This infographic is up to date because it used an attractive cartoon figure, a concise explanation, and an additional QR code to enrich the information.The implementation of infographics on 35 respondents indicates that infographic teaching materials on the history of Blambangan Kingdom are effectively used in learning supported by material points, instructions for use and evaluation questions.
Actual problems for logistics management and strategies of supply chain in Georgia

In social-economic development strategy, logistics is considered as one of the priority direction to increase the competitiveness of the country. In order to adapt the flexibility of the supply chain, the companies should properly work and carry out such logistics strategy, which allows them to identify the influence of the expected changes and make organizational or functional amendments to ensure the reduction in logistics costs. The development of logistics system contributes the integration of Georgia in global economy space and strengthens its competitive positions on international logistics market. In the work, it’s been studied the potential of increasing the functional load of Georgian ports and the potential of establishing them as logistics centers, it’s been reviewed logistics role, as a vital sector in terms of global trade and as a continuous and uninterrupted delivery of goods during a crisis period of Covid-19 pandemic. Strategies for supply chain has been studied and evaluated by sectoral mark according to expertise, economic-statistical and analytical methods and it’s been defined the role of Georgia in global logistics network and the actuality of involvement in it.
Building 10th Grade Students’ Vocabulary through Reading the Newspaper at SMK 45 Lembang

&#x0D; Using newspaper either printed or online as a medium of English learning is a unique way to stimulate students’ interest in reading since most of the students at this age have dropped their interest in reading resulting their lack of English vocabulary. The researcher decided to use the newspaper as a medium to build students’ vocabulary. The researcher chose a group of participants from a group of 10th-grade students in SMK 45 Lembang, which are class XB and Class XE. The school gave these two classes as the samples because they believed each class has relatively equal knowledge and cognitive abilities. In this study, researchers randomly selected from the two classes to be used as a sample for the Control and Experimental Class. As a result, researchers found class XE as Control class and XB as the Experimental class. The study lasted for a full month, in which each class received different treatment. As a result, the Gain value of Experimental class is higher than the Control class. Moreover, based on the result of the data analysis with the Mann-Whitney U test method, it showed that there were significant differences in Students’ Vocabulary growth, between Control class and Experimental class. Based on the calculation of Non-parametric Mann- Whitney U test, the gain data between Experimental Class and Control Class show the value of Asymp Sig. (0.000), Zα (0.05) and the value of Z (4.847). Z α (1.96). Therefore, the researcher can conclude that the method of using newspaper as a teaching material has a positive impact on the absorption and growth in students’ vocabulary.&#x0D; Keywords: vocabulary achievement, reading, newspaper
Perception of Teachers on Implementation of CCE in the Upper Primary Schools of Delhi -NCR

Central Board of Secondary Education introduced Continuous and Comprehensive Evaluation in IndianSchool system, just to reduce the burden on the students (Examination) and move forward towards happy learning.Teachers are considered as pillars of Education system and ultimate agents in implementing the CCE system as they help in shaping pupils' personality and nurture good habits among them.The present study attempts to find out perception of teachers towards continuous and comprehensive evaluation.Samples of 100 school teachers were randomly selected from Delhi and Faridabad.Self-made Questionnaire consists of 10 items for teachers was prepared and distributed among them.The findings revealed that the perception of upper primary school teachers of Delhi is better than that of NCR towards CCE.
IAM Reference Architecture

This article provides a reference model to organize the presentation of technical details associated with various implementations of identity and access management (IAM) architectural concepts. The model is conceptual, as are the set of abstract components which it provides.To move out of the conceptual realm into specifics additional articles follow, each with a focus on a specific technical use-cases. Each such use-case indicates which of the abstract components comprise a particular implementation
A Wearable Brain-Computer Interface Instrument with Aug- Mented Reality-Based Interface for General Applications

In the project we are demonstrating the combined usage Augmented Reality(AR) and brain faced com- puter interface(BI) which can be used to control the robotic acurator by. This method is more simple and more user friendly. Here brainwave senor will work in its normal setting detecting alpha, beta, and gam- ma signals. These signals are decoded to detect eye movements. These are very limited on its own since the number of combinations possible to make higher and more complex task possible. Asa solution to this AR is integrated with the BCI application to make control interface more user friendly. This application can be used in many cases including many robotic and device controlling cases. Here we use BCI-AR to detect eye paralysis that can be archive by detecting eye lid movement of person by wearing head bend.
High-speed gesture modelling through boundary analysis of active signals from wearable data glove

Assistive technology utilises communication by means of gestures with high appreciation in the fields of rehabilitation engineering and security. The necessity for such technique is to extract the communications in terms of intentions from the disabled community. Such systems play a very crucial role during emergency as well as to perform regular communication during normal course of life. To interpret and communicate most distinctive requirements of the person with disability, the caregivers and medical support agents need a well- defined and distinguishable gesture paradigm with its recognition system. Conversion of such communicative gestures is to be made precise and easy. In this proposed work, the feature construction is made with a simple modelling of the gesture signals along the time zone considerations created during the gesture activity. The identification of most active channels for every subject involved in this experiment for different gestures contributes to reduction of complexity in processing and hardware cost.