Reviewerly/exHarmony huggingface dataset:
An improved RSA image encryption algorithm using 1-D logistic map

The need to have a more secured ways of protecting sensitive images in this modern age of technology has become necessary for ensuring that such images sent via the insecure public network called the Internet are protected from attacks. To this end, various image encryption algorithms have been proposed by many researchers and RSA image encryption algorithm is one of them. Studies on RSA image encryption algorithm reveal that some images when encrypted using the algorithm, gives encrypted images that do expose some features of the plain images on visual inspection no matter the size of primes used. This is due to the fact that digital images have high redundancy and high correlation of image data that make RSA algorithm image dependent. Cryptanalysis has been a major source of concern (in particular the brute-force attack) when designing a cryptosystem since it is assumed that the cryptanalyst knows exactly the design and working of the cryptosystem under study except the secret key. Thus, making the secret key access much more difficult to the cryptanalyst makes the encryption algorithm a more reliable one. In view of these, an improved RSA image encryption algorithm using 1-D logistic map was proposed. The proposed scheme has two stages. In the first stage, the plain-image is shuffled using the chaotic properties of the map and in the second stage; the shuffled image is encryption using the RSA algorithm. The proposed algorithm and the RSA algorithm were tested on two standard test gray scale images: cameraman.tif and clock.tif using four different set of keys. Security analysis such as histogram analysis and correlation coefficient analysis were also carried out on the results obtained from the two methods. The results of the analysis show that the proposed scheme is more secured and stronger against the brute-force attack ( encrypted image which does not reveals any hint about the plain image to the attacker and also its key space has double: the two primes, initial condition and control parameter) than the RSA image encryption scheme.
Histology and embryology teaching virtualization during the COVID-19 pandemic

Introduction: The Covid-19 disease is a globally spreading pandemic with serious consequences. The Universidad Nacional de Córdoba like all universities of Argentina ordered the suspension of face-to-face education and developed a teaching-learning process focused on a virtual environment that would allow compliance with mandatory isolation and at the same time continue with the dictation of the contents in their schools. Objective: The aim of this work was to obtain and analyze information regarding the conditions of technological access and e-competences with which the students developed the virtual activities for morphological sciences learning in the current context of covid-19 pandemic. Materials and methods: A cross-sectional and descriptive study of the data obtained of anonymous and voluntary survey among students course of Histology and Embryology A was carried out. Facultad de Odontología. Universidad Nacional de Córdoba. Results:95.7% of the students had the necessary technological devices and 49.3% considered themselves digitally proficient and 37.9% beginners. Only 26.4% of the students required help for the use of technology. Conclusion: The analysis of successes and difficulties with which we go through the teaching of morphological sciences in pandemic will allow creating a reflection space for us to be better prepared for the challenges of a post-pandemic education and promoting new teaching-learning forms that combine and integrate elements of the face-to-face class and virtual learning thus contributingto improving the future health professional’s university education
The Effectiveness of using Spreadsheet Learning Media to Increase Student Learning Outcomes at SMAN 1 Sumbawa Besar

A good learning process must begin with planning in advance. in the learning process it must be done as attractively as possible so that students are motivated and enthusiastic to learn, The transition from the conventional learning process to digital learning provides a significant change, while the purpose of the study is to determine the extent to which the implementation and effectiveness of using spreadsheet learning media in improving student learning outcomes and to find out how much increase in student learning outcomes after learning using spreadsheet learning media. The type of research used is a mixed method with an experimental approach. The data collection technique used is a survey technique, with interview instruments, questionnaires and documentation. from the significance of the table that is 0.05. So that the pretest and posttest value data are normally distributed. To determine the difference in the results of the pretest and posttest, it was continued with a paired sample T test using the SPSS version 22.0 program with a calculated significance value of 0.000 and to see the effectiveness of using spreadsheet learning media, a statistical test was carried out using the N Gain score test. The results of the study found that the use of spreadsheet learning media was effective in improving learning outcomes with a percent N-Gain score of 47% which was in the medium category (quite effective).
Educational Service Platform and English Corpus Design Based on Embedded Intelligent System and Cloud Computing

Corpus has important application value in English teaching, which can provide a new way for English teaching, help to improve the quality of English teaching, and play its role in the cultivation of students’ English literacy. This study proposes the educational service platform based on embedded intelligent systems and cloud computing to analyze the practical teaching application measures of English corpus. The traditional translation assistance system has the problem of unbalanced frequency distribution of some markers, which can be solved by the embedded intelligent system and cloud computing service. According to the comparison results, the designed educational service platform is obviously superior to the traditional teaching assistance system, the frequency distribution of the annotated words in the corpus is uniform, the translation efficiency is high, and the translation accuracy is accurate. This paper helps students’ learning to avoid the solidification of students’ thinking mode of language learning, which makes learning more flexible and improves learning efficiency. This research will highlight the dominant position of students in the English teaching classroom, truly implement the concept of quality education into teaching practice, and promote the sound development of English teaching.
Supplemental Material: Petrogenesis of arsenic and platinum-group minerals from a partially serpentinized dunite in East Dover, Vermont, USA

&lt;p&gt;Table S1: Major element X-ray fluorescence whole-rock geochemical analyses in weight percent. Table S2: Trace element X-ray fluorescence whole-rock geochemical analyses in parts per million. Table S3: Electron microprobe analyses of olivine from meta-dunite in East Dover Vermont. Table S4: Electron microprobe analyses of chrome spinel from East Dover, Vermont, in weight percent. Table S5: Electron microprobe analyses of sulfide minerals from meta-dunite in East Dover, Vermont, in weight percent. Table S6: Coordinates of key sample localities.&lt;/p&gt;
Blockchain Based Hybrid Framework for Identity Management in Healthcare

Healthcare systems face numerous impediments due to the unavailability of proper mechanisms to track the transactions related to patient’s medical records. The maintenance and privacy of patient records are one of the key requirements of the healthcare system. Blockchain can be the potential solution to these problems. Blockchains have made a tremendous impact ever since their invention barely a decade ago. This paper delves into how blockchain can be used to solve the problem of patient record management by constructing scalable decentralised key systems with inbuilt sharing of credentials in a safe, secure, and digitally verifiable way. The work presents a hybrid scalable system capable of managing personal identity in a decentralized manner with no dependence on central authorities along with a rapid and simplistic way of exchanging claims among the users. The system overcomes potentially all problems associated with SOVRIN and blockchains in general by splitting itself into two symbiotic versions, one centralised and the other, decentralised.
A Neural Probabilistic Graphical Model for Learning and Decision Making in Evolving Structured Environments

A difficult and open problem in artificial intelligence is the development of agents that can operate in complex environments which change over time. The present communication introduces the formal notions, the architecture, and the training algorithm of a machine capable of learning and decision-making in evolving structured environments. These environments are defined as sets of evolving relations among evolving entities. The proposed machine relies on a probabilistic graphical model whose time-dependent latent variables undergo a Markov assumption. The likelihood of such variables given the structured environment is estimated via a probabilistic variant of the recursive neural network.
IoT Based Verified and Public Vehicle Registration through BlockChain: Future Smart Cities based Applications with Sustainable Approach

Blockchain technology replaces centralized applications with distributed computing. Modern economy is estimated by the place of motor transport in the infrastructure of the national economy. An automobile registration system is a unified information system. This information system takes care of every information about automobile registration. It is administrated by a national registry entity and has access to other government and non-government services that handle automobile information. Cyber Physical System (CPS) is defined as the combination of computation and physical process. It is mainly used in the ICT section. It is also focused on resolving the problems related to authors of the data regarding transparency, media, and storage problems by technical handling. The presented chapter uses all the above concepts in one place and integrates them to build a useful application. The presented frame allows car manufacturers, owners, repairing companies, and insurance agencies to register and add new car entries through a simple method. In addition, database technology has been leveraged to cache intermediate data. It efficiently uses the Industrial IoT and 5G technologies. Many researchers have called for rules and applications to draw old maps based on distributed applications into the blockchain. New protocols are available in this work for the International Automated Vehicle Management System, called DriveLoop, which were proposed and developed.
An Improved Graph Neural Network Method Using Relative Position Information for Session-based Recommendation

Session-based recommendation mainly solves the recommendation problem in the anonymous scene, which is a challenging task. In recent years, most methods based on graph neural network (GNN) have ignore the location information of neighboring items. So we propose a graph aggregation method that introduces relative location information to capture this information. Specifically, we use two methods to learn item embedding, the location graph aggregation method is mainly used to capture the location relationship information between neighbors, and common graph aggregation method is mainly used to capture higher-order relationship information between items. Finally, we construct a session recommendation model and demonstrate the effectiveness of the proposed method on three datasets.
Text modality enhanced based deep hashing for multi-label cross-modal retrieval

In the past few years, due to the strong feature learning capability of deep neural networks, deep cross-modal hashing (DCMHs) has made considerable progress. However, there exist two problems in most DCMHs methods: (1) most extisting DCMHs methods utilize single labels to calculate the semantic similarity of instances, which overlooks the fact that, in the field of cross-modal retrieval, most benchmark datasets as well as practical applications have multiple labels. Therefore, single labels based DCMHs methods cannot accurately calculate the semantic similarity of instances and may decrease the performance of the learned DCMHs models. (2) Most DCMHs models are built on the image-text modalities, nevertheless, as the initial feature space of the text modality is quite sparse, the learned hash projection function based on these sparse features for the text modality is too weak to map the original text into robust hash codes. To solve these two problems, in this paper, we propose a text modality enhanced based deep hashing for multi-label cross-modal retrieval (TMEDH) method. TMEDH firstly defines a multi-label based semantic similarity calculation formula to accurately compute the semantic similarity of cross-modal instances. Secondly, TMEDH introduces a text modality enhanced module to compensate the sparse features of the text modality by fuse the multi-label information into the features of the text. Extensive ablation experiments as well as comparative experiments on two cross-modal retrieval datasets demonstrate that our proposed TMEDH method achieves state-of-the-art performance.
SUPPORT VECTOR MACHINE BERBASIS CHI SQUARE UNTUK PREDIKSI HARGA BERAS ECER KABUPATEN POHUWATO

One of the staple foods for most Indonesians is rice. Rice is one of the staple foods most consumed by the people of Indonesia, the need for rice is also increasing, considering the very large and scattered population of Indonesia. The ups and downs of rice prices also have an impact on farmers because of their large production. The solution to dealing with uncertain changes in the retail price of rice is to predict prices. One way to find out the estimated retail price of rice is to make predictions using the Support Vector Machine algorithm using Chi Square. The results of the experiments that have been carried out, the prediction of rice prices has been successfully carried out. The smallest error rate in the Support Vector Machine algorithm model is RMSE 733,061. Then the proposed model approaches the value of perfection, because the comparison of the experimental results of rice price predictions produces an average accuracy value of 95.82%. Thus, the proposed method is declared successful.
Flipbook-Based Digital E-book Learning Media on Mechanical Wave Materials to Practice Critical Thinking Skills

The research aimed to know the validity, practicality, and effectiveness of e-book learning media on learning to train students' higher-order thinking skills. The research method used is the type of quantitative research. The research was carried out by giving a pretest, then being treated, and then a posttest. The subjects of this study were students of class XI Saince 2 Senior High School NU 1 Gresik. Data collection techniques using pretest-posttest and questionnaires. Data analysis used validity test, Cronbach alpha reliability test, and t-test. The results of the research that have been processed and analyzed can be concluded that the flipbook-based e-book learning media has an average validation value of 85.066%, categorized as very valid. Learning media has a practicality value of 85.067%, included in the very practical category. The questionnaire is classified as accurate because of the importance of rcount &gt; rtable and is categorized as reliable because it has an alpha value of 0.869. Through the t-test, the significance value of 0.000 is less than 0.05, meaning there is a significant effect in giving treatment. Therefore, the research can be concluded that the flipbook-based digital e-book learning media obtains a valid category, is suitable for use, and trains students' critical thinking skills.
Development of 3D ELSA (3D E-Book Based on Scientific Literacy) on Temperature and Heat

ELSA 3D (E-Book 3D Based on Scientific Literacy) is an e-book teaching material that integrates scientific literacy as a medium in the learning process on temperature and heat materials. This type of development research uses the Hannafin and Peck model. The Hannafin and Peck model begins with a needs analysis followed by the design and development stage to create 3D ELSA media which expert lecturers then review. The 3D ELSA that has been reviewed and revised is then validated using a validation sheet to determine the validity of the 3D ELSA media covering several aspects. Then the implementation is carried out by conducting a learning process using 3D ELSA media to test the effectiveness and practicality of 3D ELSA media. Quantitative descriptive analysis was used as the method of analysis. Based on the results of the research that has been done, it can be concluded that the 3D ELSA that has been developed has a validity percentage of 93%, the response of students to the 3D ELSA is 96.3%, and the observation of learning implementation is 96.6%. So that the 3D ELSA is declared to be very valid and suitable to be used as a medium in the learning process on temperature and heat material. In addition, 3D ELSA is included in the medium category with an N-gain of 0.68, so using 3D ELSA as a learning medium is declared effective because it can improve scientific literacy skills.
Is Eye-Tracking a Feasible Interaction Paradigm for Large Displays in the Sterile Field?

Abstract The paper describes how eye-tracking can be used to explore electronic patient records (EPR) in a sterile environment. As an information display, we used a system that we developed for the presentation of patient data and for supporting surgical hand disinfection. The eye-tracking was performed using the Tobii Eye Tracker 4C, and the connection between the eye-tracker and the HTML website was realized using the Tobii EyeX Chrome Extension. Interactions with the EPR are triggered by fixations of icons. The interaction was working as intended, but test persons reported a high mental load while using the system.
Early detection of cyber-bullying from twitter data

The vast volume of user created data in social media has created a wide-open path to data analytics in terms of extraction of features, analysis of polarity of information and classification of human emotional state. Sentiment analysis and data mining has reached at its peak in terms of its use in feature extraction and commercial analysis of products. Enormous approaches have been also seen in human behaviour analysis using ML (Machine Learning) algorithms and NLP (Natural Language Processing). To be very specific, it is not too hard to analyse data in granular level such as aspects. Social media play a distinct role in providing large dataset at no cost. And aspect-based sentiment analysis provides us the text analysis technique that categorisesuser provided data and assigns positive or negative value for the sentiment identified in it. In our approach we have tried to find out a solution of detection of cyber bullying in human interaction. This problem, we find a new threat in this digital era as commenting and replying to that comment play an important role in virtual communication, and just in this point, it takes no cost or hesitation factor to attack another person verbally or virtually.
Keller: Indian Sign Language based Gesture to Text and Speech Assistant for Covid-19 Protective Quotes

Communication promotes the flow of information between the people of different cultures present all over the world. As a result, it is critical that whatever one wishes to communicate with another is readily comprehended. The world is a place for people with a variety of abilities not just cultural differences. Differently abled people, who are unable to orally convey their thoughts and ideas find it challenging to communicate. This communication barrier has resulted in lack of self-development and social inequity among people with disabilities, especially the deaf-mute population. This article focuses on bridging this communication gap using a sensor-based, user-friendly, real-time solution based on Indian Sign Language (ISL) gestures. Furthermore New Education Policy, July 2020 has standardized Indian Sign Language (ISL) as a common language to interact, understand and simplify day to day communication for deaf-dumb community. The proposed method primarily focuses on ISL gestures, which are used to communicate about the current covid-19 pandemic situation and necessary precautions to combat the further spread of the covid19 infection.
PERANCANGAN IT BALANCED SCORECARD DI PERGURUAN TINGGI

The implementation of the MEA competition in the field of higher education is undeniably very closely related to the industrial revolution 4.0 where all teaching and learning process systems no longer use traditional systems but require the practice of using advanced IT technology (Information Technology). The study took the object of the UNISLA private university in Lamongan, emphasizing a qualitative case study approach to see how the implementation of IT components became a Balanced scorecard strategy at UNISLA. There are several strategic goals in implementing the IT balanced scorecard at UNISLA, among others (financial perspective: cost efficiency and profit oriented, customer perspective: increasing the satisfaction of UNISLA users including students, lecturers, and education staff, internal business perspective: developing the use of IT as a the main foundation in UNISLA business processes, learning and growth perspectives: evaluation of IT improvement in UNISLA and improvement of UNISLA users' skills.) From the explanation above we can conclude that why the application of IT in the Balanced Scorecard is so important to be applied as a support in the industrial revolution 4.0.
The Khalimsky Line Topology- Countability and Connectedness

The concepts of connectedness and countability in digital image processing are used for establishing boundaries of objects and components of regions in an image. The purpose of this paper is to investigate some notions of connectedness and countability of Khalimsky line topology.