Reviewerly/exHarmony huggingface dataset:
Property Registration Framework using Ethereum Blockchain

The land is an immovable property.Tracing the details of property and involvement of third-party is the challenging task.Fraudulent may forge documents and mislead the purchaser and if it's a litigate land it takes many years in the court battle, waste of time and resource.Problems escalate in this current land registration process which is non-transparent.Such demands made to integrate technologies and lead to the blooming of blockchain technology.Blockchain is a decentralized and transparent ledger.The smart contract is the confirmable and permanent document between two parties.This proposed framework is used to develop a registration application system in which new purchaser has to register and continue with the further process.The proposed research work is implemented using SHA256 algorithm which provides unique hash values for the messages getting stored in blocks and ethereum blockchain technology is used to store both smart contract and transaction details.
Host and Environmental Factors that Influence Plasmodium knowlesi Malaria Infection in Humans: A Systematic Review

Introduction: Plasmodium knowlesi (P.knowlesi) is a zoonotic malaria parasite, transmitted between non-human primate hosts by the Anopheles (An.) mosquitos, and causing spill-over infections in humans where the parasite, vector, host, and human converge.&#x0D; Methods: The search was done electronically to explore for appropriate papers via PubMed, and Science Direct for articles published up to March 2020, containing the words “factors associated” or “environmental factors” or “individual factors” or “ecological factors” and “P.knowlesi” and “human” including synonyms and Medical Subject Heading (MeSH) terms. A total of 27 articles from PubMed Databases and 18 articles from Science Direct were selected to be assessed for eligibility. Out of it, a total of 13 articles were selected to be analysed.&#x0D; Results: Host factors such as sex and age, as well as occupation as individual factors, while environmental factors such as rainfall and geographic elevation have some association with P.knowlesi infection in humans. This zoonotic malaria poses unique challenges that will need to be addressed if all forms of malaria are to be eliminated based on the sustainable development goal (SDG).&#x0D; Conclusion: This article highlights the importance of disease ecologies such as climate and landscape and human-environment interactions such as the land use patterns, such as agriculture or infrastructure activities) to reduce the further increase of cases and mortality globally due to P.knowlesi infection. This review focuses mainly on the host and environmental factors that influence P.knowlesi Malaria Infection in Humans.
Artificial Intelligence based Credit Card Fraud Identification using Fusion Method

Increase of online transactions has given a greater scope for increasing of credit card frauds. In this work we develop a general framework with Artificial Intelligence based Hadoop. Also that fuses multiple detection algorithms to improve accuracy, reliability. Further to support large amount of transactions storage. The workflow satisfies the design ideas of current credit card fraud identification systems. The verification process for all the transactions is implemented. If incoming transaction that passed through trained model with low probability then it is rejected.
Students’ Speaking Ability Awareness: A Qualitative Study at Zawiyah English Club Iain Langsa

The aim of this research is to analyze how the speaking class at Zawiyah English Club can improve the students’ speaking ability awareness. In conducting the study, this study used qualitative method with phenomenology approach. The total number of samples is 10 students who joined in Zawiyah English Club IAIN Langsa. The procedure of the collecting data or instrument used in this study with interviewed and observation method. The results of this research were successful in analyzing how the speaking class at Zawiyah English Club can improve the students’ speaking ability awareness. Conducting a monastic class program held in every Thursday regularly and when they are doing activities together, they keep trying to use English and everyone in the environment motivates each other. They feel aware to speak English and they always improve their skills eah other. They feel when they study, they are not under pressure. They also tend to prefer practicing speaking in the speaking classes held at Zawiyah English Club than regular classes in lectures. Then, all of the students stated that they believe they can improve their speaking ability because Zawiyah English Club could increase their awareness and confidence in speaking.
Using Pyspark Environment for Solving a Big Data Problem: Searching for Supersymmetric Particles

Supersymmetry theory predicts that every particle in the standard model has a superpartner particle with a different mass. The Classification Problem of Supersymmetric Particles in High-Energy represents a major challenge for physicists. This paper aims to resolve the Big data Classification Problem in the area of Supersymmetric Particles using the Apache Spark Environment with the "MLlib" library. This contribution attempts to explore the performance of Machine Learning methods in the context of large data such as a "Susy" dataset, collected from the UCI Machine Learning repository. In this work, the performance is measured using three metrics: Accuracy, Area Under Curve (AUC), and training Computation Time (CT). The results are promising and show that the Gradient Boosted Tree (GBT) classifier achieves a high accuracy score (79%). While the Logistic Regression (LR) algorithm realizes a well AUC score (86%).
A secured best data centre selection in cloud computing using encryption technique

In this work, we have proposed an approach for providing very high security to the cloud system. Our proposed method comprises of three phases namely authentication phase, cloud data centre selection phase and user related service agreement phase. For the purpose of accessing data from the cloud server, we will need a secure authentication key. In the authentication phase, the user authentication is verified and gets the key then encrypts the file using blowfish algorithm. Before encryption the input data is divided into column-wisely with the help of pattern matching approach. In the approach, the encryption and decryption processes are carried out by employing the blowfish algorithm. We can optimally select the cloud data centre to store the data; here the position is optimally selected with the help of bat algorithm. In the final phase, the user service agreement is verified. The implementation will be done by cloud sim simulator.
Ab Initio Calculations of Dissociation Energy of Water Molecule on Near-Term Quantum Devices Using the Pennylane Interface to Quantum Hardware

&lt;br&gt;&lt;br&gt;Fault-tolerant quantum computers may be far off, however solving real world quantum chemistry problems on near-term quantum devices is possible through the Pennylane which provides interface to use any of the quantum hardware provided by any of the quantum hardware providers such as IBM, Google or Microsoft. A demonstrated use of Pennylane to solve real world quantum chemical problems on near-term quantum devices is shown. Ab initio quantum chemical calculations of dissociation energy of water molecule on the near-term quantum hardware using the Pennylane interface yielded a dissociation energy comparable to experiment and therefore it is recommended that the quantum chemistry community use near-term quantum devices to leverage quantum computing advantage to solve quantum chemical problems.&lt;br&gt;&lt;br&gt;
Amrita-CEN-Senti-DB:Twitter Dataset for Sentimental Analysis and Application of Classical Machine Learning and Deep Learning

&lt;p&gt;&lt;b&gt;Social media is a platform in which tons and tons of text are generated each and every day. The data is so large that cannot be easily understood, so this has paved a path to a new field in the information technology which is natural language processing. In this paper, the text data which is used for the classification is tweets that determines the state of the person according of the sentiments which is positive, negative and neutral. Emotions are the way of expression of the person’s feelings which has a high influence on the decision making tasks. Here we have proposed the text representation, Term Frequency Inverse Document Frequency (tfidf), Keras embedding along with the machine learning and deep learning algorithms for the purpose of the classification of the sentiments, out of which Logistics Regression machine learning based methods out performs well when the features is taken in the limited amount as the features increases Support Vector Machine (SVM) which is also one of the machine learning algorithm out performs well making a benchmark accuracy for this dataset as the 75.8%. For the research purpose the dataset has been made publically available.&lt;/b&gt;&lt;b&gt;&lt;/b&gt;&lt;/p&gt;
An Accurate Handwritten Digits Recognition system Based on DWT and FCT

In this paper an accurate Indian handwritten digits recognition system isproposed. The system used three proposed method for extracting the most effectingfeatures to represent the characteristic of each digit. Discrete Wavelet Transform(DWT) at level one and Fast Cosine Transform (FCT) is used for features extractionfrom the thinned image. Besides that, the system used a standard database which isADBase database for evaluation. The extracted features were classified with KNearestNeighbor (KNN) classifier based on cityblock distance function and theexperimental results show that the proposed system achieved 98.2% recognitionrate.
Ontology Based Web Page Recommendation System

The emerging web page development requires semantic applications with customized administrations. The proposed methodology presents a customized suggestion framework, which makes utilization of item representations and also client profiles created based on ontology. The domain ontology helps the recommender to improve the personalization: from one perspective, client’s interests are displayed in an increasingly powerful and precise route by applying an area based derivative technique; on the other side, the stemmer algorithm derived content- based filtering approach, gives an evaluation of resemblance among a thing and a client, upgraded by applying a semantic likeliness strategy. Recommender frameworks and web personalize were assumed by Web usage mining as a critical job. The proposed strategy is s successful framework dependent on ontology and web usage mining. Extricating highlights from web reports and building applicable ideas is the initial step of the methodology. At that point manufacture metaphysics for the site exploit the ideas and huge terms separated from reports. As per the semantic similitude of web archives to bunch them into various semantic topics, the distinctive subjects suggest diverse inclinations. The proposed methodology incorporates semantic information into Web Usage Mining and personalization process
The Netherlands: From the first science information officers to the Dutch Research Agenda

Science communication efforts in the Netherlands started with exhibitions in national history museums in the 19th century and popular articles about science and technology in the media in the 1930s.From the 1950s onwards, the Dutch government stimulated popularisation of science and technology as a way to foster the science-society relationship.Democratic, and later economic and cultural considerations were the reasons for setting up oneway and two-way science communication.This may explain why attitudes towards science and technology have largely been positive compared to most other European countries, but at the same time not all new technologies are accepted.Genetic modification is an example of a topic that raised a lot of debate in the 1990s; today, opposing views on vaccination show that acceptance of science and technology is not straightforward in the Netherlands.Science communication efforts are visible in many ways in Dutch society via organisations, events and activities.These are supported or organised by both private and public partners.Nowadays, Dutch researchers are increasingly stimulated to engage with society-for instance, via the Dutch Research Agenda.Science communication in the Netherlands can build on a rich variety of expertise and inputs.
Investigation and comparative analysis of data mining techniques for the prediction of crop yield

Crop yield is affected by climatic, management, geographical, biological and other such factors. Data mining techniques can be used to analyse the effect of these factors on crop yield and to predict crop yield based on these factors. The current paper focuses on the sequence of steps to be followed in data mining process for prediction of crop yield - starting from the determination of research goals to the application of the data mining techniques to build a model. The study applies the defined data mining process to build a model for the prediction of paddy yield based on different climatic factors. The current research also provides an insight to the different metrics that can be used to evaluate various supervised data mining techniques. The metrics have been divided into three categories - threshold evaluation metrics, numerical evaluation metric, and built time and size metrics. Comparative analysis of five supervised data mining techniques has been carried out on the basis of their performance in these three categories of metrics.
On Parallel Performance Practices: Some Observations on Personalizing DMIs as Percussionists

Digital musical instrument (DMI) design and performance is primarily practiced by those with backgrounds in music technology and human-computer interaction.Research on these topics is rarely led by performers, much less by those without backgrounds in technology.In this study, we explore DMI design and performance from the perspective of a singular community of classically-trained percussionists.We use a practiced-based methodology informed by our skillset as percussionists to study how instrumental skills and sensibilities can be incorporated into the personalization of, and performance with, DMIs.We introduced a simple and adaptable digital musical instrument, built using the Arduino Uno, that individuals (percussionists) could personalize and extend in order to improvise, compose and create music (études).Our analysis maps parallel percussion practices emerging from the resultant DMI compositions and performances by examining the functionality of each Arduino instrument through the lens of material-oriented and communication-oriented approaches to interactivity.
Female labor force participation in the Middle East and North African Countries: constraints and levers

&#x0D; &#x0D; &#x0D; Despite the importance of the subject, few researches have attempted to explain the female labor force participation (FLFP) in MENA region. This research tries to exploring the geopolitical, social, ethnic and economic levers or constraints that facilitate or bloc women’s access to the labor market. A quantitative approach based on data analysis was performed through the review of the World Bank statistics related to women participation in the labor market in MENA region. Data analysis revealed that the studied labor market was marked by an overall positive progress of the presence of female workers. However, this evolution is still considered very low and slow in comparison with world standards. The research also revealed huge disparities in the level of progress of the FLFP among the studied countries. The disparities observed were interpreted in correlation with the religious, economic, political, social and cultural aspects.&#x0D; &#x0D; &#x0D;
Secure Electronic Voting using Block Chain and Homomorphic Encryption

Blockchain is the technology that has attracted enormous interest recently as it provides security and privacy through immutable distributed ledger. It is the backbone of the most popular cryptocurrency, bitcoin. Due to its robust consensus mechanism and tamper proof data storage, it is widely adopted in the applications where trust is given utmost importance.Homomorphic Encryption algorithms can be used to operate on the data that is encrypted without the knowledge of private key. Operations can be performed on encrypted data without decrypting the data. Only client knows about the private key. These two technologies can be used to securely transfer and store data in the cloud systems.In this paper we propose how this blockchain technology and homomorphic encryption can be used to build reliable, tamper-proof and efficient electronic voting system. An electronic voting system should be secure, and itshould not allow duplicate votes and be fully tamper proof, while protecting the privacy of the voters. In this work, we have designed, implemented and tested an electronic voting application and providing hashing for votes and stored in blockchaincloud.If data in database is lost, then it can be retrieved from blockchain cloud.
An Integrated Technique for Face Sketch Recognition Using DCNN

Face Recognition (FR) is considered as one of the chief use in the investigation of criminals. In the majority of the cases, information about the criminal is not available. In such situations, sketch artist draw the sketch of the guess with the oral
Rule Based Morphological Variation Removable Stemming Algorithm

Sentiment analysis is a technique to analyze the people opinion, attitude, sentiment and emotion towards any particular object. Sentiment analysis has the following steps to predict the opinion of a review sentences. The steps are preprocessing, feature selection, classification and sentiment prediction. Preprocessing is the main important step and it consists of many techniques. They are Stop word Removal, punctuation removal, conversion of numbers to number names. Stemming is another important preprocessing technique which is used to transform the words in text into their grammatical root form and is mainly used to improve the retrieval of the information from the internet. It is applied mainly to get strengthen the retrieval of the information. Many morphological languages have immense amount of morphological deviation in the words. It triggered vast challenges. Many algorithms exist with different techniques and has several drawbacks. The aim of this paper is to propose a rule based stemmer that is a truncating stemmer. The new stemming mechanism in this paper has brought about many morphological changes. The new rule based morphological variation removable stemming algorithm is better than the existing other algorithms such as New Porter, Paice/Lovins and Lancaster stemming algorithm.
Image encryption techniques for data transmission in networks: a survey

Recently, there is a need to concentrate more on protecting the information that is stored in computers from attackers due to the rapid growth of internet users. In this scenario, the issues of privacy, integrity, productivity, confidentiality and authenticity of images have become a significant issue for storage and communication of images. The encryption method is the best way towards maintaining the safety of transmitted data by transforming the information into an inconceivable form. Many image-based encryption methods have been proposed by various researchers in the past for protecting the information or data by providing the security from unauthorised users. This study discusses, analyses and identifies the issues from the previous encryption methods. This paper discusses the various encryption methods and reviews related works for each scheme. Finally, this study discusses the purpose of this image encryption technique in the future.
Random Forest: A Hybrid Implementation for Sarcasm Detection in Public Opinion Mining

Modelling the sentiment with context is one of the most important part in Sentiment analysis. There are various classifiers which helps in detecting and classifying it. Detection of sentiment with consideration of sarcasm would make it more accurate. But detection of sarcasm in people review is a challenging task and it may lead to wrong decision making or classification if not detected. This paper uses Decision Tree and Random forest classifiers and compares the performance of both. Here we consider the random forest as hybrid decision tree classifier. We propose that performance of random forest classifier is better than any other normal decision tree classifier with appropriate reasoning.
The Concept and Competitiveness of Agile Organization in the Fourth Industrial Revolution’s Drift

The corporate competitiveness is constantly being shaped by the Fourth Industrial Revolution, the explosive development of technology, the globalization and the hyper-competition. The VUCA status has now become a permanent reality: volatility and complexity cannot be traced to traditional corporate operations. The Industry 4.0 projects a physical, a digital and a biological megatrend such as advanced robotics, artificial intelligence, new materials, personalized healing, self-driving cars. The usage of the resources and the knowledge sharing, the global economy is experiencing mutations such as the sharing economy, the peer to peer economy, the gig economy in the labor market and the bigdata in planning. Meanwhile, the disruptive innovations are transforming industries and gaining exponentially competitive advantage. The special business concepts were born and whom cannot be handled by models of classic macro and micro economics: the largest taxi company in the world does not own any taxis (Uber), the largest accommodation company does not own any property (Airbnb), the largest telecommunication company has no infrastructure (Skype), the world's most valuable retailer has no inventory (Alibaba), the most popular media doesn't create its own content (Facebook), the world's largest cinema doesn't have its own movie (Netflix). In the meantime, those are treasuring huge profits, business influence and information capital. The competitiveness of their agile way of working can be proved. These calls for changes not only in the market, but also in organizational and individual terms. An adaptive corporate structure and leadership, a self-organizing group, an agile working method hold the companies in the direction of growing track and changes in the future.
Text Classification on the Instagram Caption Using Support Vector Machine

Instagram is one of the world’s top ten most popular social networks. Instagram is the most popular social networking platform in the United States, India, and Brazil, with over 1 billion monthly active users. Each of these countries has more than 91 million Instagram users. The number of Instagram users shows the various reasons and goals for them to play this social media. Social Media Marketing does not escape being one of the purposes of using Instagram, with benefits to place a market for their products. Using text classification to categorize Instagram captions into organized groups, namely fashion, food &amp; beverage, technology, health &amp; beauty, lifestyle &amp; travel, this paper is expected to help people know the current trends on Instagram. The Support Vector Machine algorithm in this research is used in 66171 post captions to classify trending on Instagram. The TF-IDF (Term Frequency times Inverse Document Frequency) method and percentage variations were used for data separation in this study. This study result indicates that the use of SVM with a percentage ratio 70% of dataset for training and 30% of dataset for testing produces a higher level of accuracy compared to the others.