Reviewerly/exHarmony huggingface dataset:
A Survey on Various Approaches used in Named Entity Recognition for Indian Languages

“Named Entity Recognition (NER)” is a application of Artificial Intelligence and “Natural Language Processing (NLP”).In NER, various classes of Named entity such as name of a person , an organization name, name of location, name of designation etc., are find out which is required in many NLP activities like question-answering system ,machine translation,  artificial intelligence, summarization of documents, academics, robotics, Bioinformatics etc. Mostly NER task was evident for foreign languages but for Indian constitutional languages, due to some challenges present for example scarcity of resources, ambiguity present in languages, morphologically rich behavior of languages etc. ,NER work has been done for few of languages. In our paper, we presented several challenges available in NER for Indian languages and compared them by measuring various standard evaluation metric values like precision, recall and F-measure. In future extension, we would develop a efficient system, which would be more accurate, and which will cater many more Named Entity tags than existing systems ,for Indian languages NER tools.S. No.LanguageMethod UsedPerformance Measure %1Hindi,Marathi, Gujarati, Bengali &TamilRule BasedF-Score:45.002MizoSVMRecall: 93.91Precision:95.32F-Score: 94.593AssameseCRF & Rule BasedF-Score: 93.224TeluguLexicon Lookup Dictionary And HMMRecall:84.35 Precision: 88.40F-score:  86.305ManipuriCRFs &RulesRecall:92.26 Precision:  94.27  F-score:93.306AssameseCRFs &Rules 7HindiBi-LSTM-CNN-CRFF-Score: 70.008Hindi-English & Tamil-EnglishGazetteer ListAverage values of  Recall:  11 Precision: 58  F-Score: 199MalayalamCRFF-Score: 92.3010Hindi-EnglishCRFs& LSTMF-Score: 95.0011TeluguNaive Bayes ClassifierF-Score: 88.8712GujaratiRule BasedF-Score: 70.0013KannadaBi-LSTMF-Score: 78.1014SindhiRule BasedF-Score: 98.7115HindiHMMF-Score: 97.14Comparative Study to Identify Named Entities In Various Indian Languages : Following table compares the standard values of measures of Precision, Recall and F-Score achieved by different authors to find named entities in various Indian languages.
EDUCATION IN THE PATTERNS OF DIGITAL CULTURE: THE INDIVIDUALITY OF THE DETERMINISTIC SUBJECT

The article presents the problem of formation and determination of the individuality of the subject included in the world of digital culture. The study focuses on educational practices as one of the key factors influencing human subjectivity. The methodological basis of this research is a critical analysis and a multidisciplinary approach. This made it possible to consider a person, his characteristics and the problems of his personality in the postmodern era, as well as to determine the features of the current educational paradigm by comparing modern and postmodern educational models. The active development of mass media and Internet communications in the second half of the XX century is considered one of the factors that contributed to the significant ontological, axiological and anthropological transformations of modern culture, and also became one of the key factors in the formation of digital culture. The category of homo digitalis is explained as a unique phenomenon of the XXI century, its analysis is presented from different positions, including the definition of negative trends: decline of reflection, banalization of the New, primitive subjectivism, laziness, inability and unwillingness of analytical and critical mental activity, psychological problems, deviant manifestations, pedagogical vicissitudes and conflicts based on confrontations between generations, etc. Rejecting logocentrism and a rigid evaluative position, the study made an attempt to overcome skepticism regarding the expansion of digitalization into the educational process in the context of the modern problem of the massive introduction of distance education caused by the pandemic. It is proposed not to stigmatize the problems of individuality, which are characteristic of modern culture, as completely controlled by manipulative technologies, especially in relation to educational practices.
What to Prioritize? Natural Language Processing for the Development of a Modern Bug Tracking Solution in Hardware Development

Managing large numbers of incoming bug reports and finding the most critical issues in hardware development is time consuming, but crucial in order to reduce development costs.In this paper, we present an approach to predict the time to fix, the risk and the complexity of debugging and resolution of a bug report using different supervised machine learning algorithms, namely Random Forest, Naive Bayes, SVM, MLP and XGBoost. Further, we investigate the effect of the application of active learning and we evaluate the impact of different text representation techniques, namely TF-IDF, Word2Vec, Universal Sentence Encoder and XLNet on the model's performance. The evaluation shows that a combination of text embeddings generated through the Universal Sentence Encoder and MLP as classifier outperforms all other methods, and is well suited to predict the risk and complexity of bug tickets.
Geographically weighted regression for compositional data: An application to the U.S. household income compositions

Author(s): Yoshida, Takahiro; Murakami, Daisuke; Seya, Hajime; Tsutsumida, Narumasa; Nakaya, Tomoki | Abstract: This study builds a bridge between the literatures for geographically weighted regression (GWR) and compositional data analysis (CoDA). GWR allows the modeling of spatial heterogeneity in regression models and is increasingly used in various fields. CoDA provides unique and useful tools for compositional data, which are restricted by a constant-sum constraint. Although compositional data are common in many scientific areas, it is not until recently that increasingly sophisticated statistical methods have been deeply investigated. Many types of spatial models based on geostatistics, spatial statistics, and spatial econometrics for compositional data have been proposed. However, there is less attention to both spatial heterogeneity and the constant-sum constraint. In this study, we propose a GWR model for compositional data. This allows us to model spatially varying relationships while considering the constant-sum constraint. We applied this model to analyze household income compositions at the county level in the US. The interpretational usefulness of the results of spatially varying compositional semi-elasticities is empirically performed.
Review of acoustically related design factors for three recent Los Angeles area music studios.

The design of a professional-quality music recording studios involves a specific set of challenges, namely the need to provide high levels of sound isolation, rigorous noise and vibration control for building support systems, and the provision of acoustically appropriate room finishes. The optimization of design solutions for each of these challenges depends upon project-specific requirements, including aesthetic objectives, base building constraints and the musical genres being recorded. This paper reviews how these challenges were successfully addressed in three recent Los Angeles area music recording/broadcast studio projects. Projects reviewed include a recording studio at University of California, Los Angeles, where challenges included the need to accommodate all musical genres, from jazz, to orchestra, to drum ensembles. The two other studios were both for broadcast organizations: KCRW, an influential NPR-affiliated music-orientated radio station and for the commercial radio broadcaster SiriusXM. The paper includes discussion of why and how various acoustical techniques were utilized, including use of "floating" construction and live room variable acoustics. Solutions for successfully incorporating significant areas of glazing into live rooms and accommodation of audiences are also discussed, along with the various acoustical room finishes that were applied.
Biometric Steganography Using MPV Technique

Biometric data, is prone to attacks and threats from cyber criminals to conduct identity theft, and its economic value makes it a product that can be traded in underground marketplaces such as the dark web. Securing it is the need of the hour. A steganographic approach is proposed as a solution to this. Biometrics are hidden inside other biometrics for safe storage and secure transmission. Steganography is a process of hiding data in a transmission medium. The main objectives while hiding data are its undetectability, robustness against image processing and other attacks, which steganography can easily achieve. This paper focuses on a process of hiding an image in another image by using mid position value(mpv) technique. Here we have to choose the secret biometric on which Arnold transform will be applied resulting in a scrambled version of the secret biometric. This will be embedded into the cover image resulting in a stego image. Lastly, the hidden secret biometric will be decoded from this stego image, which will first result in a scrambled secret biometric. Inverse Arnold Transform will be applied on this to finally result in the decoded secret biometric. The paper further explains the working and processes in detail.
ADAPTATION OF ANDROID AND DIGITAL APPLICATIONS IN EDUCATION

In education society learning is general with continuing digital revolution in education and business relationships. Main purpose of this review paper is to emerge early writing tools with new digital writing tools as computers , tablets and laptops introduce to android application which recognizes information through QR code in form of audio, video, text and etc. [2] since last few years smart phones and wireless internet connection has no ambiguity .  These technologies will introduce and improve interactivity, accessibility, and convenience in the learning process. Overall, these applications can be utilized as an inexpensive but potent tool that compliments the learning process. Useful devices like smart phones, tablets, and e-book readers connect users to the world instantly, have access to information and enabling interactivity with others. Applications that run on these devices let users not only consume but also discover and produce content.Mobile technology plays an important role in combination between advanced mobile technology and computer technology application. [4]. location based interactions  orWi-Fi identification  this shows the necessity of digital applications.The QR code was often positioned near or on the object label. On paper, this approach sounded simple, and many museums jumped on board with a positive outlook about the potential. Online approach for ticket booking for museum reduces paperwork and creates transparent system [3].Traditional classroom activities associated with “chalk and talk,” or “log in and lecture,” are now under siege, as teaching moves to a more open frame of delivery, where students engage with the materials before many classes begin, and lecturers are required to add value, by making a significant contribution to students’ understanding. It is very balancing and the need for value-added teaching and understanding that is challenging many of the existing teaching paradigms[5].
A survey on data stream analytics

With the exponential expansion of the interconnected world, we have large volume, variety and velocity of the data flowing through the systems. The dependencies on these systems have crossed the threshold of business value, and now such communications have started to be classified as essential systems. As such, these systems have become vital social infrastructure that needs all of prediction, monitoring, safe guard and immediate decision-making in case of threats. The key enabler is data stream analytics (DSA). In DSA, the key areas of stream processing constitute prediction and forecasting, classification, clustering, mining frequent patterns and finding frequent item sets (FISs), detecting concept drift, building synopsis structures to answer standing and ad hoc queries, sampling and loadshedding in the case of bursts of data and processing data streams emanating from a very large number of interconnected devices typical for Internet-of-Things (IoT). The processing complexity is impacted by the multidimensionality of the stream data objects, building `forgetting&apos; as a key construct in the processing, leveraging the time-series aspect to aid the processing and so on. In this chapter, we explore some of the aforementioned areas and provide a survey in each of these selected areas. We also provide a survey on the data stream processing systems (DSPSs) and frameworks that are being adopted by the industry at large.
Aplikasi Android Pendeteksi Kerusakan Kulit Wajah Menggunakan Metode 2D Gabor Wavelet dan Gray Level Co-Occurrence

Damage that occurs in the skin can be identified by looking at the texture and color of the skin surface. Symptoms that occur when you experience skin damage are changes that occur on the surface of the skin, such as the appearance of small red bumps on the face, red spots, rough skin texture and others. This is certainly very disturbing, besides affecting the appearance, especially if it occurs on the skin on the face, it can also give pain such as acne. In order to find out the type of skin damage experienced on the face, the author created an application that can detect the type of facial skin damage experienced. This application uses the 2D Gabor Wavelet filter method and the Gray-Level Co-Occurrence Matrix (GLCM). 2D Gabor Wavelet method is used for image extraction based on edge characteristics on skin damage images. Meanwhile, the Gray-Level Co-Occurrence Matrix (GLCM) method is used for the extraction of facial images based on the texture characteristics of skin damage / disease. Classification of the type of skin damage / disease using the K-NN algorithm.The test results in this application obtained the level of accuracy of each type of skin damage and normal skin is pustules 64.5%, papule 57.8%, nodule 76.8% and normal 70.6%. The accuracy results obtained from testing using the Receiver Operating Characteristic (ROC) algorithm by utilizing the area under curve (AUC).Keywords: Gray-Level Co-Occurrence Matrix (GLCM), 2D Gabor Wavelet, Facial Skin Damage , K-NN.
Quantum Cursed Fingerprinting (QCF): A Technique to embed Zero-Knowledge Proof in Quantum Fingerprinting technique

Quantum communication has shown astonishingly fast development taking the advantage of quantum computation power that is being developed by technology giants like IBM, Google. The security issues and communication gaps caused by these quantum computers must be curled by the quantum computing methods. There are situations where the security of data is of less concern than knowing the fact “whether the data is tempered or not”. The Fingerprinting technique provides such knowledge by creating fingerprints of such important data and keeping the record of the temperament of data. Quantum Fingerprinting (QF) follows a procedure of creation of fingerprints of data and uses a referee which tells whether the fingerprint strings match or not. In a dilemmatic situation of fingerprinting, compromising either with security or speed, the paper focuses on achieving the removal of the referee and adding some security. This paper uses the power of Zero-Knowledge Proof (ZKP) to improve security as well as removes the use of referees in QF. The Zero Knowledge Proof is a protocol by which one party can prove to another party that they know the value “X”, without conveying any information apart from the fact that they are deemed to know “X”. Thus, embedding the curse of Zero-Knowledge Protocol to quantum fingerprinting gives Quantum Cursed Fingerprinting (QCF) the power of security and removal of the referee to match the fingerprints.
Efficient ciphertext-policy attribute-based signcryption for secure big data storage in cloud

This chapter proposes an efficient ciphertext-policy attribute-based signcryption (ECP-ABSC) for big data storage in the cloud. The ECP-ABSC scheme reduces the required number of exponentiation operations during signcryption and outsources the inflated pairing computation during the designcryption process, which, in turn, reduces the computation overhead of data owner and user. Our scheme also provides flexible access control by giving data access rights to unlimited times or a fixed number of times based on the user. This flexible access control feature increases the applicability in commercial applications. Further, we prove the desired security requirements of our scheme that include data confidentiality, signcryptor privacy, and unforgeability in security analysis. The feasibility and practicality of our scheme are provided in performance evaluation.
Впровадження інновацій в освітньо-корекційну роботу в групах для дітей з порушенням мови

Reforming education and introducing new standards of educational quality into preschool education, requirements for compulsory learning outcomes and the formation of preschooler competence requires teachers to radically change the vector of educational efforts. Therefore, the main tool of new education is an innovative activity which consists in introducing qualitatively new elements into the educational process.Innovations are especially relevant in the formation of competencies of a child with a speech disorder. Because the educational-correctional process requires a creative search for new or improved classical approaches to education, significant changes in the content, forms and methods of correction, training, education. Therefore, the search and implementation of innovations has become an integral part of our work.
Perfect Reconciliation in Quantum Key Distribution with Order-Two Frames

We present an error reconciliation method for Quantum Key Distribution (QKD) that corrects 100% of errors generated in regular binary frames transmitted over a noisy quantum channel regardless of the quantum channel error rate. In a previous investigation, we introduced a novel distillation QKD algorithm whose secret key rate descends linearly with respect to the channel error rate. Now, as the main achievement of this work, we demonstrate an improved algorithm capable of retaining almost all the secret information enclosed in the regular binary frames. Remarkably, this technique increases quadratically the secret key rate as a function of the double matching detection events and doubly quadratically in the number of the quantum pulses. Furthermore, this reconciliation method opens up the opportunity to use less attenuated quantum pulses, would allow greater QKD distances at drastically increased secret key rate. Since our method can be implemented as a software update, we hope that quantum key distribution technology would be fast deployed over global data networks in the quantum era.
Cryptographic Scheme for Lightweight Device Such as IoT using Pseudo Stream Cipher and Trigonometric Technique with Key Generation

The Internet of Things (IoT) being a promising innovation of things to come and is required to associate billions of gadgets. Web of things (IoT) gadgets have been generally utilized, and Electronic correspondence is expanded quickly. The expanded number of correspondence is required to create piles of information and the security of information can be a danger. Information gathered by the IoT gadgets and the information which IoT gadget send might be the portal for an assailant to break client security. To guarantee secure correspondence between IoT centers and central point(server), a cryptographic plan for lightweight gadgets is proposed. In this plan, we make utilize pseudo stream cipher with key generation for rearranging key synchronization and improving security.. The common verification, secret key for meeting synchronization and refreshing secret key for session are finished by trading scrambled messages. Likewise, the key length and update cycle for mystery key for meeting are adaptable as indicated by application. Keys are created from mystery key for meeting for improving the security. We contrasted the plan's security and execution and some lightweight plans. As indicated by the investigation, the proposed plan can give greater security includes low overhead of correspondence which is correct for IoT Node with restricted resource and power. Encryption and decoding is finished utilizing trigonometric ideas and by utilizing the idea of stream figure. Trigonometric ideas are lightweight and improve the security up by an extraordinary degree by diminishing the odds of cryptanalysis. When contrasted with different calculations like Hill figure, RC4, RSA and Present(Lightweight square figure) and so forth, the proposed calculation gives better execution
A tecnologia como ferramenta na saúde mental dos profissionais de saúde no contexto da pandemia por coronavírus

Coronavirus (CoV) is a family of viruses, first identified in the 1960s. Due to its high transmissibility, it was not long before the outbreak in Hubei province, China, became a pandemic, which has been reflected in a substantial amount of infections and deaths. Therefore, digital technologies needed to be implemented in the reality of health professionals as a way to resolve viral contagion. The objective of this research was to carry out an integrative review with emphasis on digital technology as a tool used in the mental health of health professionals involved in the context of the coronavirus pandemic. In this review, the PVO strategy was used. The bibliographic survey was carried out in two databases and two virtual libraries: ScienceDirect, PubMed, Scientific Electronic Library Online and Virtual Library. Data collection was performed in five steps, to systematize the search and selection of collected articles it was necessary to use the recommendation of Preferred Reporting Items for Systematic Reviews and Meta Analyzes. The main results showed that digital technologies were presented as allies in the mental health of health professionals involved in the context of the pandemic. Based on the data presented, it is suggested that more studies be developed dealing with the subject, in view of the lack of research and the transition period experienced in the current context, in which many technologies are still in the process of development.
Review Web Data Analysis using Naive Bayes Algorithm

The convergence of computing and communication has resulted in an information-based civilization. However, the majority of the information is in its most basic form: data. If data is defined as facts that have been recorded, then information is the set of patterns or expectations that exist beneath the data. Databases contain a vast amount of data that is potentially useful but has yet to be discovered or expressed. It is our mission to bring it to fruition. The extraction of implicit, previously unknown, and possibly beneficial information from data is known as data mining.The objective is to create computer algorithms that automatically comb through databases looking for regularities or patterns. If strong patterns are discovered, they will most likely generalise so that reliable predictions may be made on future data. Naturally, there will be issues. Many of the patterns will be dull and mundane. Others will be fictitious, based on chance coincidences in the dataset. The technical foundation for data mining is machine learning. It's used to extract information from databases' raw data—information that's written in a readable format and can be used for a variety of reasons. The process incorporates abstraction, which entails taking the data as-is and inferring whatever structure lies underlying it. This book covers the machine learning tools and techniques that are used in real data mining to uncover and describe structural patterns in data.