Reviewerly/exHarmony huggingface dataset:
"Narrative-based human–artificial collaboration: A reflection on narratives as a framework for enhancing human–machine social relations"

This paper aims to reflect on human-artificial intelligence (AI) collaboration in cultural production and depicts the collective socio-cultural imaginary focusing on humans' intrinsic vulnerabilities related to AI systems, which are often perceived as a way of reshaping human presence within contemporary society.Abandoning an anthropocentric perspective, contemporary ecosystems should include non-human and AI systems.Our hypothesis states that their interactions could be reshaped by adopting a narrative framework.Since humans are social animals, if the power of stories is used for embracing plurality', sociality can be extended to include AI systems.Considering such premises, relationships between humans and AI may also enrich existing relational ecosystems with new meanings that challenge and redefine the limits of what is considered socially acceptable.The result is an integration of narrative tools and world building practice within interaction design processes.Storytelling can be intended as a mindset and a tool, underlying the crucial role of narratives in supporting the emotional dialogue among humans and AI systems, creating an overall sense of belonging between human and non-human actors.
A New Method for Modifying Blowfish Algorithm for IoT

Due to rapid development of internet and web applications, the prominence and the importance of the information exchange using the internet is growing. Communication through internet faces data safety as an important issue. Data has to be safe when communicating as slightly loss or danger to transmitted data can be responsible for excessive harm to the society. For network safety encryption plays a vibrant part. Many times it is little bit confusing to choose best encryption, as there are many cryptography methods for securing the data during transmission. For many applications Blowfish is currently assumed to be insecure. So it turns out to be essential to enhance this procedure through addition of different levels of safety so that it can be used in several reliable communication channels. Blowfish algorithm is modified in a way that it is platform independent; however the present encryption schemes are restricted to platform dependent proposal. This proposed modified blowfish algorithm supports text, images and media files.
Sentiment Scoring and Performance Metrics Examination of Various Supervised Classifiers

Sentiment Analysis probes public opinion on user generated content on Web like blogs, social media or e-commerce websites. The results of Sentiment Analysis are getting much attention with marketers that they are able to evaluate the success of an advertising campaign or the attitude of people on a new product launch. Business owners and advertising companies are using Sentiment Analysis to start new business strategies and to identify opportunities for new product development. In this paper, with R programming, the tweets from Twitter about Samsung Galaxy mobile phone and Apple Iphone were retrieved from three countries namely USA, UK and India for creating the dataset. The collected tweets were classified into positive, negative and neutral sentiments. The machine learning classifier algorithms like Naïve Bayes, Support Vector Machine, Random Forest, Decision Tree, Artificial Neural Network, XGBoost with K Fold cross validation were applied on the dataset and the results were tabulated for comparing and estimating which classifier algorithm yields the best accuracy. Other performance metric values like F Score, Precision, Recall were also calculated for comparison of various classifier performances on Sentiment Analysis. It was found that XGBoost method combined with K Fold cross validation has produced the best accuracy in prediction. We have also applied SentiStrength algorithm to find out the intensity or the strength of positive and negative comments from each sentence. With the help of the results in hand, we were able to predict the brand of mobile phone that was preferred in each country.
Predicting Student’s Campus Placement Probability using Binary Logistic Regression

Understudies trying to precise instructions for the most part chose instructive establishment with a notable popularity inside the primary settings. Many of those establishments several instances reputation controlled through bundles of compensation presented with the aid of the complainant for his understudies. In this putting it's far appropriate to explore and distinguish variables which could have an effect on the composition of the reason replacement special education .The threat within the State of Andhra Pradesh which has a excessive grouping established order of a unique training became appointed as research region. A careful survey of writing ends in a diagnosed proof of six determinants of speculative state of affairs inside the alternative special motive training.A arbitrary eg MBA alternative function information 250 is assembled from various organizations and located parallel relapse version became suited for the six signs for assessing information possibilities for placing alternative purpose. Assessed Results show that the possibility of putting in a simple exam is inspired by using 4 signs: CGPA, Specializes in PG, UG and Specialization in Gender.
Correction to: Personalized Multimorbidity Management for Patients with Type 2 Diabetes Using Reinforcement Learning of Electronic Health Records

A correction to this paper has been published: https://doi.org/10.1007/s40265-021-01484-3
MFCC using Speech Recognition in Computer Applications for Deaf

Speech Recognition has lately evolved as a beneficial computer technology involving various interactive speech based applications in this domain. For communicating with one another, speech forms the basic foundation. Utilizing this way of communication in the technology domain, the technique of speech recognition is formulated. This technique considers the input speech in order to extract significant information thereby drawing accurate decision related to the concerned text. Here the research proposes a technique by effectively incorporating speech recognition approach for handling web portal via voice (be it from any place or time) for accessing data. Advent and growth in technology has led to formation of STT (speech–to–text) conversion model which generates a text format of the speech that’s beneficial for the Deaf individuals and in other realms too. Data mining has achieved great success in examining the acoustic features related to sound and speech. The existing research employs the MFCC (Mel Frequency Cepstrum Coefficients) for extracting acoustic features of a voice that is identifying the gender of a given voice. Following are the stages in the system proposed: 1. speech preprocessing, 2. feature extraction, 3. converting to text4. Classification5. Displaying the web portal and 6. Storing the web portal. The research depicts speech recognition and analysis as a speech process. The STT (speech to text) model includes two levels, first being the document level and second is the sentence level. The proposed system is beneficial for the deaf individuals for accessing the data be it from any place or time and in other realms too. The system yields in great accuracy in the given time span.
Guidance-based improved depth upsampling with better initial estimate

Like optical images, depth images are also gaining popularity because of its use in many applications like robot navigation, augmented reality, 3DTV and more. The commercially available depth cameras generate depth images which suffer from low spatial resolution, corrupted with noise, and missing regions. Such images need to be super-resolved, denoised and inpainted before using them to have better accuracy. Super-resolution (SR) techniques can be used to produce a high-resolution output. Since SR is an ill-posed inverse problem, a good initial estimate is always a good regulariser to find the optimal solution. We propose an initial estimate as part of our SR pipeline, esp. ×8, which will helps in quick convergence and accurate output. We propose a cascade approach by combining residual interpolation (RI) method with anisotropic total generalised variation (ATGV) method, both uses HR guidance image. The improvements are shown qualitative and quantitative with different levels of noise.
Critical Connection of Blockchain Development Platforms

Blockchain has gained immense popularity with success of Bitcoin. Blockchain is no longer just limited to financial sector but it has expanded its horizons far beyond it. Today innumerous Blockchain Applications are being developed and so have Blockchain Development Platforms advanced. Blockchain still being a naive technology there is excellent scope for further research in Blockchain. With these advancements, new Blockchain Development Platforms are being introduced and existing ones are rapidly modifying its features. This paper aims at comparing existing popular Blockchain Development platforms in detail with help of certain parameters to provide an aide to Blockchain Developers to choose an appropriate platform for Blockchain Development.
Security in Cloud Health Care

Cloud computing plays vital role in various services to the users. The application of cloud computing includes usage in business, media transmission, banking, health care, military application, insurance, wireless communication, etc. One such application using Cloud computing is health care. The patient health history is very significant for diagnostic analysis and decision making process. The healthcare data processing and communication technology (HDCT) is building a constant and secured health care data processing and sharing Electronic Health Services (EHS) are regularly utilized by the needy, specialists, and social insurance experts to diminish medical service cost and give productive human services forms health-cloud preserves the character-particular sensitive information for numerous purposes including biomedical research, medical health insurance groups, clinical statistics analysis, and many others. The various types of attacks and detection approaches in the healthcare have been reviewed in this work. It brings out the fact that the Electronic Health Data Record (EHDR) should be processed and transmitted in a secured and confidential environment while increasing accuracy and efficiency based on various algorithms such as machine learning.
Music Computer Technologies in the System of Contemporary Musical Education: A Research in the Field of Terminology

Abstract. Music computer technologies is an independent section of modern information technology, the software and hardware complex of which allows performing operations with sound, creating and editing music material, forming and improving the music and educational process. The development of a methodology for mastering this toolkit, as well as the developing researchers’ international interaction, pose a problem for pedagogy to develop and use a unified terminological apparatus that most accurately and fully characterizes this phenomenon. The article proposed by the authors aims to identify opportunities for generalizing terminological developments that exist in this area in various research and pedagogical schools and traditions.
Deep Learning-Based Emotion-Sensitive Learning Cognitive State Analysis

The cognitive state of a student is unique and exciting.The current developments in deep learning gives an unparalleled chance to analysts to assess the cognitive state.But most of the existing cognitive state strategies centre around attention, overlooking the importance of emotions in humans.Human feelings play a huge role in the computer vision industry and numerous researches are performed with its assistance.Hence, our aim is to propose a cognitive state investigation system which is emotion sensitive.It will consequently assess the students' attention based on head posture and emotion recognized from the face detection in an unobtrusive way.The system presented is an implementation of multiple tasks learning cascaded with a convolutional neural network (CNN), introduced for detecting expression, locating landmarks, and estimating head pose all at a time.The expression detection and landmark location help in alignment of the face.The estimation of head pose and face alignment are further used to evaluate the leaner's attention.Exploratory outcomes show that this technique can obtain students' emotion with an accuracy of 94%.
An Improved Spectral Feature Alignment for Domain Adaptation in Sentiment Classification

The problem of sentiment classification is extremely sensitive to the variation of domain, thus the sentiment classification model trained in one domain is often not applicable to the data from another domain. This paper proposes an improved spectral feature alignment domain adaptation algorithm (ISFA). ISFA extracts domain-independent words by term frequency and mutual information. Based on word co-occurrence relation, the bipartite graph between domain-independent words and domain-specific words is initially constructed. Then revision of sentiment dictionary is introduced to obtain a more accurate bipartite graph. In this graph, feature representation is obtained by utilizing spectral clustering dimension reduction. Besides, a new feature representation is obtained by combination updating for GBDT training. In this paper, 20 groups of experiments show that the accuracy of ISFA is 3.4% higher than that of SFA on average, which proves that ISFA is capable of finding out the feature space that makes the distribution of the two domains much closer.
Histopathological Image Classification Scheme for Breast Tissues to Detect Mitosis

Histopathological images are widely utilized by the pathologists to determine the severity of the cancer. Usually, the pathologists analyse histopathological images manually, which demands more time and effort. The quality of image interpretation can be improvised with the help of a computerized assisting system for image analysis. This idea enhances the accuracy of the system as the computerized system helps in making decisions, which the pathologist may recheck. Understanding the benefits, this article presents a histopathological image classification scheme meant for breast tissues in detecting the mitotic cells. The goal is achieved by preprocessing the image by performing top and bottom hat transformation followed by stain normalization. The nuclei are then located with the help of Localized Active Contour Model (LACM) combined with Lion Optimization (LO) algorithm. The shape, statistical and texture features are extorted from the areas of interest and the differentiation of mitotic cells from the nonmitotic ones is performed by Support Vector Machine (SVM) classifier. The work efficiency is tested with respect to the standard performance measures such as accuracy, sensitivity, specificity and time consumption.
PENERAPAN MODEL PEMBELAJARAN KONTEKSTUAL UNTUK MENINGKATKAN HASIL BELAJAR MATEMATIKA

This research was motivated by the low of mathematics learning result in 5th grade students in SD Negeri 4 Kaliuntu. The low of mathematics learning result was caused by the low understanding of the students in the subject materials presented by the teacher. In the delivery of materials, teachers did not use learning models with a scientific approach that caused students to appear less active in learning activities. The purpose of this research was to enhance the result of mathematics learning result in 5th grade students in SD Negeri 4 Kaliuntu. The kind of this research was a classroom action research wich was conducted in two cycles. Each cycle had stages including of action planning, implementation, observation, and reflection. This research used contextual teaching learning model. The results showed that there was an increase in student learning result in each cycle. Before the research was conducted, the average of students’mathematics score that taken from the first semester was 67.98. In the first cycle could be seen that there was an increase in student learning result with the average score is 78.42 and 92% classical completeness percentage. The target of research in the first cycle hadn’t reached so that the research was continued into second cycle. In the implementation of the second cycle, the deficiencies that existed in the first cycle was fixed so that the average score of students' mathematics learning result increased to 82.94 with 100% classical completeness percentage. This indicate that the target of the research has been achieved in second cycle. The average of student learning result based on the PAP is in the high category so it can be concluded that the use of contextual teahing learning model can improve the learning outcomes of 5th grade students of SD Negeri 4 Kaliuntu Year 2017/2018. Key Word: CTL, Mathematics Learning Result
Efficient Notes Generation through Information Extraction

For a specific topic we find several reference books and textbooks to refer and the content is much more than one needs, therefore at the time of revision or quick study we need the summary and short version of the whole content for revision, especially at the time of examinations. There we expect to build up a semi-mechanized method to produce notes from English content records like Reference Books and Text books. The method talked about is viewed as a spearheading endeavor in the field of NLP (Natural Language Processing).This strategy has a wide scope in the instructive space. The procedure when executed as an application can be utilized by both employees and understudies.
Lightweight Certificate less Signcryption Scheme Based on Elliptic Curve

As of late, many new signcryption techniques are executed on elliptic cryptosystem (ECC) to lessen the calculation loads for devices with low computation requirements. This essential requirement has motivated the authors to present an efficient Signcryption scheme based on elliptic curve cryptography. The proposed system encompasses all the primary security parameters viz., confidentiality, authentication, integrity, unforgeability, non-repudiation and forward secrecy making the method widely accepted in several resource constrained applications.
Challenges in using a Standard Speech Recognition Engine in Small Vocabulary Domain

This paper discusses the challenges and proposes recommendations on using a standard speech recognition engine for a small vocabulary Air Traffic Controller Pilot communication domain. With the given challenges in transcribing the Air Traffic Communication due to the inherent radio issues in cockpit and the con-troller room, gathering the corpus for training the speech recognition model is another important problem. Taking advantage of the maturity of today’s speech recognition systems for the standard English words used in the communication, this paper focusses on the challenges in decoding the domain specific named entity words used in the communication.
Pengembangan Bahan Ajar Menulis Cerpen dengan Media Storyboard pada Siswa Kelas X SMA

This study was conducted with the aims of (1) developing teaching materials to write short with storyboard media on high school students; (2) make a lesson plan of writing short story with storyboard media at grade X of high school students; (3) implementation of writing short story with storyboard media at rade X of high school students; (4) knowing the effectiveness of teaching materials in writing short story by using storyboard media at grade X of high school students. This study need a development research method adapted from the Borg and Gall development model with 10 stages beginning with needs analysis, planning, initial product development, initial product revision, product trial, product revision, small field trial, revision product, operational field test (large group), final product revision, and product dissemination and implementation. Based on the data analysis, it was concluded that the teaching materials to write short story with the developed storyboard media was considered feasible and effective to be used as teaching materials for Bahasa Indonesia at Grade X of high school students.
Comparative Study of LBPH and Haar features in Real Time Recognition Under Varying Light Intensities

Face recognition is a commonly used biometric and has a wide range of applications. We used an access control system that integrates face recognition technology. This paper discusses two algorithms that have been used in the face detection, Haar features and Local Binary Patterns Histogram (LBPH). The experimental set up is done in an open environment using OpenCV library. Comparative study has been made between these two algorithms based on parameters like illumination and hit rate. For the testing, the same training set and samples were used.
Watermarking Schemes for High Security with Applications and Attacks: Research Challenges and Open Issues

Recently, the growth of the internet is increased day by day also the digital data such as videos, images and audio availability to the public get increased rapidly. The society required intellectual property protection. To protect the media from other attack intruders and avoid business loss is the requirement of digital media produced. Introducing watermarks can be useful to safeguard copyright. In this review an effort is made to explore various aspects of watermarking, algorithms used, and to carry out a comparative study of these techniques based on their classifications.
Interactive extracurricular activities “Language – the highest value of culture” as a preparation for the students’ final certification

The purpose of the study is to identify the prerequisites and conditions for the formation of students’ value ideas in the field of cultural and socio-political sphere; to help language teachers in preparing students for understanding the Russian language as a spiritual essence – a fundamental element of their native culture; expand and deepen students’ knowledge of Russian as a national value, which has a huge intellectual, spiritual, moral, cultural potential for personal development; about the features of the scientific style/sub-styles. In preparing the article, the following research methods were used: interpretation of methodological experience in line with culture-oriented teaching of the Russian language, ascertaining experiment, diagnostics of knowledge of axiological problems, analysis of tasks and topics of essays proposed to graduates in the Basic State Examination and the Unified State Examination; methodological development of interactive classes of extracurricular activities. The article presents: 1) diagnostic material aimed at identifying students’ knowledge and perceptions of the basic category of axiology “value”; 2) the scenario for extracurricular activities “The Russian language is the highest value of the native culture”; 3) the text „Language – the highest value of culture”; 4) examples of culturally oriented tasks that allow graduates to prepare for final certification. The materials of the classes can be used in introductory lessons of the Russian language, when organizing a week of the Russian language, events dedicated to the Day of Knowledge, the founder of the Russian literary language A. S. Pushkin, etc.