Reviewerly/exHarmony huggingface dataset:
Automatic Sarcasm Detection with Textual and Acoustic Data

This paper takes focus on the area of automatic sarcasm detection. Automatic sarcasm detection is crucial due to the needs of sentimental analysis. The rapid development of automatic speech recognition and text mining and the large amount of voice and text data opens a broader way for researchers to open new method and improves the accuracy of automatic sarcasm detection. We observe approaches that have been used to detect sarcasm, kind of data and its features including the rises of context to improve the accuracy of automatic sarcasm detection. We found that some context cannot be reliable without the presence of other context and some approaches are very dependent on the dataset. Twitter is being used by researchers as the main mine for sentimental analysis, we notice that at some aspect it still has a flaw because it is dependent to some Twitter’s special feature that will not be found in other usual text data like hashtags and author history. Besides that, we see that the small amount of research about automatic sarcasm detection through acoustic data and its correlation with textual data could make a new opportunity in the area of sarcasm detection in speech. From acoustic data, we could get both acoustic features and textual features. Sarcasm detection with voice has the potential to get higher accuracy since it can be extracted into two data types. By describing each beneficial method, this paper could be a brief way to sarcasm detection through acoustic and textual data.
The Extrovert and Introvert Students’ in Speaking Ability of English Department at IAIN Langsa

This research investigates about Extrovert and Introvert students in speaking ability of English Department at IAIN Langsa. Extrovert personality has characteristic interest in the external object and more friendly. Introvert are people that hold all of from external happenings, and dislike of large social. The aim of study investigated about whether significant difference between Extrovert and introvert students in speaking ability. The research method of study used qualitative method with descriptive research. The subject of research consisted 10 students who are 3 extrovert students and 7 introvert students. the instrument that used in this research was observation and interview. Based on the result of research students with extrovert type more active, friendly, and responsively in speaking class. Based on the observation and interview result students’ extrovert they more enjoyed in speaking class and brave to give comments or speak in class meeting. They were type personality who are preferring to practice speaking and share their opinions more often. While, students of their introverted personality are more silent, they only speak as necessary. The introvert students do not more to express themselves and they were afraid to share their opinions. It can be concluded that students extrovert personality more active in speaking ability and their interest in speaking class.
Audiovisual Pills as a Tool for Training and Professional Preparation

The social and cultural context after the COVID-19 pandemic is on many levels very different from the previous context. Studies carried out during 2020 and 2021 point to an unprecedented increase in the use of social media. This research delves into this new paradigm to take advantage of it in the teaching and learning of university studies of communication, studying in particular audiovisual pills and their possibilities. The main hypothesis is that they are a challenge but also an opportunity, in terms of: (1) updating and supporting teachers; (2) motivation and development of a professional portfolio for students; and (3) breaking the digital divide. This article focuses on the results of the qualitative questionnaires, which collected the students&rsquo; opinion about the project.
The implementation of video in teaching writing recount text at al-fattah

The objectives of this research are to identify how the implementation of video in teaching writing recount text and to know the students’ response about the implementation of video in teaching writing recount text. The subject were tenth grade of X-IPA of SMA Al-Fattah, Buduran, Sidoarjo in the academic&#x0D; 2017/2018. This research used qualitative descriptive were obtained by observing the teaching and learning activity during the implementation of video in teaching writing recount text in the class. Besides, the researcher gave questionnaire, did interview and took pictures for documentation. In this study, the teacher taught about historical event in writing recount text. There are various kind of the student’s responses, but most of them like the implementation of video in teaching writing recount text. From the result of this research, students feel more enjoy with the application of video media in learning than not using any media.
ТРАНСФОРМАЦІЇ ЦІННІСНО-СМИСЛОВОЇ СФЕРИ ПРАВООХОРОНЦІВ НА ЕТАПІ НАВЧАННЯ У ЗВО ЗІ СПЕЦИФІЧНИМИ УМОВАМИ НАВЧАННЯ

Introduction. The specifics of the law enforcement officers’ activities stipulate personal transformations, which significantly affect the characteristics of professional self-realization. Transformations of the personality’s value-semantic sphere encompass meaning-semantic and dynamic-motivational changes, as well as changes in internal connections and relationships between different levels of components and parameters that determine the level of law enforcement’s personal stability and professional reliability.Purpose. The purpose of the article is to identify and analyze the study results of the personal transformations peculiarities in the law enforcement officers’ value-and-semantic sphere at the stage of getting an education at the university with specific learning conditions.Methods: psychodiagnostic method, a comparative method, quantitative and qualitative data analysis.Results. Changes in understanding of the professional life sphere content and meaning are diagnosed. Respondents of all groups tend to strive to have concrete, tangible results of activity and receive approval from the society. In the field of education and training for third-year students and masters, it is important to show interest and achieve moral satisfaction from the learning process and get an education that will enable them to provide themselves financially and raise their own prestige in society. The preservation of one's own prestige is very important for first and second year students. In the sphere of family life at all stages of training, law enforcement officers believe that family well-being consists, first of all, in the material security of the family. In the sphere of public activity, the majority of respondents demonstrate the desire to expand social contacts. The greatest number of statistically significant differences was recorded among the indicators of the significance of values in the field of hobbies.Originality. The obtained results analysis makes it possible to reveal the level of law enforcement officers’ personal stability and professional reliability. This makes it possible to adjust the program of psychological support for police officers personal transformations, which will increase their professional level of self-realization, and will also contribute to their further process of self-realization and self-development.Conclusion. Further studies will be aimed at studying the personal transformations characteristics of law enforcement officers at different stages of professional self-realization.
Teaching musical meter to school-age students through the ski-hill graph

The purpose of this paper is to present a new approach to analyse and understand music which is suitable for inclusion in school and university textbooks wherever musical meter and rhythm is taught. This approach, which is derived from Richard Cohn’s work on and pedagogical approaches to meter theory, demonstrates that it is only through accurate representations of the individual listener’s embodied psychoacoustic experience of music, that the deepest structural complexities of music can be revealed and explained. In this paper, the ski-hill graph and cyclic graph, are introduced as suitable instruments of mathematical music theory to teach school-age students meter and rhythm through visualizations and sonifications of beat-class theory. This paper sheds light on the importance of understanding meter as a measurable psychoacoustic experience rather than as notation and throughout the paper a suitable approach is demonstrated to analyse all music where meter is detected. The paper demonstrates how Cohn’s theory is a pivotal development in the evolution of Western music theory because music theory now has the capacity for both meter and tonality to be studied equally, which, critically, enables the inclusion of music which is not notated to be included in all levels of the music curricula.
Work

A work is a deliberately created informing entity intended for communication. A work consists of abstract intellectual content that is distinct from any object that is its carrier. In library and information science, the importance of the work lies squarely with the problem of information retrieval. Works are mentefacts-intellectual (or mental) constructs that serve as artifacts of the cultures in which they arise. The meaning of a work is abstract at every level, from its creator’s conception of it, to its reception and inherence by its consumers. Works are a kind of informing object and are subject to the phenomenon of instantiation, or realization over time. Research has indicated a base typology of instantiation. The problem for information retrieval is to simultaneously collocate and disambiguate large sets of instantiations. Cataloging and bibliographc tradition stipulate an alphabetico-classed arrangement of works based on an authorship principle. FRBR provided an entity-relationship schema for enhanced control of works in future catalogs, which has been incorporated into RDA. FRBRoo provides an empirically more precise model of work entities as informing objects and a schema for their representation in knowledge organization systems.
Assessment of Heavy Metal Pollution in a Gold Mining Site in Southwestern Nigeria

The unwanted release of environmental contaminants predisposed by mining activities had reached an alarming proportion that deserves attention. Hence, the purpose of this study was to determine the degree of heavy metal contamination which soil and plants were exposed to in Ijana gold mining site, southwestern Nigeria.
Denoising 1D signal using wavelets

Signal denoising is one of the most important areas in signal processing. In the present paper, we have denoised a 1D piecewise constant (PWC) signal corrupted by additive white Gaussian noise (AWGN) using the thresholded Haar wavelet denoising method. The central idea of the wavelet transform is the multiresolution decomposition of signals. This becomes advantageous because small objects require high resolution and low resolution is suitable for large objects. In multiresolution decomposition, an approximation component is created using a scaling function, which is often termed as a lowpass filter. Detail components are obtained using wavelet functions, which are often known as highpass filters. A series of approximations of a signal is thus obtained, which has difference in resolution among them by a factor 2. Detail components contain the difference between adjacent approximations. Proper thresholding of the transformed signal results in reduced noise because, in general, the noise component of a signal has a relatively smaller magnitude and wider bandwidth. We show that our method outperforms recently reported non-convex regularisation-based convex 1D total variation denoising method on PWC signals.
A Hierarchical Bayesian Model for Matching Unlabeled Point Sets

Point set registration is the key in many scientific disciplines. Target at several challenges in registration (e.g. initial registration, outliers, missing data, and local trap), we propose a robust registration method for two point sets using a hierarchical Bayesian model, which is combined with M
Named Entity Recognition using Ensemble Learning

Upgrading Industry 4.0 to 5.0 provides numerous research opportunities for the industrialists and researchers.This industrial revolution cross the peak of automation in the life science domain.In this digitalized world, big data plays a key role to provide the valuable insights by using various analytical methods.In life science, available of huge textual data contains wide spread of valuable information.To extract the hidden information from the big data, natural language processing plays a major and significant role.In NLP, named entity recognition is one of the key factor and biggest challenge for the research community.This paper presents the high level architecture of NER using ensemble learning method.The EL model contains a dictionary based entity identifier and a self-learning classifier.Proposed model outperformed well and produced high accuracy.
Dinosaurs rule!

Simon Ings sees the mighty Tyrannosaurus rex come to life in giant models and scary VR
Exploring the Similarities between Complete and Initial Signatures of an Individual for the Purpose of Author Identification

Signature is a written depiction of someone’s full name, nickname, or a simple letter that has been used on any desired document as an indication of their identity. It is a particular case of handwriting, which includes flourishes and special characters which are produced by the force of habit. Forensically, the signatures are examined for naturalness in execution and for consistent recurrent options that confirm the established practice pattern of the author and aids in the identification of the author in cases of disputes. Commonly used parameters for the signature analysis by the handwriting experts are the formation of the letters, alignment, embellishment, spacing, pen-lifts, pen-pauses, slant, initial &amp; final strokes, and pressure. In some instances where people make initials instead of full signatures, it becomes challenging for the forensics and handwriting experts to compare such initials with complete signatures. The present work has been focused on extracting the similarities between the initial and the complete signatures of an individual to aid in the identification of an individual in such complicated cases. This study may contribute to the identification of the author in the matter of disputes where initials have been used intentionally or unintentionally
Empiric Experiments with Text-representing Centroids

Centroid terms are single, descriptive words that semantically and topically characterise text documents and thus can act as their very compact representation in automated text processing tasks that strongly rely on the semantic similarity of texts. Algorithms to classify and cluster them make use of this information. In this book, the novel, brain- and physicsinspired concept of centroid terms is introduced and deeply discussed. Furthermore, their unique properties and practical usage in major natural language processing and text mining tasks are covered. In this regard, a new graph-based method for their fast calculation is presented as well. In contrast to methods relying on the bag-of-words model, the derived centroid distance measure can uncover
A fairness-enhanced resource trading system in federated cloud environments

In federated cloud system, resource provisioning and allocation across multiple providers become a challenging issue. However, most of existing studies focused on how to improve resource utility or resource revenue, while ignores the efficiency and fairness of the resource market. In this study, we first introduce the definitions of efficient market and fairness criterion based on the classical economic theory; then, we design a resource trading protocol which is capable of offering topology-wide efficiency and fairness under certain payment rules in resource market. Theoretical analysis indicates that the proposed resource trading model is beneficial for pushing resources to resource providers who value them more, which means that resource providers can increase social welfare by repeatedly performing ration deals. To evaluate the effectiveness of the proposed trading model, experiments are conducted in a real-world cloud platform. The results show that it can significantly improve the resource revenues for providers and make better task mapping decisions.
A Novel Framework design for Semantic based Image retrieval as a Cyber Forensic Tool

Cyber forensics includes the areas of computer forensics, network forensics and internet forensics. Digital images were commonly used in cyber forensics to collect criminal images, fingerprints, images of crime events and so on. Since the current cyber forensic tools are not very much furnished with the course of action of huge image data, it becomes a big issue to obtain image evidence to prosecute the criminal, most of the evidence is available in the form of raw semantics. Cyber forensic investigators often face the challenge of manually examining an enormous quantity of digital image information to identify direct evidence with the assistance of this semantics. Semantic based image retrieval system (SBIR) is therefore the recent and best option to solve this drawback. The main purpose of this research is to design for cyber forensic tools a novel framework of semantic-based image retrieval system. We therefore present a deep learning framework based on the Convolution neural network(GoogLeNet) for recognizing distinct facial expressions from the Yale facial image database for cyber associated forensic tools, the presented framework is very effective for classification and detection based on semantics or verbal descriptions. The network has accomplished a decent accuracy of 86.25 % after training.
Perception intelligence as an element of human intellectual capital and its assessment among university students

In this paper, on the basis of a multi-factorial theory, a six-element structure of the intelligence is presented as the basis of human intellectual capital. To assess the first element - the perception intelligence, a technique was developed using a questionnaire and a mathematical apparatus for processing the data obtained. The estimation of the perception intelligence on a small sample of university students is performed. The results of the assessment can be used to develop intelligence, improve communication and learning effectiveness. It is shown that there is a direct relationship between the level of perception intelligence and success in learning.
Students’ Reading Proficiency and Academic Performance

Reading proficiency and academic performance are both of paramount importance to a learner’s holistic academic success. These aspects of a student’s journey must not be taken for granted regardless of their locale, cultural context, and academic setting. Consequently, this intellectual endeavor examined the correlation of said factors. It first probed into the students’ profile and determined their reading proficiency level (RPL) and academic performance (AP) in English based on the Phil-IRI result and mean percentage scores. Using descriptive-correlational analysis, the study investigated the significant differences in the RPL of the students when grouped according to their profile variates and the significant relationship between their AP and RPL. Findings revealed that the latter differed in terms of sex, parents’ highest educational attainment, parents’ occupation, and a number of days of attendance in school, but similar along with age, nutritional status, and attitude toward reading. Students showed a favorable AP in reading as depicted in the positive coefficient result, suggesting a direct proportional linear relationship indicating that students with higher RPL manifested higher AP than those whose reading performance was on the average only. Hence, the study inferred that students need an intervention program for their reading skills and in becoming independent readers. Also, as female students were proven to manifest higher RPL, it was recommended that teachers provide enhancement activities for male students to be at par with their female counterparts. Thus, this empirical information would be beneficial to both schools and educators in strengthening every learner's reading proficiency and academic performance.
Image De-noising using Optimized Self Similar Patch based Filter

Emerging trends in the widespread use of technology has led to proliferation of images and videos acquired and distributed through electronic devices. There is an increasing need towards capturing high fidelity images and filtering of the concomitant noise inevitable in the capture, transmission and reception of the same. In this paper, we propose an OPSS (Optimized Patch based Self Similar) filter that exploits concurrently the photometric, geometric and graphical patch similarities of the image. This model recognizes similar patches to segregate the corrupted from the uncorrupted pixels in an image and improve the performance of denoising. Photometric patch similarity is established by using Non-Local Means Decision Based Unsymmetrical Trimmed Median (NLM-DBUTM) filter, which computes weights based on the reference patch. The geometrical patch similarity is done through the K-means clustering and graphically similar patches are identified through Ant Colony Optimization (ACO) technique. These “three similarities” based models have been taken advantage of and combined to arrive at a more comprehensive and effective denoising. The results obtained through the OPSS algorithm demonstrate improved efficiency in removing Gaussian and Impulse noise. Experimental results demonstrate that our proposed study achieves good performance with respect to other denoising algorithms being compared. Experimental results are based on performance measure (evaluation parameters) through Peak Signal to Noise Ratio (PSNR), Mean squared error (MSE) and Structural Similarity Index Measure (SSIM).
Age Estimation and its Progression from Face Images

Face model improves the performance of evaluating the accurate age estimation with facial images and has enormous real-world applications. Human aging is a process of growing gradually old and mature. However, it is slow, depends upon person to person and most important it is irreversible. This paper mainly focuses on the various face model techniques, their performance metrics, databases, age estimation challenges to provide the researcher a great knowledge with recent journals in this field. Age estimation process progress with two modules: first part is feature extraction from the image and second module is age estimation. The accuracy or the desired output from age estimation model largely depends upon the features extraction, which if selected appropriately helps to achieve better results for research work.
Supplementary Education of Children in Modern Conditions of Pseda: Challenges and Prospects

Socio-economic transformations in Russia have led to the need to modernize a lot of social institutions and, first of all, the education system. The present Russian system of additional education for children has a unique potential for the development of different abilities of students. The additional education of children possessing openness, mobility and flexibility, can respond quickly and clearly to the educational request of the family, create a stable environment of culture development, and also develop a conscious civic position. The maximum use of technologies of a personality-oriented approach contributes to a significant relevance for additional education in the whole diversity of its areas. Today the system of additional education plays a huge role in the training and education of the younger generation.