Reviewerly/exHarmony huggingface dataset:
OBJECTS DETECTION BASED ON THE SEA SURFACE VIDEO FRAGMENTS CROSS-CORRELATION

The work is devoted to the development of a method for the objects detecting on an agitated sea surface video based on the analysis of the differences in the variability of the object and the sea surface image fragments on the neighboring frames. The proposed method does not use data about the object size, its shape, brightness, etc. The decision function has been developed that can be used to estimate the variability of a given frames fragment, based on the normalized cross-correlation coefficients values of the corresponding fragments on a video subsequent frames. The decision rule has been developed based on the proposed decision function, in which we use the threshold value (the critical domain boundary) determined at the training stage when analyzing the frames sequence fragments containing only the agitated sea surface image. The efficiency of the developed objects detection method on the agitated sea surface is demonstrated based on computational experiments. The values of the decision function critical domain boundary obtained at the training stage and the corresponding values of the type II error probability at the detection stage are given. The presented computational experiments results demonstrate that the developed method makes it possible to detect the object on video frames with the type II error probability equal to zero.
Reverse Image Querying

Abstract: As days go by, the volume of graphic i.e. visual data keeps increasing exponentially. This presents a more recent and complex set of problems for handling and making use of such vast, disorganised and unregulated data. Multiple organisations have launched many commercial products to tap into this market. There are multiple methods and functions for reverse image querying but most of them are either incomplete or compute-intensive to be a viable option for smaller use cases. In this study, we have implemented and improvised a rudimentary yet efficient solution by using the cosine similarity model to extract similar images for the given input image from the user. The model used is explained comprehensively together with visual representations. We have also explored multiple use cases that can be used as commercial products. The resulting web application can be utilised to act as a reverse image search engine as a standalone application or can be embedded as a submodule in a larger application.
VR/AR Environment for Training Students on Engineering Applications and Concepts

Modern technologies in virtual reality (VR) and augmented reality (AR) provide unique features that can be used to facilitate tasks in everyday life. Several courses can be built using augmented reality, such as engine maintenance, computer maintenance, chemistry lab, etc. Augmented reality technologies provide dynamic and interactive instructions to resolve a problem or present required concepts. Building an educational system based on augmented reality is not an easy task due to some difficulties and challenges, such as the cost of augmented reality tools and other hardware and software required. Also, training students with engineering concepts and precise parts involves a lot of analysis and practice to know problems and then design solutions. The paper aims to develop a virtual educational environment for training students in engineering sectors in practical laboratory sessions based on AR/VR techniques. The proposed system provides a safe and low-cost environment to train the student different concepts in engineering sector, such as basic concepts in electrical, mechanical and renewable energy engineering.
High-efficiency microwave-optical quantum transduction based on a cavity electro-optic superconducting system with long coherence time

Abstract Frequency conversion between microwave and optical photons is a key enabling technology to create links between superconducting quantum processors and to realize distributed quantum networks. We propose a microwave-optical transduction platform based on long-coherence time superconducting radio-frequency (SRF) cavities coupled to electro-optic optical cavities to mitigate the loss mechanisms that limit the attainment of high conversion efficiency. In the design, we optimize the microwave-optical field overlap and optical coupling losses, while achieving long microwave and optical photon lifetime at milli-Kelvin temperatures. This represents a significant enhancement of the transduction efficiency up to 50% under pump power of 140 μW, corresponding to few-photon quantum regime. Furthermore, this scheme exhibits high resolution for optically reading out the dispersive shift induced by a superconducting transmon qubit coupled to the SRF cavity. We also show that the fidelity of heralded entanglement generation between two remote quantum systems is enhanced by the low microwave losses. Finally, high-precision in quantum sensing can be reached below the standard quantum limit.
Virtual Health Care Robot Using Kinect Sensor

Abstract: Kinect cameras and therefore the other sensor combination framework is used to obtain real-time tracking of a person’s action skeleton. Various gestures, performed by different persons, Quaternion's of joint angles are first used as robust and significant features. we present a gesture human activity recognition system for the event of human-robot interaction (HRI) interface. Next, classifiers are used to recognize the different gestures. This work deals with different challenging tasks, like the real-time implementation of a gesture act recognition system and also the temporal resolution of gestures. The HRI interface developed during this work includes three Kinect and robots which will be remotely controlled by one operator standing before of one of the Kinect sensors. Moreover, the system is provided with a nation action for control of the robot.
Opinion Mining For Text Data: An Overview

Abstract: Nowadays there is huge growth in data People post their views and opinions through the web on different apps, blogs, articles, etc. Customers post their reviews on shopping sites about the product or service. So, it becomes beneficial for companies, manufactures, business owners and sellers to understand customers, product users or buyers but due to huge data/feedbacks or posted opinions manually analyzing text data, is impossible to do. So, opinion mining is very important so as to analyze all the data and know the sentiments from that data without much human effort and in less time huge data can be analyzed. Many researches have made the base in this field of opinion mining. Here opinion mining will be discussed starting with what is opinion mining, how opinion mining is performed, levels, types and approaches for opinion mining, and applications. Also, methods for Text Preprocessing, Feature Extraction, Evaluation and Classification Approaches that are Machine Learning approaches and Lexicon Based approaches also, various opinion mining methods such as Support Vector machines (SVM), Neural Network, Naïve Bayes, Bayesian Network, Maximum Entropy, Corpus and Dictionary based methods are discussed here.
FaDIV-Syn: Fast Depth-Independent View Synthesis using Soft Masks and Implicit Blending

Novel view synthesis is required in many robotic applications, such as VR teleoperation and scene reconstruction.Existing methods are often too slow for these contexts, cannot handle dynamic scenes, and are limited by their explicit depth estimation stage, where incorrect depth predictions can lead to large projection errors.Our proposed method runs in real time on live streaming data and avoids explicit depth estimation by efficiently warping input images into the target frame for a range of assumed depth planes.The resulting plane sweep volume (PSV) is directly fed into our network, which first estimates soft PSV masks in a self-supervised manner, and then directly produces the novel output view.This improves efficiency and performance on transparent, reflective, thin, and feature-less scene parts.FaDIV-Syn can perform both interpolation and extrapolation tasks at 540p in real-time and outperforms state-ofthe-art extrapolation methods on the large-scale RealEstate10k dataset.We thoroughly evaluate ablations, such as removing the Soft-Masking network, training from fewer examples as well as generalization to higher resolutions and stronger depth discretization.Our implementation is available 1 .
University of Al Mosul / College of Faculty of Basic Education / Dept. of physical education and sports sciences

The current research aims to:-Building a scale for building an electronic management scale for colleges and departments of physical education and sports sciences in Iraq for the academic year 2020/2021.The research community reached (1065) teachers in the colleges and departments of physical education and sports sciences in Iraq, and the research sample included the teachers of colleges and departments of physical education and sports sciences in Iraq The number of them is (320) teaching sample for the electronic administration scale, and (20) forms for the scale were excluded because they did not meet the scientific conditions, and thus the construction sample became (300) teaching and amounted to The percentage of the construction sample from the research community is (28.16%), and the stability sample was from (30) teachers who represented the Department of Physical Education and Sports Sciences in the College of Basic Education / University of Mosul, and their percentage was(2.81%) of the research community, and the exploratory experiment sample consisted of (10) teachers who represented the Department of Physical Education and Sports Sciences in the College of Education for Girls / University of Mosul, and their percentage was (0.93) from the research community.In its final form, the scale reached (39) items after deleting (18) items according to the methods of the two extreme groups and internal consistency. The researchers concluded the following:-Building the electronic management scale for colleges and departments of physical education and sports sciences in Iraq, which consists of (39) items, enjoying honesty and stability.The researchers recommend the following: -Adopting the scale prepared in the knowledge and application of electronic management of colleges and departments of physical education and sports sciences in Iraq.-Conducting a correlational study between the electronic administration in this scale prepared in this research and other administrative variables to know the same research sample.
Commercialization and Industry Perspective in the Era of Digitalization

The study focuses on the commercialization of the organizations. Malaysian organizations are facing challenges to cope with the industrial revolution. Application of IoT, big data analytics, artificial intelligence is positively impacting on the industrial development. The study focuses on the improvement of the digitalized technology in the Malaysian organizations for developing the performance of the operational management. The research methodology focuses on the secondary qualitative research method, which improve the quality of research and help n gathering relevant information
A Model of Teaching Mathematics with the Effect of Developing the Probabilistic Style of Thinking in a Digital Educational Environment: Theoretical Justification and Empirical Verification

The article is focused on the problem of inducing students to develop the non-linear, probabilistic style of thinking in the context of the digitalization of modern education. The purpose of the study is to create effective scientific and methodological tools for organizing the process of teaching mathematics in schools and universities in order to achieve high pedagogical, socially demanded results and, on the basis of these tools, to create an improved didactic model with the effect of developing the probabilistic style of thinking, flexibility, creativity and criticality in students so as to enable them to actively participate in social life. The model of teaching mathematics is constructed in the unity of the target, theoretical and methodological, content, technological, diagnostic and effective components. The structure-forming factor is an information-intensive educational environment for teaching mathematics as a set of digital information and educational content that contributes to the effective development of probabilistic style of thinking. The content component of the model is implemented in the selection and structuring of educational material based on the fractal approach, in the methodological update of a complex of foundation spirals equipped with banks of applied and research tasks, taking into account the depth of the fractal representation of educational elements. To obtain guaranteed learning outcomes while solving technological problems of implementing the model, an adaptive learning system was used as a tool for developing probabilistic style of thinking in students and creating an objective means of management. The results of introducing the model into teaching practice with subsequent statistical verification based on the descriptive statistics methods and Student’s t -test showed positive dynamics for all the structural components of the model with a confidence level of 95%. The prospect of the research is further intellectualization of the technological component of the model based on the hybridization of artificial intelligence methods to ensure the effective development of the probabilistic style of thinking with rapid changes in parameter values according to the set feedbacks.
Heuristics: Human and Nonhuman

The problems of artificial intelligence from the very beginning of this applied area of science in the mid-20th century have closely intersected with psychological problems, primarily with the psychology of thinking. As experience shows, not only real developments in artificial intelligence but also the discussed prospects for building its working models largely depend on technological progress in the field of computers and software. The paper discusses the changes in representations of heuristics understood as creative thinking and as techniques or rules that are useful for finding solutions to problems. The following issues are specifically considered: the psychological side of the problems of heuristic programming, the similarities and differences between human and computer heuristics, the probability and possible consequences of the singularity phenomenon (understood as the superiority of artificial intelligence over natural one), including the example of the functioning of the community of professional chess players. It is concluded that the progress of computer models and artificial intelligence systems are promising for the positive transformation of the human psyche.
Detecting Spoofing Attacks in Speaker Verification Systems

Abstract: The proof of writing tells that they can be powerful, however the issue is as yet present. Because of the chance of parodying assaults at different points the confirmation utilizing biometric has developed astoundingly these years, however they can be helpless against satirizing assaults. In any event, for programmed speaker check, it is difficult to counter the parodying at all focuses. Notwithstanding an extreme climate, the innovation offers great help; more industriousness will be needed in future to set palatable insurance against the assaults. This paper makes accessible a review of work that has been done in the space of ridiculing assaults and its answer for speaker check throughout the long term.
A Machine Learning Approach for Automation of Resume Recommendation System

Abstract: Finding qualified candidates for a vacant post can be difficult, notably if there are many applications. It can stifle team growth by making it difficult to hire the right person at the right time. "A Resume Recommendation System" has the potential to significantly simplify the time-consuming process of fair screening and shortlisting. It would certainly enhance candidate selection and decision-making. This system can handle a large number of resumes by first classifying them using multiple classifiers and then recommending them based on the job description. We offer research to improve data accuracy and completeness for resource matching by combining unstructured data sources and incorporating text mining algorithms. Our method identifies categories by extracting and learning new patterns from employee resumes.
Four-Class Emotion Classification Problem using Deep Learning Classifiers

Social media sites and blogs generate a vast amount of emotionally rich data in the form of tweets, status updates, blog posts etc. Such textual data are a good representative of emotions expressed by an individual or a group of people on any given topic. By analyzing the emotions within these textual data, we can get an idea about how an individual or a community expresses their views. Analytical techniques are widely used for analyzing emotions within these texts. However, due to the imbalanced nature of the training datasets the supervised classifiers fail to clearly classify the different emotion classes. As a result, these classifiers demonstrate a poor performance in identifying emotions within the texts. Here, using a constructed heterogeneous training dataset from well-known training datasets we have trained two deep learning models namely the Convolutional Neural Network (CNN), and Recurrent Neural Network (RNN) to address a four-class emotion (Anger, Sadness, Happy, Surprise) classification problem. By appropriately tuning the hyper parameters of the deep learning classifiers our study reveals that the CNN classifier has a slightly better performance (77%) than the RNN classifier (76%) for a four-class emotion classification problem.
Eternal Present? From McLuhan’s Global Village to Artificial Intelligence

Herbert Marshall McLuhan (1911-1980) was a Canadian philosopher, philologist, literary scholar and media expert. Andy Warhol famously said that in the future everyone will be famous for fifteen minutes. As for McLuhan’s fame, it stretched over decades. His ideas that technology can influence and shape society have been widely discussed up to this day. McLuhan’s work is regarded as an important conceptual contribution to media theory, and his term ‘global village’ is widely used by students and scholars, practitioners and theorists in the field of communication. The authors of this article attempt to analyze the contribution of McLuhan, as a communication expert and influential technodeterminist, to understanding the media of the 21st century. It is concluded that, despite the abundant criticism regarding the naivety and “unscientific” nature of his approach, the lack of empirical evidence for the theory he put forward, his passion for technology, as well as his belief in the decisive role of the media in the development of culture and society, McLuhan’s ideas still inspire researchers. The concept of ‘global village’ in the modern information world has not only retained its relevance - it describes the laws of the functioning of the digital society in the best possible way. The Internet and social networks have confirmed Marshall’s postulate that communication technologies enable people to become increasingly involved in one another’s lives.
Meta Value Learning for Fast Policy-Centric Optimal Motion Planning

This paper considers policy-centric optimal motion planning with limited reaction time.The motion planning queries are determined by their goal regions and cost functionals, and are generated over time from a distribution.Once a new query is requested, the robot needs to quickly generate a motion planner which can steer the robot to the goal region while minimizing a cost functional.We develop a meta-learning-based algorithm to compute a meta value function, which can be fast adapted using a small number of samples of a new query.Simulations on a unicycle are conducted to evaluate the developed algorithm and show the anytime property of the proposed algorithm.
The level of knowledge management among faculty members at the College of Education for Human Sciences - University of Mosul

Eduational and psychological sciences, English, Arabic and Sciences of the Noble Quran and Islamic Eduation at the College of Education for Human Sciences for the academic year 2020-2021.To accomplish the research aims, the researcher created a tool of knowledge management scale with (40) paragraphs, five alternatives within four axes, namely (creation and generation of knowledge, diagnosis and storage of knowledge, distribution of knowledge, and dissemination of knowledge), the tool was distinguished by honesty, distinction, and stability.
Comparative Analysis of Children’s News Program

Youngsters are the future of a country and a nation, as the news media is a vital source of knowledge for children about the outside world and plays a significant part in shaping their moral values.By means of the questionnaire survey, this research will look at the situation of children's news programs in China.It also examines domestic and international incidents to compare and contrast children's news programs.Finally, the article makes some recommendations and outlooks for the future of children's news in China.
Crafting English Domino Card (EDC) as an English Learning Media for Junior High School Students

Learning media is essential in making it easier for teachers to deliver learning materials. Besides, it can also ease students learning. Therefore, learning media is vital in helping the teaching and learning process. This research aimed to develop or craft English Domino Card (EDC) as English Learning Media for Junior High School Students. This research is categorized as development research or research and development (R&amp;D). This research was used to produce products and assess product effectiveness and practicality. In relation to the design of this study, the researcher arrived at the stage of producing a product and testing its validity. Product validity testing was carried out by two experts, media experts and material experts. The results showed that English Domino Card (EDC) as an English Learning Media for Junior High School Students was very worthy. It can be seen from the expert’s judgment.
Application of English Bridge Course in Improving English Achievement of Freshmen

On the basis of the overall analysis of the academic results of Bachelor's degree first year students at Mahendra RatnaMultiple Campus, Ilam in the then-preceding three years (2010-2012) it was identified that the failure in Compulsory English had had a considerable share for the low pass rate in all the three faculties (Education, Humanities and Management) offering the subject.With an aim to minimize the failure rate the campus authority assigned the author to prepare an English language bridge course to be commonly implemented in all the three faculties for a month before the actual classes started.In such a situation, the first task for the author was to identify and analyze the English language learning needs common to the learners from those faculties.This paper highlights how, as a process of research, those common needs were identified to be used as the contents of the course; what methodology was used; how the inadequacy of materials was dealt with; and how the assessment aspect was designed.One important message stemming out of the endeavor was that it is sometimes pointless to seek a theory or philosophy to be based on before beginning a project, or during the process: a theory is ultimately a generalization observed in this world rather than something imported from another planet.However, the paper also sets out to pinpoint and assess the theory and principles underlying the then-pragmatically developed course aimed fundamentally at fulfilling the immediate institutional need.