Reviewerly/exHarmony huggingface dataset:
Design and Implementation of Quantum half Adder and Full adder Using IBM Quantum Experience

Quantum machine learning is the combination of quantum computing and classical machine learning. It helps in solving the problems of one field to another field. Quantum computational power can be advantageous in handling huge data at a faster rate.In this regard, quantum computational power can be advantageous in handling such huge data at a faster rate. Classical machine learning is about trying to find patterns in data and using those patterns to predict future events. Quantum systems, on the other hand, produces typical patterns which are not producible by classical systems, thereby postulating that quantum computers may overtake classical computers on machine learning tasks. Hence the whole motivation in this work is on understanding and analysing the half adder and full adder circuit design using Quantum mechanics.
Neo-Kantian motifs in the works of A. Bely

The article is devoted to the work of A. Bely in the development of Russian culture in the late 19th - early 20th centuries. Attention is paid to the motives of the creative path of the philosopher-poet, who created the basis of Russian symbolism. By analyzing the cultural and historical manifestations of the second half of the 19th century and the first half of the 20th century, reflection in the works of art and science workers, an assessment of the severity of symbolism for the development of Russian philosophy and the field of art in general. In the process of the formation of symbolism in Bely&amp;apos;s work, neo-Kantian motives are clearly revealed in the formulation of the problem of the difference between subjective perception and the essence of the object of perception in itself, that is, distinguishing between the symbol and the signified. By comparing Bely&amp;apos;s views with the concept of sophiology and anthroposophy, distinct Kantian positions of the philosopher-poet stand out. These include the schematism of space and time, an attempt to apply the categories of natural science to the field of philosophy of art, as well as the demarcation of the immanent and the transcendent. Despite the fact that the ideas of the philosopher-poet in their form have similar positions with the anthroposophy of R. Steiner and with the ideas of V. Solovyov, however, the key content is the neo-Kantian methodology of &amp;quot;critical deepening&amp;quot; of thought and its rationalization. The actualization of Bely&amp;apos;s creativity and the issue of his neo-Kantian motives is carried out by attracting research from related branches of knowledge on the principles of interdisciplinary consideration and implementation of an integrated approach.
PROFESSIONAL SELF-DEVELOPMENT OF MIDDLE-AGED ADULT LEARNERS: OPPORTUNITIES FOR PSYCHOLOGICAL AND PEDAGOGICAL SUPPORT

The attitude to age in Russia and abroad is rapidly changing. Now middle-aged adults are fairly recognized as capable of continuing their educational and professional activities, active self-development, long-term economic activity and financial independence. Middle-aged adults remain involved in social life in the family and society, and are ready to develop professionally and personally throughout their lives. The process of supporting professional self-development in the educational environment should be holistic and systemically organized, in which psychological and pedagogical conditions are created for successful professional training and personal self-development. In the course of the theoretical study clarified the meaning of “professional self-development of students middle-age adults”; the highlighted stages of psychological and pedagogical support of professional self-development for adults; evaluation of the level of readiness of students of middle-age adults and their actual involvement in the process of professional self-development; updated pedagogical and psychological conditions of psychological and pedagogical support of students middle-age adults; the effectiveness of the activities of the participants of the developed support program and the effectiveness of the program as a whole are analyzed. Professional self-development of middle-aged adult students is possible through the implementation of a program of psychological and pedagogical support. For an effective process of supporting professional self-development, it is necessary to create an appropriate educational environment and conditions for the formation of students involvement and readiness in this process.
An Evaluation of English-to-Yoruba Translations of some Concepts by Selected Radio News Bulletins

This study examines translations of selected official names/titles contained in news broadcasts in the Yorùbá-speaking part of Nigeria, interrogating their adequacy and appropriateness. Sixty-five concepts/titles extracted from one hundred news bulletins presented by five radio stations across the Yorùbá-speaking states of Nigeria are examined. The study is prompted by an intuitive feeling of inaccuracy and inappropriateness of important words in news broadcasts in Yorùbá and predicated upon the fact that misinformation can be as pernicious as lack of information. The renderings of the concepts in Yorùbá are compared with their original versions in English, revealing translation weaknesses such as semantic narrowing, expansion, wordiness, and sometimes even unwitting distortions. It concludes by emphasizing the adoption of appropriate translation strategies and a more rigorous engagement with the texts as a way of guarding against unintended distortions and misinformation.
Analisis Sentimen Pengguna Marketplace Bukalapak dan Tokopedia di Twitter Menggunakan Machine Learning

A collection of tweets from Twitter users about Marketplace Bukalapak and Tokopedia can be used as a sentiment analysis. The data obtained is processed using data mining techniques, in which there is a process of mining the text, tokenize, transformation, classification, stem, etc. Then calculated into three different algorithms to be compared, the algorithm used is the Decision Tree, K-NN, and Naïve Bayes Classifier with the aim of finding the best accuracy. Rapidminer application is also used to facilitate writers in processing data. The highest results from this study are Decision Tree algorithm with 82% accuracy, 81.95% precision and 86% recall.
Space-time inhomogeneous quantum random walk in terms of quantum Bernoulli noise

The evolution equation of the Space-time inhomogeneous quantum random walk in terms of quantum Bernoulli noise not only depends on the change of time, but also on the spatial position of the walker.The model is defined on the space of square summable functions.The canonical isomorphism relationship also can deduce the representation of the model in the tensor space.Mathematical induction gives the probability distribution of the quantum random walk in the general initial state and find that it has the same limit distribution as the classical random walk.
Sudden Obstacle Appearance Detection by Analyzing Flow Field Vector for Small-Sized UAV

Achieving a reliable obstacle detection and avoidance system that can provide an effective safe avoidance path for small unmanned aerial vehicle (UAV) is very challenging due to its physical size and weight constraints. Prior works tend to employ the vision based-sensor as the main detection sensor but resulting to high dependency on texture appearance while not having a distance sensing capabilities. The previous system only focused on the detection of the static frontal obstacle without observing the environment which may have moving obstacles. On the other hand, most of the wide spectrum range sensors are heavy and expensive hence not suitable for small UAV. In this work, integration of different based sensors was proposed for a small UAV in detecting unpredictable obstacle appearance situation. The detection of the obstacle is accomplished by analysing the flow field vectors in the image frames sequence. The proposed system was evaluated by conducting the experiments in a real environment which consisted of different configuration of the obstacles. The results from the experiment show that the success rate for detecting unpredictable obstacle appearance is high which is 70% and above. Even though some of the introduced obstacles are considered to have poortexture appearances on their surface, the proposed obstacle detection system was still able to detect the correct appearance movement of the obstacles by detecting the edges.
The Realization of Hedges and Boosters in Trump's and Clinton's Utterances in The US Presidential Debates in 2016

Hedges and boosters are crucial metadiscourse markers to soften and strengthen the proposition. Presidential candidates also rely on hedges and boosters to draw the publics' intentions. This study aims to explore the use of hedges and boosters in Trump's and Clinton's utterances in the US presidential debates in 2016. Accordingly, discourse analysis was adopted in this present study to find out the realization of types and functions of hedges and boosters as well as the differences and similarities of the occurrences of hedges and boosters between those two candidates based on the taxonomies of Salager-Meyer (1997), Demir (2017), Rabab'ah and Rumam (2015) and Hyland (2005). The strategy was elaborated into six sub-research questions to find out types, functions, differences, and similarities of hedges and boosters. The data were obtained from the transcript of the debates. The findings reveal that the seven types of hedges and six types of boosters were discovered in the utterances of Trump and Clinton. Associated with the functions of hedges and boosters, it shows that Trump and Clinton tend to use hedging devices to mitigate their claims by showing some kind of uncertainty. Boosters also applied to put emphasis on the value of the truth of their statements. It was discovered that Trump used more boosters and Clinton used more hedging devices as well.
Formal instruction by Song for English Learners in SMP IT Darul Hasan while Pandemic Era

This research was examined to help the English teacher in Junior high school especially, while pandemic Covid-19 more dilate over the world. The pandemic that has hit the world in the last 3 years, it gas given much attention from all elements in the world generally, the side of education do need new innovations to keep advancing the target of education, so one of thing teachers do at SMP IT Darul Hasan Kota Padangsidimpuan to overcome the problem have tried carry out formal instruction in achieving good English grammar according to their target and age, namely through songs with grammar elements according to the lesson curriculum in social media flat form. This research have done for treat in 7 class SMP IT Darul Hasan Kota Padangsidimpuan that consist of 25 students randomly. The three classes have a different acquisition in English subject, again which the students in 7d, 7e, and 7f. So, in my conclusion that formal instruction by song in Junior high school SMP IT Darul Hasan Kota Padangsidimpuan has given a positive effect.
Feasibility of e-booklet learning media on the concept of human reproductive system

Educators are the major players in the teaching process to enhance the accomplishment of student learning results. Biology subject, mainly the concept of Human Reproductive System, necessitates media relevant to learning objectives, student conditions, and technology development. Hopefully, learning media can assist the learning process by being packaged attractively to reach learning standards. In this case, the selected form of learning media is E-Booklet. This study aims to describe the feasibility of E-Booklet Learning Media in Concept Human Reproductive Systems. The research technique involves the step-by-step study and development utilizing a 4D model: 1) define, 2) design, 3) develop, and 4) disseminate. The feasibility of the E-Booklet has indicated the results of testing by 3 (three) experts using a feasibility instrument. The Human Reproductive System E-Booklet test shows that the results are very feasible (4.49) utilized as a biology learning medium. The dissemination of E-booklets is done online through posters that contain links and barcodes of E-booklets that can be accessed via the internet.
Gangguan Memori pada Pasien Meningioma

Brain tumor patients often experience cognitive impairment. In the case of meningiomas, this disorder can affect areas of executive function and memory. Cognitive impairment in meningioma patients is influenced by the location and volume of the tumor. In a study of 38 patients with WHO grade I meningiomas, working memory capacity was lower in patients with tumor resection without adjuvant treatment compared with healthy controls. The writing of this article includes various sources originating from scientific journals and government guidelines and related agencies. Source searches were carried out on online portals for journal publications such as MedScape, Google Scholar (scholar.google.com) and the National Center for Biotechnology Information (ncbi.nlm.nih.gov), with the keyword “Meningioma”. Another study of 293 patients (220 women and 73 men) with multiple meningiomas showed that 23% of patients after surgery had neurological deficits and 12% had new permanent neurological deficits. Regarding risk factors, one study showed that the frequency of women is higher than that of men. In addition, age is also considered to have an effect on patients with meningiomas. Meningiomas are intracranial brain tumors that are often found in adults. Cognitive deficits are common in brain tumor patients. At least one area of ​​cognition is impaired in brain tumor patients.
TEACHER TALK AND THE PATTERN OF ENGLISH CLASSROOM INTERACTION IN TEACHING ENGLISH

The aim of this research was to explore the teacher talk and the pattern of interaction that occur during in the teaching - learning process. The researcher applied qualitative study in English Zone, a Course Institute in Makassar. The data sources were a teacher who has got her BA degree in State University of Makassar two years ago. There are four teenager students who participated in the class. The technique of data collecting consists of doing observation by recording audio-lingual data of the process of teaching English. While, technique of data analysis consist of transcribing data from recorded classroom observation into written text, classifying the types of teacher talk that occurred in the class, identifying the patterns of interaction occur during in the teaching – learning process and concluding the finding from all of the collected data. In brief, it could be concluded that the teacher employed ten from eleven categories of teacher talks, there are: there are eleven types of teacher talks namely dealing with feelings, praising and encouraging, joking, using ideas of students, repeating students’ response verbatim, asking question, giving information, correcting without rejection, giving direction, and criticizing the students’ response. While there are four patterns of classroom interaction that were applied in the study are: Interactions among students or student – students interactions that happened during the small group discussion and during in the classroom discussions teachers – whole class interactions that happened during the class discussion and also this pattern happened when the teacher conveyed learning material and gives instructions to the students, Interactions among teacher – group discussion that happened during the small group discussion when the teacher clarifies the students’ difficulties with the task given. Therefore, it was suggested for the teacher to conducted group discuccion that did not occur in class interaction to improve the students motivation and willingness to work together.
MANAJEMEN PEMBELAJARAN SENTRA ALAM PADA ANAK USIA DINI DALAM MENINGKATKAN KECERDASAN KONGNITIF ANAK

This study aims to understand and analyze the management of natural center learning in early childhood in improving children's cognitive intelligence in Raudlatul Athfal Zainul Hasan, Tambelang Village, Krucil District, Probolinggo Regency. This research uses a qualitative type of case study. Data collection techniques are carried out through interviews, observation and documentation. The data analysis was carried out in a circular manner, starting from the data display, followed by drawing conclusions. The results showed that the learning management of natural centers in improving students' cognitive intelligence was carried out through planned and systematic planning by the teacher with reference to policies that have been determined by the government and existing local policies, followed by implementation of learning activities that try to bring students to the real world and ends with an evaluation based on authentic assessment.
Ensemble Method For Net Traffic Classification Based On Deep Learning

With the rapid development of computer network technology, the Internet has covered all aspects of social life. Nowadays, network technology is widely used in various social fields such as economy, military, education, etc. It promotes the rapid development of society and economy, and at the same time brings unprecedented challenges. The security of information transmission and interaction in cyberspace takes network traffic as the carrier, and network traffic contains a large amount of valuable information. How to perceive the current network status through the analysis of network traffic, discover network abnormalities in time is of great significance for maintaining network security. With the rapid development of deep learning in the field of artificial intelligence, researchers have tried to transfer deep learning methods that shine in computer vision processing, natural language recognition and other fields to the field of network flow detection. This paper proposes an ensemble model based on a convolutional neural network, which is integrated on the basis of the CNN model, which reduces the deviation of each basic model and improves the accuracy of the network stream classification results. The main tasks of this paper are as follows: (1) Experiments on the basic model and the integrated model were carried out on the USTC-TFC2016 data set. (2) The experimental results show that the ensemble model reduces the deviation of the basic model and improves the classification accuracy.
High-Performance Fake Voice Detection on Automatic Speaker Verification Systems for the Prevention of Cyber Fraud with Convolutional Neural Networks

This study proposes a highly effective data analytics approach to prevent cyber fraud on automatic speaker verification systems by classifying histograms of genuine and spoofed voice recordings.Our deep learning-based lightweight architecture advances the application of fake voice detection on embedded systems.It sets a new benchmark with a balanced accuracy of 95.64% and an equal error rate of 4.43%, contributing to adopting artificial intelligence technologies in organizational systems and technologies.As fake voice-related fraud causes monetary damage and serious privacy concerns for various applications, our approach improves the security of such services, being of high practical relevance.Furthermore, the post-hoc analysis of our results reveals that our model confirms image texture analysis-related findings of prior studies and discovers further voice signal features (i.e., textural and contextual) that can advance future work in this field.
Scalable Algorithms Using Sparse Storage for Parallel Spectral Clustering on GPU

Spectral clustering has many fundamental advantages over k-means, but has high computational complexity ( $$\mathcal {O} (n^3)$$ ) and memory requirement ( $$\mathcal {O} (n^2)$$ ), making it prohibitively expensive for large datasets. In this paper we present our solution on GPU to address the scalability challenge of spectral clustering. First, we propose optimized algorithms for constructing similarity matrix directly in CSR sparse format on the GPU. Next, we leverage the spectral graph partitioning API of the GPU-accelerated nvGRAPH library for remaining computations especially for eigenvector extraction. Finally, experiments on synthetic and real-world large datasets demonstrate the high performance and scalability of our GPU implementation for spectral clustering.
Employing opposite ratings users in a new approach to collaborative filtering

Over the past few decades, various recommendation system paradigms have been developed for both research and industrial purposes to satisfy the needs and preferences of users when they deal with enormous data. The collaborative filtering (CF) is one of the most popular recommendation techniques, although it is still immature and suffers from some difficulties such asparsity, gray sheep and scalability impeding recommendation quality. Therefore, we propose a new CF approach to deal with the gray sheep problem in order to improve the predictions accuracy. To realize this goal, our solution aims to infer new users from real ones existing in datasets. This transformation allows for creating users with opposite preferences to the real ones. On the one hand, our approach permits to amplify the number of neighbors, especially in the case of users who have unusual behavior (gray sheep). On the other hand, it facilitates building a dense similar neighborhood. The basic assumption behind this is that if user X is not similar to user Y, then the imaginary user ¬X is similar to the user Y. The performance of our approach was evaluated using two datasets, MovieLens and FilmTrust. Experimental results have shown that our approach surpasses many traditional recommendation approaches.
The Application of Geomorphology Data Through Landsat Imagery for Drought Detection (Case: Gerokgak Sub-District, Buleleng Regency, Bali)

This research aims at discovering the potential of Landsat imagery for obtaining geomorphological information and its relationship with drought phenomena.The method used for this study is quantitative through the interpretation and examination of aspects of morphometry and morpho-structure-passive interpretation.Concerning the Landsat imaging using composite methods, sharpening and using DEM.The results showed that Landsat 8 imagery was able to provide very detailed information by showing that composite imagery combined with HSV fusion affirmation provides an affirmation of the upper limit of appearance.Moreover, DEM information may contain topographic information and a morpho-passive structure state in the area.This combination is able to provide information on the appearance of landform such as; structural landform, solutional landform, karst landform, volcanic landform, marine landform, and fluvial landform.Based on the results of the interpretation and field surveys, it can be concluded that areas with structural and karst landforms are experiencing faster drought than other areas in the Gerokgak sub-region.