Reviewerly/exHarmony huggingface dataset:
Near-perfect Reachability of Variational Quantum Search with Depth-1 Ansatz

Grover's search algorithm is renowned for its dramatic speedup in solving many important scientific problems. The recently proposed Variational Quantum Search (VQS) algorithm has shown an exponential advantage over Grover's algorithm for up to 26 qubits. However, its advantage for larger numbers of qubits has not yet been proven. Here we show that the exponentially deep circuit required by Grover's algorithm can be replaced by a multi-controlled NOT gate together with either a single layer of Ry gates or two layers of circuits consisting of Hadamard and NOT gates, which is valid for any number of qubits greater than five. We prove that the VQS, with a single layer of Ry gates as its Ansatz, has near-perfect reachability in finding the good element of an arbitrarily large unstructured data set, and its reachability exponentially improves with the number of qubits, where the reachability is defined to quantify the ability of a given Ansatz to generate an optimal quantum state. Numerical studies further validate the excellent reachability of the VQS. Proving the near-perfect reachability of the VQS, with a depth-1 Ansatz, for any number of qubits completes an essential step in proving its exponential advantage over Grover's algorithm for any number of qubits, and the latter proving is significant as it means that the VQS can efficiently solve NP-complete problems.
Device-independent certification of degeneracy-breaking measurements

In a device-independent Bell test, the devices are considered to be black boxes and the dimension of the system remains unspecified. The dichotomic observables involved in such a Bell test can be degenerate and one may invoke a suitable measurement scheme to lift the degeneracy. However, the standard Bell test cannot account for whether or up to what extent the degeneracy is lifted, as the effect of lifting the degeneracy can only be reflected in the postmeasurement states, which the standard Bell tests do not certify. In this work, we demonstrate the device-independent certification of degeneracy-breaking measurement based on the sequential Bell test by multiple observers who perform degeneracy-breaking unsharp measurements characterized by positive-operator-valued measures (POVMs)---the noisy variants of projectors. The optimal quantum violation of Clauser-Horne-Shimony-Holt inequality by multiple sequential observers eventually enables us to certify up to what extent the degeneracy has been lifted. In particular, our protocol certifies the upper bound on the number of POVMs used for performing such measurements along with the entangled state and measurement observables. We use an elegant sum-of-squares approach that powers such certification of degeneracy-breaking measurements.
Social Maturity: Resource Approach to the Explication of Personality Competence

The article is devoted to the theoretical substantiation of social maturity as psychological resource of personality competence. The aim of the represented material is theoretical explication of the problem of social maturity of a personality as the resource approach to the interpretation of personality competence. The method of psychological reconstruction as theoretical study of subjective architecture of the phenomenon of social maturity in the perspective of identifying the methodological potentialities of each component of the resource approach is laid on the basis.The results include theoretical analysis of the basic positions of the study of social maturity of personality and outlining the methodological interpretation in the systemic, personalityactivity, synergetic and acmeological concepts.The subjective doctrine of analysis of the stated problem allows to unite the basic ppositions of consideration of social maturity as personality competence with the attraction to the basic social abilities and mobilization of psychological resources of personality. The theoretical scheme of manifestation of social maturity within the resource potentialities of personality competence is suggested.Two methodological orientations (result orientation and uniqueness orientation), which determine the manifestation of this phenomenon by signs of external and internal motivation; the types of external and internal psychological resources are singled out, which together determine the "potential of competence" in the whole set of systemic-synergetic integrity of manifestation of self-realization of personality as a subject of social activity.It is substantiated that axiological, reflexive and anticipatory mechanisms of functioning are involved in the potential of competence of social maturity.The conclusions indicate that the proposed theoretical scheme of social maturity manifestation within the resource potentialities of personality competence can be successfully used in the applied proceedings of preventive and developmental psychotechnologies, taking into account the social status, socio-cultural development, sex and gender models of behavior of a personality.
Developing the Multilink Manipulator System for an Autonomous Underwater Vehicle

The article considers to development and integration of a multilink manipulator to AUV “MMT-3500” developed by Institute of Marine Technology Problems FEB RAS (Vladivostok, Russia). The manipulator is designed for collecting samples of marine organisms and bottom soil by the vehicle hovering over the object of the interests.A kinematic layout of the manipulator is proposed in the article. The layout provides control of the manipulator end-effector with given coordinates inside a working area of a computer vision system.The design overview and software control scheme of the manipulator are described in the article. The design overview of manipulator arms and it’s effectors are described and presented.
DEVELOPMENT OF THE STRUCTURE OF AN AUTOMATED SYSTEM FOR DIAGNOSING DISEASES

Today, the importance of information support for various medical technologies has increased significantly. The use of modern information technologies is becoming a critical factor in the development of most branches of knowledge and areas of practice, so the development and implementation of information systems is an urgent task. The clinical decision support system provides clinicians and stakeholders with individualized patient assessments and recommendations to assist in the clinical decision-making process.&#x0D; Knowledge-based information systems are widely used in medicine around the world. Modern technical capabilities make it possible to reach a qualitatively new level of presentation of the course of the disease, namely, based on appropriate mathematical models, to model the typical development of the pathological process in a particular disease, to speed up the process of diagnosing and receiving recommendations on treatment protocols.&#x0D; In Kazakhstan, there is no variety of decision support systems in medicine, especially in the process of diagnosing diseases. The purpose of this study is to develop the structure of an automated system for diagnosing diseases. The Unified Modeling Language (UML) is used as a design tool. The structure of the automated system is presented; the main components and key terms are considered. A mathematical model of diagnostics is shown (in the example of diseases of intestinal and pancreatic insufficiency) based on decision-making methods with fuzzy initial data. A diagram of the data flows of the system is presented. Thus, the paper proposes the structure of an automated system that will contribute to high-quality diagnostics due to an effective method of system organization and the use of fuzzy set theory methods.
Research on the Application of Improved Salp Swarm Algorithm in Time Difference of Arrival of Passive Location

According to the shortcomings of slow positioning speed and low detection accuracy of passive positioning that uses time difference of arrival (TDOA), an innovative location model of extreme learning machine (ELM) which is improved by Salp Swarm Algorithm (SSA) in view of Logistic Mapping, Opposition-Based Learning and Cauchy Mutation (LOCSSA) is put forward. The method firstly initializes the population by Logistic mapping and improves SSA by Opposition Based Learning and Cauchy mutation. Then uses LOCSSA to look for the optimal weights and biases of ELM. Finally, LOCSSA is used to locate the target. The results show that the ELM positioning model of LOCSSA has better accuracy and stability for target positioning, which demonstrate that the method is feasible.
The Application of K-Means Clustering Algorithm in the Quality Analysis of College English Teaching

Colleges and universities should keep up with changes in market demand, actively adapt to the needs of social development, continuously deepen the reform of college education and English teaching, improve the quality of running schools, and highlight the characteristics of running schools. The purpose of this paper is to study the quality analysis of college English teaching based on K-means clustering algorithm. The research on the prototype of the college English teaching quality evaluation system was carried out, and the clustering algorithm was applied to the college English teaching quality evaluation system to provide decision support for the management. The K-means algorithm was used to perform cluster analysis on the CET-4 scores, and the method to determine the k value of the grouping was given. When the initial value of k is 5, the result is ideal. According to the analysis results, formulate English teaching arrangements suitable for the development of such students, and classify them, so as to improve the pass rate of students' CET-4 exam.
RANCANG BANGUN SISTEM PERINGATAN DINI BAHAYA AKTIVITAS GUNUNG BERAPI BERBASIS MIKROKONTROLER ARDUINO

This research aims to design and build an early warning system device of volcanoactivity hazards based on Arduino microcontroller that can monitor changes in temperature, soilmoisture and tremor through sensors placed in the environment around the crater. This earlywarning system of volcano activity hazards is relatively simple but can be very useful to helpgovernment institutions and also the public which will reduce the risk of data collection directlyand also speed up the public to get information so that they can avoid the radius of danger. Theearly warning system of volcano activity hazards is also flexible with wifi coverage areas thatrange more than 100 meters. Based on research and test that has been done shows that thesystem created has a good effectiveness and flexibility which is able to send monitoring resultsto the ThingSpeak and then display it on a smartphone application in realtime.
The Connections Among Hamming Metric, <i>b</i>-Symbol Metric, and <i>r</i>-th Generalized Hamming Metric

The <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$r$ </tex-math></inline-formula> -th generalized Hamming metric and the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$b$ </tex-math></inline-formula> -symbol metric are two different generalizations of Hamming metric. The former is used on the wire-tap channel of Type II, and the latter is motivated by the limitations of the reading process in high-density data storage systems and applied to a read channel that outputs overlapping symbols. In this paper, we study the connections among the three metrics (that is, Hamming metric, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$b$ </tex-math></inline-formula> -symbol metric, and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$r$ </tex-math></inline-formula> -th generalized Hamming metric) mentioned above and give a conjecture about the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$b$ </tex-math></inline-formula> -symbol Griesmer Bound for cyclic codes.
Netflix Movie Recommendation System Using Collaborative Filtering With K-Means Clustering Method on Twitter

Nowadays, the development of technology is very rapid, so watching movies at home has become a means of entertainment. Netflix is one of the platforms for watching movies and provides various movie titles. However, because of the many movie titles, it makes it difficult for users to determine the movie they want to watch. The solution to this problem is to provide a recommendation system that can provide movie recommendations to watch. Collaborative filtering is a method that exists in the recommendation system by providing recommendations based on the ratings given by other users. Collaborative filtering is divided into two, namely based on items (item-based) and based on users (user-based). Twitter is a social media used to write posts called tweets. For this system, tweets serve as data that will be processed into ratings. This research was conducted using k-means clustering with collaborative filtering and collaborative filtering only. By using a dataset obtained from Twitter by crawling data and added with ratings from IMDb, Rotten Tomatoes, and Metacritic. Which resulted in a dataset with 35 users, 785 movie titles, and 6184 reviews. Then preprocessing the data with text processing, polarity, and labeling. And get the dataset that will be used for this experiment. The results of this research test show that k-means clustering with collaborative filtering gets the best results with the best prediction of 2.8466, getting an MAE value of 0.5029, and an RMSE value of 0.6354
Klasterisasi Perguruan Tinggi Swasta di Madura Berdasarkan Kinerja Sumber Daya Manusia dan Mahasiswa Menggunakan Metode K-Means Clustering

The number of private universities in Indonesia in 2020 is 3,044 private universities, in East Java 328 private universities and in Madura 30 private universities. The number of private universities in Indonesia causes intense competition. Colleges should strive to maintain and improve performance in order to ensure their activities. Therefore, it is necessary to do or group private universities based on the performance of human resources and students to encourage these universities to improve their performance. The grouping of private universities is carried out using the k-clustering method which groups data into several clusters based on data groups which are. The results of this study, the grouping of private universities in Madura into 3 clusters, namely: Cluster 1 there are 4 private universities, Cluster 2 there are 7 private universities, and Cluster 3 there are 19 private universities.
ENGLISH SPEAKING ANXIETY AMONG INDONESIAN JUNIOR HIGH SCHOOL LEARNERS: IN SEARCH OF CAUSES AND SOLUTIONS

In the last few decades, foreign language speaking anxiety (hereafter, FLSA) has been a debatable investigative issue among linguists and TESOL practitioners. One of the most salient factors is it generates an incapacitating impact for speakers to communicate orally in English as a foreign language. However, delving learning activities as a cause of FLSA and its solutions, notably in Indonesian secondary school level remains scarce. To fill the void, this study scrutinized the specific learning activities causing learners’ FLSA in the classroom and the solutions to resolve them. Three junior high school learners were recruited as the participants. The data were collected through semi-structured interviews and analyzed thematically (Braun &amp; Clarke, 2006). On the one hand, the findings outlined that the students suffered from FLSA when they engaged in questions and answer session of the classroom English language learning activities and speaking performance activities. On the other hand, the solutions of such FLSA encompassed focusing on the learning process and ignoring the disruptive behaviour of their classmates. Pedagogically, creating a less anxious atmosphere of learning English speaking practices enables students to successfully acquire English language skills (e.g., speaking) and adapt to appropriate social and academic milieu.
Pengembangan Sistem Informasi Video Conference Menggunakan Metode Rapid Application Development Berbasis Website

Technological advances can also make it easier to communicate, by conducting video conferences, it is no longer necessary to meet in person during meetings. There have been many platforms used for conducting meetings, but having your own application within the agency or company can be more effective and efficient and data security in the agency is also maintained. At this time, the Yogyakarta Communication and Information Office does not yet have its own meeting application. Based on these problems, the author proposes a video conference information system design for meetings at the Yogyakarta Information and Communications Office. The design uses the RAD method and uses UML (Unified Modeling Language) modeling which consists of use case diagrams, activity diagrams, sequence diagrams and class diagrams. The results of this study resulted in a website that could be used for video conferencing by related agencies.
The Role of Using Thinking Aloud Pairs Problem Solving (TAPPS) Strategy in Teaching Reading Comprehension to EFL Preparatory School Students

Thinking Aloud Pairs Problem Solving has been used as a strategy in teaching reading comprehension. Students should read, re-read silently, think aloud, verbalize what they think, and discuss and share information (work in pairs) to solve problems that are related to the reading passage .This strategy helps students to evaluate their reading which leads them to produce a better comprehension of the text. These aims are supposed to be achieved as follows:&#x0D; &#x0D; Finding out the role of using (TAPPS) strategy on EFL preparatory school students' achievement in reading comprehension.&#x0D; Finding out if there is any significant difference between the experimental group's achievement at the recognition and production levels.&#x0D;
Research and application of neural network approaches to solving image recognition problems

The paper investigates neural network approaches to solving number recognition problems and develops an algorithm for creating authentic datasets. In the course of the work, research and development of an algorithm for creating authentic datasets for solving the problem of number recognition is carried out. When solving image recognition problems, it is advisable to use neural network technologies, but often there is a problem of lack of data to form a full-fledged training sample during recognition. An algorithm has been developed to create a set of artificial data appropriate for use in training neural networks. The recognition of number plates and wagon numbers is assumed to be the scope of application. An algorithm that forms a set of synthetic images marked up for training has been created. The result of the algorithm application is a dataset appropriate for supplementing the training sample when training neural networks in the field of recognition of number plates and wagon numbers.
SUPPORT TECHNOLOGIES FOR STUDENTS IN ACADEMIC SUCCESS CENTERS IN UNIVERSITIES OF THE USA

The article presents the results of research into the activities of Academic Success Centers (ASC) in Universities of the USA. The need for their functioning has been updated with the help of an analysis of the general condition of the US higher education system based on various statistical indicators, which are presented in the “Report on the Condition of Education 2022. U.S. Department of Education.” It was found that the majority of after-school education institutions are faced with the problem of ensuring the academic success of students and their retention in the educational institution. The author found that the main goal of the Centers is to systematically support students in achieving educational goals and realizing their academic potential. The centers create diverse opportunities for students to develop skills that contribute to academic success and social adaptation, which in turn enable students to achieve academic and personal goals through effective learning, interpersonal development, personal responsibility, and leadership. The Centers hold seminars and trainings on strategies and skills for effective learning, development of cognitive processes, effective reading and writing of texts, essays, preparation and preparation of current and final tests, time management; services of tutoring, academic coaching, mentoring, tutoring, additional instruction, explanations and exercises for the formation of soft skills and long life education are provided. Centers also offering activity is motivational training, leadership training, commitment to success, interpersonal communication, and health care. It was found that the permanent staff of the Centers is not numerous. Successful students and post-graduate students are actively involved in the work of the Centers both on the terms of paid work and on the basis of volunteering. Educators involved in the work previously undergo appropriate training in order to acquire the qualifications of a trainer (coach), mentor, training partner, assistant consultant, etc. It was established that the values for the Centers are: students, excellence, leadership, enthusiasm, and respect. The conducted research actualized the need for a thorough systematic study of Academic Success Center activity in Universities of the USA with the aim of introducing successful aspects of their activity into the practice of higher educational institutions of Ukraine
Extreme Gradient Boosting: A Machine Learning Technique for Daily Global Solar Radiation Forecasting on Tilted Surfaces

Enhancing solar irradiance and accurate forecasting is required for improved performance of photovoltaic and solar thermal systems. In this study, Extreme Gradient Boosting (XGBoost) model was developed using three input parameters (time, day number, and horizontal solar radiation) and was utilized to forecast daily global solar radiation on tilted surfaces. The proposed model was built using XGBRegressor with five generations, 100 n estimators, and a learning rate of 0.1. Three statistical metrics, such as the coefficient of determination (R2), root mean square error (RMSE), and mean absolute error (MAE), were used to compare the model’s results to observed solar radiation data from the Nation Centre for Energy, Research and Development, University of Nigeria, Nsukka. The results showed improved prediction accuracy and XGBoost capability to estimate daily global solar radiation on tilted surfaces. In the training section, the proposed model had a statistical performance of R2 = 0.9977, RMSE = 1.6988, and MAE = 1.081, and in the testing section, R2 = 0.9934, RMSE = 2.8558, and MAE = 2.033. XGBoost model demonstrated a better performance when compared with other models in the literature. As a result, the proposed model provides an effective approach for estimating solar radiation.
Research on Underwater Image Semantic Segmentation Method Based on SegNet

At present, there is little research on underwater image semantic segmentation, and the effect of training using the traditional semantic segmentation network model on land is not ideal.This paper analyzes the current development of underwater image semantic segmentation, establishes a multi-objective underwater image semantic segmentation dataset, and proposes a network model for the impact of underwater complex conditions on semantic segmentation.Experiments show that this network has better segmentation effect than SegNet network in processing underwater images.