Reviewerly/exHarmony huggingface dataset:
REDUCING THE CLOCKWISE-ALGORITHM TO k LENGTH CLASSES

In the present paper, we consider an optimization problem related to the extension in k-dimensions of the well known 3x3 points problem by Sam Loyd. In particular, thanks to a variation of the so called “clockwise-algorithm”, we show how it is possible to visit all the 3^k points of the k-dimensional grid given by the Cartesian product of (0, 1, 2) using covering trails formed by h(k)=(3^k-1)/2 links who belong to k (Euclidean) length classes. We can do this under the additional constraint of allowing only turning points which belong to the set B(k):={(0, 3) x (0, 3) x ... x (0, 3)}.
Revisiting maximal average fidelity of teleportation

We obtain the maximal average fidelity corresponding to the standard quantum teleportation protocol for an arbitrary isotropic distribution of input states and an arbitrary resource state. We extend this result to a family of von Neumann measurements, which includes the projections onto the computational and Bell basis, considering a Bell-diagonal resource state. We focus on three specific isotropic distributions of input states: (1) completely mixed input states, (2) states with a certain (fixed) degree of purity, and (3) quasi-pure input states. We show that the standard quantum teleportation protocol can teleport arbitrary mixed states with higher average fidelity than its classical counterpart even when the resource of the protocol is a non-entangled state, specifically, a separable Werner state. Moreover, we find that the maximum average fidelity obtained with classical–quantum states used as a resource in a standard teleportation protocol also exceeds the classical fidelity. To establish the role played by the presence or absence of quantum correlations in the resource state and their relation with the correlations present in the von Neumann measurement performed by Alice, we analyze in detail the case of Bell diagonal resource states employing a family of monoparametric basis for which both the Bell and the computational (non-correlated) basis are included. Only in the case where the basis on which Alice measures is completely uncorrelated (computational basis) the maximum average fidelity does not exceed the classical fidelity for any resource state. In all other cases, the maximum average fidelity exceeds the classical one for a certain range of parameters describing the resource state, evidencing the importance of the correlations present in the measurements.
Locality-of-Reference Optimality of Cache-Oblivious Algorithms

Previous chapter Next chapter Full AccessProceedings Symposium on Algorithmic Principles of Computer Systems (APOCS)Locality-of-Reference Optimality of Cache-Oblivious AlgorithmsPeyman Afshani, John Iacono, Varunkumar Jayapaul, Ben Karsin, and Nodari SitchinavaPeyman Afshani, John Iacono, Varunkumar Jayapaul, Ben Karsin, and Nodari Sitchinavapp.31 - 45Chapter DOI:https://doi.org/10.1137/1.9781611977059.3PDFBibTexSections ToolsAdd to favoritesExport CitationTrack CitationsEmail SectionsAboutAbstract The program performance on modern hardware is characterized by locality of reference, that is, it is faster to access data that is close in address space to data that has been accessed recently than data in a random location. This is due to many architectural features including caches, prefetching, virtual address translation and the physical properties of a hard disk drive; attempting to model all the components that constitute the performance of a modern machine is impossible, especially for general algorithm design purposes. What if one could prove an algorithm is asymptotically optimal on all systems that reward locality of reference, no matter how it manifests itself within reasonable limits? We show that this is possible, and that excluding some pathological cases, cache-oblivious algorithms that are asymptotically optimal in the ideal-cache model are asymptotically optimal in any reasonable setting that rewards locality of reference. This is surprising as the cache-oblivious framework envisions a particular architectural model involving blocked memory transfer into a multi-level hierarchy of caches of varying sizes, and was not designed to directly model locality-of-reference correlated performance. Previous chapter Next chapter RelatedDetails Published:2022eISBN:978-1-61197-705-9 https://doi.org/10.1137/1.9781611977059Book Series Name:ProceedingsBook Code:APOSC22Book Pages:ii + 75
Continuous vital signs monitors: a replacement for traditional vital signs?

Lightweight, wireless vital signs monitors offer the ability to continuously monitor ward-based patients, which could revolutionise identification of patient deterioration. Continuous vital signs require correlation to traditional vital signs measurements in acutely unwell inpatients if we are to understand how best to integrate continuous data into track-and-trigger systems. We report data collected during Continuous Signs Monitoring in COVID-19 Patients (COSMIC-19) (clinicaltrials.gov: NCT04581031), a feasibility study of continuous vital signs data recorded using wearable sensors in hospitalised patients with COVID-19. The data presented here explore data completeness from the continuous sensors and compare traditional and continuous vital signs.
Image Search System Based on Machine Learning

Abstract Since the 21st century, with the continuous maturity of network technology and its integration with the education field, traditional face-to-face communication has gradually expanded to the virtual network environment. In the online learning environment, students can use the online platform to communicate directly with teachers, no longer limited by time and region. The time and space breakthrough of teacher-student interaction has brought development opportunities for teachers to constantly contact students with a long-term management mechanism. Based on this situation, this article uses artificial intelligence technology to build a network communication platform. This article first analyzes the application status of artificial intelligence technology in the network communication platform, and then introduces the artificial intelligence technology applied in this article. Then, this article uses artificial intelligence technology to design a network communication platform, and test the function and performance of the platform. The test results show that the function of the system is very accurate and reliable, and the performance of the system is sufficient to support nearly 10,000 users at the same time.
Distance education and return to schools in the minds of ukrainian schoolchildren

As a result of the coronavirus pandemic, many societal systems have suffered a future shock. Among them is the education system. Over the past two years, much research has focused on the problems of the pandemic period, which have arisen in both educators and learners. However, there is still no comprehensive understanding of them. The ‘Identification of barriers hindering the Ukrainian and Polish schoolchildren’ return to schools ’project, funded by NAWA, attempted to study and compare such problems among schoolchildren in Ukraine and Poland. This text presents the main problems during the distance learning period of Ukrainian schoolchildren, which they mentioned in a representative sociological study. One of them was the fatigue of distance education and the difficulty of perceiving educational material through the screen.
Applying Social Forms: The Project Method in Teaching Foreign Languages

The article discusses applying the project method as one social forms of teaching foreign languages. The author of the article considers that in project work students learn to cooperate, and cooperative learning fosters in them such moral values as mutual assistance, desire and ability to empathize; it improves general culture of communication and social behavior in general, forms creative abilities and activity of students, i. e. there is an inseparable process of training and education, and leads students to practical possession of a foreign language.
Relatively Integrated Ship Navigation by H∞ Fusion Filters

For the system with unknown statistical property noises, the property that the energies of the system noise and the observation noise are limited is utilized in this paper. On this basis, two novel fusion algorithms are proposed for ship integrated navigation with the relative navigation information, broadcasted by the Automatic Identification Systems (AISs) in the adjacent ships. Firstly, an H∞ fusion filtering algorithm is given to deal with the navigation observation messages, under the centralized fusion framework. The integrated navigation method based on this algorithm cannot deal with the asynchronous navigation messages in real time. Therefore, a sequential H∞ fusion filtering algorithm is also given to sequentially deal with the asynchronous navigation messages, secondly. Finally, a computer simulation is employed to illustrate the validity and feasibility of the sequential method.
Single-Image Super-Resolution Reconstruction Based on the Differences of Neighboring Pixels

The deep learning technique was used to increase the performance of single image super-resolution (SISR). However, most existing CNN-based SISR approaches primarily focus on establishing deeper or larger networks to extract more significant high-level features. Usually, the pixel-level loss between the target high-resolution image and the estimated image is used, but the neighbor relations between pixels in the image are seldom used. On the other hand, according to observations, a pixel's neighbor relationship contains rich information about the spatial structure, local context, and structural knowledge. Based on this fact, in this paper, we utilize pixel's neighbor relationships in a different perspective, and we propose the differences of neighboring pixels to regularize the CNN by constructing a graph from the estimated image and the ground-truth image. The proposed method outperforms the state-of-the-art methods in terms of quantitative and qualitative evaluation of the benchmark datasets. Keywords: Super-resolution, Convolutional Neural Networks, Deep Learning
A virtuális valóság technológiai és egészségügyi fejlődése 2000-ig.

Virtual reality is a 360-degree artificial environment, which creates the sense of real presence in spatial terms. Several medical fields utilize its mentioned property. The aim of this study is to show the history of virtual reality from 1960 to 2000 and its first ten years in healthcare. Struggling technological development was led by talented computer scientists as Ivan Sutherland and Thomas Furness. Education and psychiatry were the first two fields of virtual reality in medicine. Scientists discovered the negative aspects of virtual reality already at the beginning as a cybersickness syndrome. Both technological and medical development was slow however it contributed gradually to our contemporary and highly developed technology.
The Relationship of Economic Growth and Foreign Direct Investment on Financial Development: Empirical Evidence from Palestine

Purpose: The purpose of this research is to investigate the impact and current link between economic growth and foreign direct investment (FDI) on financial development in Palestine, as well as the role of financial development in influencing this relationship.&#x0D; Design/Methodology/Approach: The logical reasoning approach associated with quantitative research was applied in this study, which was backed up by experience and positivism as philosophical viewpoints. Data on economic growth indicators, foreign direct investment (FDI), financial development, and other control variables were also used, spanning the years (1998 to 2019). To determine whether there is an effect and a relationship between economic growth, foreign direct investment (FDI), and financial development in Palestine, Johansen's co-integration analysis method will be used.&#x0D; Results: Johansen's co-integration discovered that economic growth, foreign direct investment (FDI), and financial development have a favourable influence and a Long-Term association. Furthermore, there was a statistically significant relationship between stock market financial development indices and foreign direct investment (FDI).&#x0D; Practical Implications: This study adds to the literature by evaluating whether foreign direct investment (FDI) drives growth through financial development networks and other factors that can drive growth in addition to foreign direct investment (FDI). A well-developed financial market, according to research, will boost the impact of indirect foreign direct investment (FDI) on economic growth. By offering enough liquidity services that increase links between local and global investors, a well-developed stock market will promote capital accumulation activities and output growth.&#x0D; Originality/Value: This study is unique in that it examines the impact and relationship between economic growth and foreign direct investment (FDI) in Palestine on financial development, which must be considered in all developing countries' Long-Term development plans. Simultaneously, this study is a step ahead in examining the relationship between economic growth and foreign direct investment (FDI) in Palestine, as well as their primary function in financial development.
Evaluation of Ground Golf System Which Can Participate Remotely

In recent years, ground golf has become widespread as a place where elderly people can interact with friends while moving their bodies. In this paper we develop and evaluate ground golf system which enable the remote participation in the real ground golf community. This system presents each other ’s live image and voices to remote participants and field participants. In addition, the ball is launched at the same time as the swing of the remote participant. This system enables a new remote communication method. We actually used this system and evaluated it by various methods to clarify the points to be improved.
Introduction to Optimization

Finding the best answer among the various solutions to complex and mathematical problems is called optimization. There are two types of optimization problems; continuous optimization and discrete optimization. Finding the solution in these environments is the best solution for that particular solution. Optimization exists in many fields and sciences, and it shows that if researchers provide the most quality optimization algorithms, it can have a great impact on human life. Optimization is similar to finding a treasure in an area. In this analogy, you have to mobilize a crowd to find this treasure. Since the population does not know the location of the treasure from the beginning, these populations will start searching at random and will reach near to it at a certain time. The topic of the search here is very important. It is very important to find a mechanism that can best organize the population. The search engine must follow certain ideas and rules. In the optimization problem, the most important step is proper search. In optimization issues, the concept of the best answer, best search, best solution and best organization is desired. Nowadays, optimization can be applied everywhere we deal with big data.
The Study of Collostruction Strength between Verb Collexemes and “V+Through” Construction In American English

Construction grammar has attracted increasing attention in the field of linguistics study. With the help of related linguistics software, this paper aims to explore which verbs show strong collostruction strength with the particle “through” in “V+through” construction in American English.
Application of Big Data Information Processing Technology in Improving English Reading Speed

At present, the increasingly mature big data technology and English reading teaching are gradually integrated. Based on the background of big data, this article explores the innovative teaching mode to improve the speed of English reading, clarify the advantages of big data technology in the field of English reading teaching, building a reading teaching platform, designing an effective monitoring mechanism, enriching the application strategies of English reading teaching, and achieving the purpose of improving teaching quality.
A study on the relationship between quality perception and system use for ICT convergence solutions

Due to the impact of the global financial crisis, the global manufacturing industry faced limitations in the growth of the real economy, including a long-term economic recession, increased labor costs and spreading anxiety. In advanced countries, the manufacturing workforce is shrinking due to a decrease in the fertility rate and avoidance of manufacturing, and the industrial structure is changing to a service-oriented economic structure due to low-wage manufacturing avoidance and preference for the service industry, and preference for manufacturing industry is gradually decreasing. Meanwhile, with the introduction of solutions through information and communication technology convergence, companies are changing their form to a different paradigm from the past. With the introduction of solutions through information and communication technology (ICT) convergence, companies are changing their form to a different paradigm from the past. The development of various technologies such as 5G is ultimately changing the management paradigm at all levels. In various studies based on this, it has been argued that the introduction of technology through ICT convergence centered on the 4th industry will become a very important factor in determining future competitiveness through corporate innovation. In addition, traditional manufacturing powerhouses such as the United States, Germany, Japan, and China are also pursuing a direction to adopt integrated smart solution technology that integrates the latest ICT technologies into factories to increase manufacturing competitiveness. Accordingly, in this study, the effect of solution quality factors on acceptance intention and acceptance behavior and mediating effect on quality was empirically verified for companies currently using ICT convergence technology.
Fuzzy control-based manufacturing service composition in graph database

In recent years, the manufacturing industry is changing its way of production enabled by emerging technologies. Enterprises publish visualised resources as services on the cloud. To fulfil a complex manufacturing request, services can be composed together. However, how to compose proper services among a large number of services becomes a challenge. This paper presents a service composition graph model to deal with the challenge by using a graph database. Specifically, the service composition graph model is stored in the Neo4j graph database. Services and their inputs/outputs are stored as nodes in a directed bipartite graph that are connected with edges. The weights of edges are synthesised via a fuzzy control system according to the QoS of services. Possible compositions of services are calculated and pre-composed. When the manufacturing task arrives, an extended Dijkstra algorithm is used to find a solution. Experimental results show that the approach could return a solution satisfying both functional and QoS requirements within a short time.
Predicting bitcoin prices - ANN approach

Bitcoin, the first cryptocurrency is believed to be designed by Satoshi Nakamoto in 2009 as a peer-to-peer structure whereby users can handle directly without requiring an intermediary. Cryptocurrencies have enjoyed some success and 'bitcoin' is now the largest cryptocurrency, with the total number of bitcoins currently valued at approximately 70 billion US dollars. However, globally there are economies which favour the bitcoin and some have banned the same. While many day traders have cash out their funds, veteran traders remain unfazed. In this scenario, it is essential to look into their price behaviour which reveals that there is huge a fluctuation, i.e., highly volatile in nature. Henceforth, their relationships with the trading volume, money supply, lag prices which influences the trade in bitcoin are measured using the ANN model revealing highly significant relationship.
Money, Society, and Trust

Using insights from Georg Simmel’s The Philosophy of Money (1907), the author argues that at its core, the 2008 global financial was a crisis of trust and legitimacy that impacted the relationship between money and society. This essay underscores that by damaging trust in traditional institutions, the crisis led to the creation of new cultures of currencies, such as cryptocurrencies. Seeking to disrupt the government’s monopoly over the scarcity of money, cryptocurrencies are defined by their lack of centralized oversight, open-source software, provable correctness of the underlying transaction protocols, and global community. The author proposes that while their ultimate popularity still remains to be seen, cryptocurrencies represent a culture of alternative currency that many find appealing in light of the severe damage inflicted to trust by the financial crisis. The author emphasizes that perspectives that combine the main lessons of both the humanities and economics are essential for our future in the post-crisis world.
Students’ Perception on the Active Flipped Learning Approach in the Midst of the COVID-19 Pandemic

The purpose of this study is to examine students’ perceptions of the effectiveness of their active learning in a flipped classroom during the COVID-19 pandemic. The participants were 55 students in one of the courses in English language and literature department at a university in Korea. In this study, the researcher used the questionnaire to survey the students’ perceptions of the active flipped learning in an online learning environment. Students’ perceptions of the effects of their active flipped learning in online contexts on their academic and affective aspects were examined. As a result of this study, it was found that students recognized their learning motivation and their interests have gradually improved through active flipped learning by synchronous online learning experiences. Moreover, they considered that their self-directed learning skills were also improved through their asynchronous online learning experiences. Therefore, it is suggested that it is necessary to operate the flipped class systematically with best practice and train instructors with a professional program with best scenarios for successful active flipped learning in online learning contexts.
DeepSolfège: Recognizing Solfège Hand Signs Using Convolutional Neural Networks

Hand signs have long been a part of elementary music theory education systems through the use of Kodály-Curwen Solfège hand signs. This paper discusses a deep learning convolutional neural network model that can identify 12 hand signs and the absences of a hand sign directly from pixels both quickly and effectively. Such a model would be useful for automated Solfège assessment in educational environments, as well as, providing a novel human computer interface for musical expression. A dataset was designed for this study containing 16,900 RGB images. Additional domain-specific image augmentation procedures were designed for this application. The proposed CNN achieves a precision, recall, and F1 score of 94%. We demonstrate the model’s capabilities by simulating a real-time environment.