Reviewerly/exHarmony huggingface dataset:
Realization and Investigation of Non-Reciprocal Raman Gain in a Nanophotonic System

We demonstrate non-reciprocal amplification of light using Raman gain. The non-reciprocal response originates from spin-polarized atoms chirally coupled to a nanophotonic waveguide. We show that the gain scales superlinearly with the number of emitters.
SEISMIC RAY TRACING USING ANN-BASED EIKONAL SOLVER

In this work we investigate the potential of seismic ray tracing based on the seismic travel-time field (i.e., solution of the eikonal equation) computed using artificial neural networks and conventional finite-differences. In a series of numerical tests, we show that the network-based eikonal solver requires considerably less dense computational grid than the finite-difference method.
SELF-EXAMINATION PROCEDURE OF AN EDUCATIONAL ORGANIZATION IN THE CONTEXT OF DIGITAL TRANSFORMATION OF THE EDUCATIONAL PROCESS: MAIN DIRECTIONS FOR IMPROVEMENT

SELF-EXAMINATION PROCEDURE OF AN EDUCATIONAL ORGANIZATION IN THE CONTEXT OF DIGITAL TRANSFORMATION OF THE EDUCATIONAL PROCESS: MAIN DIRECTIONS FOR IMPROVEMENT. The state policy in the field of education is aimed.
A Study on the Effectiveness of Career Exploration Program for Middle School Students Using the WDEP of Reality Therapy

The purpose of this study is to verify the effects of middle school students'' career exploration program using Reality Therapy (Want Doing Evaluation Planning) on self-esteem and career decision-making self-efficacy. The research questions are as follows. First, what is the effect of middle school students'' career exploration program using WDEP on self-esteem? Second, what is the effect of middle school students'' career exploration program using WDEP on career decision-making self-efficacy? The subjects of this study were middle school students in D city, and they were provided 10 times per session for 100 minutes per session once a week. The experimental design was designed by pre-post test of the experimental group. In this study, Wilcoxon sign rank test was conducted using SPSS/WIN 27.0 to investigate the effects of middle school students'' career exploration program using Reality Therapy on self-esteem and career decision-making self-efficacy. The results of this study are summarized as follows. First, there was significantly improved in the self-esteem (Z=2.66, p<.05). It means that the self-esteem of the middle school students who participated in the career exploration program was significantly improved. Second, there was a significantly improved in the career decision-making self-efficacy (Z=2.67, p<.05). It means that the career decision-making self-efficacy of the middle school students who participated in the career exploration program was significantly improved. In conclusion, the career exploration program used in this study improved self-esteem and career decision-making self-efficacy of middle school students. Therefore, the career exploration program for middle school students using the Reality Therapy technique can be an effective method for career exploration of middle school students, and it can be usefully used in school field for career education and career guidance of middle school students.
Implications of Laozi’s political thoughts from the standpoint of Social Policy

The purpose of this study is to explore the study framework through categorizing the contentsof Laozi’s political thoughts and establishing the dimensions of social policy and to grasp theirimplications from the standpoint of social policy by using the framework. The implications ofLaozi’s political thoughts from the standpoint of social policy are such as followings. First,Laozi’s political thoughts shares human dignity, social solidarity consciousness, and freedomamong the relative values of social policy. Second, His political thoughts shares some part ofhuman respect or human dignity in relation to the purpose of social policy. The primary targetperson of social policy should become social disadvantaged people and then nation peoplebecome next. Third, His political thoughts suggest the imperative requirements such as peacemaintenance and war opposition in order to construct welfare state or welfare society. Therefore Laozi’s thoughts including his political thoughts should be highlighted and utilized invarious aspects covering social welfare and social policy.
Student Efforts in Rural Areas to Face Problems Nahwu Mobile Learning Online

Online learning that a solution to education during the COVID19 has created a problem for the unprivileged society as limited internet access, but they have kept participating; students made several efforts. This study aims to determine the actions of students living in rural areas in overcoming the problems of online learning nahwu for students of STIQ Amuntai who live in rural areas. This study used a descriptive qualitative approach. The subjects of this study were several students of the IIB PBA STIQ Amuntai. They live in rural areas and settle far from the Amuntai sub-district, South Kalimantan, Indonesia. Data were obtained through interview and documentation techniques with 20 students. The data were analyzed using data reduction, presentation, and conclusion drawing, then data accuracy with the persistence of observation and triangulation. The results of the study are the efforts made by these students in overcoming problems such as unstable signals, lack of focus in studying, low telephone specifications, limited internet quota, difficulty understanding material, little reference material, and boredom, namely: a) going to a place that has a signal (network) stable b) go to a place that is not noisy; c) study in groups on one mobile phone; d) search for free wifi; e) foster self-motivation; d) preparation of materials and independent search of additional literature. Therefore, this study suggests that institutions need to be involved in solving problems related to limited access to offline learning or collaboration with internet network providers.
CCATMos: Convolutional Context-aware Transformer Network for Non-intrusive Speech Quality Assessment

Speech quality assessment has been a critical component in many voice communication related applications such as telephony and online conferencing. Traditional intrusive speech quality assessment requires the clean reference of the degraded utterance to provide an accurate quality measurement. This requirement limits the usability of these methods in real-world scenarios. On the other hand, non-intrusive subjective measurement is the ``golden standard" in evaluating speech quality as human listeners can intrinsically evaluate the quality of any degraded speech with ease. In this paper, we propose a novel end-to-end model structure called Convolutional Context-Aware Transformer (CCAT) network to predict the mean opinion score (MOS) of human raters. We evaluate our model on three MOS-annotated datasets spanning multiple languages and distortion types and submit our results to the ConferencingSpeech 2022 Challenge. Our experiments show that CCAT provides promising MOS predictions compared to current state-of-art non-intrusive speech assessment models with average Pearson correlation coefficient (PCC) increasing from 0.530 to 0.697 and average RMSE decreasing from 0.768 to 0.570 compared to the baseline model on the challenge evaluation test set.
E-College : an aid for E-Learning systems

The use of Android apps has significantly increased over the past few years, making android the most accepted and trusted operating system for smart devices. According to a survey, in 2020, over 30.5 billion Android mobile apps were downloaded compared to merely 6 billion in 2016, which is quite noteworthy. People worldwide are also becoming habitual to the use of android apps such that they want everything to be available on their mobile devices. The authors have developed ‘E-College’ - an android-based mobile learning application that helps users grasp various programming languages like C++, Java, and Python and help them with their undergraduate computer engineering course curriculum-related resources. The proposed application allows the learner to access a particular programming language's tutorials and explains it with an example and the required code snippet. Using this application, users can also assess themselves by utilizing the provided quiz section, which has various questions. The proposed mobile application also has a recommendation system section that uses machine learning techniques to intelligently serve the most relevant and suitable content for each user. It considers the user's previous learnings on the application and suggests new and relevant learning content for that particular user. During the ongoing global pandemic situation, E-college application is the most effective way to learn and acquire technical skills without stepping out of their home and fraee of cost.
3 Social media and learning in an era of coronavirus among chemistry students in tertiary institutions in Rivers State

3 Social media and learning in an era of coronavirus among chemistry students in tertiary institutions in Rivers State was published in Volume 3 Computational, Education, and Materials Science Aspects on page 37.
Repetition and Replication: Laying the Groundwork for an Empirical Study

How easy is it to repeat a previous corpus-based study? Repetition is a basic demand of scientific investigations. Hence our focus in this chapter is on an attempt to repeat some studies by Geoffrey Leech of modal verbs and word frequencies. In failing to repeat a number of observations we note the difficulty of repeating studies in corpus linguistics, in spite of the field having proposed that the ability to do this is one of its distinct strengths.
References

The Science of Deep Learning emerged from courses taught by the author that have provided thousands of students with training and experience for their academic studies, and prepared them for careers in deep learning, machine learning, and artificial intelligence in top companies in industry and academia. The book begins by covering the foundations of deep learning, followed by key deep learning architectures. Subsequent parts on generative models and reinforcement learning may be used as part of a deep learning course or as part of a course on each topic. The book includes state-of-the-art topics such as Transformers, graph neural networks, variational autoencoders, and deep reinforcement learning, with a broad range of applications. The appendices provide equations for computing gradients in backpropagation and optimization, and best practices in scientific writing and reviewing. The text presents an up-to-date guide to the field built upon clear visualizations using a unified notation and equations, lowering the barrier to entry for the reader. The accompanying website provides complementary code and hundreds of exercises with solutions.
Optimal Bi-Annual Tilt Angles and Optimal Tilt Transition Timing for Fixed Tilt Arrays in the United States

Abstract As global dependency on renewable energy grows, it is imperative to utilize every Photovoltaic (PV) panel in the most efficient way possible. An important consideration for increasing PV panel energy production is to carefully select the tilt angle relative to the ground of the installed panel. Tracking arrays resolve this issue by dynamically tracking the sun throughout the course of the day, but tracking technology includes additional capital costs and is not affordable for residential systems. The goals of this study are to explore the use of a bi-annual fixed tilt array, where the tilt angle of the fixed array is changed at two times in the year to better capture the seasonal variation in solar irradiation. The goal of this study is to use optimization techniques to resolve the ideal tilt angles as well as the optimal time to change between these two angles for every state in the continental United States. Biannual arrays are then compared to fixed tilt and 1D tracking arrays while examining local weather variations and their effect on the optimal PV tilt angle and solar PV production. In general, PV panels with a fixed tilt in states at higher latitudes collect 90% of the energy that a 1D tracking array would collect, whereas bi-annual tilt angle array produce on average 97% of the energy that a 1D tracking array collects, making the bi-annual tilt method nearly as effective as 1D tracking at these latitudes. Fixed tilt arrays in the southern United States collect on average 85% of the energy that a 1D tracking array would collect, whereas bi-annual tilt arrays in the southern United States produce at maximum 90% of the energy that a 1D tracking array produces. Nearly all states optimize energy production when the tilt angle is changed during the month of March and the month of August. This paper also examines the relationship between summer and winter temperatures and cloud cover, and their effect on optimal tilt and overall PV performance.
Measuring the Optical Constants for Adaptable Spectral Libraries

To support stand-off detection, spectral libraries are being developed that include the optical constants, n(ν) and k(ν). Variable angle spectroscopic ellipsometry and single-angle reflectance are used to derive these data, enabling the reference spectra to be modeled for different parameters.
A Proposal of Code Modification Problem for Self-study of Web Client Programming Using JavaScript

web client programming JavaScript HTML CSS code modification coding reading self-studyIn current societies, web application systems take central roles in computer systems.Thus, web client programming using JavaScript has increased values to add dynamic features and functions in web pages by well working with HTML and CSS.In this paper, as a new type of exercise problem for its self-study, we propose a code modification problem (CMP).In CMP, a source code with HTML/CSS elements and JavaScript functions for study, and the screenshots of both the original and the slightly altered web pages are provided to the students, who will need to edit the source code to generate the modified page.The goal of CMP is for students to carefully read the source code and comprehend how to use the components and functions through modifying parameters, values, or messages there.String matching is used to check the correctness of any answer.Through solving CMP instances, the students are expected to master the basic concepts of web client programming.To evaluate the proposal, we generated and assigned 25 CMP instances to 37 students in Okayama University.In addition, we offered project assignments of freely implementing source codes by referring to solved CMP instances to evaluate their learning effects.With the solution results, the validity of the proposal has been confirmed.
Online SLAM-Integrated Kinematic Calibration for Industrial Manipulators using RGB-D Sensors

Kinematic calibration of industrial manipulators is required for accurate work. Moreover, it is necessary to measure the environment around the manipulator for motion planning. However, it takes long time for kinematic calibration and measurement of the environment around the manipulator. We study SLAM-integrated kinematic calibration, which can simultaneously calibrate the kinematic parameters of an industrial manipulator and create a map of the environment around the manipulator. This method can perform efficient kinematic calibration and measurement of the environment around the manipulator. However, when errors occur in the kinematic parameters due to changes over time or accidents, it is necessary to stop the work and calibrate. In this paper, We eliminate the need to stop the work for calibration by performing SLAM-integrated kinematic calibration online during operation. The effectiveness was confirmed by verification in a virtual environment. Verification in the real environment revealed that there is a room for accuracy improvement.
EMG measurement of muscles around the oral cavity in speaking English

The purpose of this study is to improve the pronunciation of English, something that Japanese people have difficulty with. Therefore, this study focuses on the Japanese pronunciation of English and investigates the movement of the muscles around the oral cavity in speaking English using EMG measurement. We investigated the pronunciation of vowels, which is important in English pronunciation, and measured English words that containing short and long vowels among single vowels. In order to investigate whether it is possible to identify single vowels from the acquired EMG signals, we used root-mean-square analysis, which quantifies the graph, and wavelet analysis, which can analyze the signal into frequency and time components. Currently, we haven't got enough clear distinction between single vowels, yet we will seek further evaluation methods for identifying vowels.
Clustering of flag-raising play using IHMM and Convolutional Autoencoder

Human motion recognition is a widely known research topic in computer vision. In supervised learning of motion, it is necessary to collect and label a huge amount of data for training. We thought that labeling could be done efficiently by automatically dividing the collected data into several patterns in advance when preparing the teacher data. We extracted the features of the motion data of the flag-raising play using the convolutional autoencoder, and clustered using the Infinite Hidden Markov Model. We use motion capture to measure flag-raising play, and PERCEPTION NEURON is used for motion capture. The flag-raising play consists of raising and lowering the left hand and raising and lowering the right hand. The accuracy of the convolutional autoencoder has been improved by updating the model of the convolutional autoencoder and the preprocessing of the data. we got closer to the number of correct tags by updating the model of the convolutional autoencoder from the result of Infinite Hidden Markov Model.
Peranan Cloud Computing Dalam Bisnis Perusahaan

Cloud computing has existed almost at the same time as when the Internet was introduced to the public. But this term is not as popular as the Internet in many countries, for example in Indonesia. Although cloud computing has been widely used for storages and backups, there are more of its capabilities that have not been explored. This paper aims to introduce the advantages of cloud computing for business, since many small and medium enterprises can not afford to develop their own websites at their local premises. The main reasons for that condition are inadequate fund for the costs and the lack of IT staff to develop and maintain their websites. With cloud computing, those enterprises can compete on the virtual world with small costs.
Quantum advantage through the magic pentagram problem

Through the two specific problems, the 2D hidden linear function problem and the 1D magic square problem, Bravyi et al. have recently shown that there exists a separation between $\mathbf{QNC^0}$ and $\mathbf{NC^0}$, where $\mathbf{QNC^0}$ and $\mathbf{NC^0}$ are the classes of polynomial-size and constant-depth quantum and classical circuits with bounded fan-in gates, respectively. In this paper, we present another problem with the same property, the magic pentagram problem based on the magic pentagram game, which is a nonlocal game. In other words, we show that the problem can be solved with certainty by a $\mathbf{QNC^0}$ circuit but not by any $\mathbf{NC^0}$ circuits.
Wacky Jabber

A sweetish suite of machine translations of a pseudo-Swedish paragraph concocted on a whim by Douglas Hofstadter. The resulting gobbledygook reveals the true zombie-like nature of these highly vaunted and often virtuosic programs.
Interactive academic EFL writing assisted by GT for Chinese non-English major students

An updated version of Google Translate (GT) incorporating a system of artificial intelligence, Google Neural Machine Translation (GNMT) was launched in 2016. Some studies have been conducted to examine the use of the upgraded GT as an educational tool, especially for college students majoring in English. The present study focused on implementing GT into academic English writing for Chinese non-English major university students to understand its effectiveness, advantages, and impact. Students successively composed an essay in Chinese, completed a corresponding composition in English, translated their Chinese text into English using GT, and finally revised their self-written (SW) versions by referring to their GT-translated versions. Three types of online computational assessments were used to evaluate their writing. Results indicated that the GT-translated versions were significantly better than the SW versions. Students significantly improved their English writing in the revised self-written (RSW) versions after interacting with instant feedback from their individual GT-translated versions, with an even greater improvement for the students with lower English proficiency. Students also held positive perceptions about the use of GT as a useful tool in academic EFL writing.
Deep Transfer Learning Approach for Identification of Daily Living Human Activities

Deep learning is one of the of AI methods where there are number of layers of information which are addressed as neurons and assists with understanding the information proficiently. AI helps the machines and frameworks to comprehend the human activities themselves and afterward answer in a manner that is controlled effectively toward the end client of that specific application, framework and so forth. Various deep learning calculations are utilized to execute the idea where the profound gaining begins the interaction by taking information from one layer and give it to the following layer of information. A great deal of data and information is put away as layers and order where they are associated with one another by organization of neurons which go about as data of interest for each layer. Transfer learning is the new concept in deep learning where the data and information is transferred from one model to other model and thus it saves time and resources and cost of utilising it. Deep transfer learning contributes to get results in different model by using already existing model or by utilising few components of already existing model. There are many profound learning systems which are utilized across different spaces to simple and work on the errand of the business. The paper will explain the types of deep transfer learning methods, its benefits as well as challenges to implement the concept. It is widely used to identify daily human activities.
Statistical Analysis of Cloud Layers and Derivation of Motion Directions of Two Layer Clouds

The daytime sky at Toyohashi city was observed every five seconds from April 2021 to December 2021 by using two all-sky cameras. Based on the images, the number of the cloud layer was statistically analyzed for every hour. The results indicate that two-layer clouds occupy a large temporal fraction as well as one-layer clouds. Therefore, the motion of the two-layer clouds was examined by the optical flow analysis with Lucas-Kanade method. Two directions were clearly obtained from the polar histogram of the angle of the optical flow vectors.