Reviewerly/exHarmony huggingface dataset:
Braille Innovation Technology in Teaching and Learning Process For Visual Impairment

The innovation of braille makes learning for children with visual impairments easier. The breakthrough braille innovation developed is able to encourage the creation of creative, active, and practical learning for children with visual impairments. This study aims to collect and analyze articles related to innovation technology of braille for teaching and learning process to visual impairment. The design of study used literature review that use data collection methods with search related topics, data analysis and also writing research results. The results of this study that braille innovations technology for reading, writing and conceptualizing of reading are useful in the learning process of children with visual impairments.
An eigenfunction expansion formula for one-dimensional two-state quantum walks

Abstract The purpose of this paper is to give a direct proof of an eigenfunction expansion formula for one-dimensional two-state quantum walks, which is an analog of that for Sturm–Liouville operators due to Weyl, Stone, Titchmarsh, and Kodaira. In the context of the theory of CMV matrices, it had been already established by Gesztesy–Zinchenko. Our approach is restricted to the class of quantum walks mentioned above, whereas it is direct and it gives some important properties of Green functions. The properties given here enable us to give a concrete formula for a positive-matrix-valued measure, which gives directly the spectral measure, in a simplest case of the so-called two-phase model.
Localizing Text in Images and Videos based on Morphology

Many multifaceted images comprise observable text. If the occurrences of this text can be identified, segmented, and recognized automatically, they will be a prized source of high-level semantics; for retrieval and indexing. In this paper, we will propose a novel method for localizing and detecting text in complex images and video frames based on morphology. A morphological Gardient is generated by computing the variance between the dilation and the erosion image. Then the candidate of regions are connected via a morphological closing operation and every text areas are determined used the occurrence of text in each candidate. The identified text regions are localized perfectly via the projection of the text pixels in the morphological Gardient map. This method is sturdy to different position, character size, color and contrast. The updating of the text region between images is also used to minimize the processing time. Tests are realized on divers images to confirm the good efficient of our method.
Contour Propagation for Radiotherapy Treatment Planning Using Nonrigid Registration and Parameter Optimization: Case Studies in Liver and Breast Cancer

Radiotherapy treatments are carried out using computerized axial tomography. In radiation therapy planning, the radiation oncologist must do a manual segmentation of volumes of interest to delineate the organs that should be irradiated. This way of carrying out the process generates long execution times and introduces a subjective component. In this study, a contour-propagation algorithm is formulated to automate the segmentation, based on elastic registration or nonrigid demon registration. A heuristic algorithm to find the parameters that optimize the registration is also proposed. The parameters found along with the contour-propagation algorithm are able to estimate contours of scans with Dice similarity coefficients (DSC) greater than 0.92 and maintain stability with B-spline registration, which takes in the parameters found as input. The study allows for validating the results using the correlation coefficient (CC) to compare the similarity between the voxels’ gray-scale intensity of the estimated tomography and the original tomography, obtaining values greater than 0.96. These values were validated under medical criteria and applied to liver and breast CT scans, indicating good performance for radiation therapy planning.
PEMODELAN TOPIK PADA KELUHAN PELANGGAN MENGGUNAKAN ALGORITMA LATENT DIRICHLET ALLOCATION DALAM MEDIA SOSIAL TWITTER

Large scale social restrictions (PSBB) is a policy issued by the Government of Indonesia as one of the efforts to reduce the spread of the Covid-19 virus. The impact of the policy is that it requires people to conduct activities online . This makes the internet users in Indonesia in the year 2020 up to 73.7%. Each provider must be able to determine strategies in order to maintain the quality of service and customer loyalty. Good reputation for the company is also important, so customers want to use internet services through their company. One of them is by listening to the complaints of the customers towards the company. In this research, modeling the topic of customer complaints carried out using the Latent Dirichlet Allocation Algorithm. The Latent Dirichlet Allocation Algorithm was chosen because the method has good performance. The topic modelling process is carried out using the gibbs sampling estimation. The topic that is often complained to First Media is that internet was turns off while working, while for IndiHome is that the internet often turns off and disconnect. Based on the results of the interpretation, 70% for First Media and 81,81% for IndiHome that these topics had been in accordance with what is complained by customers through their tweets. From the topic that have been known, it can be used as an evaluation for their company in order to maintain service quality and customer loyalty
Hardware/Software Co-Design of a Circle Detection System Based on Evolutionary Computing

In recent years, the strategy of co-designing Hardware/Software (HW/SW) systems has been widely adopted to exploit the synergy between both approaches thanks to technological advances that have led to more powerful devices providing an increasingly better cost–benefit trade-off. This paper presents an HW/SW system for the detection of multiple circles in digital images based on a genetic algorithm. It is implemented on an Ultra96-v2 development board, which contains a Xilinx Zynq UltraScale+ MPSoC device and supports a Linux operating system that facilitates application development. The design is powered by developing an interactive computing environment by means of the Jupyter Notebook platform, in which different programming languages coexist. The specific advantages of each of these languages have been used to describe the hardware component that accelerates the evolutionary computation for circle detection (VHDL), to execute SW-HW interaction functions, as well as the pre- and post-processing of the images (ANSI-C) and to code, evaluate, and document the system execution process (Python). As a result, a computationally efficient application was obtained, with high accuracy in the detection of circles in synthetic and real images, and with a high degree of reconfigurability that provides the user with the necessary tools to incorporate it in a specific area of interest.
Proxy

When we looked at the Decorator design pattern, we saw different ways of enhancing the functionality of an object. The Proxy design pattern is similar, but its goal is generally to preserve exactly (or as closely as possible) the object’s original API while offering certain internal enhancements.
Null Object

We don’t always choose the interfaces we work with. For example, I’d rather have my car drive me to my destination by itself, without me having to give 100% of my attention to the road and the dangerous lunatics driving next to me. And it’s the same with software: sometimes you don’t really want a piece of functionality, but it’s built into the interface. This means you have to provide some value even if you don’t need this particular piece of functionality.
Solar Power Panel Monitoring and Data Acquisition System

Abstract: As the world now is turning towards renewable energy sources and countries like Iceland have obtained 100% renewable energy status and India has also started to lean towards renewable energy, moreover rooftop solar panels are becoming a trend nowadays but In order to know how efficiently the solar photovoltaic system is working and for performance evaluation there should be some monitoring system. Therefore here we propose a system using a microcontroller and internet of things technology using sensors to monitor the parameters of the solar photovoltaic system remotely from anywhere using smart phones and computers using web server. Some solar photovoltaic systems are located in inaccessible locations and it is difficult to monitor it and the solar panels are not utilized to its full efficiency all day ,in order to achieve the solar panel must absorb maximum sunlight every instant , in order to achieve it here we propose a sun tracking technology to control the solar panel and rotate it so it absorbs maximum sunlight every instant .The system is based on a new cost effective technology using a microcontroller and internet of things technology monitors and controls the solar photovoltaic system remotely from anywhere around the world.
Anonymity Technologies in Investigative Journalism: A Tool for Inspiring Trust in Sources

Investigative journalism, like other sectors of social life, has undergone significant changes due to globalization, technological progress, and the Western world’s turn to neoliberalism. This context has facilitated the emergence of new practices within the profession, particularly new modes of communication between journalists and their confidential sources. This qualitative study focuses on the meaning journalists attribute to the use of these technologies in their relationships with their sources. Anonymity tools are being used to build the professional identity of investigative journalism (both collectively and individually) and therefore constitute a resource in the power relationship between journalists and their sources, a relationship that is not fundamentally changed by their use.
Re-engineering the human resource In framework Strategic leadership

The purpose of the research is to discover the nature of the relationship between strategic leadership and its dimensions (strategic orientation, core competences, human capital, organizational culture, organizational control), and human resource re-engineering and its dimensions (the human dimension, the technological dimension, and the organizational dimension). Several questions, including: What is the impact of strategic leadership on human resource re-engineering, and to answer this main question and other questions, the research was built on two main hypotheses, and five sub-hypotheses were derived from each of them. The research using a set of statistical methods and tools (the use of structural equation modeling with partial least squares (PLS-SEM) by (SmartPLS) program for the data obtained by means of a questionnaire distributed to a sample consisting of (66) managers in Fayd Al Qassim Company, as (66) questionnaires were distributed, and (59) correct questionnaires were retrieved, i.e. with a recovery rate of (89%). The research included four sections, the first included the scientific methodology, and the second was specialized In the theoretical framework, the third included presentation and analysis of the results, then the fourth topic came to present a set of conclusions and recommendations.
POLITENESS IN BUGINESE WEDDING CEREMONY

&lt;p&gt;One of the cultural elements of communication that must be considered is politeness. Politeness is indispensable in communication, especially in Southeast Asian cultures, which have degrees of politeness. As cultural aspects affect the communicative language, politeness would be expected in society. One of the politeness implementations is the polite language used in the Buginese traditional wedding ceremony. In order to reveal politeness and its strategies in the traditional Buginese wedding ceremony, the study employed a qualitative method with observation and analytical descriptive approach by examining the politeness strategies and conversational language used in the Buginese wedding ceremony processions. The data were obtained from the video recordings of the wedding ceremony and the interviews with four newlyweds. The result showed that positive politeness strategies were predominantly used in the Buginese wedding ceremony. The study also revealed that the positive politeness strategies were closely connected to the cultural values of South Sulawesi, which showed a strict sequence of the traditional wedding ceremony that must be followed. The sequence symbolizes the tie that binds two human beings in goodness and beneficence, which must be conducted religiously. The study concludes that the language used during the traditional Buginese wedding ceremony adhered to the positive politeness principle, although the nature of the language was conversational.&lt;/p&gt;&lt;p&gt;&lt;strong&gt; &lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Keywords&lt;/strong&gt;: politeness, politeness strategy, polite conversational language, Buginese wedding ceremony.&lt;/p&gt;
Research On The «Aesthetic Education Function» Of Contemporary Russian Chorus Art

In the modern school, there is a serious need for the moral and aesthetic education of the younger generation. In this regard, this article is aimed at identifying or revealing the effectiveness of the use of choral singing in aesthetic development. The leading approach (or method) to the study of this problem is the approach of Kabalevsky, Abdullin, Asafiev, Apraksina, Shkolyar., which makes it possible to comprehensively consider at school and make the work of the choir a social phenomenon at school, is not an easy task, and joint efforts are needed to solve such a problem team leader, choir members, school administration, parents. The choir is a complex organism, the creation of which, and most importantly, its maintenance, formation, development requires tremendous energy, knowledge, and skills of all interested parties. The article presents theoretical provisions, discloses problems and prospects, conducts research and draws conclusions. The materials of the article are of practical value for teachers of schools and gymnasiums. Analysis, synthesis, systematization, generalization, experiment were used as methods. The results of the article are to determine the effectiveness of the use of choral singing in pedagogy. The purpose of the study is to determine the effectiveness of the introduction of choral singing.
An NLP approach to Image Analysis

In Natural Language Processing, measuring word frequency combined with word distribution can yield a precise indicator of lexical relevance, a measure of great value in the context of Information Retrieval. Such detection of keywords exploits the structural properties of text as revealed notably by Zipf’s Law which describes frequency distribution as a ‘long tailed’ phenomenon. Can such properties be found in images? If so, can they serve to distinguish high content items (particular colours coded as RGBs) from low information items? To explore this possibility, we have applied NLP algorithms to a corpus of satellite images in order to extract a number of linguistic-type features in bitmaps so as to augment the original corpus with distributional information regarding its RGBs and observe if this addition improves accuracy throughout a Machine Learning pipeline tested with several Transfer Learning models.
Application Prospects of Artificial Intelligence Technology in Joint All-Domain Command and Control

Joint All-Domain Command and Control (JADC2) is a military development strategy proposed by the U.S. military in response to a new type of competition between major powers; JADC2 focus on breaking barriers between various operational domains, realizing rapid information sharing and dynamic allocation of combat resources, shortening the time of decision making and improving the quality of decision making. The successful application of artificial intelligence (AI) technologies in the fields of image recognition, natural language processing, and task planning reveals the potential of applying related technologies to the field of JADC2. This paper analyzes the core concepts and latest progress of JADC2, summarizes the typical application scenarios of AI technologies, divides the AI technologies into cognitive and perceptual AI technologies according to the characteristics of the research field, then introduces specific AI technologies and model training methods that can be applied in the field of JADC2. Finally, a typical joint operation case illustrates the application of AI technologies in the process of specific operational activities.
Adaptive Unscented Kalman Filter Algorithm for Multi-domain Command and Control Information Transmission

This paper studies the carrier frequency tracking algorithm of multi-domain command and control transmission signal in low Carrier-Noise-Ratio (CNR) and high dynamic conditions. On the basis of analyzing the shortcomings of existing methods, a closed loop carrier frequency tracking algorithm of simplified adaptive unscented Kalman filter (AUKF) is presented. This new algorithm can not only avoid the errors due to linearization because of its good nonlinear processing capability, but also can eliminate the phase information of the phase shift keying (PSK) modulation. In addition, it is found that the new algorithm could estimate the measurement noise covariance and process noise covariance adaptively, so it is able to compensate the errors resulting from the change of the noise statistics. The simulations show that the simplified AUKF algorithm has a much smaller frequency estimation error than that of the UKF algorithm while keeping the convergence speed. Furthermore, the simplified AUKF algorithm has a lower computation complexity than the original AUKF algorithm. So it will have great significance on the information transmission of multi-domain command and control.
Time Series Impact Through Topic Modeling

A time-series of numerical data and a sequence of time-ordered documents are often correlated. This paper aims at modeling the impact that the underlying themes discussed in the text data have on the time series. To do so, we introduce an original topic model, Time Series Impact Driven by Topic Modeling (TSITM), that includes contextual data by coupling Latent Dirichlet Allocation (LDA) with linear regression, using an elastic net prior to set to zero the impact of uncorrelated topics. The resulting topics act as explanatory variables for the regression of the numerical time series, which allows us to understand the time series movements based on the events described on the text data. We have tested our model on two datasets: first, we used political news to explain the US president&#x2019;s disapproval ratings; then, we considered a corpus of economic news to explain the financial returns of 4 different multinational corporations. Our experiments show that an appropriate selection of hyperparameters leads to significant correlations: both an intrinsic baseline and state of the art methods were significantly outperformed by TSITM in MSE, MAE and out-of-sample <i>R</i><sup>2</sup>, according to our hypothesis tests. We believe that this framework can be useful in the context of reputational risk management.
Monocular 3D Human Pose Estimation with Domain Feature Alignment and Self Training

Despite great success in 3D monocular human pose estimation, the progress of accurate prediction for unseen poses or complex backgrounds is still limited due to the lack of labeled data. In this paper, we use synthetically generated images with 3D ground truth and unlabelled real data to address this domain gap challenge. Unlike recent works that apply the adversarial loss to their models, we propose a novel domain feature alignment method (DFA) that avoids the disadvantages of unstable training and wrong alignment. In addition, our method leverages self-training with data enhancement to create robust pseudo-labels for real data. The experimental results show the effectiveness of combining self-training with our DFA method on Human 3.6M testing data without using any 3D ground truth real data.
Segmented Adaptive Singular Value Decomposition for Data Compression of IGBT

As Insulated Gate Bipolar Transistor (IGBT) is widely used in industrial practice, a compression algorithm based on two-dimensional block adaptive threshold singular value decomposition is proposed to solve the problem of storing massive data when IGBT is switched on. In order to more effectively improve the compression ratio and reduce the error of data, this method is to arrange the set of one-dimensional IGBT data into a two-dimensional matrix normalizing to form two-dimensional gray image processing according to each part of the image characteristic of regional block. After adjustment by adaptively presetting threshold characteristic values of singular values, we use compression sensing to complete data compression. Multiple sets of original data can not only ensure the mean square error, but also meet the requirements of high compression ratio, high precision and low distortion, which significantly reduces the amount of data stored. The experimental results show that when the mean square error is about 0.05% and the mean absolute error is about 0.015, the compression ratio of 3% and the signal-to-noise ratio of 41.5dB can be achieved, which verifies the feasibility of the algorithm and has certain practical value.
The Effect of a Proposed Strategy According to the Constructivist Theory on the achievement of Sociology for Fourth-Grade Literary Students

The objective of the research is to identify the impact of a proposed strategy, based on constructive theory, on the acquisition of sociology in literary fourth graders, including the research sample from)60 ( students, from the fourth grade of literature at the Assyria Preparatory School for Boys of the General Directorate of Salah al-Din Education for the academic year 2021-2022, distributed into two groups.(Experimental and control), for each group (30) students, the experiment was applied in the first semester of the 2021-2022 school year, the collection test was applied to the two research groups, and after statistical data collection and analysis the result was in favour of the pilot group studied with the proposed strategy, due to the use of constructive theory in building the proposed strategy and its application in teaching science The meeting.
BRefine: Achieving High-Quality Instance Segmentation

Instance segmentation has been developing rapidly in recent years. Mask R-CNN, a two-stage instance segmentation approach, has demonstrated exceptional performance. However, the masks are still very coarse. The downsampling operation of the backbone network and the ROIAlign layer loses much detailed information, especially from large targets. The sawtooth effect of the edge mask is caused by the lower resolution. A lesser percentage of boundary pixels leads to not-fine segmentation. In this paper, we propose a new method called Boundary Refine (BRefine) that achieves high-quality segmentation. This approach uses FCN as the foundation segmentation architecture, and forms a multistage fusion mask head with multistage fusion detail features to improve mask resolution. However, the FCN architecture causes inconsistencies in multiscale segmentation. BRank and sort loss (BR and S loss) is proposed to solve the problems of segmentation inconsistency and the difficulty of boundary segmentation. It is combined with rank and sort loss, and boundary region loss. BRefine can handle hard-to-partition boundaries and output high-quality masks. On the COCO, LVIS, and Cityscapes datasets, BRefine outperformed Mask R-CNN by 3.0, 4.2, and 3.5 AP, respectively. Furthermore, on the COCO dataset, the large objects improved by 5.0 AP.