Reviewerly/exHarmony huggingface dataset:
Typical problems of unqualified theses of engineering master: Analysis based on expert review opinions of Tianjin's sampling theses in 2017

Background: The evaluation of the quality of professional master's degree theses has attracted less attention. This paper analyzes the content based on the expert review opinions of the engineering sampling theses in Tianjin in 2017. Methods: This paper focuses on the review opinions of unqualified theses, and extracts three core characteristics of unqualified theses: lack of innovativeness, academic inadequacy, and poor standardization. Results: Lacking in innovativeness means topics, method, and applied value are outdated. Academic inadequacy means the author does not possess adequate knowledge, does not pay sufficient intellectual effort and the dissertation's design is unreasonable with the content irrelevant to the subject. Poor standardization is manifested in poor writing, inappropriate disciplinary paradigm, and academic misconduct. Conclusions: Therefore, strictly monitoring the quality of theses from the system, setting up standardized courses for theses, and improving the academic quality of graduate students have become the priority to the cultivation of engineering masters.
GHW for (x,x+y)-construction of codes

Suppose that A1 and A2 are two linear codes over Fm with parameters [n,k] and [n,k′], respectively. For the code A={(x,x+y):x∈A1,y∈A2}, we asked about dr(A) in terms of dr(A1) and dr(A2), so we obtained an upper bound for dr(A) in terms of them. In addition, we obtained d2(A) in which A1 and A2 are codes over F2. Additionally, we obtained d2(A) in non-binary case, where it is different of what we have for binary case. Suppose that M is a linear code over a finite field. The minimum of the support sizes among r-dimensional sub-codes of M is called the r-th generalized Hamming weight of M that we will denote it by dr(M).
Video Saliency Object Detection with Motion Quality Compensation

Video saliency object detection is one of the classic research problems in computer vision, yet existing works rarely focus on the impact of input quality on model performance. As optical flow is a key input for video saliency detection models, its quality significantly affects model performance. Traditional optical flow models only calculate the optical flow between two consecutive video frames, ignoring the motion state of objects over a period of time, leading to low-quality optical flow and reduced performance of video saliency object detection models. Therefore, this paper proposes a new optical flow model that improves the quality of optical flow by expanding the flow perception range and uses high-quality optical flow to enhance the performance of video saliency object detection models. Experimental results on the datasets show that the proposed optical flow model can significantly improve optical flow quality, with the S-M values on the DAVSOD dataset increasing by about 39%, 49%, and 44% compared to optical flow models such as PWCNet, SpyNet, and LFNet. In addition, experiments that fine-tuning the benchmark model LIMS demonstrate that improving input quality can further improve model performance.
Alfabetización informacional y Tecnologías de la información y la comunicación. El caso de una universidad peruana

In the context of virtual education that in recent years we have been forced to employ, the use of ICT played a fundamental role, especially since it is the main means of searching for information, which led us to the objective of determining the relationship that exists between the use of Information and Communication Technologies (ICT) and the development of skills in Information Literacy (IL) in university students. For this study, a correlational level methodology of non-experimental design was used, with a census-type population made up of 57 students of the Optometry career of the Federico Villarreal National University, to whom two questionnaires were applied both to measure the use of ICTs and for competence in information literacy in university students. After the statistical analysis in the SPSS program, the result was that the level of correlation was very low (0 &lt; r &lt; 0.2) and positive, that is, the greater the frequency of use of ICT, the greater the development of IL skills. , in turn, presented a significance of 0.040, so the null hypothesis was rejected, with a significance level of 5%, concluding that there is a statistically significant relationship between the frequency of use of ICT and the development of competencies in IL in Optometry students from UNFV Lima- 2021.
PERANCANGAN SISTEM INFORMASI PENYEWAAN STUDIO MUSIK PADA WAYZON STUDIO MUSIK

Wayzon Studio Musik is one of the studios at seramg banten that provides two types of rentals, namely studio rentals and musical instrument rentals such as guitars, pianos, drums, basses, other musical instruments and sound systems. The studio rental system currently takes place by means of consumers registering directly on the spot and the recording process is carried out on a notebook and then continued with scheduling on the blackboard. the current system allows errors in the recording process, data loss, scheduling conflicts that often occur, the difficulty of finding information on music equipment rental services, the difficulty of managing transaction data and reports. based on the exposure to the current system, a studio rental system is needed that makes it easier to carry out the recording process, data search process, musical instrument rental, studio booking process and the process of finding information on music equipment rental services. This music studio rental system is designed using a codeigniter framework, bootstrap and a database management system (DBMS) using MYSQL. In this web development, the method used is the waterfall and Unified Modeling Language (UML). This system makes it easier and faster for administrative officers to provide scheduling information on studio and musical instrument rental services, minimizes errors in the process of processing transaction data and making reports and makes it easier for customers to find information on music equipment rental services. This system will display a monthly studio or musical instrument rental schedule (dashboard) and the report system will display transaction data that can be printed easily.
DEVELOPING ASSESSMENT INSTRUMENTS FOR ENGLISH LITERACY IN BLENDED LEARNING FOR JUNIOR HIGH SCHOOL STUDENTS

This research intended to develop assessment instruments for English literacy in blended learning. The study employed survey, observation, interview, and document study as the methods with a questionnaire, observation checklist, interview guide, and school document as the instruments to collect the data framed within RnD design with the 4D model by Thiagarajan et al. The developed instruments were categorized as ‘very high validity’ and ‘very good’ for their content validity (1.00) and product quality (96% and 98%) by the two judges. It indicates that assessment of learning, assessment for learning, and assessment as learning combined with authentic materials are necessary to improve the learning process as well as the students’ English literacy skills. It also implies that English teachers need to highlight the use of assessment for learning and assessment as learning since those assessments lack attention previously.
Prácticas profesionales de estudiantes normalistas de matemáticas con el programa Aprende en casa II y III

This research project refers to the actions carried out by students of the bachelor’s degree in Secondary Education with Specialization in Mathematics (LESEM) at the Escuela Normal Superior, taking the 7th and 8th semesters in the 2020-2021 school year, during the period of the pandemic caused by the COVID-19 virus, within the framework of the national educational programs Learn at Home II and III. The aim of the project is to answer the following questions: What are the difficulties faced by mathematics students when developing their professional practices in the context of confinement when the medium is the use of information technologies; and how do mathematics students put into practice the development of the traits of the graduate profile when the medium for teaching and learning is the use of information technologies?The objective is to identify difficulties of mathematics students when the medium they use for the development of their teaching work are digital platforms and/or classes presented through TV and radio. According to the features of the graduate profile of the current curriculum of LESEM, the analysis of the mastery of purposes and contents is contemplated, as well as the didactic competence that they put into practice when performing their professional practices with high school students in the framework of the confinement and the program Learn at Home II and III. Some instruments to be used: observation records, lesson plans and diaries; the categories of analysis that will be used to examine their practice are the following: Teaching planning, teaching style, content mastery, temporality and evaluation of learning. The results obtained will be very useful for the proposal of pedagogical alternatives that can be incorporated into the reformulation of current curricula.
Change Prediction using Selective Cross Project Validation with Ensemble Learning

The goal of predicting the change-proneness of a software is to recognize parts of a software that are prone to change and require managers' and other stakeholders' attention. This leads to a reduction of the overall cost which would be spent in the software’s development and maintenance. Previous versions of a project may be used to predict such classes. However, this may not be possible for a project in its infancy where previous classes do not exist. Cross-project change-proneness prediction provides an alternative means of achieving the same goal by using a different project for the classification process.In this paper, we utilize selective cross project algorithms to choose an appropriate project from the source project candidate pool. To choose a source project, three algorithms were used. The first algorithm relied on the change-proneness rate of the source and target project. The remaining two algorithms relied on the Euclidean distance between the characteristic vectors of the source and the target project. The classification process was executed by using two ensemble methods – Bagging and Random Forests – to determine the feasibility of the ensemble techniques for cross project prediction. The performance is evaluated using the AUC, F-Measure, and MCC performance metrics. Results show that the algorithm utilizing the change-proneness rate performed better than all remaining algorithms used in this study.
Power Data Integrity Detection System Based on Blockchain Theory in Encryption Environment

The text classification range of power data integrity detection is chaotic, which leads to the stagnation and high delay of power data detection. In this paper, a power data integrity detection system based on blockchain theory in encryption environment is designed. The power data inspection instrument is constructed to process the data volume of power data integrity detection, set the logic unit, collect and store the power data integrity detection operation parameters, design the power data integrity detection interface circuit, and extract the power data jitter signal amplitude. It also detects the operation parameters of encrypted power data integrity, uses text classification training to adjust and train the characteristic items of power vector number, establish the blockchain power data integrity detection algorithm, comb the text classification range, decompose the power data in the sample set, and complete the design of power data integrity detection system based on blockchain theory in the encrypted environment. The test results show that the stagnation delay of power data detection before operation is 7.0 ms, and after the operation of the system, the integrity of the power data detection system has been at 6.0 ms, ensuring the power data integrity detection effect.
A Multiple Watermarking Scheme for Digital Audio Signals

Watermarking is a method for the verification of the authenticity of a digital object. In this work we investigate the watermarking of audio signals utilizing watermarked images. We present a multiple watermarking scheme for the watermarking of digital audio signals. The proposed technique exploits an image as a watermark which has been already watermarked with a self inverting permutation. The watermarked image, is then embedded in the LSB values of the digital audio signal. By conducting a series of evaluation experiments, including an attack vector consisting of cropping, noise, and re-sampling attacks, we investigate the robustness of the proposed multiple watermarking technique and prove its potentials against various factors affecting each type of attack.
Single Cross-domain Semantic Guidance Network for Multimodal Unsupervised Image Translation

Multimodal image-to-image translation has received great attention due to its flexibility and practicality. The existing methods lack the generality of effective style representation, and cannot capture different levels of stylistic semantic information from cross-domain images. Besides, they ignore the parallelism for cross-domain image generation, and their generator can only be responsible for specific domains. To address these issues, we propose a novel Single Cross-domain Semantic Guidance Network (SCSG-Net) for coarse-to-fine semantically controllable multimodal image translation. Images from different domains are mapped to a unified visual semantic latent space by a dual sparse feature pyramid encoder, and then the generative module generates the result images by extracting semantic style representation from the input images in a self-supervised manner guided by adaptive discrimination. Especially, our SCSG-Net meets the needs of users in different styles as well as diverse scenarios. Extensive experiments on different benchmark datasets show that our method can outperform other state-of-the-art methods both quantitatively and qualitatively.
IMPLEMENTATION OF THE STORYTELLING METHOD USING THE BIG BOOK AS AN ATTEMPT TO INCREASE KINDERGARTEN TEACHERS’ STORYTELLING SKILLS AT BUKIT RAYA PEKANBARU

This paper is based on the Kindergarten teachers’ skill lack of storytelling at Bukit Raya Pekanbaru. It can be seen from the initial survey that the researchers conducted indicate that most of the teachers are evidently not skilled at storytelling yet properly. Of the 18 teachers who test their storytelling skills, only 53.3% were skilled at storytelling well. Conversely, 46.7% are not skilled at storytelling yet properly. The purpose of this paper is to find out the increase in teachers’ storytelling skills after applying the storytelling method using the big book, which was conducted at a kindergarten in Bukit Raya Pekanbaru. The type of research uses School Action Research. Based on the results of the data presentation and discussion, it can be concluded that the implementation of the storytelling method using the big book can improve kindergarten teachers’ storytelling skills in Bukit Raya Pekanbaru. It is indicated from the research findings that in the pre-cycle the average score of teachers’ storytelling skills was only 53.3%. After applying the storytelling method in cycle I, teachers’ storytelling skills increased to 73.3%. After conducting reflection and improvement in cycle II, the average score increased to 88.9%. Thus, the hypothesis in the research was accepted, which indicates that "there is an increase in Kindergarten teachers’ storytelling skills through the storytelling method using big books in Bukit Raya Pekanbaru".
SCHOOL LITERACY MOVEMENT TROUGH THE CLASSROOM READING CORNER AT INPRES ELEMENTARY SCHOOL TOMBOLO, TOMBOLOPAO DISTRICT, GOWA REGENCY

This study aimed to determine the implementation of the School Literacy Movement at the habituation stage, the development stage, and the learning stage through the classroom reading corner at Inpres Elementary school Tombolo, the supporting and inhibiting factors for the use of the classroom reading corner in the implementation of the School Literacy Movement at Inpres elementary School Tombolo. This research was a qualitative research. The study was conducted at Inpres elemtary School Tombolo, Tombolopao District, Gowa Regency. There were 12 informans in this study consisting of the principal, 5 class teachers, 1 librarian, 5 student representatives from each grade level. Data were collected through direch observasition at the Education Unit, in-depth interviews with informants, and documentation of activitees as well as administrative completeness of the implementation of the School Literacy Movement.The results showed that the implementation of the School Literacy Movement at Inpres Elemtary School Tombolo, had been carried out well starting from the Habituation Stage, Development State, and Learning State by utilizing the classroom reading corner, in general, two reading strategies are used, namely silent and loud. The implementation of the School Literacy Movement continues in several classes during the learning period from home deu to the C.19 pandemic by utilizing digital platforms. Sources of reading materials only use the classroom reading corner and school library in the implementation of the School Literacy Movement.
Innovative Development of a Flying robot with a Flexible Manipulator for Aerial Manipulations

Abstract4This paper presents an innovative development of a flying robot or an aerial robot, with a flexible manipulator, called the Dexterous Aerial Robotic System (DFTS), for aerial manipulations, especially for inspections and reparations of various structures such as wind turbines, power lines and open gas pipelines, decorations and painting of high industrial chimneys and walls of high buildings, as well as transport and delivery of courier shipments, relocation and manipulation of assemblies and units in inaccessible or dangerous environments.The proposed DFTS consists of two independent but interconnected systems or functional units, which have two main separate functions respectively, including a basic carrying function, and a precise positioning and stabilization function.The system with a basic carrying function is actually the main flying system, the unmanned aerial vehicle (UAV); it is remotely controlled and piloted.Meanwhile, the aerial manipulation platform, called the vertical take-off and landing platform VTOL, which is an active flying platform with 6 degrees of freedom (DOF) is used for positioning and stabilization; and it is attached to the UAV via the soft link.With the use of a long soft link, the problems which are caused by the air turbulent flows generated by the UAV are minimized, and the aerial manipulations of objects are safely controlled and operated.The VTOL which is equipped with a grasping mechanism was successfully developed, prototyped and tested.The experimental results showed that, the developed VTOL can self-stabilize with the inclination angle of being up to 8 degrees.
Generation of Synthetic Tabular Healthcare Data Using Generative Adversarial Networks

High-quality tabular data is a crucial requirement for developing data-driven applications, especially healthcare-related ones, because most of the data nowadays collected in this context is in tabular form. However, strict data protection laws complicates the access to medical datasets. Thus, synthetic data has become an ideal alternative for data scientists and healthcare professionals to circumvent such hurdles. Although many healthcare institutions still use the classical de-identification and anonymization techniques for generating synthetic data, deep learning-based generative models such as generative adversarial networks (GANs) have shown a remarkable performance in generating tabular datasets with complex structures. This paper examines the GANs’ potential and applicability within the healthcare industry, which often faces serious challenges with insufficient training data and patient records sensitivity. We investigate several state-of-the-art GAN-based models proposed for tabular synthetic data generation. Healthcare datasets with different sizes, numbers of variables, column data types, feature distributions, and inter-variable correlations are examined. Moreover, a comprehensive evaluation framework is defined to evaluate the quality of the synthetic records and the viability of each model in preserving the patients’ privacy. The results indicate that the proposed models can generate synthetic datasets that maintain the statistical characteristics, model compatibility and privacy of the original data. Moreover, synthetic tabular healthcare datasets can be a viable option in many data-driven applications. However, there is still room for further improvements in designing a perfect architecture for generating synthetic tabular data.
Ghost Module Network for Lightweight Weather Classification

The past decade has witnessed significant progress on compute vision. The application of convolutional neural networks (CNNs) to weather recognition can make up for the lack of specific details in the current weather system. However, deploying CNNs on some devices is a tough nut to crack due to the few computation resources and memory. To resolve this issues, we propose a scheme that Embedding ghost module makes CNNs more lightweight. Ghost module can take advantage of the similarity between feature. To make the image data more reliable, we collect a series of plateau climate image from existing monitoring equipment as a dataset, namely, MWC53K, which contain five types of weather: rain, snow, fog, clear, moonlight. Besides, focal_Loss is adopted to solve the problem of data imbalance in actual weather. We perform quantitative evaluations on our own MWV53K dataset. Experimental result demonstrate that our method achieves the state-of-the-art efficiency while keeping high accuracy. The code will available soon at github.
ALGORITHM AND SOFTWARE TOOLS FOR IMPROVING INTERPOLATION ACCURACY BASED ON CUBIC SPLINE

In this work, the construction of the cubic spline for the continuous function defined in the segment, as well as the approximation algorithm of the interpolation process and the software for determining the interpolation error were developed. We used cubic splines of the third degree in this work. In the spline definition formula, the value of the coefficient is expressed by the distance between the nodes of the function and the distance between the nodes. The spline-functions method was improved based on the result of analytical analysis to study the methods of approximating functions and functional connections obtained from experience
A new contrast metrics to estimate the amount of distortion in image edges affected by the motion of the rotating object

The image distortion usually influenced by several factors, most notably the relative motion during capturing image between the camera and the object. In this work, the effect of the rotational motion of a fan and its effect on distorting in edges of a captured image of the object consisting of black and white regions will be studied. Then four contrast criteria were proposed to calculate the image edge points contrast vectors. Next, determining the coherence and consistency of these criteria with each other. Where the consistency of the four contrast metrics was confirmed, as they were found related to each other by a linear relationship. Also, estimating the effect of the rotation radius for the fan blade on the amount of distortion in image edge for the target behind it. It was found that the four contrast values increased significantly with increasing the radius of rotation, i.e. with increasing the linear velocity for the fan blade points. That is, the amount of distortion decreases with increased radius and increased linear velocity for the fan blade points.