Reviewerly/exHarmony huggingface dataset:
Deep Learning Model for Educational Recommender Systems

Research in the field of recommender systems is evolving rapidly and these systems are increasingly being applied to specific domains, including educational technologies. In the field of education, in general, recommender systems are used to improve the processes of online learning and teaching. However, with the growth in the number of educational resources and their diversities, the problem of information overload is becoming increasingly critical. Therefore, providing learners with personalized educational recommendation tools is a necessity. The objective of this work is to propose a new approach to recommend resources to students according to their preferences. This recommendation approach introduces a general framework called collaborative filtering (CF) based on neural networks, which complements classical models and machine learning algorithms such as KNN, SVD of collaborative filtering. The experiments we have performed prove the performance of the proposed approach.
Robust Object Detection and Tracking in Flood Surveillance Videos

Divya, S. Kaviya, P. Chitrakala, S. Bhatt, C. M.Object detection has shown significant improvements in recent days due to advancements in deep learning technologies. Flooding being one of the major disasters leads to loss of life and property. Object detection and tracking in those scenarios would prove to reduce the damage caused by such disasters. In order to enable object detection in such sturdy conditions, robust object detection and tracking in flood surveillance videos (RODT) was proposed. The RODT was made possible by augmenting the data set using various techniques by making it applicable to the robust conditions such as rainy weather, during night, tilted objects and in blurry frames. The significance of proposed RODT system is to save human life by detecting and tracking objects in terrible weather conditions.
Information system of distribution of material aid for university students

The article discusses the solution of a number of problems related to the distribution of financial assistance for students of universities: late submission of applications, paper submission, changing categories, all this complicates the process of filing and considering applications for financial assistance, thereby increasing the burden on employees of directorates of institutes. The purpose of this work is to increase the efficiency and accessibility of this process through an information system that will allow you to submit applications online, and employees of the directorate or dean’s office to track this process in a timely manner. This article provides an algorithm for the distribution of material assistance, presents design solutions and software implementation. The developed system will allow to exclude personal interaction between the staff of the directorate and students in this process.
Speech Disorders Classification by CNN in Phonetic E-Learning System

Speech disorders may affect the process of phonetic transcriptions. In the Automated Phonetic Transcription-the grading tool (APTgt), a linguistic E-learning system, to reduce the influence of disordered speech in the phonetic exams, we proposed a speech disorders classification module that aims to classify disordered speech and non-disordered speech. The Mel-frequency cepstral coefficients (MFCCs) are utilized to represent the features of the speech sound files. With the two different formats of MFCCs, we adopted two approaches to classifying the MFCCs: calculating the similarity between MFCC values by dynamic time warping (DTW) algorithm and classifying the distances by support vector machine (SVM); directly image classification by the convolutional neural network (CNN). We will focus on the second approach in this paper.
Autonomous Robot Navigation by Area Centroid Algorithm Using Depth Cameras

This work tries to demonstrate how the use of depth map cameras has considerable advantages compared to laser range measurements. As is known, the laser 2D can only see objects in a single plane, its scanning plane. Then, when using depth map cameras, we have as many planes as the vertical resolution the camera has. In addition, it is possible to derive, with this way of measuring the environment, the height of the objects above the ground, giving the system the 3D characteristic. As we will demonstrate, this 3D feature is not required to navigate a robot under an object (a bridge, for example).
Order-Aware Graph Neural Network for Sequential Recommendation

Graph neural networks (GNNs) have gained impressive success in the task of sequential recommendation due to their advantage in obtaining the complex transition patterns of items. However, existing GNN-based sequential recommenders still face some problems: (1) The global order information is lost when converting a sequence into a graph. (2) The long-term dependencies in a sequence are ignored due to the over-smoothing problem in GNNs. In this paper, we propose an order-aware GNN with long-range connections (OAG-LC) for sequence modeling. To capture the global order of a sequence, a novel graph update mechanism is proposed, which evolves the graph embedding recurrently over time rather than concurrently for order preservation. And a novel gate is used to incorporate both order and structural information in the update phase. To model the long-term dependencies of user behaviors, we convert the sequence into a graph via reachability and apply the attention mechanism for information propagation through the long-range connections. Furthermore, the proposed graph construction method differentiated repeated items with their positions for information lossless encoding. We conduct extensive experiments on four public datasets, and the experimental results demonstrate the effectiveness of our proposed model.
TDS Level Control of Water Purifier Using Fuzzy-PID Controller

Water TDS (total dissolved solids) level is one of the foremost important parameters to be monitored for domestic, industrial, and agricultural purposes. In this paper, the controller designed for the RO (reverse osmosis) filter gives the desired TDS value much faster and with less fluctuations. The classical PID controller has been modified with addition of fuzzy rule base. The rule base with triangular and Gaussian membership function has been studied, and advantage of using Gaussian membership function in this paper has also been focused. The mathematical model of the RO system is used for testing of the fuzzy-PID controller. The model is used to compare the response of fuzzy-PID with triangular and Gaussian membership function.
Modification of Transformer Machine Translation Model Design Based on Deep Learning

Machine translation can realize low-cost communication between different countries and languages in the world. It has the advantages of low cost, easy control, fast speed and so on. At the same time, the advancement of machine translation plays a bench-marking role in other fields of natural language processing. At present, the world-famous Transformer model uses the “encoder-decoder” framework, completely abandons the cyclic neural network, and uses the multi-head self-attention mechanism and feed-forward neural network to build the model network. Inspired by the cognitive nature of its text coding process and the linguistic cognitive essence of translation activity, this paper integrates information of the part of speech words in the text into the coding process, which is added with the word vector representation and position vector representation as the final input vector. In this study, the modified Transformer model is to be verified by experiments. In the experiment, the original Transformer model is used as the baseline for comparative analysis. The experimental results show that the translation of transformer model with part of speech information is better than that of baseline model.
Case Study: Recommender System

In this chapter, we will build a search engine Sofia using latent semantic analysis. Sofia is a content-based filtering system that captures the semantics contained in the unstructured web text. Sofia looks for similar articles in a text corpus when a query document arrives. You will find that much of the basic theory has been covered in Chap. 12. In this chapter, we focus on introducing the full workflow of this system, and how to address a series of technical challenges in building Sofia.
Parallel Image Processing for Liquid Level Detection

The liquid level detection in a transparent bottle is the requirement in the food, Beverage industry, Scene understanding, Chemical Laboratories, and Forensic sciences. The liquid level detection indicates the quantity of the liquid in the bottle to assure customer satisfaction. The liquid level in a transparent container is an edge, a sudden change in intensity. The problem of liquid level detection is an image processing application of the Canny Edge Detector. The image data set is prepared using different sizes, transparency, color, and orientation as straight, landscape, and reverse. The transparent bottle classification accuracy rate is 87.5%, and the overall accuracy rate is 69.56%. The Serial and parallel algorithms are developed to improve the speed of execution. The multiprocessing and concurrent process pool of the multiprocessing approach found 4.6 times better turnaround execution time over synchronous pool map, concurrent thread pool, asynchronous thread pool, and serial execution.
Performance Evaluation

In this chapter, the models proposed in this book models are evaluated for different datasets, and the results are reported and discussed in detail. First, the performance of the proposed video quality models, i.e., the coding impairment models, for datasets created using passive viewing-and-listening tests are evaluated and compared with each other. Second, the gaming QoE model performance based on the validation part of the interactive dataset is presented. In addition, the evaluation of other models predicting the impairment factors affecting the gaming QoE (e.g., $$I_{cntr_I}$$ ) are also discussed in this chapter. Third, the performance of ITU-T Rec. G.1072 is reported in a separate section due to differences in the validation dataset compared to the gaming QoE model proposed in this book. Finally, the chapter is concluded with a discussion and summary of the findings.
Symbolical Resources of a Personality

The article presents the analysis of theoretical and methodological aspects of the study of symbolization and symbolical resources of a personality. The author has provided the analysis of the essence of symbolical processes and their role in socio-psychological adaptation of a subject. In a psychological context, the symbolization process is aimed at supporting and facilitating the interaction of a subject with other people, inner self, and the subjective world. Symbolization processes generate and inspire meanings of life, open up new opportunities for a person in the way not thought of before, which expand his or her inner world and spiritual experience, increase the range of variability of actions and emotional manifestations, remove stereotypes of behavior and activities, provide an opportunity for a more harmonic interaction with other people as well as the world of culture, science, and creativity.
Indoor Auto-Navigate System for Electric Wheelchairs in a Nursing Home

We are currently living in an age of COVID, where we wish to reduce physical contact as much as possible. It is even more important for patients who live in nursing homes and need wheelchairs. It is noticeable that people who live in nursing homes usually have an elder average age, and are more likely to have some underlying disease. Therefore they need extra care to resist COVID. As we all know, the most common and effective countermeasure against COVID is to avoid close contact. However, for most people who lives in a nursing home, there are plenty of daily activities that are mandatory for them. They have to spend considerable time moving on a wheel chair with a assistant pushing the wheelchair. Which made the assistant and the user a close contact to each other. We plan to design a auto-navigation computer system for electric wheelchairs. So it can be possible for electric wheelchair users to go to various places in nursing home without a assistant aside, reducing the risk of infection, as well as the human resource needed.
Linear Separability as a Condition for Solving Multiple Problems by a Single Threshold Neuron

The paper discusses the linear separability of data classes and the relationship of threshold neurons with class classifiers. The possibility of constructing a neuron that can solve two different problems without the need for an intermediate change in its parameters and architecture is shown theoretically. The idea is illustrated with a specific example of a neuron solving problems simultaneously with both Boolean functions “AND” and “OR”. A conclusion has been drawn for the existence of a neuron that can solve a class of an infinite number of problems. A necessary condition for this is that the domain of the problems is linearly separable from the surface in the input data space and the existence of parallel classifiers for separability for each individual problem.
APPLYING A PROJECT APPROACH TO PRESERVE CRITICAL COMPETENCIES OF THE ENTERPRISE THROUGH THE IMPLEMENTATION OF A COMPREHENSIVE HR-PROGRAM OF MENTORING

The article considers issues faced, by an industrial enterprise,when implementing mechanisms for the formation of sustainable competitive advantages based on the transfer of unique technological competencies to theyoung generation, and also describes the methodology for applying the project approach to preserve the critical competencies of the enterprise through the implementation of a comprehensive mentoring program.
An Enhanced Moth Flame Algorithm for Peak Load Distribution Optimization

Peak load distribution optimization (PLD) is a typical multi-constrained nonlinear optimization problem considered an essential vital part of the power system to achieve energy-saving and consumption reduction. This study introduces an enhanced version of the moth flame optimization algorithm (EMFO) for the PLD problem. The actual operation constraints of the power system of the PLD are modeled for the objective function of optimization. In the experimental section, the IEEE-bus benchmark system is used as the case study to test the performance of the proposed scheme. The results show that the proposed scheme can solve the power system PLD problem with feasibility and significant economic benefits.
Siamese Tracking with Bilinear Features

Bilinear features arise in fine-grained visual recognition. They are advantageous to encode detailed representations and attributes to differentiate visually similar objects. The apparent similarity is challenging in visual tracking where background distractors interfere siamese trackers to localize the target object. Especially when distractors and the target belong to the same object category. To increase the discrimination between similar appearance objects, we propose an efficient bilinear encoding method for siamese tracking. The proposed method consists of a self-bilinear encoder and an cross-bilinear encoder. The bilinear features generated via the self-bilinear encoder and the cross-bilinear encoder represent target variations itself and target distractor difference, respectively. To this end, the proposed bilinear encoders advance siamese trackers to capture target appearance variations while differentiating the target and background distractors. Experiments on the benchmark datasets show the effectiveness of bilinear features. Our tracker performs favorably against state-of-the-art approaches.
FourierMask: Instance Segmentation Using Fourier Mapping in Implicit Neural Networks

We present FourierMask, which employs Fourier series combined with implicit neural representations to generate instance segmentation masks. We apply a Fourier mapping (FM) to the coordinate locations and utilize the mapped features as inputs to an implicit representation (coordinate based multi layer perceptron (MLP)). FourierMask learns to predict the coefficients of the FM for a particular instance, and therefore adapts the FM to a specific object. This allows FourierMask to be generalized to predict instance segmentation masks from natural images. Since implicit functions are continuous in the domain of input coordinates, we illustrate that by sub-sampling the input pixel coordinates, we can generate higher resolution masks during inference. Furthermore, we train a renderer MLP (FourierRend) on the uncertain predictions of FourierMask and illustrate that it significantly improves the quality of the masks. FourierMask shows competitive results on the MS COCO dataset compared to the baseline Mask R-CNN at the same output resolution and surpasses it on higher resolution.
Review on Color Image Processing Techniques

The purpose of Color Image analysis is to show physical perceptive image information. The creation of digital images is also a crucial phase. It provides image processing frameworks that extract characteristics from picture data which can be used for system definition, comprehension, and details. It encourages the customer using desktop computers as well as other throughput devices (scanner, etc.) to take an immediate-copy of a picture and also to put it in a desktop application (.jpg,.ggif,.png, etc.). It contributes to photographic characteristics such as changes and analysis. In even our own everyday life, picture batch image processing is still have been using. It is the one that interacts with the human condition and eye which is the most powerful statement processing system. The main purpose of this paper is to examine the growth and continued development and execution of color image processing absolutely necessary for images and videos to generally operate and visually improve the images. This paper reviewsa few color image processing techniques and suggests the best color image processing techniques in terms of speed and accuracy.
Online Resume Builder

A resume is a formal document used by individuals to provide an overview of their professional qualifications, including their relevant work experience, education, skills and other accomplishments. A well-designed resume is an essential document which enables an individual to showcase their skill sets qualifications during the recruitment or hiring process. Therefore, it is a widely used item that a jobseekeroftenusesinseekingemploymentinjobs.Usually,individualsgetconfusedwhilecreatingresume.Theydon'thaveclearideaofwhatkind of details should be included in a resume. In resume builder, individuals just have to fill their details in the respective fields which will automatically generate a well-structured resume for them. This project not only focus on resume creation but also enables easy input giving for the user by Smart auto-suggestion feature. And also, users can review their resume with real-time preview features. For people with no idea on how to prepare a Resume, we provide a best class Resume Builder for free and without any interruption like authentication, credentials, ads, etc. Users may create any kind of Resume (For example: Fresher, Professor, Veterans, etc.) with professional &amp; elegant look using the resume builder. Hence, an Online Resume Builder supports an individual to generate an elegant resume in an easy manner.&#x0D; &#x0D;
RETROSPEKTIVNI OGLED JEZIČKIH VEŠTINA U NASTAVI STRANOG JEZIKA I STATUS VEŠTINE PISANjA

At the beginning of the twentieth century L2 teaching practice has been established based on the theoretical framework and practice of L1 teaching. Striving to meet the needs of L2 students sufficiently there was a need to shift the focus of the teaching practice through many traditional and contemporary approaches. Although today there is a rather equivalent distribution among all four language skills in the classroom, for a long period of time the writing skill has been marginalized. In order to understand the status of the writing skill in the L2 classroom, this study attempts to recapture the development and the position of the writing skill from the middle of the XX century to the contemporary practice today in relation to the status of other language skills. In this research we have applied a descriptive and a comparative analysis to discover that the writing skill position has just recently obtained a coexisting, equivalent status in the L2 class- room in relation to other skills and the results enlighten the teaching techniques that have been utilized for the writing skill respectively in the transition from the traditional towards the contemporary teaching approaches.
Adaptive Noise Detector and Partition Filter for Removing Impulse Noise from Grayscale Images

The random-value impulse noise (RVIN) denoising method based on the preset detection threshold or local window information does not have good generalization performance and edge-preserving denoising effect. In this paper, we present a novel two-stage method to remove RVIN. Based on the idea of pixel clustering and grouping, we divide all pixels in the damaged image into several categories according to the characteristics of gray distance similarity, and then iteratively solve the optimal detection threshold of each group to identify the noise. In the noise removal stage, we propose a partition decision filter. For the noise pixels in flat and detail areas, LCI weighted filter and edge direction filter are designed respectively to recover the pixels damaged by RVIN. The experimental results show that the proposed method not only has good noise reduction performance and generalization performance for both natural and medical images with medium and high noise levels, but also outperforms other advanced filtering techniques in terms of visual effects and objective quality evaluation.
4 Human motion dataset

This dissertation deals with machine learning techniques for inverse dynamics of human motion. Inverse
Primer, Part 1

Developers come to the world of web app development via many paths and are not always grounded in the basic technologies that web apps rely on. In this chapter, I provide a brief overview of HTML, introduce the basics of JavaScript and TypeScript, and give you the foundation you need to understand the examples in the rest of the book, continuing with more advanced features in Chapter 4 . If you are already familiar with HTML and TypeScript, you can jump right to Chapter 5 , where I use Angular to create a more complex and realistic application.
The Emergence of a Contemporary Repertoire for the Shō

The shō has played an important role in the creation of Japanese cultural identity. In examining this issue, we show the emancipation of contemporary shō repertoire in the last three decades. We outline the process of the creation of the cultural identity of shō from a historical perspective, explaining the physical structure, music tradition, and contemporary shō music. Shō has unique names for each bamboo pipe and each harmony. The limited number of shō harmonies determines traditional sound images. Some contemporary composers have collaborated to create original repertoires for shō; Maki Ishii, Toshi Ichiyanagi, Cort Lippe, Motoharu Kawashima.