Reviewerly/exHarmony huggingface dataset:
Development of Guidelines for Beginning Counting Assessment Learning Problems of Elementary School Age

Based on the results of the literature study, it was found that there were not a few children who had problems in calculating the beginning or often referred to as learning problems. This study uses a qualitative approach, and uses the library research method by looking at data based on article sources, handbook journals and research that has been carried out by previous research. The data collection technique used is literature study. The research was conducted with the aim of compiling guidelines for initial numeracy assessment for children with learning problems of elementary school age. This study produces a product in the form of a preliminary numeracy assessment guide for children with learning problems of elementary school age who have gone through the validation or expert judgment stage with the conclusion that the initial numeracy assessment guideline for children with learning problems of primary school age is appropriate to use. Assessment activities are activities to determine the abilities, barriers and needs of children so that it can be seen which learning programs are deemed appropriate to be given to children. The initial numeracy assessment guideline is appropriate for parents or teachers to use at school to determine the ability of the child's early numeracy barriers and needs.
Local Mixer with Prior Position for Cars’ Type Recognition

Deep learning has attracted attention widely as the successful application of deep learning for vision tasks, such as image classification, object detection and so on. Due to the robustness and universality of deep learning, automotive manufacturing, a crucial part of national economy, needs deep learning to make production lines more intelligent and improve efficiency. However, some superior generally deep learning models, such as ViT, TNT, and Swin transformer, cannot meet automotive manufacturing requirements with high accuracy on a specific scene. As for automotive production lines, engineers usually adopt some smart designs, which can provide prior knowledge for designing deep learning models. Specifically, in an image, the position of target is usually fixed. Therefore, in order to take advantage of prior position, this paper designs a local mixer with prior position to capture local feature. Its main idea is that dividing the whole feature map into window feature maps and connecting window feature maps along channel dimension in order to make convolution kernel parameters for each window feature map are independent from others. Besides, MLP is adopted as global mixer to capture global feature and the pyramidal architecture with CNN is adopted. Comprehensive results demonstrate the effectiveness of proposed model on cars’ type recognition. In particular, the proposed model achieves 97.938% accuracy on our data set, surpassing some transformer-like models.
Face Recognition Based on Convolutional Neural Networks

Since science and technology have been progressing steadily in recent years, deep learning's potential applications have expanded greatly. From unlocking the screen of a phone with a human face to driverless technology, which has emerged in recent years. Facial recognition is proving to be a boon to life. Among various deep learning algorithms, the appearance of convolutional neural network (CNN)has made unprecedented progress in image recognition. In this paper, the basic principles of convolutional neural networks are explained, and the most important concepts are introduced. The convolutional neural network is used for experiments. The input layer, convolution layer, pooling layer, fully connected layer, and output layer are the nine layers that make up the traditional and complete convolutional neural network model, which is used as the experimental foundation. LFW dataset is used for training, and the experimental results are given. At the end of the paper, the accuracy and loss functions are analyzed and the accurate results of facial recognition are achieved.
HOMESTAY BOOKING SYSTEM

Finding the bare minimal prerequisites for establishing a homestay ecosystem for the tourism business which must be consistent with environmentally and socially responsible tourist practises.It is impossible to maintain sustainable homestay tourism unless tourist are satisfied.In order to address this, the present research sought to look into the connection between sustainable Homestay tourism and tourist's satisfaction.The attraction is the first-hand experience of culture, cuisine, and interaction with the community for a reasonable price.These are initiatives where the economic benefits from tourism go directly to the community and if located close to an area of conservation value, also contribute to the protection of the site.Results have shown that sustainable homestay tourism development is closely related to tourist satisfaction in three ways viz.socio-cultural, economic, and environmental sustainability.Finally, this study includes a meaningful conclusion, theoretical and managerial consequences, and future research directions.
Automatic Image Tagging Based on Text Analysis Using Natural Language Processing Techniques

I have seen that in any newspaper there are many articles related to different things and the article consists of some text and one or more images which are related to the given text. Some of the images given in the article have caption (which depicts the image) and the other images do not have any caption. Hence if I download the image which has no caption then after download, I will not understand what the image specifically describes.&#x0D; To address this kind of situation it is necessary to give the image some caption which depicts about the situation of the image and the information about the image. After download the image if I give some relevant tag to the image then it will be helpful for all.&#x0D; In modern era images are taken and stored digitally. Also, the prices of the image capturing devices are decreasing. Hence people are taking more and more pictures but handling of pictures are necessary at this situation. Additionally, there is a huge uptick in the use of web-based image-sharing programmes or applications. One of the most widely used of these applications is Flickr, which was acquired by Yahoo and now stores over 4 billion images.&#x0D; Image tagging by hand takes time and is subjective. Nobody has time to tag their images. Additionally, because people differ and think in different ways, comparable images will be tagged in various ways by different people. Differences in language, emotion, vocabulary, education, culture, taste, etc. may be the root of this.
2013 Favorite Subscription 2022 PhS Library Issue 5 (june) PhS Library Issue 4 (april) PhS Library Issue 3 (february) PhS Library Issue 2 (december) You are here Home » Archive » 2022 ISSUE No 6 (November) Добавить статью GENERAL AND APPLIED LINGUISTICS Category functions in the process of recategorization Ch.G. Gogichev Pages: 3..11 DOI: 10.20339/PhS.6-22.003 1 Правка The mechanisms of deviation from norms in computer-mediated communication I.G. Ovchinnikova, L.L. Cherepanova Pages: 12..20 DOI…

The purpose of the article is to form a conceptual structure of the diplomatic style. The diplomatic style is not diplomatic discourse. Both are two different categories. The parameters of diplomatic communication for modern society differ in style. Diplomacy is a diplomatic tactic not only in relations between states but also in the management of social groups and interpersonal relations. Successful diplomatic communication requires effective strategy and tactical skills. Because diplomatic communication is a socio-political relationship, it has a style. The article presents a conceptual structure typical of the diplomatic style. First, the stylistic structure of the diplomatic language was determined, gestures and facial expressions used in diplomatic relations were analyzed. Types of negotiations, the characteristics of a diplomat — the characteristics of a leader were identified. The etiquette of diplomatic speech was defined. The etiquette of diplomatic uniforms has been clarified. All this proved to be a conceptual structure of diplomatic style. Diplomacy of agreement and compromise is not only a peacemaker but also a commercial interest, an invitation to trade, publication, distribution‎.
Android-Based Short Message Service Filtering using Long Short-Term Memory Classification Model

Short Message Service (SMS) is a technology for sending messages in text format between two mobile phones that support such a facility. Despite the emergence of many mobile text messaging applications, SMS still finds its use in communication among people and broadcasting messages by governments and mobile providers. SMS users often receive messages from parties, particularly for marketing and business purposes, advertisements, or elements of fraud. Many of those messages are irrelevant and fraudulent spam. This research aims at developing android-based applications that enable the filtering of SMS in Bahasa Indonesia. We investigate 1469 SMS text data and classify them into three categories: Normal, Fraudulent, and Advertisement. The classification or filtering method is the long short-term memory (LSTM) model from TensorFlow. The LSTM model is suitable because it has cell states in the architecture that are useful for storing previous information. The feature is applicable for use on sequential data such as SMS texts because every word in the texts constructs a sequential form to complete a sentence. The observation results show that the classification accuracy level is 95%. This model is then integrated into an Android-based mobile application to execute a real-time classification.
A compact solution for ultra-light drone optical auto-detection and distance estimation using AI

This paper proposes a system for ultra-light drone (ULD) auto–detection using only one non-static optical PTZ camera. The system includes multi-stages of suspect objects detection, clarification, and distance estimation. An AI model for detection and clarification stages is designed based on the YOLOv3 architecture and trained with a practical dataset. In the detection stage, the camera continuously pans, tilts, and zooms to take panoramic images of the detection zone and pass them to the AI model. Once the AI model detects a suspect object, it will switch to the verification stage. In this stage, the camera controlled by the AI model’s output focuses on the target to clarify and estimate the distance to ULD. The proposed solution was implemented and tested with popular fly cams. The results show that the system can auto-detect ultra-light drones effectively with high accuracy.
Comparative Study on Image Captioning

Image captioning is a technique to generate a correct description of an image with proper structure. Now a days, Machines can describe the images and convert it into suitable language which is grammatically true. In this paper, we reviewed the existing image captioning techniques in details, divided into different categories, datasets, and results. We are focusing on those methods, which are correct grammatically and syntactically and related to deep learning (Neural network). We have also compared and reviewed the different datasets like COCO, flicker8K, etc., and results of different image captioning techniques.
Can Haptic Feedback on One Virtual Object Increase the Presence of Another Virtual Object?

This paper investigated whether increased presence from experiencing haptic feedback on one virtual object can transfer to another virtual object. Two similar studies were run in different environments: an immersive virtual environment and a mixed environment. Results showed that participants reported a high presence of untouched virtual object after touching a virtual object in a virtual reality environment. On the other hand, it was difficult to confirm that such presence transfers occurred in an augmented reality environment.
A Mixed Reality Platform for Collaborative Technical Assembly Training

We have developed a mixed reality (MR)-based platform for basic mechanical engineering concepts as a learning environment for collaborative assembly tasks. In our platform, multiple co-located users interact with virtual objects simultaneously, and during that time, the platform collects data related to participants’ collaboration and team behavior. We implemented four main sections in the platform including setup, introduction, training, and assessment. The platform provides the opportunity for users to interact with virtual objects while also acquiring technical knowledge. Specifically, for the technical component of the platform, users are asked to assemble a hydraulic pump by manipulating and fitting various parts and pieces into a provided pre-assembled blueprint. We conducted a preliminary expert panel review composed of three experts and received positive feedback and suggestions for further development of the platform.
Visualizing Perceptions of Non-Player Characters in Interactive Virtual Reality Environments

Visual effects and elements to visualize the perceptions of one’s own virtual character (also referred to as Visual Delegates) are often used in video games, e.g., status bars visualize the character’s sense of health, filters on the interface layer visualize the character’s state of mind. It is still largely unexplored whether Visual Delegates can also be used to transfer the perception of non-player characters comprehensibly. Therefore, we developed a medical virtual reality scenario using five different types of Visual Delegates to visualize three different perceptions of a virtual non-player patient. We tested for character assignment in a qualitative user study (N = 20). Our results can be used to decide more effectively what types of Visual Delegates can be used to convey perceptions of non-player characters.
A Method of Estimating the Object of Interest from 3D Object and User’s Gesture in VR

In VR, gaze information is useful for directly or indirectly analyzing a user’s interest. However, there are inconveniences in using the eye tracking in the VR device. To overcome the drawback, we propose a method of estimating an object of interest from user’s gesture instead of eye tracking. LightGBM model is trained by using distance and angle-based features that are extracted from 3d information of the object and the position and rotation of the VR device. We compared accuracy of each feature for VR device combinations and found out that it is more efficient to use all devices instead of individual devices and to use angle-based feature instead of distance-based feature with accuracy of 79.36%.
Visual Considerations for Augmented Reality in Urban Planning

The design process in architecture and urban planning has always been accompanied by a discourse on suitable visual representation. This resulted in both a wealth of visualisation styles and high sensitivity among planners regarding the visual communication of their work. Representation of projects throughout phases of the planning process often adheres to established visual standards, from concept sketch to high-end rendering. A look at contemporary Augmented Reality (AR) apps for urban planning indicates however that the quality and precision of representation seem to lag somewhat behind, entailing risks that projects are misinterpreted. This poster describes our design research on three urban planning apps developed with Swiss municipalities and outlines results that improve visual representation in AR throughout different planning phases.
Rich virtual feedback from sensorimotor interaction may harm, not help, learning in immersive virtual reality

Sensorimotor interactions in the physical world and in immersive virtual reality (IVR) offer different feedback. Actions in the physical world almost always offer multi-modal feedback: pouring a jug of water offers tactile (weight-change), aural (the sound of running water) and visual (water moving out the jug) feedback. Feedback from pouring a virtual jug, however, depends on the IVR’s design. This study examines if the richness of feedback from IVR actions causes a detectable cognitive impact on users. To do this, we compared verb-learning outcomes between two conditions in which participants make actions with objects and (1) audiovisual feedback is presented; (2) audiovisual feedback is not presented. We found that participants (n = 74) had cognitively distinct outcomes based on the type of audiovisual feedback experienced, with a high feedback experience harming learning outcomes compared with a low feedback one. This result has implications for IVR system design and theories of cognition and memorisation.
The Path of Remittances to Consumption or Saving! Albania Case Study

Since the change of the political systems in the 1990-s in Albania, massive emigration has been a continuous phenomenon of different scales in Albania. The outflow migration phenomenon is associated with the inflow of remittances to the origin families. Remittances have been a vital financial source of living for a considerable number of households. Therefore, they constitute an important financial mechanism for funding the country's economy. Empirical regression analysis in emerging economies suggests ambiguous results of remittances in the economy. Therefore, it is the purpose of this paper to investigate the effect of remittances on macroeconomic variables such as aggregate consumption, national saving, and the economic growth rate in Albania. Econometric models based on the ordinary least squared method (OLS) are performed to analyze the effect among the variables, and time series data are retrieved from the World Bank and Institute of Statistics of Albania databases. Model results based on data from the period 1992-2019 show that most of the remittance income is consumed by the recipient families contributing to the aggregate consumption demand. According to the model’s results, a 1 percent increase in remittances contributes to a 3.2 percent increase in aggregate consumption in the country. While remittances have neither a significant effect on a country's national aggregate saving nor the country's economic growth rates.
Content Deduplication with Granularity Tweak Based on Base and Deviation for Large Text Dataset

The concept of storage optimization has evolved as one of the hottest research projects in big data which brings out better solutions such as data compression which almost converges towards the deduplication technique. Deduplication is a technique that finds and eliminates duplicate content by storing only the unique copies of data whose efficiency is being qualified based on the amount of duplicate content that they hideout from the data source. The deduplication technique is a well-established storage optimization technique, so in the due course of time, various tweaks have been provided for its betterment, but it quite has some limitations that it cannot determine the tiny changes that occur among similar contents, and the chunks which are generated by segmenting and hashing the data are more sensitive to changes which produce a new chunk for every small change which ruins the concept of storage optimization, so to tackle this, content deduplication with granularity tweak (CDGT) in the Hadoop architecture has been proposed for large text datasets. The CDGT aims to improve the efficiency of deduplication by utilizing the Reed Solomon technique. This pumps out more duplicate content by verifying both intracontent and intercontent as consequence performance enhancements are met, and this system incorporates cluster-based indexing to reduce the time involved in data management activities.
Debugging

All but the most trivial programs are without errors (the first time you write them). Dealing with errors will be a big part of your life as a developer.
Text Recycling and Excessive Attribution: A Pragmatic Perspective

Text recycling—commonly referred to as self-plagiarism—is an issue that is currently garnering considerable attention with regard to its acceptability as a practice and questions of when, where, and how much of it can be permissible. Although the problem of self-plagiarism or excessive text recycling can, in the opinion of some, be circumvented by paraphrasing and the reordering of text, the practice does not constitute a legitimate means to generate new and original text. A possible means to moderate the problem of text recycling that is strongly recommended is a declaration statement explicitly stating and identifying the use of recycled text. Further problems with text recycling relate to questions as to who is the progenitor of any recycled text in question and therefore who is the owner, in a moral sense, of the text under scrutiny in cases of changing sets of authors. This leads to concerns over insufficient author attribution. On the other hand, excessive attribution can result if a too conservative mindset is adopted. Due care and cognizance of excessive/insufficient attribution are necessary to avoid such problems as well as a recognition of the concept of text ownership as described herein. Such concerns are not limited to text recycling but are present also for other types of contributions to a publication covering both mundane physical contributions (e.g., supply of materials, organisms, or apparatuses) and the continuing deployment of previously espoused or established metaphysical contributions (e.g., ideas, hypotheses, strategies, or concepts or the instigation of projects).
Student Reception of English Learning through Animated Videos in Sidoarjo Elementary Schools

This study aims to determine how students respond in learning English using animated videos in grade I SD PLUS FATIMAH AZ – ZAHRO' Sidoarjo. This research is a qualitative research in which the data is taken from the analysis of direct observation and interviews with English class teachers. Collecting data in this study using documentation and interviews. The data analysis technique uses data reduction, data presentation, and drawing conclusions. The results of this study indicate that student responses are divided into three components, namely cognitive, affective, and conative. This study also shows that students in one class are divided into three parts in the ability to understand English learning, namely the competent level, medium level, and low level. Lack of interest in learning English and internal and external factors such as family background and students' skills or abilities are one of the causes of students' lack of response to learning English.&#x0D; Highlights: &#x0D; &#x0D; The study focuses on understanding student responses in learning English using animated videos in a specific grade and school in Sidoarjo.&#x0D; The research employs qualitative methods, gathering data through direct observation, interviews with English teachers, and documentation.&#x0D; The study identifies three components of student responses: cognitive, affective, and conative, and highlights the varying levels of English understanding among students. The lack of interest and external/internal factors also affect students' response to English learning.&#x0D; &#x0D; Keywords: English learning, Animated videos, Student responses, Grade I, SD PLUS FATIMAH AZ – ZAHRO' Sidoarjo