Reviewerly/exHarmony huggingface dataset:
SECOND-Order Encoder and Restore Detail Decoder Network for Image Semantic Segmentation

Traditional convolution and pooling operations in the previous semantic segmentation methods will cause the loss of feature information due to limited receptive field size. They are insufficient to support an accurate image prediction result. To solve this problem, Firstly, we design a Second-Order Encoder to enlarge the feature receptive field and capture more semantic context information. Secondly, we design a Restore Detail Decoder to focus on processing the spatial detail information and refining the object edges. The experiments verify the effectiveness of the proposed approach. The results show that our method achieves competitive performance on two datasets, including PASCAL VOC2012 and Cityscapes with the mIoU of 80.13% and 76.31%, respectively.
LSIHS: Long and Short-term Recommendation Model Integrated with Hierarchical Structure

Personalized news recommendation is essential to relieve information overload and improve users’ experience. The existing recommendation models would only be concerned with the users’ single representations. In fact, everyone has some long-term interests and short-term interests, and these interests are diverse and multi-grained. In this paper, we propose a Long and Short-term Recommendation Model Integrated with Hierarchical Structure (LSIHS). The model uses a three-level hierarchical structure to capture multi-grained long-term interests, uses the Gated Recurrent Unit (GRU) to capture the short-term interests, and uses the long-term interests to initialize the GRU. We do some experiments on three datasets. The results show that the model effectively improves the performance of personalized recommendation.
Estrategia CMID adaptada a la virtualidad para estudiar el equilibrio térmico en formación inicial docente

The use of the Interactive Lecture Demonstrations strategy adapted to virtual session to a fifth-year student teachers’ class is described. The results are analyzed under the approach oriented to the student teachers' level of understanding of the concept of thermal equilibrium and to their pedagogical knowledge. At the beginning, 83% of the students had inadequate previous ideas about how the temperature of two objects in thermal contact, both with different mass and different initial temperatures, change over time. After applying the strategy, Hake's factor was determined to know the learning gain. Its value was 0,429, which is considered a medium gain. The student teachers’ exit ticket showed the high valuation given by them to the ILD strategy. Student teachers highlighted the importance of social learning and the process of their own physics concept reconstruction through a metacognition exercise.
Research on the Value of educational psychology in the Reform and Development of Higher Education

With the rapid development of social economy and higher education, China's higher vocational education has also been developed significantly.However, due to the lack of certain historical precipitation and insufficient teachers compared with ordinary colleges and universities, higher vocational education has led to the problems of low teaching quality and poor learning effect of students, which are increasingly prominent.In this situation, educational psychology is an emerging discipline with unique advantages, which can provide effective solutions to the problems existing in higher vocational education.From the perspective of educational psychology theory, this paper analyzes the problems faced by higher vocational education and the role of educational psychology in solving these problems, aiming to explore the role and value of educational psychology in the process of development of higher vocational education in China.
Evaluation of the Performance of the Roraya I Irrigation Network in Baito District in South Konawe Regency

Development and management of irrigation networks requires good infrastructure so that it will support increased food production, improve community welfare and optimize the use of water resources. The purpose of the study was to analyze the performance of the physical infrastructure irrigation system in the Roraya I Irrigation Area, and to analyze the handling of the physical infrastructure irrigation system performance in the Roraya I Irrigation Area The results of the analysis of the performance of irrigation networks on physical infrastructure are lacking and need attention, with a weight value of 59.44%, and for handling irrigation networks on physical infrastructure in the form of maintenance that is heavy repair or replacement
DEVELOPING DIGITAL COMPETENCE FOR PHILOLOGY TEACHERS IN THE NORTHERN MOUNTAINOUS AREA OF VIETNAM

Enhancing the digital competence of teachers is not only an urgent issue to help students live in a safe and effective digital environment, but also a key to improving the quality of education, bridging the gap in education and leaving no student behind. However, the development of this competence for English language teachers in the northern mountainous area of Vietnam still faces many difficulties. The article presents research results on digital competence: the concept, importance, and framework of teachers' digital competence and proposes some measures to develop digital competence for Philology teachers in the northern mountainous area of Vietnam.
Provision and administer Cloud Spanner instances and databases

Managing a large number of databases canbe a daunting task, especially when the databases arecritical to the performance and trustability of theoperations and services they support. In this design, weexplore how Cloud Spanner can be used to streamlinedatabase operations and ameliorate the overallperformance and operation of database structure. Webegin by introducing Cloud Spanner and its crucialfeatures, including its capability to gauge horizontally,its high vacuity, and its SQL support. We also describethe process of designing and creating Cloud Spannerdatabases, including how to define the schema, configureaccess control, and set up covering and waking. We alsobandy advanced features of Cloud Spanner similar aspartitioning, sharing, and secondary indicators, and howthey can be used to optimize query performance andreduce costs. Throughout the design, we validate ourprocess, challenges, and issues, furnishing a case studythat demonstrates the benefits of using Cloud Spannerfor database operations. We show how Cloud Spannercan ameliorate the ease of operation and reduce the totalcost of power of database structure, while also perfectingperformance and trustability. We also give perceptivityand stylish practices that can be useful for otherassociations looking to borrow Cloud Spanner oranalogous pall- grounded database results. Bystreamlining database operations with Cloud Spanner,associations can concentrate on erecting betteroperations and services, rather than spending time andcoffers on managing and maintaining their databases.The benefits of using Cloud Spanner include increasedscalability, high vacuity, and SQL support, as well asreduced costs and bettered ease of operation.
Securing Access to Applications with IAP and Compute Engine

Cloud Identity- Aware Proxy (IAP) is a security service handed by Google Cloud Platform that allows directors to authenticate and authorize access to web operations and VMs running on Google Cloud. This service provides a fresh subcaste of security to operations and VMs by vindicating the stoner's identity and determining if they've authorization to pierce the resource. Setting up Cloud IAP for Compute Engine involves configuring access programs, OAuth2.0 customer IDs, and firewall rules. Once configured, IAP allows only authorized druggies to pierce the operation, grounded on their Google identity and class in specific Google groups. In this process, directors must produce an access policy, which determines which druggies or groups can pierce the operation. They must also produce an OAuth2.0 customer ID, which is used for authentication with IAP. Eventually, the director must modernize the Compute Engine case firewall rules to allow business from IAP. The benefits of setting up Cloud IAP for Compute Engine include enhanced security for the operation and the capability to manage access to coffers centrally. It also eliminates the need to manage access control within the operation and simplifies the process of granting or repealing access for druggies. While setting up Cloud IAP for Compute Engine can be a complex process, following the recommended way ensures that the operation is secure and only accessible to authorized druggies.
The Role of Civic Education to Overcome the Limitations of Meritocracy

Objectives The purpose of this study is to explore the role of civic education to overcome the limitations of meritocracy in Korean society.&#x0D; Methods To this end, after analyzing the relevant literature on the characteristics and limitations of meritocracy, in relation to the meritocracy culture currently operating in Korean society and the problems of education it has caused, the promotion of social inequality, the destruction of individual morality, and the instrumentation of education center was explored. Based on this, the role of civic education to overcome the limitations of meritocracy was considered in relation to the cultivation of virtues that citizens should have.&#x0D; Results In Korean society, meritocracy has become a rational ideology required for fair competition, breaking away from family succession in the past. However, meritocracy has made people recognize that the differential distribution of rewards according to ability is reasonable, and has also influenced the spread of consciousness that regards individual abilities as purely the product of one’s own efforts. A strong belief in meritocracy is of little help in resolving social inequality and can harm relationships between people. In Korean society, meritocracy encourages savage competition and has an impact on undermining the essence of education.&#x0D; Conclusions By cultivating humility and solidarity, students can overcome the limitations of meritocracy and grow into desirable citizens who live with a greater sense of responsibility for the community. There is a need for civic education that leads students to cultivate a sense of solidarity based on the virtue of humility and a sense of respect for others.
Single Imputation Using Statistics-Based and K Nearest Neighbor Methods for Numerical Datasets

Handling missing values is often an unavoidable problem.Imputation is a preferred option in handling missing values compared to removing all row records which will reduce the number of datasets and can lead to poor research results if the size of the remaining data is too small.The problem that often occurs is that there are often wrong conclusions due to some records that have missing values, therefore this study will test several simple imputation methods, namely statistical-based imputation and kNNI.The results of testing the error value with RMSE and MAPE show that kNNI imputation results are much better than statistical-based imputation.Based on the standard used in the MAPE test, the kNNI test results (error values) are almost entirely very good because the error value is <10% except for three test results in dataset 1 at k=10, k=15 and k=20, while the statistical-based imputation results are only good because the error value is between 10% and 20%, even one of the results exceeds 20% Although kNNI is better than statistical-based imputation, it is necessary to choose the right k value to get the best imputation results.
Toward a Holistic Virtual Environment for Graph Visualization and Analysis

Interactive data visualization plays a crucial role in the interpretability of large datasets. Virtual reality offers unique advantages in exploring data, beyond traditional 2-D views. This article presents a set of interaction artifacts designed for analyzing and interpreting complex datasets through immersive 3-D graph visualization and interaction. Our system makes complex datasets easier to work with by offering a wide range of visual customization tools and intuitive methods for selection, manipulation, and filtering. It also provides a cross-platform, collaborative environment that can be accessed by remote users through traditional computers, drawing tablets, and touchscreen devices.
Examining the Generalizability of English Cyberbullying Detection Models on Malay Informal Text Using Direct Translation

As cyberbullying on social media platforms becomes more rampant in Malaysia, there is a need for automatic cyberbullying detection models that can handle text in the local Malay language. Although Malay is widely used in Malaysia, it remains a low resource language particularly the availability of high-quality Malay cyberbullying corpora required to train machine learning models to effectively identify cyberbullying in the local context. Our study explores the possibility of borrowing from an existing cyberbullying corpus (Formspring with 13,153 posts) in a resource rich language to train an English cyberbullying detection model, and then evaluate the performance of the model on a test set containing 3663 Malay WhatsApp messages translated to English. By using direct translation, we reveal that the model performance greatly relies on the quality and accuracy of the English-to-Malay translation, a problem that is exacerbated by many informal Malay expressions and slangs in WhatsApp messages.
Remote Perception Attacks against Camera-based Object Recognition Systems and Countermeasures

In vision-based object recognition systems imaging sensors perceive the environment and then objects are detected and classified for decision-making purposes; e.g., to maneuver an automated vehicle around an obstacle or to raise alarms for intruders in surveillance settings. In this work we demonstrate how camera-based perception can be unobtrusively manipulated to enable an attacker to create spurious objects or alter an existing object, by remotely projecting adversarial patterns into cameras, exploiting two common effects in optical imaging systems, viz., lens flare/ghost effects and auto-exposure control. To improve the robustness of the attack, we generate optimal patterns by integrating adversarial machine learning techniques with a trained end-to-end channel model. We experimentally demonstrate our attacks using a low-cost projector on three different cameras, and under different environments. Results show that, depending on the attack distance, attack success rates can reach as high as 100%, including under targeted conditions. We develop a countermeasure that reduces the problem of detecting ghost-based attacks into verifying whether there is a ghost overlapping with a detected object. We leverage spatiotemporal consistency to eliminate false positives. Evaluation on experimental data provides a worst-case equal error rate of 5%.
What happened in Digital and Computational Pathology at the European Congress of Pathology, Basel, 2022?

The WG Digital &amp; Computational Pathology, formerly called the WG IT (Computational) enjoyed an active presence at the 34th European Congress of Pathology (ECP) 2022 in Basel. Whether tackling the important question of “AI: useful or useless” in different disease entities, to a live demonstration of “AI in the wild” during the hugely popular Computational One-Day Symposium, or discussing critical aspects of quality management and ethics at the AI Taskforce meeting, the presence of digital and computational pathology could certainly be felt. Importantly, abstracts for poster sessions and oral free papers were abundant, highlighting the increasing relevance and interest of these topics for pathologists across Europe and beyond. Here, we give a short report on the activities connected to digital &amp; computational pathology at the ECP.
Deep-learning-based interpretability and the ExaMode project in histopathology image analysis

With digital clinical workflows in histopathology departments, the possibility to use machine-learning-based decision support is increasing. Still, there are many challenges despite often good results on retrospective data. Explainable AI can help to find bias in data and also integrated decision support with other available clinical data. The ExaMode project has implemented many tools and automatic pipelines for such decision support. Most of the algorithms are available for research use and can thus be of help for other researchers in the domain.
A Study of Mobile Application ‘PRAGATI’

In today’s digital age, where technology is at the forefront of our daily lives, learning has become more accessible than ever before. With smart phones and tablets being a staple for most people, the development of tutorial apps has revolutionised the way people approach learning. A tutorial app is a software application designed to provide educational content and guidance to its users. Tutorial apps can be used to learn a wide variety of subjects, ranging from languages, mathematics and programming. These apps offer a unique and personalised learning experience that is tailored to the user needs and learning style. Tutorial apps use different methods of teaching, including interactive exercises, quizzes, games, videos, and audio lessons, to make learning engaging and fun.
AN INTRODUCTION TO CLOUD COMPUTING PLATFORM

Being immersed in the general and inevitable trend of the times, our country is step-by-step transforming itself into the stage of industrialization and modernization. Everything is coming down to ease, convenience and, above all, accuracy. Therefore, digital transforming is a great opportunity to close the gap towards the goal of becoming a much more developed country. Cloud computing plays a huge role in creating a revolutionary change in a good part of the economy, including Vietnam's banking system. Basically, it helps change the way existing resources are used, the operating structure by storing, distributing and processing information. Cloud computing application is becoming an inevitable course as it allows banks to integrate tasks through shared tools and platforms. As a result, decisions in economic movements are efficiently and promptly determined. The article focuses on introducing cloud computing platforms, digital transformation structures, analyzing the current situation, thereby giving recommendations on using cloud computing in the digital transformation of Vietnamese banks.
Web Peta Informasi Kodisi Jalan Kabupaten di Kecamatan Talang Kelapa Kabupaten Banyuasin

Road conditions affect the level of service and community comfort in supporting the economic, social, and cultural activities of the community, if road conditions do not support this it will hinder these activities. However, the problem in the field is the condition of the damaged roads and the reporting system that has not been integrated so repairs are slow. Therefore we need a systematic and integrated road condition reporting system so that the order of priority for handling road conditions is correct. Mapping the road network using a Web-based Geographic Information System is one of the solutions that can be used to overcome this problem. The method used in this study is the GIS application for mapping road conditions in the Talang Kelapa sub-district, Banyuasin district with a total of 143 Km of roads. After that, the mapping of the GIS application made a website so that users can access road conditions from anywhere with an internet network. The results of research on previous road conditions using the Surface Distress Index (SDI) method show that there are 4 categories of road conditions in the Talang Kelapa sub-district, namely: Heavily Damaged, Lightly Damaged, Moderate and Good. integrated with the Website, where the Website address https://peta_jalan_banyuasin.gis.co.id/ can be accessed.
RANCANG BANGUN SISTEM INFORMASI PENERIMAAN PESERTA DIDIK BARU BERBASIS WEB PADA SMK ISLAMIC CENTRE CIREBON

Learning media is a means of communication in the teaching and learning process in the form of hardware and software to achieve learning processes and outcomes effectively and efficiently, and can overcome the limitations of learning space and time. The purpose of this research is to design and produce a distance learning system product using raspberry pi as a portable server. The method used is the method of research and development (Research and Development) with the technique of observation, interviews and literature studies that are tailored to the needs of learning media in SMK Negeri 1 Cirebon. The test technique for this distance learning system uses the Black Box, namely testing is done by checking all statements in the program that are executed at least once and server testing is carried out by 30 students of industrial electronics engineering at SMK Negeri 1 Cirebon. The results of this study are a web server that runs on a raspberry pi 4 and can be accessed via a local or public network. The advantages of this tool are that it is cheaper than a server and is portable so that it can be moved from one place to another. The test results show that the server running on the raspberry pi 4 can function properly and can be implemented based on its purpose.
Analysis of the current algorithms for calculating regions area of users interest when streaming video content

Currently, there are many algorithms for evaluating video quality, which use the region of interest search algorithm for correct operation. In order for algorithm developers to improve the performance of region-of-interest search methods, in this paper we compare algorithms for searching regions of interest using data obtained during subjective tests. Subjective estimates of the region of video interest require a lot of time for experimentation and are not feasible in real-time applications. Interest in this technology is growing every year. In this article, we compare several algorithms for calculating regions of interest: a neural network, an algorithm for calculating a binarization threshold for a grayscale image, a method for detecting a prominent area using a high-dimensional color transformation, and a watershed segmentation algorithm. This work will be useful for video compression researchers, as well as for creating additional test materials, planning future experiments and improving existing algorithms for searching regions of interest.
Exploring the Effects of Scanpath Feature Engineering for Supervised Image Classification Models

Image classification models are becoming a popular method of analysis for scanpath classification. To implement these models, gaze data must first be reconfigured into a 2D image. However, this step gets relatively little attention in the literature as focus is mostly placed on model configuration. As standard model architectures have become more accessible to the wider eye-tracking community, we highlight the importance of carefully choosing feature representations within scanpath images as they may heavily affect classification accuracy. To illustrate this point, we create thirteen sets of scanpath designs incorporating different eye-tracking feature representations from data recorded during a task-based viewing experiment. We evaluate each scanpath design by passing the sets of images through a standard pre-trained deep learning model as well as a SVM image classifier. Results from our primary experiment show an average accuracy improvement of 25 percentage points between the best-performing set and one baseline set.