Reviewerly/exHarmony huggingface dataset:
Extracting Emotion and Sentiment Quotient of Viral Information Over Twitter

In social media platforms, viral or trending information are consumed for several decision-making, as they harness the information flux. In apt to this, millions of real-time users often consumed the data co-located to these virilities. Thus, encompass sentiment and co-located emotions, could be utilized for the analysis and decision support. Traditionally, sentiment tool offers limited insights and lacks in the extraction of emotional impact. In these settings, estimation of emotion quotient becomes a multifaceted task. The proposed novel algorithm aims, to (i) extract the sentiment and co-located emotions quotient of viral information and (ii) utilities for comprehensive comparison on co-occurring viral information, and sentiment analysis over Twitter data. The emotion and micro-sentiment reveals several valuable insight of a viral topic and assists in decision support. A use-case analysis over real-time extracted data asserts significant insights, as generated sentiments and emotional effects reveals co-relations caused by viral/trending information. The algorithm delivers an efficient, robust, and adaptable solution for the sentiment analysis also.
Multidimensional Analysis of Serpentinite Dehydration Networks and Implications for Volatile Flux in Subduction Zones&amp;#160;

&amp;lt;p&amp;gt;Subduction zones are principal pathways for the cycling of volatiles such as &amp;lt;sub&amp;gt;&amp;amp;#160;&amp;lt;/sub&amp;gt;hydrogen and carbon&amp;lt;sub&amp;gt;&amp;lt;/sub&amp;gt;from the Earth&amp;amp;#8217;s surface to the mantle and back to the atmosphere. This cycling has significant long-term effects on Earth&amp;amp;#8217;s climate. However, the processes that lead to volatile release during subduction and total volatile fluxes are poorly understood. In our study, we will quantify and characterize the network architecture of dehydration pathways exhibited as mineralized olivine-bearing metamorphic veins in the exhumed meta-serpentinites from the Erro-Tobbio unit, Italy [1]. Applying network analytical methods and graph theory both macroscopically and microscopically can provide the mode of propagation and describe the controlling factors affecting the evolution of these dehydration networks. Furthermore, multiscale observations can confirm the scalability of the vein network and if quantitative results such as permeability or volatile flux can be extrapolated to larger scales.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Along with 2-D network analysis, these vein networks will be analyzed in 3-dimensions using X-ray tomography and sophisticated machine-learning methods, such as generative adversarial networks. The results of both will be compared, which can then assure whether current machine-learning methods can effectively create statistically equivalent copies of these networks. Lastly, the synthesis of 2-D and 3-D multiscale results should provide meaningful parameters for accurate calculations of volatile flux during the dehydration of subducting slabs.&amp;amp;#160;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;amp;#160;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;[1] Pl&amp;amp;#252;mper &amp;lt;em&amp;gt;et al.&amp;lt;/em&amp;gt; (2017) &amp;lt;em&amp;gt;Nature Geoscience &amp;lt;/em&amp;gt;&amp;lt;strong&amp;gt;10(2)&amp;lt;/strong&amp;gt;, 150-156.&amp;lt;/p&amp;gt;
Deep based learning: ebin sorting system development

Vietnam was the fifth country that dumped more plastic into the oceans than the rest of the world combined. The country produces an average of 25.5 million tons of waste per year, of which 75% is buried. Several burial sites in major cities such as Hanoi, Ho Chi Minh city, and Da Nang city are overloaded and negatively affecting citizens’ lives. Therefore, sorting at source would significantly reduce soil resources and groundwater pollution and save money on collection costs, transportation, treatment, and easing the pressure on the landfills. Using computer vision may help classify easily recyclable trash into different categories based on its material. This paper proposes an experiment on a customed Convolution Neural Network (CNN) based waste detector for three classes of trash: Plastic bottles, Cans, and Glass. The study used up to 900 hand-collected image data separated into 500 for analysis and 400 remains for assessing the result. All trashed objects used for generating data were collected around the Ho Chi Minh city University of Technology (HCMUT, Vietnam). The Deep Learning model used in this research, named SSD MobileNet V2, is part of the open-source Tensorflow Object Detection API. The system gave the result, the relative match percentage of different amounts of data we fed the model. The system showed linear relativity between the amount of data trained AI100, AI200, AI300, AI400, AI500, and the mean Average Precision (mAP) when testing the system. From this on, the study conducted another experiment to ensure that the performance of the trained model would meet expectations, AI401. In this experiment, the system showed over 80% inaccuracy overall. By back-analysis, this paper would be a good vision for researchers to study and enhance the system’s accuracy to serve the purpose of trash classification in innovative trash bin applications.
Evaluasi Kualitas Website Menggunakan Webqual 4.0 (Studi Kasus: Sistem Informasi Kebencanaan Kabupaten Boyolali)

This study aimed to measure the quality of the Disaster Mitigation Information System (Sikabi) belonging to the Regional Disaster Management Authority of Boyolali Regency. Quality tests are carried out to determine the quality and functionality of the system that functions optimally and can display accurate, easily accessible, and useful information for disaster mitigation in the region. The results of the study are useful for providing feedback to information system developers regarding the quality of the website usability aspect, the quality of the information presented, and the quality of the interactions provided as well as the user satisfaction at accessing the Disaster Information System website. This study uses the Webqual 4.0 method which has 4 assessment variables, namely in terms of usability (information quality), interaction service (interaction quality), and user satisfaction while accessing the website (overall impression). From the research results, the information quality variable has a sig value. 0,000 &lt;0,05 which indicates that there is an influence of information quality on user satisfaction in using the Sikabi website. Therefore, we recommend improving the quality of the information displayed on the Sikabi website page.
Educating Students in Better Campus Environment in the Vision of Human - Environment System

College is a major venue to shape high-calibre talents, and campus environment plays a critical part in this regard. The author, in the perspective of Human - Environment System, gauges the connotation of campus environment and how it affects the shaping of college students, and studies how to enhance campus culture with scientific outlook to send high-calibre graduates to the country.
Simulation-to-Reality Domain Adaptation for Offline 3D Object Annotation on Pointclouds with Correlation Alignment

Annotating objects with 3D bounding boxes in LiDAR pointclouds is a costly human driven process in an autonomous driving perception system. In this paper, we present a method to semi-automatically annotate real-world pointclouds collected by deployment vehicles using simulated data. We train a 3D object detector model on labeled simulated data from CARLA jointly with real world pointclouds from our target vehicle. The supervised object detection loss is augmented with a CORAL loss term to reduce the distance between labeled simulated and unlabeled real pointcloud feature representations. The goal here is to learn representations that are invariant to simulated (labeled) and real-world (unlabeled) target domains. We also provide an updated survey on domain adaptation methods for pointclouds.
Application of Edge Computing in the Quality Control of Cable Production Process

Abstract Given the lack of quantifiable evaluation criteria for the quality supervision and control in the existing power cable industry, insufficient research on the correlation of production indexes in the production process, and low timeliness in the analysis and processing of massive multi-source production data, the video monitoring model and data-driven process quality evaluation strategy model under the edge computing framework were constructed. Next, all the production data and test data in the cable production procedures were captured using edge nodes, and the factory-side data was cleansed, processed, and analyzed. The cable manufacturing quality was evaluated through edge computing, and the business process was arranged based on the edge computing results, so as to improve the cable product quality and finally optimize the total value chain of production in the whole cable industry.
Effects of a New Media Data Interaction System on Teaching Efficiency in Vocational Education

The new media data interaction system has profound influences on the teaching efficiency of vocational education. Therefore, its effects on the teaching efficiency of vocational education were analyzed in this study. The analysis was carried out from the perspective of the satisfaction of students with the application of the new media data interaction system in their vocational education and teaching practices. According to scale statistics and the multi-grade fuzzy satisfaction calculation model, results reveal that students are relatively satisfied with the services provided by the new media data interaction system and its effects on teaching efficiency, thereby indicating that such teaching mode can lead to good teaching efficiency. These students also have relatively positive attitudes toward teaching activities based on the new media data interaction system, and this teaching mode can improve their academic performance in vocational education, hence achieving good teaching efficiency. Students of classes that use the new media data interaction system also report higher learning efficiency compared with those students in classes that do not use this system.
Analysis and research on breakdown cause of lightning arrester at low voltage side of 220kV transformer

Abstract This paper describes an event of zinc oxide arrester breakdown at low voltage side due to single-phase grounding at medium voltage side of 220kV transformer. Combined with the system wiring mode, equipment damage, system background and test data, the causes of fault and the transmission mechanism of overvoltage are studied in detail, It is concluded that the single-phase grounding short circuit on the medium voltage side leads to the displacement voltage of the neutral point, and the overvoltage is transmitted to the low voltage side through the capacitive coupling between the transformer windings, resulting in the breakdown of the arrester. The correctness of the conclusion is verified by calculation, and reasonable rectification measures and suggestions are put forward to effectively limit the generation of overvoltage on the low-voltage side of the transformer and ensure the safe and stable operation of the power grid.
Fraud Feedback Detection using Machine Learning Technique

In the era of e-commerce, people often purchase the most of product from online shopping websites, customers rely on the number of reviews and stars of product to choose the right product for them. Fraud companies also pay to fraudsters to increase the rating of product, this tends to mislead the people and people end up with the product that they are not satisfied with. This can be stopped in some extent with the help of machine learning algorithms. The purposed method uses Machine Learning Algorithm like Random Forest, ANN, Support Vector Machine which helps the people to differentiate between fraud feedbacks and original reviews.
Multidimensional Sentiment Cube Mining for Process Monitoring

Process monitoring is essential for quality improvement because it is necessary to find the answers to which business issues need to be understood. In the era of social media, many critiques concern the business domain, including life insurance, which is one of the significant business sectors in Thailand. To utilize this useful cloud corpus for the business improvement process, we propose a novel methodology for process monitoring using the concept of multidimensional sentiment cube (MDSC) mining to raise usefulness with the business process model notation (BPMN). As the ability of MDC raise unlimited analysis perspectives merge with sentiment analysis (MDSC), this method can provide more sets of data for association rules mining and meet the needs to be analyzed. The cube analysis scenario, which uses association rules mining results, can reveal a significant hidden issue among aspects and sub-aspects associated under our design with their measurements. The results can be used for monitoring, which presents the customer's sentiment from social media in the real business case and identifying in the real process model.&#x0D; HIGHLIGHTS&#x0D; &#x0D; A methodology for process monitoring using the concept of multidimensional sentiment cube (MDSC) mining raise the usefulness of the business process model notation (BPMN) by utilizing the corpus for the business improvement process&#x0D; This method can provide more sets of data for association rules mining as the ability of MDC raise unlimited analysis perspectives to merge with sentiment analysis (MDSC)&#x0D; The results can monitor the customer’s sentiment from social media in the real business case and identify in the real process model&#x0D; &#x0D; GRAPHICAL ABSTRACT
Emerging Optical Materials, Devices and Systems for Photonic Neuromorphic Computing feature issue: publisher’s note

This publisher’s notes amends the title of [ Opt. Mater. Express 12 , 1214 ( 2022 ) 10.1364/OME.451016 ].
Education Policy of Sudan and Utilization of the Mobile Device (iPad) Technology: Opportunities and Challenges

The Sudanese education system, in recent years, has seen a significant expansion because of the significant increase in the numbers wishing to learn. There is a necessary need for expanding educational services to cover this vast number of scholars. The existing service is showing a clear deficit through physical, human, and spatial limitations. This illustrates the necessity to employ modern technologies such as mobile devices (iPad) to support education. Therefore, this paper seeks to review the use of mobile device (iPad) technology in education and explore the opportunities and challenges of utilizing iPad technology in the education system of Sudan. This paper reached to the use of mobile device (iPad) technology in the Sudanese education system providing opportunities for networking learning, social learning, interactive learning, and distance learning. There are several challenges facing the utilization of mobile device (iPad) technology in the Sudanese education system in which the delivery of information by traditional methods is better than the use of mobile learning, there is no clear plan for the usage of mobile devices by the competent authorities, lack of training to use and employ the mobile learning. The paper recommended providing facilities to improve opportunities to incorporate technology into the Sudanese education system.
Statistical analysis of the impact of the e-learning platform Furago on French learners’ listening skills

Albéric Derible, Éric Wiel - The current study focuses on an e-learning platform called Furago designed to provide language instructors with exercises complementing activities already implemented in their classes.
MOBILE USER INTERFACE DESIGN FOR SMALLHOLDER AGRICULTURE TO BE A SMART FARMER: A SCOPING REVIEW

Mobile user interface (UI) design plays a very important role in determining an application that can be adopted by all types of users, especially those residing in rural areas. This review aims to provide a mapping of previously published studies on mobile UI design application for smallholder agriculture to be a smart farmer. The focus of this scoping review is on the design elements of the proposed UI, strategies of inquiry used and to find out if there is a UI design that involves geospatial context by published articles. The results show that interview and observation are the most common field study methods used to obtain information in designing mobile UI, and the most widely applied UI elements are audio and Interactive Voice Response (IVR). There are many user interface elements that can be used by farmers who have different skills level in dealing with mobile technology. Icon interface is an important element in designing mobile UI for rural farmers based on previous results. Other than that, the use of location function in mobile UI design shows an upward trend where three recent articles used location function to report crop pest and disease and determine the nearest market location. In addition, there is a need to design geospatial elements such as map for mobile UI that match the skills of rural farmers to support the fourth Industrial Revolution in agriculture to be a smart farmer.
The Role of Machine Learning and Internet of Things in Digital Health Transformation

It is expected that by 2030, 60% of world’s population will be in cities. With increase in population and the complexity of the infrastructure, cities need intelligent techniques. The rapid development of information and communication technologies (ICT) supports the concept of smart cities. Recently, this concept has played a significant role in academia and industry. In the era of internet of things (IoT), cities have become smarter and connected devices generates massive amount of data. Thus, Machine learning (ML) can be applied to improve the intelligence and the abilities of IoT applications. ML is a branch of artificial intelligence (AI) that handles with the analysis and construction of systems from the knowledge obtained from the data. The applications of ML and IoT has attracted many researchers. These applications include smart health, smart education, smart transportation and others. So, ML and IoT can develop a smarter environment and a simple lifestyle. The aim of the current chapter is to provide a review on the role of ML and IoT in smart cities and it is mainly focused on the role of AI, IoT and blockchain in digital health transformation. It also discusses the challenges of IoT in smart cities. Future research directions are suggested at the end of the chapter. It was found that ML and IoT approaches had remarkable contribution to the development of smart cities. Moreover, blockchain can provide an effective solution to overcome the security challenge of IoT. In addition, secure healthcare digital systems can be achieved via integrating IoT with Blockchain. Also, fog computing technology can be integrated with IoT systems to minimize the latency of e-healthcare.
A REGULATION APPROACH OF PUBLISHING FALSE OR FAKE NEWS: A CASE STUDY OF VIETNAM MAGAZINES

Over years 2016, 2018, 2020, there are many fake news and false information published online in the case of Vietnam magazines and newspaper, after Thanh nien newspaper, then Tuoi tre newspapers also delivered fake or false information online (tuoitre.vn) in 2018, for instance.Rumours, false news and misinformation continuously spread and became viral across different media and social media platforms.The worst of all is the existence of opportunist who take advantage of the articles/victims' mishaps to make illegal personal gain by seeking donation that will go to their pocket.This reveals a shocking truth that social media and ICT could be manipulated thus brought with it both opportunities and risks, as well as false hope particularly to the articles who need immediate and eminent help during the occurrence of the disaster (Suruhanjaya Komunikasi dan Multimedia Malaysia, 2014).By using some examples of a case study and qualitative analysis methods, including synthesis, explanation, and inductive approaches, this study figure out that the case of publishing fake news taking place has cause troubles and misunderstandings in society and other bad effects; hence, we need suitable mechanism to solve people in charge and need to propose new standards and training program for staff of Vietnam newspapers.Then lessons for educating student sin universities esp.In journalism major are suggested with direction from President Ho Chi Minh ideologies stating the revolutionary role of journals and newspapers.
A Generic Framework for Structuring Configuration Management for Socio-technical System: Application to Control Rooms

Control rooms are workspaces that serve the purpose of managing and operating physically dispersed systems, services and staff. They embed multiple types of systems and software, which may themselves have several characteristics. Configuration management consists in processes and techniques to systematically identify and manage the characteristics of these systems and software, as well as their changes, in order to ensure the reliability of the operations. However, systems and software are not the only elements for which several characteristics are to be managed in order to ensure the reliability of the operations in a control room. The following elements are also important: procedures, organizational processes, team structures and crewmembers. In addition, the characteristics of these elements may also vary over time. Operational procedures may change, as well as processes, team structure and crewmembers skills’ level and knowledge level. In this paper, we propose a conceptual framework to address in a systematic and integrated way, and from a socio-technical point of view, the configuration management of all of the elements of a control room. These elements are systems and software, crewmembers that are in charge of the operations, operational procedures the crewmembers apply, as well as processes and standards released by organizations that are responsible for the operations.
The Newspaper Reading Habits of University Students: A case Study of University of Peshawar, Khyber Pakhtunkhwa, Pakistan. (2018)

Through a questionnnaires based survey, newspaper reading habbits of the students of different faculties of university of Peshawar have been studied, in which a sample size of about 100 students have been used. This study demonstarates that majority of the students read Urdu Newspapers, like Daily Mashriq, Ajj, Express and Jang. While, some also read English Newspapers as well , like Daily Dawn and The Frontier Post etc. Moreover, the research reveals that ; political section of the newspaper is the most preffered section for the students. It, also highlights that, majority portion of the respondents prefer home to read a newspaper, while some prefer to read online newspapers in the hostel or department library.
CHEHRA: An Application for Forensic Face Sketch Construction and Recognition

In this modern age, the overall crime rate is increasing day-by-day and to cope up with this the law enforcement departments too should find ways that would speed up the overall process and help them in bringing one to justice. One such way can be using face recognition technology for identifying and verifying the criminal. The traditional approach here is to use the hand-drawn face sketches drawn by forensic sketch artist to identify the criminal, modernizing this would mean using the hand drawn sketch and then matching them with the law enforcement departments database to identify the criminal. We believe, there is a need for creating an application which would not just provide a set of individual features like eyes, ears, mouth, etc. to be selected to create a face sketch but also would help in finding the criminal much faster and efficiently.