Reviewerly/exHarmony huggingface dataset:
P091 Assessing Level of Interest in In-person and Virtual Nutrition Education Among SNAP-Ed Eligible Utahns

<h3>Background</h3> In response to SARS-CoV-2, Utah's Supplemental Nutrition Assistance Program-Education (SNAP-Ed) pivoted from in-person to virtual nutrition education classes. Virtual nutrition programs have been found to be effective among certain demographics. Additionally, virtual classes may be a preferred mode of SNAP-Ed nutrition education delivery. <h3>Objective</h3> The objective of this needs assessment was to compare the level of interest in in-person and virtual nutrition classes, as well as several online platforms among SNAP-Ed eligible Utahns. <h3>Study Design, Settings, Participants</h3> An electronic survey was sent to eligible Utahns through a listserv of current SNAP recipients, a SNAP-Ed e-newsletter, and links posted on SNAP-Ed social media platforms. Survey respondents were asked to report demographics, preferred frequency and duration of classes, and electronic device use and access barriers. Respondents also ranked six preferred modes of delivery including in-person, Facebook Live, YouTube, Zoom, Canvas, and other. <h3>Measurable Outcomes/Analysis</h3> Descriptive statistics were collected and analyzed. Responses to questions about class duration and frequency, virtual platforms, and electronic device use were compared among age groups, ethnicities, gender, and rurality. Respondents ranked six modes of delivery on a scale of 1-6 (1 = most preferred; 6 = least preferred) and mean scores were calculated. <h3>Results</h3> Two-hundred sixty-nine individuals completed the survey. In-person classes were ranked as the most popular mode of delivery (mean = 2.57) followed by Facebook Live (2.77), YouTube (2.84), Zoom (2.97), Canvas (3.89), other (5.73). In-person classes were ranked highest among most subgroups, however virtual classes were most popular among respondents aged 18-24 & older than 35. Respondents most selected weekly (49%), 45-minute classes (33%) as the preferred frequency and duration. Seventy percent reported no barriers to internet access. <h3>Conclusions</h3> The results of this assessment suggest that virtual education may be a valuable tool to reach certain subgroups of SNAP-Ed eligible Utahns. However, given the expressed preference of in-person classes, virtual education should be used as a supplemental approach to traditional group classes. <h3>Funding</h3> Supplemental Nutrition Assistance Program - Education
Are the coronavirus disease 2019 (COVID-19)-themed applications launched during the pandemic sustainable?

Many digital applications (Apps) were launched during the coronavirus disease 2019 (COVID-19) pandemic for various purposes such as information sharing, risk assessment, self-management of symptoms, contact tracing, home monitoring, and decision making. Since the quality of COVID-19-themed Apps varied and was less reliable based on measurements using the mobile Apps rating scale method, some of these Apps are considered useful while some are said to have the potential to harm users. This suggests the need for authorized institutions to validate and ensure the safety and security of these Apps before it was launched in public. This is necessary considering the potential dangers arising from App inaccuracies, as well as the potential misuse of user data due to data breaches. With these considerations in mind, we consider that the vaccine passport is an App with a COVID-19 theme that must be refined and applied sustainably amid the ongoing global crisis and the uncertainty of this pandemic.
"A Study on the Usage of the Conjectural Expression Souda, Youda, Mitaida and Rashi in Books, Newspapers, and Magazines -Compared to the Aspect of Use in Natural Speech-"

本稿では基本的に日本語の述語を構成している「名詞(+だ)、形容詞、形容動詞、動詞」に続く助動詞を中心に、その形態的な(接続と活用)誤用を調べた。その主な結果は次の通りである。 (1) 学習者レベル[㊤、㊦]によって正解率差が大きい[㊦：41.4%、㊤)：74.1%]ので、ある程度学習すれば大きく向上すると推測される。 (2) 学習者㊦の問6[1グループ動詞+(ら)れる(可能)+ば], 11[くる+たい+ば], 13[くる+ない+なる+た]、14[名詞+らしい+た+です]、17[する動詞+らしい+た]、21[動詞+ない+そうだ+です]すべて正解率が0.0%であるが、この中で問21、6、11、14は学習者㊤の正解率が低く(15.4％以下)、難易度が高い問題と判断される。 (3) 39問題で学習者の回答タイプは平均5.0個(3~9個)であり、7問題は一つの回答タイプが30％以上の割合を示している。しかし、様々な回答タイプが見られることから、習得過程は単純ではないと思う。
Point Cloud Generation with Stereo and Monocular Depth Estimation on FPGA

This research proposes a system that leverages stereo vision and monocular depth estimation to form a depth map from which a 3D point cloud scene is extracted. The emergence of competitive neural networks for depth map estimation presents an opportunity for deployment on embedded systems. Both stereo and monocular depth algorithms were tested on multiple FPGA hardware platforms. To perform acceleration on configurable hardware, a Deep Learning Processing Unit (DPU) IP was used for processing AI workloads, together with a Pseudo-LiDAR reprojection for 3D reconstruction on the Arm® processor. The DPU performance configuration will depend on the logic resources the targeted board has. This paper highlights the performance, resource utilization, and bottlenecks that came across different tested combinations of both hardware and neural network architectures.
A Digitally-secured Automated Fleet Management Scheme for Electric Buses based on Blockchain

Electrification of public transportation is one of the plausible ways through which many countries are adopting sustainable mobility. As the new transportation paradigm is being embraced by many nations, the uncertainties in traction technology, management of bus-charging, and demands of efficient public mobility will pose challenges in ensuring the timely schedule of the fleet. Also, with an additional level of financial transaction, between the bus operators and the charge operators, and the digital payment modes getting preferences, trust and security issues would arise. A blockchain-based system for fleet management can ensure minimal transaction cost and an efficient schedule and operation. As new transaction mechanisms emerge, blockchain could facilitate transactive energy exchanges. This paper proposes a blockchain-based mechanism for electric buses (EBs) charging. An optimization framework incorporating blockchain transactive operation has been proposed to solve for the most efficient fleet schedule at the least charging cost. The architecture of the proposed methodology is detailed, and the case study of Quito-Ecuador is evaluated.
Milestones of research activity in quantum computing: EPS grand challenges

We argue that quantum computing underwent an inflection point circa 2017. Long promised funding materialised which prompted public and private investments around the world. Techniques from machine learning suddenly influenced central aspects of the field. On one hand, machine learning was used to emulate quantum systems. On the other hand, quantum algorithms became viewed as a new type of machine learning model (creating the new model of {\it variational} quantum computation). Here we sketch some milestones which have lead to this inflection point. We argue that the next inflection point would occur around when practical problems will be first solved by quantum computers. We anticipate that by 2050 this would have become commonplace, were the world would still be adjusting to the possibilities brought by quantum computers.
Assistive Devices for Visually, Audibly and Verbally Impaired People

Abstract: There are some people who don’t have the ability to speak or they lose it in an accident. They find it difficult to express their thoughts or to convey their message to other people. In this project we propose a Sign Language Glove which will assist those people who are suffering for any kind of speech defect to communicate through gestures i.e. with the help of single handed sign language the user will make gestures of alphabets. The glove will record all the gestures made by the user and then it will translate these gestures into visual form as well as in audio form. This project uses Arduino controller to control all the processes and flex sensors along with accelerometer sensors will track the movement of fingers as well as entire palm. A LCD will be used to display the user’s gesture and a speaker to translate the gesture into audio signal is planned if possible for execution. This project can be further developed to recognize complex like food, water, etc.
Designing a Vulnerability Management Dashboard to Enhance Security Analysts’ Decision Making Processes

Network vulnerability management reduces threats posed by weaknesses in software, hardware, or organizational practices. As networks and related threats grow in size and complexity, security analysts face the challenges of analyzing large amounts of data and prioritizing and communicating threats quickly and efficiently. In this paper, we report our work-in-progress of developing a vulnerability management dashboard that helps analysts overcome these challenges. The approach uses interviews to identify a typical security analyst workflow and proceeds with an iterative design that relies on real-world data. The vulnerability dashboard development was based on a common security analyst workflow and includes functions to allow vulnerability prioritization according to their age, persistence, and impact on the system. Future work will look to execute full-scale user studies to evaluate the dashboard’s functionality and decision-making utility.
Phishing: A Way of Attacking the Privacy

The Internet provides a fantastic platform for ordinary people to communicate. Criminal minds have figured out a means to steal personal information without having to meet the person and with the least danger of getting detected. It’s known as phishing. Phishing is a significant threat to the ecommerce sector. Customers’ trust in ecommerce is shattered, and electronic service providers suffer significant financial losses as a result. As a result, understanding phishing is critical. This document educates readers on phishing assaults and anti-phishing the recipient, the auction site will have a good yield. Anti-phishing strategies and online security rules have been recommended by both academia and industry practitioners in order to protect customers’ interests. Some commercial anti-spam and anti-phishing products block email from ”blacklisted” sites that they claim deliver spam and phishing emails, but allow email from software. Because of the obvious usability issues ”whitelisted” sites that they claim are known not to send it. This strategy appears to be anticompetitive because it unfairly discriminates against smaller and lesser-known sites.
Application of SVM-KNN Network Detection and Virtual Reality in the Visual Design of Artistic Images

The birth of computers has brought us unexpected progress and development in many ways. In this very real world of our human existence, the beginning of human perception of the world. It is a sensory organ that collects sensory information, and the same goes for people’s artistic creation and design. This paper discusses the classification effect of the combined model of support vector machine and SVM-KNN on the problem of virtual reality art images, analyzes the parameters of the optimized combined model, and then conducts a series of simulation analyses on the optimized model. So using this method can make the collected data more real and reliable, and it will be very convenient for us to process. Use the SVM algorithm to train the classifier when performing data classification and compare different training sample sizes and different kernel functions for empirical analysis and in-depth analysis of the accuracy of the two and the impact of the model. Through the data comparative analysis of SVM-KNN, the obtained results are more real and effective.
Blockchain: Basics, Applications, Benefits, and Opportunities

Blockchain has played a major role in financial, sales, medical, cryptocurrency, gaming, and other areas or fields. blockchain comes into focus mainly due to the bitcoin cryptocurrency. and now blockchain has been used in the development of various applications to help make records such as files, audio, video, paintings, gaming nfts secured and provide greater transparency, improved traceability, efficiency, and speed, and reduced cost. in this paper, we will be looking at what blockchain is, what is blockchain consists of, its structure, framework, and how blockchain works in a distributed network environment.
A remark on a conjecture of Navarro and Tiep

We prove a divisibility property of the fixed field in a cyclotomic field Q(e2iπ/k) of the Frobenius automorphism Gal(Q(e2iπ/k)/Q)∋τ:ξ↦ξp, where p is a prime, k is a positive integer relatively prime to p, and ξ is any kth-root of unity. This implies that, for a finite group G, recent Navarro-Tiep’s conjecture on fields of values of p′-degree irreducible characters of G follows from the celebrated Galois-McKay conjecture under a natural condition on p and the order of G.
Hierarchical Average Precision Training for Pertinent Image Retrieval

Image Retrieval is commonly evaluated with Average Precision (AP) or Recall@k. Yet, those metrics, are limited to binary labels and do not take into account errors’ severity. This paper introduces a new hierarchical AP training method for pertinent image retrieval (HAPPIER). HAPPIER is based on a new $$\mathcal {H}\text {-AP}$$ metric, which leverages a concept hierarchy to refine AP by integrating errors’ importance and better evaluate rankings. To train deep models with $$\mathcal {H}\text {-AP}$$ , we carefully study the problem’s structure and design a smooth lower bound surrogate combined with a clustering loss that ensures consistent ordering. Extensive experiments on 6 datasets show that HAPPIER significantly outperforms state-of-the-art methods for hierarchical retrieval, while being on par with the latest approaches when evaluating fine-grained ranking performances. Finally, we show that HAPPIER leads to better organization of the embedding space, and prevents most severe failure cases of non-hierarchical methods. Our code is publicly available at https://github.com/elias-ramzi/HAPPIER .
Evaluation of Blended Learning Effect of Engineering Geology Based on Online Surveys

Engineering geology applies geological theories and methods to the practice of engineering activities, evaluates the engineering geological conditions of the engineering site through engineering geological investigation and comprehensive research of theories, solves the engineering geological problems related to engineering activities, predicts and demonstrates the occurrence and development laws of engineering geological problems in the engineering activity area, and puts forward technical measures for prevention and control, so as to contribute to the planning, design, and construction and provide necessary geological and technical data for use and maintenance. Based on the theory of multiattribute decision-making, this paper puts forward the evaluation index system of engineering geology teaching quality in applied universities. A curriculum teaching quality evaluation index system is constructed, which is composed of four main indexes: online resources and teaching, offline teaching process, classroom teaching quality evaluation, and classroom teaching quality evaluation. Furthermore, 11 second-class indices and 28 third-class indices are considered. The judgment matrices and membership degree of each attribute are obtained through use of a questionnaire, and the total weight of each subitem is calculated using the analytic hierarchy process. The calculation results show that the classroom instructional quality of the engineering geology course can be considered excellent; furthermore, other courses could also be evaluated using the same method, where those with low evaluation results can be further improved. Using the fuzzy comprehensive evaluation method based on the analytic hierarchy process, we evaluate the instructional quality, comprehensively consider the nonlinear and fuzzy characteristics of evaluation factors, can scientifically calculate the weight value of each evaluation index, and combine qualitative and quantitative aspects, in order to objectively provide an evaluation of the classroom instructional quality of teachers, which is conducive to the high-quality construction of university courses.
Knowledge Integrating System Using Video Mining

Abstract: A system will be developed in which only admin can upload videos on Cloud Server. Videos are sorted based on category and videos are automatically uploaded on Cloud Server on the schedule provided by the admin. Users can watch videos online. Users can rate videos that will be analyzed by the system. This system automatically removes videos that are less popular
A Semantic Network Analysis of T-commerce Industry: Focused on Media Data

Despite the rapid increase in big data information due to the quantitative growth of the T-commerce industry and the diversity of channels, this study extracted morpheme-based keywords from big data analysis on T-commerce-related articles in the past 21 years. As a result of the study, T-commerce’s growth process could be largely divided into three stages: preparation, introduction, and growth. It was confirmed that it was divided into three clusters in the preparation period: ‘information provision’, ‘diversity’, and ‘business propulsion’, three clusters in the introduction period: ‘activity’, ‘convenience’, and ‘reliability’, and four clusters in the growth period: ‘usefulness’, ‘convenience’, ‘economy’, and ‘reliability’. In practice, it suggests that marketing capabilities should be focused on improving the usefulness and convenience of high word concentration among the four clusters of usefulness, convenience, economy, and reliability formed in CONCOR analysis.
An Evaluation of Topic Models for the Estimation of Unobserved Variables in Structured and Unstructured Documents

&lt;p&gt;For effective data collection, researchers are often faced with three challenges of where, what and how? Where to find researchable data, with what tools and methodologies to scrape websites for such data, and how to perform the required analytics and extract insightful knowledge. This study examines the possibility and the extent user tweets could influence the direction of research, especially in the field of machine learning and artificial intelligence. In this paper, we use the Latent Dirichlet Allocation (LDA) topic modelling technique to discover machine learning research topics popularity in 35,860 unorganized datasets (tweets) from 20 Artificial Intelligence and machine learning related handles, while using 7,241 articles from 42 years’ Neural Information Processing Systems (NIPS) conference papers dataset, an organized document as a control. The Latent Semantic Index (LSI) and the Hierarchical Dirichlet Process (HDP) are used to compare the performance of the LDA. Embedding methods such as the bag of words and the term frequency inverse document frequency (tf-idf) are used to encode the corpora and compared. Results suggest that using the structured dataset guaranteed better classification, though the unstructured dataset is quite informative. However, a t-test showed that the difference between the results of the two datasets was not significant. The LDA model consistently out-performed LSI and HDP across topics, respectively. A comparison of the Gensim and Mallet Python frameworks showed that Mallet promised a better topic modelling result than Gensim.&lt;/p&gt;
A Cross-dataset Evaluation of Wearable Fall Detection Systems

The popularity of wearables and their seamless integration into our daily lives have transformed these devices into an appealing resource to deploy automatic fall detection systems. During last years, a massive literature on new methods and algorithms for these wearable detectors has been produced. However, in most cases these algorithms are tested against one single (or at best two) datasets containing signals captured from falls and conventional movements. This work evaluates the behavior of a fall detection system based on a convolutional neural network when different public repositories of movements are alternatively used for training and testing the model. After a systematic cross-dataset evaluation involving four well-known datasets, we show the difficulty of extrapolating the results achieved by a certain classifier for a particular database when another dataset is considered. Results seem to indicate that classification methods tend to overlearn the particular conditions (typology of movements, characteristics of the employed sensor, experimental subjects) under which the training samples were generated.
Brief Announcement: Composable Dynamic Secure Emulation

This work extends the composable secure-emulation of Canetti et al. to dynamic settings. Our work builds on top of dynamic probabilistic I/O automata, a recent framework introduced to model dynamic probabilistic systems. Our extension is an important tool towards the formal verification of protocols combining probabilistic distributed systems and cryptography in dynamic settings (e.g. blockchains, cybersecure distributed protocols etc).
Improvement of Neo-Confucianism of Seoin through Kim Jang-Saeng's Geunsarok Seokeui

This study is aimed at exploring compilation process of annotation for Chin-ssu Lu (近思錄) of Kim Jang-saeng (金長生, 1548-1631) and its importance in the history of thoughts. Zhu Xi (朱熹, 1130-1200) and Lu Zuqian (呂祖謙, 1137- 1181) wrote Chin-ssu Lu for the beginners' learning. It took great part in beginner's learning with Xiaoxue (小學) that provides fundamental guideline in action. In spite of its recognized importance, Chin-ssu Lu did not receive attention from intellectuals of the time, while Xiaoxue received constant attention after emphasis on practice of Kim Jong-Jik (金宗直, 1431-1492). Chin-ssu Lu was re-examined by Yi Hwang (李滉, 1502-1571) of the 16th century. Studying Four Books and Five Classics, Yi Hwang provided a groundwork for translation of Confucian textbooks with studying Chin-ssu Lu in his later years. But he could not finish his work. Most annotations of beginner's learning based on Zhu Xi's studies (朱子學) was organized by Seoin (西人). Kim Jang-saeng compiled the annotations of Chin-ssu Lu for the first time by writing Geunsarok Seokeui (近思錄釋疑). Unlike previous annotations, Geunsarok Seokeui contained various theories of intellectuals of Joseon and these theories took greater part than theories of Chinese intellectuals based on Zhu Xi's other writings due to Joseon's cumulated former studies about the annotations. As study of Four books and Five Classics proceeded in Joseon, independent perspectives to understand Zhu Xi's studies were born. In this trend, Kim Jang-saeng compiled these studies and made a basis for study about Chin-ssu Lu. In the process, Kim Jang-saeng supplemented Yi Yi's position in the controversy over Neo-Confucianism that continued from Yi Hwang and created a foundation for maintaining the school.