Reviewerly/exHarmony huggingface dataset:
Face mask detection algorithm for multi task recognition in complex environment

The right wearing masks can effectively prevent the spread of viruses. There are usually complex distractions in densely populated environments, which will affect detection tasks of face masks. However, the current detecting algorithm based on Faster R-CNN can not meet mask wearing detection of small targets in complex environments, so this paper puts forward a mask wearing detection algorithm based on the improved Faster R-CNN. This algorithm changes the traditional single RPN network model into one multi-task enhanced RPN model, which can improve the detection and recognition accuracy, the improved Soft-NMS algorithm is used to delete the redundant candidate boxes of regional candidate network output. At the same time, CIoU loss function with better performance, which fully considers the center point distance between the target and the detection frame and improves the accuracy of detection, replaced the original IoU loss function. 3000 sample images are used to do training and experimental verification of the model according to 1:3ratio of positive and negative samples. Experimental results show that compared with the Faster R-CNN algorithm, the algorithm proposed in this paper improves the face detection accuracy and face mask wearing detection by 7.15% and 15.99%respectively. Besides, the average detection accuracy improved by 11.57% and the FPS by 4.6.
Practice-Oriented Teaching in Preparing Future TeachersPsychologists for Professional Activity

In this article, devoted to the problem of professional training of future teachers-psychologists based on practice-oriented teaching, the research results, tested during the educational process, are presented. They are as follows: the essence of the concept "professional competence" of a teacher is specified; based on the analysis of existing approaches to the study of the structure of professional readiness, personal, intellectual-operational, motivational, communicative, and reflexive components are determined; the structural and functional model of practice-oriented teaching of future teachers-psychologists has been developed following the pedagogical features of practice-oriented teaching and the identified pedagogical conditions, which includes four interrelated blocks: the target, the methodological, the content-procedural, the learning outcome. The criteria of professional training of future teachers-psychologists on the basis of practice-oriented teaching (personal, intellectual-operational, motivational, communicative, and reflexive) and levels of readiness are defined: reproductive (low), adaptive (medium), and integrative (high). The development and consolidation of skills in students is carried out by solving specific tasks of professional activity, during which students try to explain the procedure for solving a specific professional task and check the actual material in practice. The practice-oriented content of the educational material allows bringing teaching closer to specific situations of professional activity, the chosen specialty, to form the life experience of students, thus increasing the level of knowledge and skills, cognitive interest, and, as a result, to form the level of professional competence of students.
LIBRARY AND INTERNET USE AS A SOURCE OF INFORMATION BY STUDENTS OF FEDERAL POLYTECHNIC EKOWE BAYELSA STATE

It is no news that the source of academic information is very important to students. Fundamentally, academic libraries provide much relevant research materials in both printed and electronic formats to support students and lecturers alike. Institutions such as Federal Polytechnic Ekowe have, therefore, invested resources in acquiring library infrastructure to facilitate research work. This study sought to analyze students use of library and internet resources for academic activities. Primary data were collected using a questionnaire from 126 students who were selected using a simple random sampling procedure. The data were analyzed using descriptive statistics. The results specify that students use both library and internet resources for their academic work. However, the use of the internet is more than that of the Polytechnic’s library resources. Demographic and economic variables were recognized as determinants for the use of library and internet resources. The results have several implications for students’ academic work in the institution.
DeltaFS: a scalable no-ground-truth filesystem for massively-parallel computing

High-Performance Computing (HPC) is known for its use of massive concurrency. But it can be challenging for a parallel filesystem's control plane to utilize cores when every client process must globally synchronize and serialize its metadata mutations with those of other clients. We present DeltaFS, a new paradigm for distributed filesystem metadata. DeltaFS allows jobs to self-commit their namespace changes to logs, avoiding the cost of global synchronization. Followup jobs selectively merge logs produced by previous jobs as needed, a principle we term No Ground Truth which allows for efficient data sharing. By avoiding unnecessary synchronization of metadata operations, DeltaFS improves metadata operation throughput up to 98X leveraging parallelism on the nodes where job processes run. This speedup grows as job size increases. DeltaFS enables efficient inter-job communication, reducing overall workflow runtime by significantly improving client metadata operation latency up to 49X and resource usage up to 52X.
MINAT BACA SISWA DITINJAU DARI DUKUNGAN ORANG TUA DAN MOTIVASI BERPRESTASI

The aim of this study was to analyze the relationship between students' interest in reading and parents support and motivation for achievement. The collection data method used in this study was a scale method, and the population of this study was 720 high school students. Sampling of the type used is cluster random sampling to give all classes an equal chance. Sampling from 8 existing classes resulted in 5 classes with a total of 150 students. Charging scale is carried out in each class for a predetermined amount of time. From the results of the study, the calculation of the regression analysis of achievement motivation according to parental support and reading interest obtained a value of R = 0.201. p = 0.000; (p <0.05) Fcount = 18.520, sig. = 0.000 <0.05, which indicates that X1, X2 and Y are linear. These results indicate that there is an important relationship between parental support and interest in reading and motivation for achievement.
Edge-to-cloud Virtualized Cyberinfrastructure for Near Real-time Water Quality Forecasting in Lakes and Reservoirs.

The management of drinking water quality is critical to public health and can benefit from techniques and technologies that support near real-time forecasting of lake and reservoir conditions. The cyberinfrastructure (CI) needed to support forecasting has to overcome multiple challenges, which include: 1) deploying sensors at the reservoir requires the CI to extend to the network’s edge and accommodate devices with constrained network and power; 2) different lakes need different sensor modalities, deployments, and calibrations; hence, the CI needs to be flexible and customizable to accommodate various deployments; and 3) the CI requires to be accessible and usable to various stakeholders (water managers, reservoir operators, and researchers) without barriers to entry. This paper describes the CI underlying FLARE (Forecasting Lake And Reservoir Ecosystems), a novel system co-designed in an interdisciplinary manner between CI and domain scientists to address the above challenges. FLARE integrates R packages that implement the core numerical forecasting (including lake process modeling and data assimilation) with containers, overlay virtual networks, object storage, versioned storage, and event-driven Function-as-a-Service (FaaS) serverless execution. It is a flexible forecasting system that can be deployed in different modalities, including the Manual Mode suitable for end-users’ personal computers and the Workflow Mode ideal for cloud deployment. The paper reports on experimental data and lessons learned from the operational deployment of FLARE in a drinking water supply (Falling Creek Reservoir in Vinton, Virginia, USA). Experiments with a FLARE deployment quantify its edge-to-cloud virtual network performance and serverless execution in OpenWhisk deployments on both XSEDE-Jetstream and the IBM Cloud Functions FaaS system.
An algorithm of solving nonlinear boundary value problem for the Van der Pol differential equation: Dzhumabaev D.S., Mursaliyev D.E., Sergazina A.S., Kenjeyeva A.A.

Periodical boundary value problem for the Van der Pol differential equation is solved by parametrization’s method. Interval is divided into 2 parts, the values of the solution at the left-end points of the subintervals are considered as additional parameters and original problem is reduced to the boundary value problem with parameters. Using solutions to the Cauchy problems for the differential equations with parameters, boundary condition, and the continuity condition at the dividing point, a system of nonlinear algebraic equations with respect to introduced parameters is composed. Explicit form of this system exists in exceptional cases. However, for the given parameters, the values of functions, which present left-hand sides of the system, and their derivatives by parameters, we can find by solving the Cauchy problems for ordinary differential equations on the subintervals. We find solutions to the Cauchy problems by forth order Runge-Kutta method. The solution of the composed system is found by Newton’s method.
UAV Aerial Photography Target Detection and Tracking Based on Deep Learning

With the development of aviation technology, UAV technology has gradually become a research hotspot in the aviation field, and it plays a vital role in civil and military construction. Target detection and tracking of aerial video is a key technology for UAV reconnaissance, disaster relief, enemy monitoring, and military strikes. This paper studies the YOLOv3 target detection algorithm and SiamMask target tracking algorithm based on deep learning, and compares these algorithms Based on the situation of long aerial photography distance and small target, the algorithm is improved and fused to realize rapid target identification and tracking under UAV aerial photography. At the same time, in order to simplify the model and accelerate the speed of model training and reasoning, the simplification of the tracking algorithm model is studied. Finally, an aerial photography experiment was conducted in an outdoor environment to verify the effectiveness of the UAV target detection and tracking algorithm.
The fincen files

A massive leak of secret files from the United States reveals the world's banks have been processing trillions of dollars in suspicious transactions. The documents were obtained by BuzzFeed News an...
Improved Algorithms for Low Rank Approximation from Sparsity

Previous chapter Next chapter Full AccessProceedings Proceedings of the 2022 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA)Improved Algorithms for Low Rank Approximation from SparsityDavid P. Woodruff and Taisuke YasudaDavid P. Woodruff and Taisuke Yasudapp.2358 - 2403Chapter DOI:https://doi.org/10.1137/1.9781611977073.95PDFBibTexSections ToolsAdd to favoritesExport CitationTrack CitationsEmail SectionsAboutAbstract We overcome two major bottlenecks in the study of low rank approximation by assuming the low rank factors themselves are sparse. Specifically, (1)for low rank approximation with spectral norm error, we show how to improve the best known running time to running time plus low order terms depending on the sparsity of the low rank factors, and(2)for streaming algorithms for Frobenius norm error, we show how to bypass the known Ω(nk/∊) memory lower bound and obtain an sk(log n)/poly(∊) memory bound, where s is the number of non-zeros of each low rank factor. Although this algorithm runs in exponential time, as it must under standard complexity-theoretic assumptions, we also present polynomial time algorithms using poly(s, k, log n, ∊–1) memory that output rank k approximations supported on an O(sk/∊) × O(sk/∊) submatrix. Both the prior running time and the nk/∊ memory for these problems were long-standing barriers; our results give a natural way of overcoming them assuming sparsity of the low rank factors. Previous chapter Next chapter RelatedDetails Published:2022eISBN:978-1-61197-707-3 https://doi.org/10.1137/1.9781611977073Book Series Name:ProceedingsBook Code:PRDA22Book Pages:xvii + 3771
Development of Online SABASIA (Suka Bahasa Indonesia) Teaching Materials for Indonesian Language Learning for International Students as a Pioneer for FIBAA International Accredited Study Programs at State Islamic Universities

Teaching materials are needed to implement learning: the Indonesian Language for Foreign Speakers (BIPA). BIPA learning is one of the facilities for international students to learn Indonesian; besides, it is also used as a pilot program for International Accreditation at a university; in its journey, it requires innovation of teaching materials to support the BIPA learning process. This study aims to determine the feasibility and effectiveness of online SABASIA (Suka Bahasa Indonesia) teaching materials in Indonesian language learning for international students as a pioneer of the FIBAA Accredited Study Program at State Islamic Universities. This research is a type of research and development (RnD). The research data were obtained using observation, discussion with experts, interviews, and questionnaires. The results showed 1) at the online SABASIA (Suka Bahasa Indonesia) teaching material innovation stage, international students received a positive response, with 79% of international students at State Islamic universities in dire need of innovative teaching materials. The quality of developing SABASIA (Suka Bahasa Indonesia) Online teaching materials is done by validating the experts and then getting product revisions. It was found that online SABASIA (Suka Bahasa Indonesia) teaching materials are acceptable and appropriate for international students to use in helping to deepen the Indonesian language, especially in State Islamic Universities. 2) the effectiveness of online SABASIA (Suka Bahasa Indonesia) teaching materials In Indonesian language learning for international students at state Islamic Universities, the results of the pre-test and post-test have increased so that they are declared effective and can be used as pioneering FIBAA internationally accredited study programs in universities, State Islam. The development of online SABASIA (Suka Bahasa Indonesia) teaching materials is an innovation in learning Indonesian using information and communication technology, based on bilingual.
Use of Electronic Information, E-Library Resources in Research and Education - A Study

sorted into I) concentrates on Environemental Education (EE) - one of the parts of Education for Sustainable Development (ESD), ii) concentrates on identified with issues on ESD, iii) considers on sustainable development, iv) concentrates on ESD and educational program, v) concentrates on ESD and different learning draws near, vi) investigations
A BERT-based Siamese-structured Retrieval Model

Due to the development of deep learning, the natural language processing tasks have made great progresses by leveraging the bidirectional encoder representations from Transformers (BERT). The goal of information retrieval is to search the most relevant results for the user’s query from a large set of documents. Although BERT-based retrieval models have shown excellent results in many studies, these models usually suffer from the need for large amounts of computations and/or additional storage spaces. In view of the flaws, a BERT-based Siamese-structured retrieval model (BESS) is proposed in this paper. BESS not only inherits the merits of pre-trained language models, but also can generate extra information to compensate the original query automatically. Besides, the reinforcement learning strategy is introduced to make the model more robust. Accordingly, we evaluate BESS on three public-available corpora, and the experimental results demonstrate the efficiency of the proposed retrieval model.
Panorama geral sobre o processamento técnico de fotografias no home office

Due to the home office imposed by the pandemic, some activities related to the technical processing of the imagery collection of the National Department needed to be rethought and underwent adaptations. Thus, in view of the new conjuncture and work dynamics, this article aims to present a case report on how this process has occurred, ensuring the continuity of activities, even if at a distance. Moreover, a bibliographical research was carried out, with the purpose of basing the concepts mentioned in the plot of the article. In short, we observed that the Home Office was a solution that worked and that presented advantages such as increased productivity and greater collaboration between the team, in a way that the Home Office, combined with face-to-face activities, can be continued even after the pandemic.
Analysis of participation concept in public secondary students

Participation and peaceful coexistence are modeled within the institutional established practices. The aim was to analyze the content of graphic production (drawings) and written, about the participation of public high school students. The technique of drawing and writ- ten productions was used to know their conceptualization of participation. The population consisted of 204 students from 5 public secondary schools in Queretaro, Mexico. Results show that graphic representation of participation is circumscribed to the classroom and to verbal forms within the classroom, which was confirmed in the written productions. It becomes necessary that in the diverse contexts were girls and boys develop they are provided with genuine experiences of participation that will allow them to enlarge not only their concept about participating but to enlarge their possibility of actions.
LibGuides: Education: Elementary Education

This guide one-stop-shop for services and resources to support classes in the College of Education.
PENERAPAN METODE TEOREMA BAYES UNTUK MENDETEKSI HAMA PADA TANAMAN PADI MAYAS KALIMANTAN TIMUR

The community very much needs the nutritional needs of food during a pandemic. One source of nutrition that can be obtained is rice or rice derived from rice plants. Mayas rice is a rice plant with advantages in terms of high taste quality and components of certain physiological functions that are beneficial to health. However, Mayas rice has quite a lot of pest attacks, thus reducing agricultural production. On the other hand, the knowledge possessed by the community regarding pests in Mayas rice is still very minimal. Hence, people find it difficult to determine the proper pest control method. Bayes theorem applied in an expert system can be a solution to diagnose the types of pests that attack Mayas rice. The research data is a knowledge base that contains 32 symptoms that appear and 10 types of pests that attack Mayas rice. The results showed that the percentage of certainty in the diagnosis of the types of pests that pounded Mayas rice was based on the symptoms given by the user. The level of testing using ten test cases displays the results of an expert system for identifying types of pests that attack Mayas rice which is suitable for use with a percentage of 90%.
Regional Language Teachers Perception Of Makassar Languange Book.

Regional Language Teachers Perception Of Makassar Languange Book. The purpose of this study was to describe the teacher's perception of the Makassar language textbook. The data in this study is the local language teacher's perception of the seventh grade Makassar language textbook. The sources in this study were Regional Language Teachers, totaling 3 people. The data collection in this study was a questionnaire technique and an interview technique. This study was processed by using the percentage test (%), then described and reinforced by the results of interviews, the data obtained were analyzed using the percentage formula. The results of research and data analysis that have been carried out regarding the perception of Regional Language teachers towards Makassar language textbooks for class VII that Makassar language textbooks for class VII publishers UD MANDIRI/CV MITRA SAHABAT with a percentage of 83.35% in the Very Easy category and strengthened by the results of interviews.
FL-WBC: Enhancing Robustness against Model Poisoning Attacks in  Federated Learning from a Client Perspective

Federated learning (FL) is a popular distributed learning framework that trains a global model through iterative communications between a central server and edge devices. Recent works have demonstrated that FL is vulnerable to model poisoning attacks. Several server-based defense approaches (e.g. robust aggregation), have been proposed to mitigate such attacks. However, we empirically show that under extremely strong attacks, these defensive methods fail to guarantee the robustness of FL. More importantly, we observe that as long as the global model is polluted, the impact of attacks on the global model will remain in subsequent rounds even if there are no subsequent attacks. In this work, we propose a client-based defense, named White Blood Cell for Federated Learning (FL-WBC), which can mitigate model poisoning attacks that have already polluted the global model. The key idea of FL-WBC is to identify the parameter space where long-lasting attack effect on parameters resides and perturb that space during local training. Furthermore, we derive a certified robustness guarantee against model poisoning attacks and a convergence guarantee to FedAvg after applying our FL-WBC. We conduct experiments on FasionMNIST and CIFAR10 to evaluate the defense against state-of-the-art model poisoning attacks. The results demonstrate that our method can effectively mitigate model poisoning attack impact on the global model within 5 communication rounds with nearly no accuracy drop under both IID and Non-IID settings. Our defense is also complementary to existing server-based robust aggregation approaches and can further improve the robustness of FL under extremely strong attacks.
Impossible Differential Cryptanalysis on ESF Algorithm with Simplified MILP Model

MILP-based automatic search is the most common method in analyzing the security of cryptographic algorithms.However, this method brings many issues such as low efficiency due to the large size of the model, and the difficulty in finding the contradiction of the impossible differential distinguisher.To analyze the security of ESF algorithm, this paper introduces a simplified MILP-based search model of the differential distinguisher by reducing constrains of XOR and S-box operations, and variables by combining cyclic shift with its adjacent operations.Also, a new method to find contradictions of the impossible differential distinguisher is proposed by introducing temporary variables, which can avoid wrong and miss selection of contradictions.Based on a 9-round impossible differential distinguisher, 15-round attack of ESF can be achieved by extending forward and backward 3-round in single-key setting.Compared with existing results, the exact lower bound of differential active S-boxes in single-key setting for 10-round ESF are improved.Also, 2108 9-round impossible differential distinguishers in single-key setting and 14 12-round impossible differential distinguishers in related-key setting are obtained.Especially, the round of the discovered impossible differential distinguisher in related-key setting is the highest, and compared with the previous results, this attack achieves the highest round number in single-key setting.