Reviewerly/exHarmony huggingface dataset:
OpenVX safety-critical applications

There are an increasingly varied number of areas in which computer vision and neural networks are being employed. Many of these have obvious safety implications, such as the use of both in autonomous vehicles. For other applications, the need is less obvious. In some cases an application may currently be considered trivial, a novelty where safety need not be paramount, but this may change, and safety may become increasingly important in the future as this technology becomes commonplace and we come to rely upon it more heavily. In this chapter we discuss various standards applicable in different industries, and how we can use the features available in OpenVX SC to create solutions that may be deployed into safety-critical environments. An example of a “shim layer” written in C++ and applicable to the automotive industry is given.
Download BlueStacks for Linux (Ubuntu/Debian/Mint/Fedora) %%currentyear%%

Learn how to download and install BlueStacks for Linux computer. Find out how you can run Android apps on your computer using the best Android emulator ...
Event-related potential characteristics analysis on vigilant attention development of school-age children

ObjectiveTo explore the characteristics of event-related potential(ERP) in the development of alert attention of children aged 6-11 years old.MethodsA total of 144 children aged 6-11 years old were enrolled in a continuous performance test (CPT, Go/Nogo stimulus task). The latency and amplitude of frontal region cue/uncue-P3 and CNV were analyzed and compared in all age groups.Results(1)Behavioral comparison among different age groups: correct number(35(31, 38), 37(34, 38.25), 37(34.75, 39), 38(35, 39.25), 39(37.25, 40), 39(39, 40)), correct reaction time((566.88±86.63)ms, (530.10±83.40)ms, (509.17±88.99)ms, (488.31±76.23)ms, (463.45±75.78)ms, (417.24±75.78)ms), the differences were statistically significant(P<0.01). (2)Fz lead ERP characteristics: ①Comparison of cue-CNV and uncue-CNV: 6-year-old group((-8.54±4.56)μV vs (-10.13±6.36)μV), 7-year-old group((-9.20±5.34)μV vs (-11.53±4.29)μV), 8-year-old group((-8.37±4.78)μV vs (-11.35±6.38)μV)in amplitude and 9-year-old group((689.25±268.22)ms vs (826.13±174.62)ms)in latency were significantly different(P<0.05). ②Comparison of cue-P3 and uncue-P3: 6-year-old group((4.29±4.11)μV vs (7.45±3.83)μV), 7-year-old group((4.47±4.71)μV vs (5.82±4.40)μV), 8-year-old group((3.76±3.39)μV vs (6.24±4.91)μV), 9-year-old group((4.27±3.57)μV vs (5.93±3.08)μV), 11-year-old group((4.24±4.66)μV vs (6.13±4.42)μV)in amplitude were significantly different(P<0.05). ③Longitudinal comparison among age groups: the latency of cue-CNV in 9-year-old group and 11-year-old group were shorter, and the difference was significant(P<0.05). The amplitudes of cue-CNV and cue-P3 in 10-year-old group were shorter than those in other age groups(P<0.05).ConclusionWith the increase of age, the reaction time of school-age children shortened and the correct rate improved.The age of 9-10 may be the high-speed period of the development for brain network on vigilant attention and psychological prediction which may be related to the maturation and development of frontal cortex.Key words: Event related potential; School-age children; Vigilant attention
Bibliometric analysis on postoperative sleep nursing from 2008 to 2017

ObjectiveTo systematically analyze the research status and development trend of postoperative sleep nursing from 2008 to 2017 in China.MethodsWe systematically retrieved literatures on postoperative sleep nursing published in Chinese Biology Medicine disc (CBM) , China National Knowledge Infrastructure (CNKI) , WanFang Data and Vip Database from 1st January 2008 to 31st December 2017. The bibliometrics was used to statistical analysis.ResultsA total of 485 literatures met criteria were included finally. From 2008 to 2017, the number of literatures had a growth trend every year. Literatures were published in 145 journals in China with 8.0% in the nursing core journals. A total of 10.1% of the researches had fund support, 61.6% of literatures had been quoted and 10.2% of them were quoted ≥10 times. Authors were from 28 provinces in China and the cooperative rate was 53.0% with 2.21 for the cooperative level. The research type focused on intervention study, and diseases were main in cancer, orthopedics and mixed surgery patients, and research contents mainly included symptoms of decline, influencing factors and intervention of postoperative sleep quality.ConclusionsIn China, researches on postoperative sleep nursing have development tendency but with problems such as uneven regional development, insufficient research support, single assessment tool and imperfect study design. The overall quality needs to be improved.Key words: Postoperative period; Sleep; Nursing research; Journal article; Bibliometrics
Cloud modeling of quasi - order groups on general fuzzy automata

In this paper, first a simplified version of a general fuzzy automaton with a fixed c is defined and then a subepisode of a simplified version of a general fuzzy automaton with a constant c is defined and explained connected and strong connected them, and finally, a model of quasi-order hypergroup on general fuzzy automaton with constant c is presented and the relationships between them are reviewed.In this paper, first a simplified version of a general fuzzy automaton with a fixed c is defined and then a subepisode of a simplified version of a general fuzzy automaton with a constant c is defined and explained connected and strong connected them, and finally, a model of quasi-order hypergroup on general fuzzy automaton with constant c is presented and the relationships between them are reviewed.In this paper, first a simplified version of a general fuzzy automaton with a fixed c is defined and then a
Install and Configure Docker on Windows Server

The previous chapter introduced the container technology, its origins, and how SQL Server now runs on Linux and Docker containers. But for someone who has minimal to no experience with Linux, this can be a bit overwhelming. So, instead of jumping straight into Linux, this chapter will help you get started with Docker containers using a platform that you are already familiar with – the Windows Server operating system. Microsoft partnered with Docker, Inc. to bring Docker containers on the Windows Server operating system, making it easy for Windows and SQL Server administrators to learn and deploy Docker containers.
On Improving Validity of Deep Neural Networks in Safety Critical Applications

Context: Deep learning has proven to be a valuable component in object detection and classification, as the technique has shown an increased performance throughput compared to traditional software algorithms. Deep learning refers to the process, in which an optimisation process learns an algorithm through a set of labeled data, where the researcher defines an architecture rather than the algorithm itself. As the resulting model contains abstract features retrieved through the optimisation process, new unsolved challenges emerge that need to be resolved before deploying these models in safety critical applications. Aim: The aim of this Licentiate thesis has been to study what extensions are necessary to verify deep neural networks. Furthermore, the thesis studies one challenge in detail: how out-of-distribution samples can be detected and excluded. Method: A comparative framework has been constructed to evaluate performance of out-of-distribution detection methods on common ground. To achieve this, the top performing candidates from recent publications were used as a reference snowballing baseline, from which a set of candidates were studied. From the study, common features were studied and included in the comparative framework. Furthermore, the thesis conducted semi-structured interviews to understand the challenges of deploying deep neural networks in industrial safety critical applications. Results: The thesis found that the main issue with deployment is traceability and quality quantification, in the form that deep learning lacks proper descriptions of how to design test cases, training datasets and robustness of the model itself. While deep learning performance is commendable, error tracing is challenging as the abstract features in the do not have any direct connection to the training samples. In addition, the training phase lacks proper measures to quantify diversity within the dataset, especially for the vastly different scenarios that exist in the real world. One safety method studied in this thesis is to utilize an out-of-distribution detector as a safety measure. The benefit of this measure is that it can both identify and mitigate potential hazards. From our literature review it became apparent that each detector was compared with different techniques, hence a framework was constructed that allowed for extensive and fair comparison. In addition, when utilizing the framework, robustness issues of the detector were found, where performance could drastically change depending on small variations in the deep neural network. Future work: Future works recommend testing the outlier detectors on real world scenarios, and show how the detector can be part of a safety strategy argumentation.
A Study on the Performance Evaluation of Machine Learning for Predicting the Number of Movie Audiences

The accurate prediction of box office in the early stage is crucial for film industry to make better managerial decision. With aims to improve the prediction performance, the purpose of this paper is to evaluate the use of machine learning methods. We tested both classification and regression based methods including k-NN, SVM and Random Forest. We first evaluate input variables, which show that reputation-related information generated during the first two-week period after release is significant. Prediction test results show that regression based methods provides lower prediction error, and Random Forest particularly outperforms other machine learning methods. Regression based method has better prediction power when films have small box office earnings. On the other hand, classification based method works better for predicting large box office earnings.
Second-formulation adaptive wavelet optimization technique applicable in material sciences

Abstract We developed a second-formulation adaptive wavelet optimize finite element (SFAWOFE) method on a general manifold with the help of approximation theory. The SFAWOFE method used to solve Burger’s equation with periodic and Dirichlet boundary conditions. The beauty of the SFAWOFE process is the numerical solution is optimized for the finite element method and does not affect the computational algorithm. We construct an algorithm for numerical results that have been optimized finite element method on a diffusion wavelet, which formed employing the adaptive wavelet plot. The algorithms and trial problems used to calculate magnetostatic networking range dipoles in material science. For the trial problem, the processing time checked out the SFAWOFE method has calculated and analyzed the analogous processing time checked out the finite element method on a general manifold. Finally, we verify the SFAWOFE method convergence for each trial problem and high efficient.
Experimental and Research Verification of the Methodology of Forming the High School Students’ Artistic Taste for the Vocal Heritage (Late XIX-Early XX Century)

The article highlights the results of research and experimental work on verifying the methodology of forming the artistic taste of high school students in the vocal heritage of Ukrainian composers of the late XIX – early XX centuries. The study purpose was to evaluate theelaborated methodology for the formation of the artistic taste of high school students in the process of studying the vocal heritage of Ukrainian composers. The study was accomplished using the method of paired comparisons that resulted in the scale of the comparative assessments in the control and the experimental group of high schoolstudents during the extracurricular activities in Kyiv, Zaporizhia and Dnipropetrovsk regions. The effectiveness of the proposed method was supported by the results of the statistical purposes of processing the experimental data using the χ2-criterion formula. The criteria formonitoring the formation of the high school students’ artistic taste regarding the national heritage of the late XIX-early XX centuries were outlined; the three levels (high, medium, low) of high school students’artistic taste formation were identified. The effectiveness of the applied methodology was evaluated by the series of tests comparing the results at the ascertaining and forming stages of the study. The authors argue that the data of the forming experiment showed significant positive changes in the levels of formation of high school students’ artistic taste according to all the determined criteria, which testifies to theeffectiveness of the developed facilitation methodology.
Modified Visual Honey Encrytion

Nowadays as the usage of mobile phones is increasing day by day the security for the messages sent through it is decreasing rapidly. Many attacks namely brute force attack, dictionary attack and key logger attacks are used by the intruder to hack the messages. Therefore, to avoid such attacks many techniques were developed to secure the messages that are being sent through the network. Some of the techniques are Advanced Encryption Standard (AES), Data Encryption Standard (DES), Triple Data Encryption Standard (3DES), Rivest Shamir and Adelman (RSA) and so on. But these techniques have unique challenges along with their advantages like less speed and possibility of brute force attacks. The propsed method is Honey encryption technique which is more secure as it avoids brute force attack and it is also considered to carry out the encryption process much more faster than the conventional honey encryption.
Guides: COVID-19 Resources: News and Updates

The Saint Paul Public Library COVID-19 Resource Collection: a guide to references on a wide variety of COVID-19 topics.
PENGARUH MODEL PEMBELAJARAN TALKING STICK BERBANTU MEDIA PATUNG TERHADAP HASIL BELAJAR MATEMATIKA SISWA KELAS V SDN 05 LONING

Abstract: Effect of Media-assisted Talking stick Learning Model on Class V Students' Mathematics Learning Outcomes of SDN 05 Loning. This study aims to determine the effect of sculpture media-assisted talking stick learning model on the results of mathematics learning in class V students of SDN 05 Loning. This study involved all fifth grade students of Loning Elementary School 05. This type of research is quantitative with the experimental method and Pre-Experimental Designs (nondesigns) design. The form of research design used is one-group pretest-posttest design. Data on Mathematics learning outcomes, collected by the test method while the instruments used are objective tests. The collected data were analyzed using descriptive statistics and inferential statistics namely t-test. The results showed that there were differences in learning outcomes between students who were learning with a medium sculpture-assisted talking stick learning model with students learning with conventional learning models. Keywords: Model Talking stick Learning, Result of Learning Mathematics Abstrak: Pengaruh Model Pembelajaran Talking stick Berbantu Media Patung Terhadap Hasil Belajar Matematika Siswa Kelas V SDN 05 Loning. Penelitian ini bertujuan untuk mengetahui pengaruh model pembelajaran talking stick berbantu media patung terhadap hasil belajar Matematika siswa kelas V SDN 05 Loning. Penelitian ini melibatkan semua siswa kelas V SDN 05 Loning. Jenis penelitian ini adalah kuantitatif dengan metode eksperimen dan desain Pre-Experimental Designs (nondesigns). Bentuk desain penelitian yang digunakan adalah one-group pretestposttest design. Data hasil belajar Matematika, dikumpulkan dengan metode tes sedangkan instrumen yang digunakan berupa tes objektif. Data yang terkumpul dianalisis dengan menggunakan statistik deskriptif dan statistik inferensial yaitu ujit. Hasil penelitian menunjukkan bahwa terdapat perbedaan hasil belajar antara siswa yang belajar dengan model pembelajaran talking stick berbantu media patung dengan siswa yang belajar dengan model pembelajaran konvensional. Kata Kunci : Model Talking stick, Hasil Belajar Matematika
CogniShield Review: Over-priced and over-hyped nootropic

Summary CogniShield is a terrible nootropic for those of you who are looking for a safe, natural supplement for enhancing cognition. CogniShield ...
Discussion of “Prediction, Estimation, and Attribution” by Bradley Efron

Professor Efron has presented us with a thought-provoking paper on the relationship between prediction, estimation, and attribution in the modern era of data science. While we appreciate many of his arguments, we see more of a continuum between the old and new methodology, and the opportunity for both to improve through their synergy.
Resource Description Framework and Friend Of A Friend-Based Web and Mobile Applications Prototype in an Education Environment A real-time management of students academic profiles

This paper presents the design of both Web and Mobile applications for managing the data of students and teachers of an educational institute using RDF (Resource Description Framework) and FOAF (Friend Of A Friend) based vocabulary. The implementation of an OWL (Ontology Web Language) as the core of a school administration system shows advantages compared to the standard database structure systems, this also increases the possibilities for smartphones to become the staple tool for classroom management. This project involves two main phases, the first one focused on the creation of the tools for the academic staff and the second being a mobile app for students to use in class. Partial results showed that the use of linked data provides useful information for the teacher to be aware of details of the students like how being close to a specific classmate has a noticeable impact on his/her class performance.
Music for violin and drum kit

The scored Music for Violin & Drum Kit is a compilation of 13 individual movements composed for violin and drum kit by Andrew Maddick in collaboration with Thomas Husmer. The composition represents research undertaken for the author's PhD titled Creative Collaborative Composition in the Context of Interdisciplinary Dyads.
US voter data sold on dark web

Illegally gathered voter registration information could be used to influence elections
INTEGRATION OF SOLAR TRACKER AND MAXIMUM POWER POINT TRACKING FOR IMPROVING PHOTOVOLTAIC (PV)SYSTEM EFFICIENCY

This paper presents a method to integrate the solar tracker and the maximumpower point tracking (MPPT) to improve the photovoltaic (PV) system efficiency. Theintegrated system provides a closed-loop solar tracker without the sensors. Instead ofusing the solar sensor, the output power of the MPPT is employed as the feedback signalto the solar tracker. The solar tracker estimates the solar azimuth and elevation anglesusing an astronomical algorithm based on the latitude, longitude and the date-time of thelocal site. To improve the solar tracking accuracy, the fuzzy logic controller is employed toadjust the angle according to the power slope of maximum power with respect to the solartracker angle. From the simulation results, the proposed method increases the PV energyby 23.23% compared to the fixed PV panel. It improves the efficiency of the existingintegrated solar tracker by 0.25% based on the simulation models.
The Implementation of School Literacy Program and The Condition of Vocational School Students’ Reading Interest

One of important skill in 21st century education is literacy skill, specially in vocational school students that should be ready to enter the job world. The problem that is happening now is Indonesian students’ literacy skill is still low, so is the reading interest. The objectives of this study are to explore the implementation of school literacy program, to analyze the students’ reading interest, to identify the problems in school literacy program, and to arrange the improvement of school literacy program. This study conducted in two vocational schools in Bandung City. The method used is qualitative method with technique observation, interview, and questionnaire distribution. The results of this study are all two schools have implemented school literacy program well, the condition of students’ reading interest at three school is in good condition, the problems in school literacy programs is about time management and teachers’ quality, and it can be implemented community based school literacy program to develop the program. The conclusion is the government together with schools need to develop the community based school literacy program to improve the quality of program and increase the students’ reading interest
ІНФОРМАЦІЙНО-КОМУНІКАЦІЙНІ ТЕХНОЛОГІЇ ЯК ЗАСІБ ПІДВИЩЕННЯ ЯКОСТІ НАВЧАЛЬНОГО ПРОЦЕСУ В СИСТЕМІ ПІСЛЯДИПЛОМНОЇ МЕДИЧНОЇ ОСВІТИ

The article discusses the relevance of the use of ICT-based multimedia technology as a means of improving the quality of the educational process in the system of postgraduate education. The article highlights the features of interactive whiteboard and Smart Notebook software, which can be used in the educational process of modern health professionals in the system of postgraduate education. Examples of teaching and methodological elements developed in the Smart Notebook software are provided.
IMPLEMENTASI SUPPORT VECTOR MACHINE PADA ANALISA SENTIMEN TWITTER BERDASARKAN WAKTU

Sentiment analysis is one branch of science from data mining that aims to analyze, understand, process, and extract textual data in the form of opinions on entities such as products, services, organizations, individuals, and certain topics. In determining positive, negative or neutral categories, a public response on twitter can be done manually by reading each tweet. This certainly requires a lot of time and takes a lot of energy. In this study using the Support Vector Machine classification algorithm to classify tweet data into positive, negative or neutral sentiments. Analysis is carried out based on a certain time span, because each time can have a different topic of discussion and from the results of these data can be seen the development of sentiment trends and can be seen how the public response to a particular topic. The tweet data is obtained by crawling periodically with the target keywords of the names of candidates and vice president in the 2019 election. The dataset used in this study uses 600 tweets. In testing the classification using k-fold cross validation by dividing into 10 data parts, average value of 66% accuracy, 67% precision and 66% recall.
Guides: COVID-19 Resources: Statistics

The Saint Paul Public Library COVID-19 Resource Collection: a guide to references on a wide variety of COVID-19 topics.