Reviewerly/exHarmony huggingface dataset:
Lawsuit claims Facebook groups led to fatal shootings in Kenosha

Four people are behind a federal lawsuit against Facebook, accused shooter Kyle Rittenhouse, and a former Kenosha alderman.
Probably Approximately Correct Learnable Fuzzy System

Author(s): Wang, Yan | Advisor(s): Liu, Honghu | Abstract: This dissertation develops the probably approximately correct (PAC) learnable fuzzy system to predict clinical outcomes from a small number of survey questions (short form). There are five layers in the system: input, fuzzification, inference, defuzzification, and production. The major product in this dissertation is to derive the PAC learnable knowledge-driven machine learning algorithm by growing sample using Bootstrap samples with Gaussian distributed noise. The input layer is the procedure for preparing data input. In the fuzzification layer, sample size is significantly increased using bootstrap re-sampling with replacement. The fuzzy set with proposed membership function is generated by introducing Gaussian distributed noise to survey responses of the bootstrap samples to reflect uncertainty. This is a natural language extension from the point option in survey questions to region input with probabilities from survey design space. The inference layer includes both classification and prediction. Here we use machine learning techniques to derive the algorithms in this layer, e.g. Naive Bayesian method and eXtreme Gradient Boosting (XGBoost). The final predicted values require a defuzzification process in the next layer to remove noise in prediction. There are four types of input after fuzzification, original input, fuzzy input, input required interpolation and input required extrapolation. The defuzzification process is based on weighted means of related information. The last step of the system is the output layer with algorithms, final prediction and validation internally and externally. Lastly, we apply this fuzzy system to derive PAC learnable algorithms to predict oral health clinical outcomes. The input predictors include short forms and demographic information. The short forms, developed from Graded Response Models in Item Response Theory, have two versions (children and their parents). The clinical outcomes are referral for treatment needs (categorical) and children’s oral health status index score (continuous). The prediction is evaluated internally and externally by sensitivity and specificity of a binary variable, correlation (between original value and predicted value) and root mean square error (RMSE) of a continuous variable. Both internal and external validation show the improvement of prediction when new information is added and generalizability as well as the stability of the algorithm. The best prediction (high sensitivity and relatively high specificity for categorical variables, low RMSE and high correlation) is reached when using child's self-reported short form, plus parent's proxy-reported short form, and demographic characteristics.
A Study on Training Data Selection for Object Detection in Nighttime Traffic Scenes

With the growing demand for robust object detection algorithms in self-driving systems, it is important to consider the varying lighting and weather conditions in which cars operate all year round. The goal of our work is to gain a deeper understanding of meaningful strategies for selecting and merging training data from currently available databases and self-annotated videos in the context of automotive night scenes. We retrain an existing Convolutional Neural Network (YOLOv3) to study the influence of different training dataset combinations on the final object detection results in nighttime and low-visibility traffic scenes. Our evaluation shows that a suitable selection of training data from the GTSRD, VIPER, and BDD databases in conjunction with selfrecorded night scenes can achieve an mAP of 63,5% for ten object classes, which is an improvement of 16,7% when compared to the performance of the original YOLOv3 network on the same test set.
ОСОБЛИВОСТІ ГРОМАДСЬКОЇ ДІЯЛЬНОСТІ СТУДЕНТСЬКОЇ МОЛОДІ ВИЩИХ НАВЧАЛЬНИХ ЗАКЛАДІВ УКРАЇНИ НА РУБЕЖІ ХІХ-ХХ СТ.

The article presents the analysis of formation and development of social activity of student youth of higher educational institutions of Ukraine of the end XIX - beginning of XX century. It is shown that the first manifestations of student social activity originate with the emergence of the students as a social group, which is inherent in the pursuit of corporate activities, social activities, pooling of interests. It is established that in the period of the end XIX – beginning of XX century social activities of the students were razvivalas influenced by government policies, social, political and economic factors and is regulated by the normative acts of the government (University statutes, rules for students). Forms and types of student participation in democratic social movement were various, evolved in accordance with the direction of development of society and political conditions. Highlighted the main directions of social activity of students of the study period: academic (emphasis on academic work, projects, scientific, literary, and cultural character), national, political. Key words: students, social activities, public activity, university, student union.
Secure software modeling methods for forensic readiness

Proactive preparation of software systems for forensic investigation (forensic readiness) during the software development process, has been addressed only recently and has many open challenges. Representation of the forensic concerns and specific requirements of forensic readiness is one of them. A common way of representing concepts in software development is modeling. This paper is focused on the possibility of reusing existing secure software modeling methods for the needs of forensic readiness.
Supporting terminology extraction with dependency parses

Terminology extraction procedure usually consists of selecting candidates for terms and ordering them according to their importance for the given text or set of texts. Depending on the method used, a list of candidates contains different fractions of grammatically incorrect, semantically odd and irrelevant sequences. The aim of this work was to improve term candidate selection by reducing the number of incorrect sequences using a dependency parser for Polish.
Top 7 Reasons You Should Buy An iPhone

In 2007, Apple broke the mold of phone design and redefined an entire era by releasing its flagship device, the iPhone. Since then we’ve ...
Pendekatan Kedwibahasaan dalam Pengajaran Bahasa Indonesia pada Siswa Kelas Rendah

The purpose of this study is to describe the application bilingual approach in teaching Indonesian subjects to lower elementary school  of SDN 15 Sempalai Tebas. This research is focus on field research using sociolinguistic studies. The object of this research is teachers and low-grade elementary school students. The data collection techniques used in this study were direct observation techniques, free listening and in-depth interviews. Tools used in data collection are: a. observation guide and field notes, b. Audio visual recording equipment, and c. Interview guide. The data were analyzed by using interactive analysis of the Milles and Huberman model. The results showed that the bilingual approach was used by the teacher in the learning process. The teacher applies a bilingual approach in the learning process by using the Malay Language with Sambas dialect Dialect, alternately with Indonesian Language. In teaching and learning activities when the teacher explains the subject matter to students, Indonesian language uses in speech of simple vocabulary, while the Malay Language with Sambas Dialect is used in the complex vocabulary in the learning process at the classroom.
PragerU : les plateformes sont-elles libres de modérer les contenus postés par leurs utilisateurs ?

obs. sur United States Court of Appeals for the Ninth Circuit, Prager University v. Google LLC, FKA Google Inc.; Youtube LLC, No. 18-15712, February 26, 2020
PERBANDINGAN METODE DIMENSI FRAKTAL DAN JARINGAN SYARAF TIRUAN BACKPROPAGATION DALAM SISTEM IDENTIFIKASI SIDIK JARI PADA CITRA DIGITAL

Identification is the process of finding the data owner. Fingerprints are a unique part of each individual. The first step of the identification process is pre-processing like cropping, sharpening, resizing and grayscale. The cropping process to take part of fingerprint on the image. The sharpening process is useful for helping the otsu method in extracting features. Resize is to change image resolution while grayscalse is to change the color image into gray image. Next is the feature extraction process using the otsu method. The otsu method is used to define the threshold when the image binary process. White pixels are a feature of fingerprints. The characteristics of fingerprints are an important part of the fingerprint. Fingerprint characteristics taken with grid process. The grid process is to divide the image into sections. The identification process uses fractal dimension and neural network method. The resemblance of the test image and the training image is measured by the correlation coefficient method. Both methods are able to identify the training image 100%. The image being tested is an image with varying damage. Percentage of ability of fractal dimension method in identifying 85% while Backpropagation method 90%. In this research, how to take on characteristics is very important for the identification process.
Scene Graph to Image Generation with Contextualized Object Layout Refinement

Generating high-quality images from scene graphs, that is, graphs that describe multiple entities in complex relations, is a challenging task that attracted substantial interest recently. Prior work trained such models by using supervised learning, where the goal is to produce the exact target image layout for each scene graph. It relied on predicting object locations and shapes independently and in parallel. However, scene graphs are underspecified, and thus the same scene graph often occurs with many target images in the training data. This leads to generated images with high inter-object overlap, empty areas, blurry objects, and overall compromised quality. In this work, we propose a method that alleviates these issues by generating all object layouts together and reducing the reliance on such supervision. Our model predicts layouts directly from embeddings (without predicting intermediate boxes) by gradually upsampling, refining and contextualizing object layouts. It is trained with a novel adversarial loss, that optimizes the interaction between object pairs. This improves coverage and removes overlaps, while maintaining sensible contours and respecting objects relations. We empirically show on the COCO-STUFF dataset that our proposed approach substantially improves the quality of generated layouts as well as the overall image quality. Our evaluation shows that we improve layout coverage by almost 20 points, and drop object overlap to negligible amounts. This leads to better image generation, relation fulfillment and objects quality.
Prediction of Damage to Electronic Devices Based On Power Consumption Characters Using Artifician Neural Network

This study was conducted to determine the ability of artificial neural network in predicting the damage of electronic devices based on the character of electric power consumption. each electronic device has standard input and power consumption when the condition of the device is good. This test is performed using artificial neural network backpropagation with sigmod activation function.  To conduct training on the system, we perform the recording of power consumption of electronic devices that are considered in good condition. Data is recorded as a volt ampere line in a given time unit. From the results of testing and implementation of artificial neural network is able to recognize the good pattern of device consumption by using 300 or more hidden network. Artificial neural network backpropagation successfully detects abnormal power consumption with a success rate of over eighty percent.
PENINGKATAN HASIL BELAJAR MENULIS KARANGAN NARASI DENGAN MENGGUNAKAN METODE SAINTIFIKSISWA KELAS VI SDN 07 TUJUAH KOTO TALAGOKECAMATAN GUGUAK KABUPATEN LIMA PULUH KOTA

This research is motivated by problems in the learning process, namely students have difficulty in expressing their ideas into writing or essays. The formation of words or sentences used by students is inaccurate or inappropriate, as well as the use of punctuation and spelling. In learning activities writing the teacher is more likely to apply teaching writing by prioritizing the results of the process. This study aims to improve narrative writing skills using the scientific method of class VI SDN 07 VII Koto Talago, Guguak District, Lima Puluh Kota Regency. The method used in this study is qualitative and quantitative methods. Qualitative research is research that intends to understand phenomena, about what is experienced by research subjects such as behavior, perceptions, motivations, actions and others. The results of the study describe learning using the Scientific method can improve student learning outcomes which initially in pre-cycle only reached 64 who are in sufficient qualifications. In the first cycle increased to 74 who were in qualifications more than enough, after the second cycle, the students' scores increased again being an average of 90 who are in excellent qualification. The increase includes three indicators, namely (1) narrative characteristics, (2) use of punctuation, (3) capital letters. Third, improving narrative writing skills using the Scientific method of class VI SDN 07 VII Koto Talago District of Guguak, Lima Puluh Kot Regency can be achieved due to several factors including teachers and students. Based on the results above it can be concluded that the narrative text writing skills using the scientific method increased, from sufficient qualifications to more qualifications until they were in excellent qualifications. Thus it can be concluded that, through the cooperative method the type of make a match improvement in students' essay writing skills increased significantly from stage to stage.Key Words: escritura de narrativas, métodos científicos
I/O Performance Optimization Analysis of Container on Cloud Platform

Because the containers share the operating system kernel of the host, the performance interference, that is, the performance isolation problem will occur between the containers due to the resource competition. This paper defines the I/O isolation of container system from the perspective of SLA of I/O service, analyzes the I/O evaluation index and queue model of container system, collects the change trend of I/O performance index of container system through experiments, analyzes the quantitative relationship between the indexes, and the impact of overloaded container on the overall I/O performance of container system. Based on this analysis, this paper proposes an algorithm and designs a logic model to improve the isolation of I/O performance of the container system by dynamically adjusting the intensity of I/O load of the overload container, and verifies the feasibility of the algorithm through a simple experiment.
Design and Development of Website-Based Sales Information System at PT. Surabaya Trading Industri

In the system that runs on PT. Surabaya Trading Industry, that need to be resolved. The sales process for a company takes a long time and customers have to come to the company because of the large number of orders that must be checked one by one because it is based on a lot of documents and there may be broken and unreadable. PT. Surabaya Trading Industry has difficulty in marketing and recording orders, especially in customers whose geographical location is far from the company so that customers must come to the company, this causes difficult access to facilitate customers. So that all existing orders can be managed and monitored, we need a system to manage orders. A solution is given in the form of a web-based sales information system application at PT. Surabaya Industrial Trading. Tthis application can help PT. Surabaya Trading Industry to manage order data, provide a function of stock and order monitoring that is recorded when ordering takes place so that the company can find out information about the order. The application also helps in providing order reports, income reports, and stock reports.
PENGELOLAAN DATA KEUANGAN PENDAPATAN ASLI DAERAH (PAD) SEKTOR PARIWISATA KABUPATEN PADANG PARIAMAN

The development of technology makes motivation for an agency to improve the service system and management of local revenue in the tourism sector and culture for the local district. Data management and financial allocation in the Padang Pariaman District Tourism Office is currently done manually, both recording financial data, transactions, and financial income reports. Lack of management of transaction data and reports, makes it difficult for Padang Pariaman tourism agencies to determine errors in financial reporting of local revenue (PAD), as well as data loss and difficulties when searching for data. To overcome this problem, we need a specific information system or program that can facilitate the Padang Pariaman tourism office in managing financial statement data. With this application, it is hoped that it can provide accurate and detailed reports and make inputing services on the management of financial data of local revenue in the tourism sector in Padang Pariaman Regency run well and effectively.
Review of "Prosperity: Better Business Makes the Greater Good" by Colin Mayer

Prosperity: Better Business Makes the Greater Good Colin Mayer Oxford: Oxford University Press, 2018 (261 pages)
Evaluation of the Effect of Steganography on Medical Image Classification Accuracy

Predictors and features that are used in teleradiology and machinebased auto diagnosis in medicine are often not put into consideration while evaluating medical image Steganography algorithms. In this paper, the effect of embedded security data in automated diagnosis was evaluated using Support Vector Machine (SVM) image classification of Chest X-rays Scan of Normal and Pneumonia patients. The goal is to quantify and qualify disease classification parameters because of the addition of steganographic security data in to the image. Four textural image features: Contrast,Homogeneity Energy, and Entropy were used as medical image biomarkers. Their statistical properties for the disease conditions (normal or pneumonia)were profiled and used in SVM training. The evaluation parameters for the machine learning models include accuracy, specificity, recall, and precision. The baseline (before the addition of security data)performance was 86.14% accuracy,82.18% recall, 90.10% specificity, and 89.25% precision while a typical performance after the addition of security data was 82.18% accuracy, 85.15% recall, 79.21% specificity, and 80.37% precision.We conclude that embedding strength, watermark payload, and region of embedding should be carefully selected to avoid the automated diagnostic outcome by a steganographic security changing algorithm algorithm to a medical image.
Our Model and Repository

In this chapter we’re going to introduce “data” to our API, so we’ll begin our journey with our Model and Repository classes.
For the people, by the people - An Open Access eTextbook powered by faculty, students and librarians

Poster presented at the Ontario Library Association Super Conference on February 1, 2019. Creative Commons CC BY-NC-SA 4.0.
Sidon basis in polynomial rings over finite fields

Let $${\mathbb{F}_q}\left[ t \right]$$ denote the polynomial ring over $${\mathbb{F}_q}$$ , the finite field of q elements. Suppose the characteristic of $${\mathbb{F}_q}$$ is not 2 or 3. We prove that there exist infinitely many N ∈ ℕ such that the set $$\left\{ {f \in {\mathbb{F}_q}\left[ t \right]:\deg f < N} \right\}$$ contains a Sidon set which is an additive basis of order 3.
Las escritoras y sus obras en los manuales de italiano como lengua extranjera. Female writers and their works in Italian as a foreign language textbooks.10.20420/ElGuiniguada.2020.337

Literature is an extremely valuable resource in language teaching. However, according to numerous studies taken from feminist literary criticism, female authors are generally underrepresented in, anthologies, textbooks and lists of literary prize winners. This is due to the numerous obstacles female writers encounter when their merits must be recognized by the established canons, which are fundamentally androcentric and patriarchal. The purpose of this paper is to determine how many female authors are present and how much of their work is included in six Italian as a Foreign Language textbooks currently in use. The results show that female authors featured in only 8% of the textbooks, and that their works are rarely included, with just two examples being found. This absence is completely unjustified given the huge number of talented women who have contributed to the creation of the literary landscape in the past and continue to do so in the present.
LibGuides: Guitar: ALLIES

This is a library guide for students of the guitar. This page will tell you how to request a book from another library.
Utilization of Assertive Speech Act in Indonesian TV Talk Show as the Oral Discussion Text Learning Media

This research was conducted to see how the benefits of speech act used in speech titles on Indonesian television for learning Indonesian text in New Normal Era, especially its use as a medium for oral discussion text learning. The purpose of this study is also related to the development of more innovative learning media by utilizing electronic television media in the form of speech titles. The results of this study can then be used by teachers as information and experiments on the use of speech acts as a medium in the teaching and learning process that will be carried out in schools. Besides, this research is also useful for future researchers who will raise related themes as one of the references.The research method used in this study is a qualitative descriptive method. The approach used in this study is the pragmatic approach, which is the focus of this research is the language used in communication. Data collection is done by listening and note-taking techniques. Data sources in this study came from speech acts of the speaker in the TV talk show in Indonesia.The results showed that there were three forms of assertive speech acts that could be used as learning media for discussion texts, namely 1) assertive speech acts explained, 2) assertive speech acts supported, and 3) assertive speech acts refused.The results of the study can be applied to the learning of discussion texts of Indonesian subjects in Indonesian.The renewal of this study compared to similar research conducted previously is the implication of the speech acts on the learning of discussion texts. Previous research discusses the use of speech acts for learning Indonesian in general, and specific uses have not yet been found in the discussion text.Keywords:Speech Act, Assertive Speech Act, Talkshow, Oral Discussion TextLearning Media.