Reviewerly/exHarmony huggingface dataset:
In-situ Extraction of Randomness from Computer Architecture Through Hardware Performance Counters

True Random Number Generators (TRNGs) are one of the most crucial components in the design and use of cryptographic protocols and communication. Predictability of such random numbers are catastrophic and can lead to the complete collapse of security, as all the mathematical proofs are based on the entropy of the source which generates these bit patterns. The randomness in the TRNGs is hugely attributed to the inherent noise of the system, which is often derived from hardware subsystems operating in an ambiguous manner. However, most of these solutions need an add-on device to provide these randomness sources, which can lead to not only latency issues but also can be a potential target of adversaries by probing such an interface. In this paper, we address to alleviate these issues by proposing an in-situ TRNG construction, which depends on the functioning of the underlying hardware architecture. These functions are observed via the Hardware Performance Counters (HPCs) and are shown to exhibit high-quality randomness in the least significant bit positions. We provide extensive experiments to research on the choice of the HPCs, and their ability to pass the standard NIST and AIS 20/31 Tests. We also analyze a possible scenario where an adversary tries to interfere with the HPC values and show its effect on the TRNG output with respect to the NIST and AIS 20/31 Tests. Additionally, to alleviate the delay caused for accessing the HPC events and increase the throughput of the random-source, we also propose a methodology to cascade the random numbers from the HPC values with a secured hash function.
Build Design of Information Media Application in Purwokerto Based on Multimedia

Abstract Transportation is a major problem for newcomers in certain places. Types of transportation and trails make newcomers confused when they want to visit a certain place. There are several media that can solve the problem, but the limitations of the media make it difficult for newcomers to find the right track in the city, for example in Purwokerto city. One of the media that can be used is multimedia-based media. In this case, it can be created using Adobe Flash CS5. This software can be used to create animations about urban transport vehicle lines in Purwokerto. Multimedia applications make users know information that is accurate, precise, fast and interesting.
A Multimodal Meeting Browser that Implements an Important Utterance Detection Model based on Multimodal Information

This paper proposes a multimodal meeting browser with a CNN model that estimates important utterances based on co-occurrence of verbal and nonverbal behaviors in multi-party conversations. The proposed browser was designed to visualize important utterances and to make it easier to observe the nonverbal behaviors of the conversation participants. A user study was conducted to examine whether the proposed browser supports the user to correctly understand the content of the discussion. By comparing a text-based browser and a simple video player, it was found that the proposed browser was more efficient than the video player and allowed the user to obtain a more accurate understanding of the discussion than the text-based browser.
Increasing Vocabulary Mastery Through Animals Video At Kindergarten PGRI Bulucenrana

The objective of the research was the find out whether or not of animal videos increases vocabulary mastery in PGRI Bulucenrana kindergarten students. This study uses an experimental design. The population of this research is one group, group B in TK PGRI Bulucenrana. In the academic year 2018/2019 with a total population of 12 students. The sample of this study was 12 students. The sample of this study was 12 students or a total sample. This study used media animals video in class. Researchers found that the use of animal videos can increase vocabulary mastery in Bulucenrana PGRI kindergarten students. The average value of the initial test (21,08) is lower than the average value of the final test (77,50), it is also evidenced by the P-Value (0,000 &lt; 0,05) a significant level of 0,05. So the researchers concluded that H0 was rejected and H1 was accepted. Based on data analysis, the researcher concludes that: animals video media is effective in increasing vocabulary mastery in Bulucenrana PGRI kindergarten students&#x0D;
PENGARUH GERAKAN LITERASI SEKOLAH TERHADAP MINAT BACA SISWA KELAS SMK

In Indonesia, interest in reading in all circles is still lacking, especially among students and students who are actually people who are struggling in the world of education. This is because the school community does not understand the benefits of literacy. In addition, there are quite a lot of obstacles that occur during reading activities. Today the government makes a policy to foster a culture of literacy through how to familiarize students with reading for 10-15 minutes before learning is carried out. The main subject of this research is class X students. The formulation of the research problem this time is: 1) How is the influence of GLS in increasing student attention reading? 2) What are the obstacles in literacy? The purpose of this study is to be able to determine the influence and barriers of the GLS program to attend to reading students in vocational schools. The type of research method used is a type of qualitative research. The process of collecting the data used is a questionnaire. The results of this study illustrate that attention or interest in reading students increases this can be seen from the results of questionnaires that illustrate that attention to reading of students increases after the GLS student literacy culture can be improved, their reading activities can be observed, and their reading skills develop well by growing literacy culture in students.
Понятийный круг многосторонней организации обсуждения: эвристический аспект

The conceptual and terminological field, which includes different forms and types of dialogical speech, from the point of view of their interdisciplinary and meta-subject significance, as well as from the positions of heuristically organized teaching how to generate texts, is analyzed in the article. The traditional parallels of a dialogue and conversation are characterized by the value for the heuristic teaching. The content and specificity of the concept of polylogue are described on the base of philosophical, linguistic, literary, cultural and other sources. Possibilities and methodological perspectives of introducing the concept of a heuristic polylogue into the theory of the educational process are argued.
Laser centerline extraction method for 3D measurement of structured light in multi-scenarios

3D measurement of structured light technology is an extremely vital approach to obtain 3D information of objects. Extraction of the centerline of laser stripe is a key factor that could affect the accuracy and speed of 3D measurement of structured light in the meantime. A method of extracting centerline of laser stripe for 3D measurement of structured light that adaptive to multiple scenarios was proposed. The adaptive convolution template was generated by making full use of the geometric information and correlation of laser stripe in the image, which can filter and enhance the image quality of laser stripe and enable the gray value of cross-section of laser stripe satisfy the Gauss distribution. The sub-pixel accurate localization and extraction of laser stripe centerline were realized by gray weighted algorithm. The experimental results show that the proposed adaptive convolutional algorithm can extract the laser stripe centerlines of the objects with different shapes and materials based on multi-scenarios and overcome the influence of uneven brightness and noise at the same time. Based on the algorithm, the extraction time of single frame is shortened to 0.107 s and the relative error is reduced to 0.076 5%, which improves the extraction accuracy and speed of laser stripe centerline effectively.
On the number of irreducible polynomials of special kinds in finite fields

Let $\mathbb{F}_q$ be the finite field of order $q$ and $f(x)$ be an irreducible polynomial of degree $n$ over $\mathbb{F} _q$. For a positive divisor $n_1$ of $n$, define the $n_1$-traces of $f(x)$ to be $\mathrm{Tr}(\alpha; n_1) = \alpha+\alpha^q+\cdots+\alpha^{q^{n_1-1}}$ where $\alpha$'s are the roots of $f(x)$. Let $N_q^*(n; n_1)$ denote the number of monic irreducible polynomials of degree $n$ over $\mathbb{F} _q$ with nozero $n_1$-traces. Ruskey, Miers and Sawada have found the formula for $N_q^*(n; n)$. Based on the properties of linearized polynomials, we obtain the formula for $N_q^*(n; n_1)$ in the general case, including a new proof to the result by Ruskey, Miers and Sawada.
Guidelines to Convert Legacy Applications into Docker Container Services

In the past people would buy a program on a disc and install it ontheir local computer or server. Today, cloud computation allows usersto access their applications over the Internet while also prov ...
A Classification Model for Modeling Online Articles

Due to the constant evolvement of the web and the viral spread of online news on social media, predicting the popularity of a news article became a topic of interest to many categories of people ranging from marketing personnel to politicians. In this paper, we focus on comparing four classification algorithms on a dataset consisting of 39000 news articles taken from Mashable website. The articles were classified into two classes: Popular and not popular. Four different machine learning algorithms were used for classification of the data (KNN, Naïve bayes, Adaboost, and decision tree). Finally, the four classification methods were compared with each other.
STRATEGI “GERBANG PELANGI” DALAM MENGOPTIMALKAN PRESTASI SMA NEGERI 1 GANTUNG

ABSTRACT Pelangi (Gerakan Pengembangan dan Penguatan Literasi, Sinergi raih Prestasi) as an alternative to solving problems in optimizing the achievements of SMA 1 Gantung. The main focus of Pelangi is to empower all school stakeholders in their daily activities by allocating available educational resources to achieve school achievements. Development of academic and non-academic school achievements through the carried out with three (3) main principles, namely: (a) Development and strengthening of literacy into a real movement and action, (b) Establish communication and synergy with various parties, and (c) Building a shared commitment to achieve both academic and non-academic achievements. The results of the Pelangi implementation include: (a) Development and strengthening of literacy into a real movement and action (the formation of a school literacy team and the school literacy task force, the implementation of extracurricular activities that support literacy skills, the formation of literacy classes, documented work of students in the literacy museums in schools, giving appreciation to educators, students and education personnel as well as community elements in the form of the SMA 1 Gantung award, (b) Good communication and synergy with various parties (growing commitment and cooperation from teachers, participants students, librarians, committees, parents to supervise, monitor and ensure the sustainability of the school literacy program), (c) building a shared commitment to achievement (improving the quality of teacher performance and learning quality of students become more meaningful to the emergence of creativity and courage of educators, educational staff education, students to continue working). Keywords: Gerbang Pelangi, school achievement.
The Data Wrangler’s Handbook: Simple Tools for Powerful Results

A good many years ago, when personal computers were still in their tweens and windows were the glass-covered apertures in the walls of our houses, one handy DOS utility displayed a geeky quote of t...
LibGuides: Remote Library Services: Home

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Preservation of Patient Level Privacy: Federated Classification and Calibration Models

Author(s): Huang, Yingxiang | Advisor(s): Ohno-Machado, Lucila | Abstract: With the launching of the Precision Medicine Initiative in the United States, by the National Institute of Health, and the emergence of a large volume of electronic health records, there are many opportunities to improve clinical decision support systems. A large number of samples are needed to build predictive models that have adequate discrimination and calibration. However, protecting patient privacy is also an important issue. Patient data are typically protected in localized silos, and consolidation of datasets from different healthcare systems is difficult. Federated learning allows the training of a global model by amassing intermediate calculations from localized medical systems. The knowledge learned from the data can be transferred and aggregated to achieve better performance than the one achieved by individual local models. Federated learning may help build better models, providing more accurate predictions. There are two types of measures to assess how well a model performs: discrimination and calibration. While most papers report discrimination measures, calibration has often been neglected but it is a critical metric for evaluation. In this dissertation, I show a novel way to build classifiers and calibration models in a federated manner. I also show how I can evaluate and improve model calibration in this manner. Federated modeling enables the accumulation of knowledge and information that are otherwise locked behind local medical systems.
Active Learning for Semantic Segmentation

Neural Networks have proven their capabililties in computer vision tasks. How- ever, their ability depends on the quantity and quality of data. Larger training dataset usually improves the performa ...
Enhanced ABC Variant (JA-ABC4) in Optimizing Economic Environmental Dispatch (EED)

Artificial bee colony (ABC) optimization algorithm has been successfully applied to solve variousoptimization problems. ABC is a kind of bio-inspired algorithm (BIAs) that has attracted the attention ofoptimization researchers. ABC imitates the foraging behaviour of honeybees, thus it can be classified intoswarm-intelligence-based (SI) algorithm; one of the prominent classes in BIAs. ABC has shown tremendousresults in comparison with other optimization algorithms such as Genetic Algorithm (GA), DifferentialEvolution (DE) algorithm and Particle Swarm Optimization (PSO) algorithm. Moreover, the advantages ofABC include it is simple and flexible. Despite of these advantages, ABC has been found to be trapped in localoptima on multimodal functions and exhibited slow convergence speed on unimodal functions. Motivated bythese, researchers have proposed various ABC variants but none of them are able to solve both problemssimultaneously. Thus, this paper proposes a new modified ABC algorithm referred to as JA-ABC4 with theobjectives to robustly find global optimum and enhance convergence speed. The proposed algorithm has beencompared with the standard ABC and other existing ABC variants on twenty-four commonly used benchmarksfunctions. The performance results have shown that the proposed algorithm has yielded the best performancecompared to the standard ABC and two other good ABC variants (BABC1 and IABC) in terms of convergencespeed and global minimum achievement. For further justification, JA-ABC4 has been tested to optimizeeconomic environmental dispatch (EED) on 10-unit generator system. The results obtained have also illustratedthe robust performance of JA-ABC4 in solving complex real-world problems.
Uso de un objeto virtual del aprendizaje para desarrollar competencias de investigación en educación superior

Foundation : Educational practices in universities require the use of research to find and generate new theories and knowledge. In Mexico, in public universities, curricular programs related to the development of research skills are increasingly scarce in this component. Objective : to analyze the results of the application of a virtual learning object to develop skills in university students which are necessary to develop research projects in education. Methods : qualitative study, with action research design, in a sample of 41 students of the sixth semester of Science in Education, at the Autonomous University of the State of Hidalgo, Pachuca de Soto, Mexico. Focus group techniques and participant observation were used. The intervention was carried out through the development of didactic units and with the use of a virtual learning object. Results : the students, in a teacher-led workshop class, managed to theorize about the approach and research problem justification, research questions, and objectives. Regarding virtual learning object, they considered it a fundamental support tool to complete the first part of their research project. Conclusion : The virtual learning object was a didactic resource capable of guiding students towards the development of skills in their research projects; it helped and exemplified the students of Science in Education to formulate the problem statement, the justification, objectives and questions of a research project.
Computational Analysis of Historical Hebrew Newspapers: Proof of Concept

Abstract This article focuses on one decade, 1874–1883, in the relatively long lifespan of the Hebrew weekly Ha-Tzefirah , which was founded in Warsaw in 1862. Applying computational tools to the study of the early Hebrew press requires a unique effort. The Hebrew language in general is distinct in its characters, morphological structure, and word order. The contribution of this proof-of-concept study is two-fold: First, computational analysis provides a long-term indication of trends in the discourse that cannot be attained through qualitative study. The second contribution is on the micro level: Computational analysis can potentially shed light, in a diachronic perspective, on the use of a specific term or the discussion of a specific geographical location.
Research Journal of Educational SciencesÂ

Coverage Area: Â Researches in the field of Education Sciences including management of education systems, strategies and policies for education, possible new model of education system, possible different technique implement in education systems, intercultural education and modern technology-based educations, leadership in education, education and information science, child education, adult education, psychology and sociology education, political science and economic education, country development and education systems, etc.
The impact of differentiated assessment on teaching and learning: multi-case studies of PutraPacer application in a higher education institution

Acknowledging the diversity of learners in the 21st century, differentiation need to be integrated in classroom instruction and assessment. There are researches on differentiated assessments that have been carried out in Malaysia. These researches featured strategies and the usage of different tools to carry out differentiation in teaching and learning. However, to date, there is no generic, systematic and dedicated tools available yet for teachers or lecturers to achieve and employ alternative assessment for differentiated classroom. Hence, PutraPacer is developed as a customizable intelligent web application for differentiated assessment. The purpose of this research is to explore the impact of PutraPacer as a differentiated assessment tool on teaching and learning in the higher education. This is a multi-case study which will be carried out on three experienced lectures from different streams, together with their respective students. The outcome of this research should be able to enrich the practice of differentiated assessment in the field of education and at the same time providing another alternative to assessing mixed-ability classroom with a more comprehensive and systematic tool.
LibGuides: Online Resources for Remote Library & Learning : Home

Utilize the information & tools listed in this guide to assist with library usage and online learning in the event that library/campus services are disrupted by Covid-19.
A Novel Adaptive Approach for Sentiment Analysis on Social Media Data

Sentiment analysis (SA) is the approach of determining polarity of any content whether the given sentence contains positive, negative, or neutral sentiments. In many real-world situations, it is required to know the public emotions about happening in surrounding environment. Thus, this analysis helps in decision making on a particular task. There is a huge area where sentiment analysis can be utilized to improve the decision making like while launching a new product, adding additional features in existing products, announcing of a new government policy, etc. This paper shows sentiment analysis system which is based on machine learning algorithm used by TextBlob API using python. Proposed system uses natural language tool kit (NLTK) dataset for training the algorithm. This newly implemented application is used to do sentiment analysis on “twitter” (a social networking application) real-time data. Its experimental results are also presented in this paper. The results/analysis can help big brands, companies, and governments in planning future activities.
Thai Words Segmentation Using an Unsupervised Learning Technique

Word Segmentation or Tokenization is the process of determining the best likely sequence of words from a sequence of text. For Thai language, word segmentation is not a trivial task as words and sentences in Thai are written continuously without any spaces or delimiters. Most techniques for word segmentation, especially when using machine learning, requires manually tagged data where words begin and end as a training dataset. In this study, an unsupervised machine learning technique that does not require the use of manually tagged data was developed. The technique involves breaking input text into syllables and then uses Genetic Algorithms (GA) to merge the syllables back into words. GA identifies the best segmentation of words by minimizing word distance which is the novel concept developed in this study. It is the sum of all syllable distances of every pair of syllables within a word. The syllable distance is the measure of how far apart each pair of syllables is in a document. The implementation was done using Python and achieves 70% accuracy (F1 measure) while using a 100k untagged words training dataset. The performance also improves with more training data and some tuning of GA parameters.
Unmanned Aerial Vehicle for Surveillance

Nowadays, the security and surveillance is important element for any industry. The experiment aims to provide secure-effective solution for surveillance systems. There were several stages such as component design, hardware assembly, calibration, flight board modification, defined flight plan and verification and validation. The experiment prototype was consisting mechanical system and electrical system. The mechanical was propulsion system contained motor, electronic speed controller, batteries and propeller while electrical system contained flight control board, vision system, sensors and communication hardware. The system assembly and component connection was done using reference schematic. The mission plan was tested in university campus, the quadcopter had followed pointed path in the map as expected. The face classifier had been trained to analyze input image and detected faces. The upper body classifier had been trained to analyze same input image and detect upper body on the image. This classifier had been applied in different images from an aerial view with different distance.