Reviewerly/exHarmony huggingface dataset:
Improving students’ speaking performance through language board game at the eighth grade of SMPIT Permata Bunda

The objectives of the research are to find out whether there is significant difference of students’ speaking performance after they got treatment by using Language Board Game and Pair Dialogue, to find out aspects of speaking improve the most in both classes, and to find out the students’ response about Language Board Game. An experimental group was used in the research. The result showed that there was significant difference between students who were taught through Language Board Game and Pair Dialogue. The gain in the experimental class was 15.1334, while the control class was 10.9375. Besides that both techniques also affected the aspects of speaking especially in term of fluency aspects. The result of students’ response showed that 97.84 % give the positive response toward Language Board Game. It could be concluded that the Language Board Game was effective to improve students speaking performance. Keywords: L anguage board game, p air d ialogue, speaking performance.
IMAGE ENCRYPTION BY APPLYING SECURE HASH SHA-256: A REVIEW PAPER

A new image encryption algorithm based on chaos and SHA-256 is proposed in this paper in order to resolve the complexity of key management in one-time pad encryption systems and also resist the assault of selected plaintext. It adopts the structure of uncertainty and diffusion. First, to ensure that each encrypted result is different, the environment of a plaintext image is surrounded by a sequence created from the SHA-256 hash value of the plaintext. Secondly, by adding the disruption term associated with the plaintext to the chaotic sequence, the image is scrambled according to the random sequence obtained. Third, in the diffusion stage, the cypher text (plaintext) feedback mechanism of the dynamic index is adopted, i.e., the cypher text (plaintext) position index used for feedback is dynamic. In the one time pad encryption scheme, the above steps can ensure that the algorithm can avoid selected plaintext attacks and can resolve the complexity of key management
Optimization of National Rice Production with Fuzzy Logic using Mamdani Method

The purpose of this article is to optimization of national rice production with fuzzy logic using Mamdani method. Based on the results of the study, it is known that four parameters need to be considered to maintain the price stability of necessities, namely production; availability; demand and distribution. Optimization of production by producers and optimization of the ordering of goods by distributors are important steps to maintain price stability for necessities. Optimization of production and ordering of staple goods will have a significant impact on the financial sector because it is closely related to the prediction of the number of raw materials used, production costs, storage costs, and also distribution costs of goods. One of the fuzzy inference methods that can be used for this optimization is the Mamdani method. To get the output on the application of the fuzzy logic of the Mamdani method, four stages are needed, formation of fuzzy sets; application of implication functions; composition of rules and defuzzification. Fuzzy logic Mamdani method can be used to predict the amount of national rice that must be produced. If it is known that the need is 21,908,784 tons of rice and the supply is 65,457,456 tons, the amount of national rice that must be produced is 14,624,592 tons.
일본 고등학교 역사교육 변혁과 주제학습 강화

This paper compared the 2009 edition and the 2018 edition of Japanese high school course of study, and analyzed the reinforcement of theme-based learning in Geography and History and the change in history education thereof. The results of analysis are as follows;First, instead of abolishing the four history subjects (World History A·B, Japanese History A·B) of the 2009 edition of the high school Geography and History, the required subject, Modern and Contemporary History, and optional subjects, Advanced Japanese History and Advanced World History, were newly established. These three subjects introduce the content composition and learning method with theme-based learning as the key element.Second, while the 2009 edition described the purpose of theme-based learning as cultivating historical thinking skills as before, the 2018 edition reflects the nature of the competence-based curriculum and presents the qualities and abilities (knowledge and skills, thinking skills, judgment, expressive power, etc.) to be fostered in history subjects.Third, from the perspective of content composition, the 2009 edition relates to theme-based learning on the premise of syntactic composition as before, but the 2018 version shows a switch to a new composition that relates the entire content centering on theme-based learning, instead of syntactic composition.Fourth, in the 2009 edition, the learning method was systematized to improve learning ability and learner''s subjectivity step by step, while considering the characteristics of each subject, which was passed on to the 2018 edition too. The biggest change in the 2018 edition was to develop a new type of learning activity, connecting content composition and learning methods focusing on theme-based learning. The major items of each subject were organized in the form of unit learning with theme-based learning as an important element. In addition, the 2018 edition connected major items so that students can develop independent learning activities step by step.Fifth, the prerequisites and tasks to settle theme-based learning in the schools are; ①improvement of history textbook composition system and description method, ②changeover from teacher’s fact-delivery class to course that promotes students'' independent learning and exploratory activities, ③providing various and abundant teaching materials, ④ implementation of teachers’ training to develop skills necessary for new types of class, etc.
THE EFFECTIVENESS OF CO-OP CO-OP & MAKE A MATCH COMBINATION MODELS IN ONLINE LEARNING

Combining Cooperation-Cooperative (Co-op Co-op) and Make a Match model can stimulate students to be active in online learning. Students were able to construct their knowledge independently by using the Co-op Co-op model. Learning atmosphere became attractive with finding the partner games during the class used the Make a Match model. This combination model made students more active and did not quickly feel bored. This research aimed to know the effectiveness of the Co-op Co-op and Make a Match model in online learning for based competency in operating survey tools and mapping to improve students’ achievement. The current research used quasi-experiment research. The experiment class consists of 35 ten grade students of Building Information Modeling (DPIB) one, while the control class consists of 36 ten grade students of Building Information Modeling (DPIB) two. Pre-test and post-test were given by using Google form to both groups. The average score of N-Gain achieved 75,9%, which means the implementation learning model was effective to advance students’ achievement. Independent sample T-test got T count = 4,59 > T. It can be said there was a significant difference in average score between experiment and control group. Furthermore, the students’ interest questionnaire achieved 84,5. In conclusion, Co-op Co-op and Make a Match model in online learning by using supporting tools (Google Meet, WhatApp group, etc.) not only effective to improve students’ achievement but also got positive responses from the participants. The teacher can use this combination model to improve students’ interest and achievement in online learning.
Tokenization of Unearned Revenue Under the Quantity Rule

We show some sufficient conditions for centralized cryptocurrencies to compete in tandem with traditional cash. To this end, from the asset side we assign to these new breed of IOU tokens the role of an American perpetual call option that is exercised (redeemed) for units of issuer's/producer's good. From the liability side, tokens play the role of advances backed by originator's collateral akin to trade finance banking products.
Object Analyzer for Visually Impaired People

New technologies are rapidly changing how many of us live our lives. Advances in connectivity are allowing us to access and transmit information faster than ever before. Changing how consumers interact with businesses and service providers Although new technologies are undoubtedly changing our commercial interactions, the application and proliferation of new technologies like Artificial Intelligence (AI) are having a much broader and positive impact on society. However, much of the focus on Artificial Intelligence (AI) has been on how its commercialization will impact the global labor force The proposed project is intended to detect the object in front of the visually impaired person, give out information regarding the object in front of them with the help of machine learning and neural network.
Fossil Texture Mapping With Computeriation Techniques As A Tool In Paleontology With Pheomelanin Pigment Method

Fossils are a form of living things or microorganisms in the past that have been buried in the soil or water for millions of years, a method or branch of science is needed to identify these fossils which are commonly used to determine the nature and way of life of humans in the past to improve their life. In the future, the science  studies this field is called paleontology, which is a branch of the study of fossils and living things with the aim of extracting useful information useful in other fields such as geology, mining and marine. One of the important functions of paleontology is how we can reconstruct the size and type of living things based on data from bones obtained from excavations, the conventional way is that a palentologist will estimate the types of living things based on bone shape of the land area where the fossil is found, this will not be difficult if the fossils are found in intact conditions or excavated in the upper soil where the fossil conditions are generally clearly visible, but this is very different if the fossils found in damaged condition aren’t intact or in petrified conditions making it difficult to in identification, so that estimates of the type of fossil plants or living things unidentify to read, the researchers previously tried to combine fossil reading and mapping techniques with the help of computer vision techniques, where an identification process is a computer capable of estimating and reading the type of fossil and displaying it in a visual form, the form shown is usually the blood flow of the connective tissue and the hair or hair of the animal, technology has a high accuracy and by reading a network of pigment or melanin in these animals, the melanin color in the fossil becomes a reference where the fossil lived and the type of carnivore or herbivore, this melanin color serves as an additional tool so that a pelentologist can use it as a recommendation tool to identify and read an object correctly with predictability and high accuracy
ABC: Efficient Selection of Machine Learning Configuration on Large Dataset

A machine learning configuration refers to a combination of preprocessor, learner, and hyperparameters. Given a set of configurations and a large dataset randomly split into training and testing set, we study how to efficiently select the best configuration with approximately the highest testing accuracy when trained from the training set. To guarantee small accuracy loss, we develop a solution using confidence interval (CI)-based progressive sampling and pruning strategy. Compared to using full data to find the exact best configuration, our solution achieves more than two orders of magnitude speedup, while the returned top configuration has identical or close test accuracy.
4-Uniform Permutations with Null Nonlinearity.

We consider n-bit permutations with differential uniformity of 4 and null nonlinearity. We first show that the inverses of Gold functions have the interesting property that one component can be replaced by a linear function such that it still remains a permutation. This directly yields a construction of 4-uniform permutations with trivial nonlinearity in odd dimension. We further show their existence for all n = 3 and n ≥ 5 based on a construction in Alsalami (Cryptogr. Commun. 10(4): 611–628, 2018). In this context, we also show that 4-uniform 2-1 functions obtained from admissible sequences, as defined by Idrisova in (Cryptogr. Commun. 11(1): 21–39, 2019), exist in every dimension n = 3 and n ≥ 5. Such functions fulfill some necessary properties for being subfunctions of APN permutations. Finally, we use the 4-uniform permutations with null nonlinearity to construct some 4-uniform 2-1 functions from $\mathbb {F}_{2}^{n}$ to $\mathbb {F}_{2}^{n-1}$ which are not obtained from admissible sequences. This disproves a conjecture raised by Idrisova.
A Study on the Impact of Holding Period on BHAR(CAR) in IPO Process: Focus on Business Relationship

Purpose - The purpose of this paper is to examine the impact of holding period of IPOs on BHAR(CAR) of IPOs in IPO process, especially focused on business relationship of underwriters and institutional investors. Design/methodology/approach - This paper collected monthly IPO fund data in KOSDAQ during 2004 to 2012 and OLS(Ordinary Least Square) was hired to analyze the data. Findings - Underwriters do allocate IPOs with high BHAR(CAR) to business-related institutional investors holding IPOs longer to make the price of IPOs stable (market-making) for underewriters. Research implications or Originality - This paper finds the impact of holding period of IPOs on BHAR(CAR) of IPOs in IPO process, especially focused on business relationship of underwriters and institutional investors in Korea.
Coronavirus scams: A look at schemes busted by the FBI

By March 30, the FBI's Internet Crime Complaint Center had received more than 1,200 reports of COVID-19 scams.
PERANCANGAN SISTEM INFORMASI AKUNTANSI PENJUALAN BERBASIS WEB PADA SAIIOPROJECT JAMBI

SAIIOPROJECT Jambi is one of the businesses engaged in the sale of goods and services in the world of photography. Management in the sale of goods and services in this business is still done manually so that the performance in the process of selling goods is still not optimal. In order for optimal management to use a sales information system. This research was conducted in the sales of goods, this information system uses the calculation of COGS (Cost of Goods Sold). The approach method used by the author is data collection, interviews, observation and reference studies and designing a system based on the results of the research conducted. The development of this sales information system uses a waterfall model and the data flow model used is DFD (Data Flow Diagram). Programming language using PHP, Notepad ++ and HTML. This research produces a sales information system that can be implemented in the SAIIOPROJECT Jambi business
Patriots made 'mistake' letting Tom Brady go, Joe Montana says

Brady, 42, signed with the Tampa Bay Buccaneers earlier this month after 20 seasons with the Patriots.
Holographic calibration setup based on a set of reference kits comprising axial computer-generated holograms and base test plates

A solution for the relevant metrological issue of the control and calibration of contact and contactless measurement equipment used in modern optical manufacturing is proposed. It is based on using a reference kit comprising an axial computer-generated hologram and a pair of spherical test plates with extremely high matching.
Faster Kernel Interpolation for Gaussian Processes

A key challenge in scaling Gaussian Process (GP) regression to massive datasets is that exact inference requires computation with a dense n x n kernel matrix, where n is the number of data points. Significant work focuses on approximating the kernel matrix via interpolation using a smaller set of m inducing points. Structured kernel interpolation (SKI) is among the most scalable methods: by placing inducing points on a dense grid and using structured matrix algebra, SKI achieves per-iteration time of O(n + m log m) for approximate inference. This linear scaling in n enables inference for very large data sets; however the cost is per-iteration, which remains a limitation for extremely large n. We show that the SKI per-iteration time can be reduced to O(m log m) after a single O(n) time precomputation step by reframing SKI as solving a natural Bayesian linear regression problem with a fixed set of m compact basis functions. With per-iteration complexity independent of the dataset size n for a fixed grid, our method scales to truly massive data sets. We demonstrate speedups in practice for a wide range of m and n and apply the method to GP inference on a three-dimensional weather radar dataset with over 100 million points.
Image Co-saliency Detection and Co-segmentation from The Perspective of Commonalities

Image co-saliency detection and image co-segmentation aim to identify the common salient objects and extract them in a group of images.Image co-saliency detection and image co-segmentation are important for many content-based applications such as image retrieval, image editing, and content aware image/video compression. The image co-saliency detection and image co-segmentation are very close works. The most important part in these two works is the definition of the commonality of the common objects. Usually, common objects share similar low-level features, such as appearances, including colours, textures shapes, etc. as well as the high-level semantic features.In this thesis, we explore the commonalities of the common objects in a group of images from low-level features and high-level features, and the way to achieve the commonalities and finally segment the common objects. Three main works are introduced, including an image co-saliency detection model and two image co-segmentation methods.𝗙𝗶𝗿𝘀𝘁𝗹𝘆, an image co-saliency detection model based on region-level fusion and pixel-level refinement is proposed. The commonalities between the common objects are defined by the appearance similarities on the regions from all the images. It discovers the regions that are salient in each individual image as well as salient in the whole image group. Extensive experiments on two benchmark datasets demonstrate that the proposed co-saliency model consistently outperforms the state-of-the-art co-saliency models in both subjective and objective evaluation.𝗦𝗲𝗰𝗼𝗻𝗱𝗹𝘆, an unsupervised images co-segmentation method via guidance of simple images is proposed. The commonalities are still defined by hand-crafted features on regions, colours and textures, but not calculated among regions from all the images. It takes advantages of the reliability of simple images, and successfully improves the performance. The experiments on the dataset demonstrate the outperformance and robustness of the proposed method.𝗧𝗵𝗶𝗿𝗱𝗹𝘆, a learned image co-segmentation model based on convolutional neural network with multi-scale feature fusion is proposed. The commonalities between objects are not defined by handcraft features but learned from the training data. When training a neural network with multiple input images simultaneously, the resource cost will increase rapidly with the inputs. To reduce the resource cost, reduced input size, less downsampling and dilation convolution are adopted in the proposed model. Experimental results on the public dataset demonstrate that the proposed model achieves a comparable performance to the state-of-the-art methods while the network has successfully gotten simplified and the resources cost is reduced.
PENYUSUNAN FORMULIR NASABAH, SLIP SETORAN TABUNGAN, DAN BUKU TABUNGAN (BUMDes)

The program for preparing customer registration forms, deposit slips, and passbooks at BUMDes is needed to add programs available on BUMDes for the progress of the BUMDes themselves. The purpose of the customer registration form itself is clear, namely for recording the identity of prospective customers in a file tailored to the identity given by the customer to the BUMDes management. The purpose of the Passbook is a note or record of incoming and outgoing funds, along with interest in each transaction in writing and witnessed by customers and management of BUMDes. The deposit slip as a note in the form of two copies, the purpose of this two-fold note is also proof that the customer has deposited the funds to the BUMDes management, so the first slip is given to the customer and the other is given to the BUMDes management as an archive. This program hopes to be able to help the community in depositing funds, which is more precisely the program.
SVA Library Research Guides: Online Resources and Services: Streaming Video

The following guide outlines the collections, services, and support available remotely to students, faculty, and staff.
Virtual Healthcare Assistant

This research is aimed to design an hyperintelligent healthcare assistant possessing artificial intelligence whose ability is to grasp conversations using NLU models which have been set up with medical colloquial. After training this assistant on medical phraseology data, it is be able to analyze discourses amid a physician and a sick person (after his permission) so that it can write out, recapitulate the colloquial as marginalia for mentioning after-time, and systematic draft reports are produced indeed (probably takes hours to produce manually), automatically cue physicians with simplifying interrogations at the time of documentation, Inquires simplifying interrogations in peculiar circumstances, like, likelihood of dissimilar diagnosis or a dissimilar specimen of medical advice that the physician should acknowledge, thus, decrease the manual chore of healthcare work force saving time which can be devoted to take care of sick people.
Analysis of Determinants of Private Investment in Ethiopia

To make private investment more attractive, most African countries have liberalized market and attempted to create enabling environment in recent decades. Ethiopia, like many African countries, took some steps towards liberalizing market and the macroeconomic regime as well as introducing some measures aimed at improving the investment regulatory framework. This study analyses the determinants of private investment in Ethiopia using a time series analysis over the period of 1975 to 2009.The study gave an extensive account of the theoretical explanation of private investment as well as reviewing the policy regimes, the investment regulatory framework and institutional set up in the country over the study period. It also undertakes empirical analysis to establish the determining factors of private investment in Ethiopia. Our findings show that growth rate of real GDP, availability of credit, and public investment among others, have positive impact on private investment. On the other hand, macroeconomic instability (liberalization), lending rate, and consumer price index (CPI) have negative impact on private investment. The results suggest that policies that address only some components of macroeconomic instability may not be enough to revive private investment. Thus, the findings imply that liberalization of the market and regulatory regimes, stable macroeconomic and political environment, and major improvements in infrastructure are essential to attract private investors to Ethiopia. DOI: 10.7176/JESD/12-7-03 Publication date: April 30 th 2021
LibGuides: DVDs in Education, Music and Media: Documentary Films on DVD

Tips for searching for DVDs, and lists of special interest DVDs Search tips and lists of non-fiction DVDs in Education, Music and Media
Trump to review Oracle-TikTok deal Thursday, reiterates security is paramount

President Trump said that he will review the deal between Oracle and Chinese-owned video app TikTok on Thursday and it “has to be 100 percent” safe from a national security standpoint for him to sign off on it.