Reviewerly/exHarmony huggingface dataset:
A Systematic Technical Survey of Lightweight Cryptography on IoT Environment

The world becomes a small village due to the connecting heterogeneous devices such as RFID, smart devices, sensors. Systems such as the system of large industrial companies, private spaces, and public utilities are connected via the internet of things (IoT) to be embedded systems linking the world. In general, this process requires transferring data and storing them in different devices. Therefore, data cryptography is considered the main concern during transmission. The increasing number of interconnected systems will be very large, requiring strong cryptographic among different devices. Yet, these devices have limited resources in size and cost. These restrictions are not available in traditional cryptography but there is a new trend for cryptographic called lightweight cryptography (LWC) which plays a vital role in security IoT environment. Hence, the current paper presents a comprehensive survey of LWC algorithms to provide a clear vision for future research to secure IoT environment by using LWC. The survey used in this paper aims at providing a clear classification and accurate definition of LWC algorithms (symmetric-key)along with comparison and performance analysis of LWC algorithms (block cipher and hash function) based on such important features such as latency, area, throughput, and power and energy consumption.
Crypto assets: the role of ICO tokens within a well-diversified portfolio

This paper re-examines the discussion on blockchain technology, crypto assets and ICOs providing also evidence that in crypto markets there are currently two classes of assets, namely standalone cryptocurrencies (or 'coins') and tokens which result from an ICO and are intrisically linked to the performance of the issuing company or venture. While the former have been arguments of various empirical studies regarding their price dynamics and their effect on the variance of a well-diversified portfolio, no such study has been done to analyze listed tokens, which in our sample are over 700 and with a backing of about §17.3Bn from their respective ICOs. Therefore, investors interested in optimizing their portfolios should first assess the diversifier, hedge or safe haven role of tokens vis-a-vis traditional assets, on top of 'coins' in order to sensibly use this new asset class. After constructing various indices to represent both the token asset class as a whole and its sub-classes, we model dynamic conditional correlations among all the assets in our sample to obtain time-varying correlations for each token-asset pair. We find that tokens are effective diversifiers but not a hedge or a safe haven asset. We evidence that tokens retain important systematic differences with the two other asset classes to which they are most generally compared to, namely 'coins' and equities
Applying of quick on the draw strategy to improve students' skill in writing descriptive text at SMA IT Indah Medan at 10TH grade academic year 2019/2020

This study discusses about increasing empirical evidence of students' ability to write descriptive texts by using a quick a strategy for grade X students of SMA IT INDAH Medan.the subjects who used in this researh was the student from X Grade SMA IT Indah Medan 2019/2020. This research was used Classroom Action Research (CAR) method which consists of in two cycles. Instruments for agreeing on data were interviews, observations and diaries, and for qualitative data using written tests. Quantitative data is taken from pre-test and post-test. Based on qualitative data, the use of quick on the draw strategy in writing texts can enhance and encourage students in learning. Based on the results of student scores, the average score of students continues to increase in each test. The average student score in the pre-test was 51.74 with two students or 8.70% achieving the Minimum Graduation Score or KKM (75). Post-test results in the first cycle, the average value of students is 70.09 with 12 students or 52.17% graduated from KKM. Post-test results in cycle 2, the average value of students is 81.78 with 19 students or 82.60% passed the KKM. Resolved it Quick on the Draw in writing descriptive text as a grading strategy can improve students' ability to write descriptive text.i
Digital Platforms and the Rise of Global Regulation of Hate Speech

The EU Code of Conduct on hate speech requires online platforms to set standards to regulate the blocking or removal of undesirable content. The standards chosen can be analysed for four variables: the scope of protection, the form of speech, the nature of harm and the likelihood of harm. Comparing the platforms’ terms of use against existing legal standards for hate speech reveals that the scope of speech that may be removed increases significantly under the Code’s mechanism. Therefore, it is legitimate to consider the platforms as substantive regulators of speech. However, the Code is only the latest example in a global trend of platforms’ activities affecting both the substantive regulation of speech and its governance. Meanwhile, states’ authority to set standards of acceptable speech wanes.
Prediction of Technology Trend of Educational Robot Industry Based on Patent Map Analysis

This paper starts with the research of the education robot industry, conducts a detailed investigation, analysis and summary from the theory, analysis method and application of education robot, patent map research at home and abroad and other aspects. By collecting relevant patents of educational robots at home and abroad, the research status of educational robots is understood. Apply the research of patent map to the education robot technology, modify and supplement the existing patent map appropriately, dig the related patent literature of education robot deeply, draw the detailed patent map of education robot at home and abroad, and analyze it. This paper summarizes the research on hot technology of educational robot, explores the key technology of educational robot, and predicts the life cycle of key technology, so as to predict the key technology and hot technology of educational robot.
Proof Automation in the Theory of Finite Sets and Finite Set Relation Algebra

{log} ('setlog') is a satisfiability solver for formulas of the theory of finite sets and finite set relation algebra (FSTRA). As such, it can be used as an automated theorem prover (ATP) for this theory. {log} is able to automatically prove a number of FSTRA theorems, but not all of them. Nevertheless, we have observed that many theorems that {log} cannot automatically prove can be divided into a few subgoals automatically dischargeable by {log}. The purpose of this work is to present a prototype interactive theorem prover (ITP), called {log}-ITP, providing evidence that a proper integration of {log} into world-class ITP's can deliver a great deal of proof automation concerning FSTRA. An empirical evaluation based on 210 theorems from the TPTP and Coq's SSReflect libraries shows a noticeable reduction in the size and complexity of the proofs with respect to Coq.
Quantitative Analysis of Static Load Balancing Algorithms in Cloud Computing Environment

Cloud computing is an emerging internet-based technology emphasizing commercial computing. Cloud is a platform providing dynamic pool of resources and virtualization. It is based on pay-as-u-go model. The reliability of clouds depends on the way it handle loads, to overcome such problems clouds must be featured with the load balancing mechanism. Load balancing is required as we do not want one centralized server’s performance to be degraded. Load balancing is categorized to be either static or dynamic. The main purpose of this paper is to implement and compare the round robin, randomized, central manager and threshold static load balancing algorithms through the simulation environment provided by the cloud analyst simulator
Slovenian RoBERTa contextual embeddings model: SloBERTa 1.0

The monolingual Slovene RoBERTa (A Robustly Optimized Bidirectional Encoder Representations from Transformers) model is a state-of-the-art model representing words/tokens as contextually dependent word embeddings, used for various NLP tasks. Word embeddings can be extracted for every word occurrence and then used in training a model for an end task, but typically the whole RoBERTa model is fine-tuned end-to-end.SloBERTa model is closely related to French Camembert model https://camembert-model.fr/. The corpora used for training the model have 3.47 billion tokens in total. The subword vocabulary contains 32,000 tokens. The scripts and programs used for data preparation and training the model are available on https://github.com/clarinsi/Slovene-BERT-ToolThe released model here is a pytorch neural network model, intended for usage with the transformers library https://github.com/huggingface/transformers.
Review on the Organization of ‘Independence Movement History’ in “Korean History” by 2015 Revised Curriculum

“Korean History” by the 2015 National Curriculum has organized the Independence Movement showing the following features. Firstly, it has divided the ‘Japanese colonial era’ into three, to comprehend the Japanese colonial policy and the Korean people’s nationwide movement in connection with international situations thereabout. Moreover, it identified the independence movement continuously from the 1910s to the post-liberation period and presented changes in the independence movement over time. It’s emphasis on social movement is greatly noticeable. We find it meaningful to observe the country Koreans were trying to establish. Accordingly, the activities of Koreans in the 1920s and 1930s, which had been covered as national movements in one, were re-classified into national activities and social movements.<BR> There were many inquiry activites on ‘Japanese colonial era’ which to evaluate the historical significance of various national activities and also to identify the importance of social movements as well. Through these activities, it seems that they wanted to understand the independence movement in various ways and promote critical thinking.
The Serial Cohort: A Confederacy of Catalogers

In 2018, at a time when Duke University Libraries’ Technical Services department was shrinking through attrition, the decision was made to further leverage the particular skill sets of a select group of monographic catalogers by training them to also undertake the complex copy cataloging of serials. In this presentation, the author shared the assumptions underlying how this decision was originally made, the initial plan for how this would be accomplished by studying the Cooperative Online Serials Program training materials and the eventual formation of the Serial Cohort with a view to creating an iterative process the author would design and manage. The presentation included problems, obstacles, and time constraints faced and addressed in the creation process.
Penerapan osborn’s learning model untuk meningkatkan kemampuan menulis deskripsi peserta didik kelas iv sekolah dasar

This research is a CAR (Classroom Action Research) or better known as Classroom Action Research (CAR) which is carried out to find out how the Osborn learning model can be used to improve students' ability to write descriptions. This class action research consisted of cycle III. Each cycle is carried out in 2 x meetings with 2 x 35 minutes in every 1 meeting. This research uses four stages: planning, implementing, observing and reflecting. The completeness criteria set is 70% of all students exceeding KKM 72. The purpose of this research was to determine the improvement in writing description skills by applying the Osborn learning model to grade IV students of SD Negeri Tunggulsari I, Laweyan Subdistrict, Surakarta City. The subjects in this research were the students of Class IV Tunggulsari 1 Elementary School as many as 24 students as well as the fourth grade teachers of SD Negeri Tunggulsari 1. This research was conducted at Tunggulsari I Elementary School in November 2019. Data collection techniques were taken from observation, tests and documentation. This research was conducted at Tunggulsari I Elementary School in November 2019. Data collection techniques were taken from observation, tests and documentation. The results showed that the grades of grade IV students of SD Negeri Tunggulsari I in writing descriptions through the Osborn learning model had achieved KKM completeness 72. The conclusion of this study is to use Osborn's learning model in writing descriptions increased with the percentage of pre-action completeness of 8.33% increased to 33.33% in the first cycle, in the second cycle also increased to 70.83% and again increased to 83.33 % in cycle III. the contribution of research to the world of education is to provide an innovation in terms of learning models that can be applied to overcome one of the problems namely the problem of writing descriptions.
Using of Exact Queries and Expansion Queries in Searching for Indonesian Translated Al-Quran Verses

This paper presents a search technique for translating verses in the Al-Quran into Indonesian by developing a query expansion of the hot themes currently being discussed in social media. The hope of finding information in the verses of the Koran is very high as a step to respond and find a holistic religious perspective on the theme being discussed. The method of searching for verses using Indonesian translations is still deemed inadequate. The availability of dictionaries and indexes for the Indonesian translation of the Al-Quran is still very little, most of the verse search indexes use the Arabic book language including the very popular ones are Al-Mu'jam al-Mufahras lialfazhi Al-Qur'an and Fathurrahman li Thalibi Ayatil Qur'an. Researchers have carried out many studies to make certain techniques in searching to find related words in the Al-Quran, including from exact matching, matching according to major themes in the Koran (topic matching), matching with synonyms and a search for explanatory books (tafsir matching). This is done to find relevant verses and provide comprehensive information on the search terms. This research was conducted on 11 random keywords to the entire translation of the Al-Quran and the query results were tested based on the Al-Quran Index Book How to Find Al-Quran Verses compiled by N.A. Baiquni. HE. S Compoundqi, and R.A. Azis. The results of this study indicate that the use of query expansion gets a value of 44% and the exact query gets a value of 33% to find related themes, however the use of query expansion is better than the use of exact queries in the search for the translation of the Indonesian Al-Quran.
Leafy automata for higher-order concurrency

Finitary Idealized Concurrent Algol (FICA) is a prototypical programming language combining functional, imperative, and concurrent computation. There exists a fully abstract game model of FICA, which in principle can be used to prove equivalence and safety of FICA programs. Unfortunately, the problems are undecidable for the whole language, and only very rudimentary decidable sub-languages are known. We propose leafy automata as a dedicated automata-theoretic formalism for representing the game semantics of FICA. The automata use an infinite alphabet with a tree structure. We show that the game semantics of any FICA term can be represented by traces of a leafy automaton. Conversely, the traces of any leafy automaton can be represented by a FICA term. Because of the close match with FICA, we view leafy automata as a promising starting point for finding decidable subclasses of the language and, more generally, to provide a new perspective on models of higher-order concurrent computation. Moreover, we identify a fragment of FICA that is amenable to verification by translation into a particular class of leafy automata. Using a locality property of the latter class, where communication between levels is restricted and every other level is bounded, we show that their emptiness problem is decidable by reduction to Petri net reachability.
The classification and propagation of program comments

Natural language comments are like bridges between human logic and software semantics. Developers use comments to describe the function, implementation, and property of code snippets. This kind of connections contains rich information, like the potential types of a variable and the pre-condition of a method, among other things. In this paper, we categorize comments and use natural language processing techniques to extract information from them. Based on the semantics of programming languages, different rules are built for each comment category to systematically propagate comments among code entities. Then we use the propagated comments to check the code usage and comments consistency. Our demo system finds 37 bugs in real-world projects, 30 of which have been confirmed by the developers. Except for bugs in the code, we also find 304 pieces of defected comments. The 12 of them are misleading and 292 of them are not correct. Moreover, among the 41573 pieces of comments we propagate, 87 comments are for private native methods which had neither code nor comments. We also conduct a user study where we find that propagated comments are as good as human-written comments in three dimensions of consistency, naturalness, and meaningfulness.
ANALISIS SENTIMEN LAYANAN AKADEMIK MENGGUNAKAN METODE NAÏVE BAYES CLASSIFIER PADA KOMENTAR MAHASISWA

Sentiment analysis is the process of classifying comments and in this study is divided into three parts, namely positive, negative and neutral classes. Classification is very important to know student satisfaction with lecturer performance. Comment data can be obtained from the Janabadra University Quality Assurance Agency website.The Naive Bayes Classifier method is a method based on bayesin's probability and theorem. This method is used to classify the results of student comment data written on the student satisfaction form towards the lecturer so as to produce the desired automatic classification.The results of this study are used to determine the classification of student comment data so that the performance of lecturers can be easily identified from the comments given by students. The Analysis Sentiment results contained emotion category consisting of Unknown 1935, Joy 31 and Sadness 3. While the Polarity Analysis results from the comments of Janabadra University students consisted of negative values 23 and positive 1999. Keywords : Student Comments, Naive Bayes Classifier Method, Sentiment Analysis.
ANALISIS KOMPOSISI FOTO PADA LANDSCAPE PHOTOGRAPHY

Abstract:Photo composition is the arrangement of elements in the image. These elements include lines, shapes, colors, light. Photo compositions are used by photographers to express feelings into photos. The compositions discussed are Rule of Third, Symmetry, Framing, Perspective, Fill The Frame photo compositions. Landscape photography is a method or process of producing images or photos with a set landscape. The method used is to make observations on several photos samples to find out what photo compositions are produced on the photo. And the results obtained are in a photo there are different photo compositions depending on the choice of the photographer to create interesting and unique photos.
Lacey police seeking public's help identifying suspects in high school break-ins

It's already difficult enough right now for kids to learn without thieves stealing the electronics they will need. And now Lacey police are trying to solve a rash of burglaries at River Ridge High School.
A Brief Analysis of the Role of Chinese Culture in English Phonetics Teaching in Higher Vocational Colleges

The Chinese national culture has a long history, and the traditional culture is the essence of it, which is also the cultural content that our students must master. Combined with the situation of higher vocational teaching, this paper points out the role of Chinese culture in teaching in detail, and puts forward the implementation path of culture infiltrating into higher vocational English phonetics teaching, which mainly includes deepening the teaching reform, creating a learning environment, changing teaching concepts, and improving teaching methods, aiming to provide an effective reference for the development of higher vocational English teaching.
MODERATION AS A WAY TO EFFECTIVELY CONDUCT EVENTS: METHODICAL ASPECT

The article discusses moderation, which is used for organizing and conducting various events, including internal meetings and working meetings; business meetings and negotiations; consultations for clients and partners, as well as training events. The main factors determining the need to involve a moderator in various events are identified. A step-by-step procedure for preparing and conducting the event is presented, which covers all stages from the organization to making decisions or recommendations. The features of conducting educational and online events using the moderation method are highlighted. The results of the research on this issue are summarized.
Probability hypothesis density filter for adjacent multi-target tracking

In the adjacent multi-target scenario, the Gaussian mixture probability hypothesis density (GM-PHD) algorithm encounters problems of inaccurate target number estimation and low tracking accuracy. To tackle these problems, this paper proposes an improved components management strategy for GM-PHD algorithm. We develop a master-slave mode to process Gaussian components, the master components whose weights exceed the extraction threshold are retained to avoid merging them each other, which guarantees the accuracy of target number estimation. Meanwhile, the slave components which satisfying the merging conditions are merged with the corresponding master components to improve the target tracking accuracy. Simulation results show that the proposed algorithm can achieve better performance than conventional GM-PHD algorithm in different clutter environments.
An improved anti-occlusion FDSST algorithm with SSDA

Aiming at the occlusion problem in the target tracking algorithm FDSST (Fast Discriminative Scale Space Tracking), this paper designs an improved SSDA (Sequential Similarity Detection Algorithms)-based FDSST anti-occlusion algorithm. The algorithm mainly improves the model update strategy of FDSST, the main processes are as follows: Firstly, judge whether the target has occlusion according to the oscillation degree of the correlation filter response graph; then, when there is occlusion, the SSDA algorithm is applied to re-detect the target according to the search strategy, to restore the occluded target and re-track the target. Our method was transplanted to onboard Jetson TX2, and the actual test was carried out on the public dataset OTB50 and the aerial video dataset respectively. The experimental results show that the proposed algorithm retains the advantages of FDSST and improves its anti-occlusion ability effectively.
Syntactic Complexity of Learning Content in Italian for COVID-19 Frontline Responders: A Study on WHO’s Emergency Learning Platform

The goal of this paper is to offer a model to quantify the level of complexity of the linguistic content of a corpus in Italian extracted from OpenWHO, WHO’s health emergency learning platform (Rohloff et al. 2018; Zhao et al. 2019). The nature of the computational ranking costs of a typology of relativization strategies is investigated. To reach this goal, the results of the corpus are compared with other three syntactic annotated corpora from Italian belonging to different genres (news, social media, encyclopedic entries, legal). The results show that online learning contents in public health reduce complex structures in syntactic terms. The case study presented here provides a methodology to quantify syntactic and computational complexity in corpus studies.