Reviewerly/exHarmony huggingface dataset:
An Evaluation of the Layers of a Deep Network on the Optical Character Recognition Problem

Various layers of Convolutional Neural Networks, one of the most common methods of deep learning, have been examined by many researchers, and methods that will increase performance and reduce the complexity of computing have been proposed in classification using this architecture. In this paper, we investigate, over the Optical Character Recognition problem, which layers does the deep architecture owe its high performance in classification. For this purpose, we evaluated the effectiveness of the first layers of deep architecture by classifying the features extracted from deep architecture with a Support Vector Machine. Then, we evaluated the effects of these methods in classification by applying the Fully Connected Layer and Global Average Pooling Layer methods in the last layers of the deep neural network. Experiments pointed out that the deep network owes its performance to all of its layers, but alternative solutions on the upper layers of the architecture can reduce the computational complexity without a significant change in the performance..
Dynamic Cantor Derivative Logic

Topological semantics for modal logic based on the Cantor derivative operator gives rise to derivative logics, also referred to as $d$-logics. Unlike logics based on the topological closure operator, $d$-logics have not previously been studied in the framework of dynamical systems, which are pairs $(X,f)$ consisting of a topological space $X$ equipped with a continuous function $f\colon X\to X$. We introduce the logics $\bf{wK4C}$, $\bf{K4C}$ and $\bf{GLC}$ and show that they all have the finite Kripke model property and are sound and complete with respect to the $d$-semantics in this dynamical setting. In particular, we prove that $\bf{wK4C}$ is the $d$-logic of all dynamic topological systems, $\bf{K4C}$ is the $d$-logic of all $T_D$ dynamic topological systems, and $\bf{GLC}$ is the $d$-logic of all dynamic topological systems based on a scattered space. We also prove a general result for the case where $f$ is a homeomorphism, which in particular yields soundness and completeness for the corresponding systems $\bf{wK4H}$, $\bf{K4H}$ and $\bf{GLH}$. The main contribution of this work is the foundation of a general proof method for finite model property and completeness of dynamic topological $d$-logics. Furthermore, our result for $\bf{GLC}$ constitutes the first step towards a proof of completeness for the trimodal topo-temporal language with respect to a finite axiomatisation -- something known to be impossible over the class of all spaces.
Forest Tree Algorithm- An Efficient Approach of Data Mining Over Decision Tree

Mining of Data (DM) is a way to display different models, summaries and values derived from a given data collected. The DM itself works in the process of searching for analytical information on the large number of available databases. An example of a predictive enigma is targeted marketing. There are many factors that affect data mining performance in large data sets. In this article we will use the forest tree technique to improve performance in search for data and implementation, surely overcome the previous work performance that includes the approach of the existing tree decision tree algorithm.
An effective classification technique for XML documents using hyper parameter optimized classifiers

In real world XML data plays a significant role in the application of World Wide Web. Now a days, in research   the data classification in XML document for heterogeneous structure proves to be a challenging task. A number of algorithms are available in XML data classification process. In the existing technique the performance is degraded in the classification process of XML document. In this paper the machine learning technique TSRSA (Tuning Swarm Rapid Swarm Algorithm) is proposed to classify the XML data. First, the elements are extracted by using kernel vector space model. Second, we classify the XML data using the algorithm of TSRSA optimization technique. TSRSO is using hyper parameters to obtain the better classifier. The experiments are demonstrated in the existing technique ELM (Extreme Machine Learning), Standard algorithms (SVM Support Vector Machine, DT-Decision Tree, NB-Navie Bayes, and KNN-K Nearest Neighbor), KPCA-Kernel Principal Component Analysis and KELM Kernel Extreme Machine. In this research the proposed TSRSA algorithms are compared with the existing technique. The various performance parameters are compared with reference to the existing and the proposed model.
Analysis of Linguistic and Written Errors of Arabic Language Learners in Iranian Universities (A Case Study of MA Theses Submitted to Tarbiat Modares University in Field of Arabic language Teaching)

Writing skill is one of the language skills in teaching Arabic in Iranian Universities. Some courses are dedicated to teaching this skill in Arabic. Nevertheless, students still face problems in writing in Arabic and experience linguistic and written errors at various educational levels. Therefore, in the present study, the authors tried to analyze linguistic and writing errors of 20 MA theses submitted to the Department of Arabic Language Teaching Tarbiat Modares University. The study was conducted to provide solutions for reforming the Arabic teaching curriculum, especially the writing skill in Iran, and reducing errors of students in the future. The descriptive-analytical and error analysis methods and statistical analyses were used. The results showed that the linguistic errors in these theses were 1005 errors. Syntactic errors were the most common language errors, and the errors related to the additional words (prepositions) were mostly grammatical. Other common errors were spelling errors, errors related to the humazat, alqate morphological errors, errors related to the detection of definite (marefah) from indefinite (nakarah), semantic errors, and the use of non-functional words and phrases in the Arabic language. Then, the interpretation of the errors revealed the traces of interlingual interference. Some of the most important causes for making errors by students in their theses were Arabic language teaching methods, educational environment, Arabic language difficulties and rules, the indolence of students, and lacking sufficient knowledge about some language rules.
Semantic Textual Similarity using Machine Learning and Conceptual Relatedness

Large amount of data is available in today’s world which can’t be stored in physical devices. This data contains huge amount of redundant information which could be grouped together and categorized. We present a system which gives the degree of equivalence between two statements i.e. Semantic Textual Similarity (STS). Given two textual fragments, the goal of the system is to determine their semantic similarity i.e. how much are they similar in terms of their meaning. Our system makes use of four different measures of text similarity: 1. Word n-gram overlap. 2. Character n-gram overlap. 3. Se-mantic overlap. 4. Conceptual overlap. Using these measures as features, it trains a sup-port vector regression model on SemEval STS data. Evaluation is done using the Pearson Correlation Coefficient.
AN ANALYSIS OF STUDENTS’ ABILITY IN USING AUXILIARY VERB OF PASSIVE VOICE SENTENCES AT THIRD SEMESTER OF STKIP YPM

This research studies about the students’ ability in using auxiliary verb on passive voice sentences at the English Department students STKIP YPM. The purpose o f this research was to find out the students’ understanding in using auxiliary verb on passive voice sentences at the third semester STKIP YPM. This research was descriptive qualitative method. The population was 15 students at third semester on English Department STKIP YPM. They were selected as the sample by using total sampling technique. The data was collected by using writing test on passive voice sentences. The finding showed that students’ understanding in using auxiliary verb on passive voices sentences at third semester of English Education Program of STKIP YPM in academic year of 2015/2016 were good enough.
Deepening Interactive Processing of NLP on Application Side

Natural Language Processing (NLP) is a discipline that focuses on natural language understanding in the information interaction between human and computer, and plays an important role in the intelligent service field of Internet of Things. A complete policy transformation and generation system is developed, which can solve various functional requirements. Then, according to the functional requirements, the performance and using methods of various tools that can achieve the functional goals are analyzed. Taking IoT acquisition layer sensing devices as social network resources, an interactive IoT service framework based on natural language processing was designed, and an interactive platform of agricultural IoT for Weibo was developed, which realized the functions of data query, command setting and regular reporting between users and IoT devices in natural language. The end-to-end command control of the Internet of Things is realized, which proves the feasibility that the control strategy system of the Internet of Things can be applied to realize command control processing in the Internet of Things.
외국인 유학생 감염병 관리방안 : 부산시 소재 대학의 코로나19 대응을 중심으로

Background & Objectives: The purpose of this study is to present infectious diseases control and crisis response plans for International students by investigating the management of International students and prevention of infectious diseases targeting International students infectious disease control managers at universities in Busan in a situation where the risk of infectious diseases increases due to the spread of COVID-19. Methods: The data were collected from 14 International students infectious disease control managers at universities in Busan. Statistical analysis was done by using SPSS 22.0. Results: There were differences in the importance and performance of COVID-19 infectious disease control and support work by university. Conclusions: It is necessary to integrate management of support and roles of infectious diseases control for foreign students. Furthermore, strengthening the competence of experts and communication tools with international students are needed.
Community Information System A Tool In Social Media

Communication with a given cluster target system in social cultural atmosphere demand a means of information distribution with limited stress. Surfing the websites such as “My Space” and “Facebook” has become a prevalent phenomenon in the younger population. Nowadays, social network websites are the integral part of social, learning and working life for community (people with same goals, ideology. The implemented system is to be compiled into a single program from other units and finally tested as whole system. The work has modules. In each modules are require functions, it most return a value System testing is testing conducted on a complete integrated system to evaluate the system's compliance with its specified requirements. The Community Information System as a Social media platform is a graphical representation of members in a community in social network like twitter and Facebook. The community Information system collect user with common idea, market and recommendation. The system collected the products and price per units then automatically compute it and present the total cost of it to the customer.
Analisis Ujaran Kebencian dalam Bermedia Sosial: Kajian atas Semangat Perdamaian dalam Al-Quran

Hate speech has a negative effect on everyone. Social media plays a role in opening up space in expressing opinions in cyberspace. The development of technology with the opening of communication access seems to disturb the peace. The hope of a safe, peaceful and harmonious life is disturbed by the spread of hate speech. Al-Quran as a way of life is important to be re-presented in reducing hate speech and its negative effects. The purpose of this article is to analyze hate speech in social media and find the spirit of peace in the Koran. The method used is library. The results and discussion reveal that hate speech is spread in various ways and in various forms. Al-Quran forbids every individual to make hate speech and provide solutions by presenting the spirit of peace, namely: by speaking noble, full of courtesy and respect (qoulan karima), telling the truth or the truth (qoulan sadidan), and speaking weakly. soft (qoulan layyina).
The cost of immortality: A Time To Live for smart contracts

Smart contracts, scripts at the heart of blockchainbased applications, are meant to be available forever once deployed. However, this property has a price. The amount of space required to store new contracts keeps increasing. This increase impacts each participating node's performance and makes it inconvenient for low-end devices to participate in the network. Among all contracts deployed in the blockchain, a vast majority will lead to little if any usage. We demonstrate that, in the course of one year, 70% of deployed contracts lead to no use. Unfortunately, unused contracts keep occupying space on the blockchain. To tackle this issue, we propose a new protocol to identify and delete unused contracts. Through simulation, based on Ethereum historical data, we show that deletion of smart contracts after an inactivity period of 90 days could lead to a 66% reduction in the number of contracts stored over a year.
The use of seamless learning strategy on student vocabullary mastery

This study aims to see empirical evidence of the effect of unlimited learning on students’ vocabulary mastery. Researchers used experiments in class 1 MTs Darussalam Gapluk Purwosari Bojonegoro. It aims to increase students’ awareness by expanding their room from home and school to their everyday lives. Seamless learning allows for continuous learning experiences in a number of environments, such as school or home, while seamless learning is spread across multiple environments. Seamless learning is a flawless network where learning takes place anywhere and anytime. Some of the benefits of using a seamless approach include: 1) students can study classes and time without limits 2) students can study at any time, and anywhere 3) integrated learning between formal and non-formal education. Based on the outcome of the estimation of post-test, the average post-test score was 82.6667, while the pre-test average was 52000. This means that the average post-test is 52000. The score is higher than the pre-test.
Classification of the IDR-USD Exchange Rate with Multilayer Perceptron Based on Detection Rate

Artificial neural network (ANN) is a set of units in processing a model based on the habits of human neural networks. ANN has one of its duties, namely classification with the concept of supervised learning. ANN also has various methods in performing its duties such as Multilayer perceptron (MLP). Where MLP is one of the ANN methods that can classify based on data as conceptualized in data mining. Very useful classifications and trends in the field of research because of the review of data that will generate knowledge. Nominal Exchange Rate is one of the datasets tested in this study. The exchange rate of the Indonesian Rupiah (IDR) against the United States Dollar (USD) is very necessary both in terms of stock movements and other businesses. So that, it is necessary to use classification to predict future exchange rates. In this study, the MLP method was carried out by obtaining a validation test using MAPE based on the detection rate ofÂ sebesar 0.500079879%.
RANCANG BANGUN SISTEM INFORMASI PENJUALAN BERBASIS WEB PADA PT BILLINDO UTAMA

PT Billindo Utama is a company engaged in the sale of general supplier, marine, hardware, tools & equipments and was founded in 2010, located in tanjung uncang, riau island, batam. The problem being faced by Billindo Utama is the order system is still oflline so that it doesn’t make it easier for customer to make purchase, this COVID19 virus pandemic must follow health protocols and can reduce visiting customer, and there is no customer database systematically recapitulated in a systemized manner which can pose a risk of losing customer data. If Billindo Utama markets its products throught web e-commerce then the problems faced by Billindo Utama at this time will be solved. Based on the problems being faced by Billindo Utama the researchers will conduct research with aim of to find out how to design and implement a web-based sales information system at Billindo Utama. The method used in the research process is the SDLC waterfall model which consists of system analysis, system design, coding, and testing. The results of research on Billindo Utama is this e-commerce web can facilitate transactions, marketing, and all product information will be conveyed and it’s hoped that next system developer can add some features.Keywords: System, Information, E-Commerce, COVID19, Web
극지과학문화 확산을 위한 극지연구소 체험형 견학 프로그램 개발

The goal of this study is to develop a hands-on type polar field trip program to inform the importance of the recent polar research and to contribute to the spread of polar science culture. For this purpose, the direction of program development and field trip course were established based on the current Korea Polar Research Institute tour program and research exhibition facilities analysis. Based on this, a total of 6 types field trip programs were developed, including one basic tour program and one optional experience program for the overall introduction of polar research institutes and polar science fields, and four optional experience programs for each education participant that enables field trips and professional experiential learning activities by polar science field. The developed program was revised and supplemented through a total of two trials, and a field trip program manual was produced, including guidance scripts, experience kits, activity sites, and instructor guides for each field trip. At the end, a follow-up study was proposed based on the significance and research results of the developed program.
The Contemporary Distance Learning Industry in the Context of COVID-19

The article examines the state and trends in the development of distance learning in the world in conditions of covid-19, identifies the main specific difference between distance education and other forms of education, and analyzes the state of the world market of educational services via the Internet. The important features and characteristics of distance learning, examples of its organization in higher educational institutions, as well as statistics on the development of distance learning in the world are presented. The main problematic points on the way of introducing the distance education system in the context of a pandemic and the factors hindering the development of this promising form of education are identified. In addition, the article examines the psychological and pedagogical features of distance learning with the current conditions of the development of education at the university. The psychological characteristics of students and their learning difficulties have been determined. It also clarified the problems faced by teachers in the organization and implementation of distance learning. Practical recommendations for the support of distance learning for students have been developed.
Multilayer Holographic Perceptrons for All-optical Aberration Detection

We present aberration detectors based on multi-layered perceptrons printed by two-photon nanolithography. Through all-optical inference, the perceptrons can collect phase information from a point spread function performing direct aberration detection in a single step.
Design Of Automatic Cat Feeding Device Using Amazon Deeplens and Arduino Uno

Cats are one of the cutest animals that are human pets. The cat owner has needs that require him to leave his cat at home. The existence of AI camera technology that can learn to distinguish objects such as one of the products from amazon namely Amazon Deeplens, AI technology from Amazon Deeplens allows cat owners to create automatic cat feeders that can reduce the risk of cat stress. The approach method used in making this tool is the Research and Development (R&D) method. R&D is a research method used to produce and test the effectiveness of the product. Based on previous research, this pet feeder has become a good enough solution to give our cat comfort when we can’t feed directly.
Deadlock Preventıon Usıng Schedulabılıty In Vırtualızed Cloud Envıronment

Cloud computing is to provide a on demand IT resources/services like server, storage, database, networking, analytics, software etc. over internet. It provide a diversity  of  distributed computing  system, and it has a group of virtualized  and   inter-connected  systems  based on provider–stage agreements  between  the  consumers  and  service providers. Here, a computer architecture and algorithms were developed for cloud platform   via the dynamic provisioned of virtual systems to perform and support soft and real -time task scheduling. The architecture integrated soft real-time task scheduling algorithms, namely master node and virtual machine node schedules. In addition Adaptive Adaptive Scoring Job scheduling algorithm is also applied. The motive of cloud computing is to tie together the power of both distributed computing and parallel computing as well as   aggregate idle resources on the Internet such as Central Processing Unit (CPU) cycles and storage spaces for better consumption. Cloud computing, which connects a commodity hardware with high speed networks, that can meet the same computing power as a supercomputer does, with a lower cost. However, cloud is a heterogeneous system. Independent tasks scheduling in cloud is more complicated. To make use of the power of cloud entirely, we require an well-organized job scheduling algorithm to allocate jobs to resources in a cloud. This project proposes an Adaptive Scoring Job scheduling algorithm (ASJS) for the cloud environment. Compared to other algorithms, it can reduce the time of job completion, which may compose of computing-intensive jobs and data-intensive jobs. Python 3.6 is used as the front end language to develop the application.
Brief Announcement: Sinkless Orientation Is Hard Also in the Supported LOCAL Model

We show that any algorithm that solves the sinkless orientation problem in the supported LOCAL model requires Ω(log n) rounds, and this is tight. The supported LOCAL is at least as strong as the usual LOCAL model, and as a corollary this also gives a new, short and elementary proof that shows that the round complexity of the sinkless orientation problem in the deterministic LOCAL model is Ω(log n).