Reviewerly/exHarmony huggingface dataset:
The Effectiveness of ARIAS Learning Model Based on Digital Literacy in Terms of Critical Thinking Ability of Elementary School Students

This study aims to determine the effectiveness of the digital literacy-based ARIAS learning model on the critical thinking skills of elementary school students.This research is quantitative research with experimental research methods.The research design used was a Quasi-Experimental Design with a Posttest Only Control Design type.The sampling technique used was cluster random sampling.Based on the average score of students 'critical thinking skills in the experimental class, it was obtained that it was 1698.3 which was higher than the average score of students' critical thinking skills in the control class which was 1556.6.The result of the analysis of the hypothesis test is known that T count (2.297)> T table (1.686) then H0 is rejected or Ha is accepted.Thus the ARIAS (Assurance, Relevance, Interest, Assessment, and Satisfaction) learning model based on digital literacy is effective in terms of the critical thinking abilities of elementary school students.
Creative Economy of College Student Gamification based on E-Commerce

The application of Blockchain technology in the context of providing security for transactions in the digital era 4.0 to prevent manipulation of transaction recording reports by irresponsible parties. By using research methods 10 (ten) literature reviews and methods of formulating problems, designing research, collecting data, processing &amp; presenting data, analysis &amp; research reports are expected to solve security problems in transactions. At present security in transactions is still very minimal, therefore a blockchain technology is needed to secure transactions where data can still be manipulated. Specifically, there are 2 (two) benefits of this research that use blockchain technology, (1) transactions become safer in the presence of encryption codes, (2) transactions become more transparent with blockchain. This research implements the encryption code into the payment system using AI Coin, where payment is now cashless, to make it more secure and transparent in transactions.
PENINGKATAN HASIL BELAJAR IPS SEJARAH MATERI LETAK DAN LUAS INDONESIA MENGGUNAKAN ALAT PERAGA PETA

This study aims to improve student learning outcomes in class VII B MTsN 1 Pangandaran in social studies subjects. Improved student learning outcomes by being given action through the use of maps as learning aids. This research uses Classroom Action Research which consists of two cycles. Each cycle consists Two meetings. Each Meating consist of four stages, namely planning, acting, observing and evaluating the results of the action and reflecting until the expected improvement. The population of this study were all students of class VII B MTsN 1 Pangandaran with 30 students. The results of the study indicate that the use of maps as learning aids can improve student achievement in social studies subjects. This is evidenced by an increase of 20% compared to pre-treatment. Learning achievement in the first cycle of the second meeting increased by 40% to 67% in the second cycle of the 1st meeting. Similarly, learning outcomes in the second cycle of the first meeting increased by 20% to 87% at the end of the second cycle of the second meeting. -learning is proven to be able to improve student learning outcomes on the concept of understanding the human environment using of maps as learning aids of the location and area of ​​Indonesia in class VII B MTsN 1 Pangandaran.
Iterative Image Inpainting with Structural Similarity Mask for Anomaly Detection

Autoencoders have emerged as popular methods for unsupervised anomaly detection. Autoencoders trained on the normal data are expected to reconstruct only the normal features, allowing anomaly detection by thresholding reconstruction errors. However, in practice, autoencoders fail to model small detail and yield blurry reconstructions, which makes anomaly detection challenging. Moreover, there is objective mismatching that models are trained to minimize total reconstruction errors while expecting a small deviation on normal pixels and a large deviation on anomalous pixels. To tackle these two issues, we propose the iterative image inpainting method that reconstructs partial regions in an adaptive inpainting mask matrix. This method constructs inpainting masks from the anomaly score of structural similarity. Overlaying inpainting mask on images, each pixel is bypassed or reconstructed based on the anomaly score, enhancing reconstruction quality. The iterative update of inpainted images and masks by turns purifies the anomaly score directly and follows the expected objective at test time. We evaluated the proposed method using the MVTec Anomaly Detection dataset. Our method outperformed previous state-of-the-art in several categories and showed remarkable improvement in high-frequency textures.
Research and analysis on the current quality of shower products

Shower head, also known as shower head, is a device that allows water to diverge and flow out in the form of droplets or sprays. It was originally a device for watering flowers, potted plants and other plants. Later, someone modified it to be used as a shower, making it a common device in the bathroom, called a shower head, mainly used for showering in households or public places. In terms of structure, the shower is generally composed of a body, a switching component, a water distribution component, a rotor, a water outlet, a face cover, a water outlet component, a water-saving device, a plug, a button, and so on. This article mainly analyzes the industrial distribution of shower heads, product quality spot checks and the causes of quality problems.
Awareness and Practice of Guidance Functions by the Teachers in Urdaneta City

This is a Descriptive research that aimed to determine the level of awareness and practice of guidance functions by the teachers in Urdaneta City during the School Year 2019-2020. The subjects of the study were the 155 guidance designate teachers in private schools in Urdaneta City. Descriptive method was utilized in the interpretation and analysis of level of awareness and practice of the guidance designate teachers. Complete enumeration was also used to administer the survey questionnaire. Based on the findings, the researcher concluded that, Majority of the respondents are in the middle age. Subject taught is Edukasyong Pagpapakatao. The highest educational attainment is Baccalaureate Degree in which they are classified as novice in terms of number of years in teaching and number of relevant trainings attended. The employment status is casual. The respondents have High level of awareness on their guidance functions. The Level of Practice of the Guidance Functions of the teachers is Moderately High. There is a significant relationship in the Level of Awareness and Level of Practice in the Guidance Functions in the profile of the respondents across different services.                In the light of the findings and conclusions, the researcher recommended the following:  a) Teachers should be developed professionally, be sent to relevant trainings and be exposed in subjects where they can apply the guidance functions; b) Encourage the guidance designates to pursue graduate studies for career advancement to gain more experience to cater the needs of the students; c) School Heads should send guidance teacher / designates to seminars and trainings to further increase their level of awareness to the guidance functions; d) Guidance teacher designates should optimize the implementation of guidance functions along different services such as information service, consultation service, placement service, testing service, referral service and support system service; e) Guidance designates should strengthen the information dissemination in the community about the programs offered regarding the consultation of parents, teachers, and community personnel to enhance their relationship to the students; and d) Enhanced the guidance programs, career guidance, and homeroom guidance programs.
Color Image Segmentation and Detection of Barrels Using Gaussian Mixture Model

This paper is based on segmentation and detection of the color barrels. The main goal is to identify the barrels, there may be one or more barrels in the test and the training set in the given RGB images after managing segmentation color. Besides, Gaussian Mixture Model, Bayesian Model, linear regression method and other techniques are used to obtain more precise results of training images as well as prediction. We identify different color barrels such as red, blue, green and the barrel mean, variance and distance is approximately estimated by importing functions in this class by using linear regression model. GMM that is modeled as pixels and color classes, for the categorization of pixels by the class of color, and then we can differentiate the area of pixels of the barrel from non-barrel. The distance is estimated by two purposes interior One to detect the barrel and other to find the bounding box information counting four vertexes, height and width of the barrel.
An Effective Task Scheduling Framework for Cloud Computing using NSGA-II

Cloud computing is a model for convenient on-demand user’s access to changeable and configurable computing resources such as networks, servers, storage, applications, and services with minimal management of resources and service provider interaction. Task scheduling is regarded as a fundamental issue in cloud computing which aims at distributing the load on the different resources of a distributed system in order to optimize resource utilization and response time. In this paper, an optimization-based method for task scheduling is presented in order to improve the efficiency of cloud computing. In the proposed approach, three criteria for scheduling, including the task execution time, the task transfer time, and the cost of task execution have been considered. Our method not only reduces the execution time of the overall tasks but also minimizes the maximum time required for task execution. We employ the Multi-objective Non-dominated Sorting Genetic Algorithm (NSGA-II) for solving the scheduling problem. To evaluate the efficiency of the proposed method, a real cloud environment is simulated, and a similar method based on Multi-Objective Particle Swarm Optimization is applied. Experimental results show the superiority of our approach over the baseline technique.
CNL-RDF-query

The most commonly used search engines do not always show the information that the user needs, because they do not take into account factors such as the context or natural language ambiguity. Therefore, other types of search engines that considered these factors emerged in last few years, such as question-answering systems or semantic web-based search engines. In this work, we present CNL-RDF-Query, a controlled natural language interface for querying rdf-based ontologies and relational databases. The system guides users in the construction of queries with the knowledge of domain ontology. Our proposal has been tested in the domain of the IMDb movie repository.
A novel data placement strategy to reduce data traﬀic during run-time

High impact scientific applications processed in distributed data centers often involve big data. To avoid the intolerable delays due to huge data movements across data centers during processing, the concept of moving tasks to data was introduced in the last decade. Even after the realization of this concept termed as data locality, the expected quality of service was not achieved. Later, data colocality was introduced where data groupings were identified and then data chunks were placed wisely. However, the aspect of the expected data traffic during run time is generally not considered while placing data. To identify the expected data traffic, the knowledge of the history of data movements is useful. In this work, this knowledge is utilized and an approach to intelligently select the nodes for placing data groups to ensure the least possible data movements is proposed. Systematic scrutiny of log files is conducted and a gain matrix is generated based on maximum likelihood estimation of data movements. Formally, the gain matrix is inversely proportional to the expected data traffic inside the data center. It reflects the performance gain obtained by assigning a block to a node with the lowest possible future data movements. To identify the optimal placement, a many-to-one assignment problem-based algorithm is presented. By experimental analysis, it is observed that the movement of data is significantly reduced by the proposed approach. It is also found that the performance has improved considerably.
Research guides: LibrarySearch Tips: Refine Results Using Filters

A guide to the University of Toronto Libraries' LibrarySearch platform How to improve your results using filters
Construction and Practice of Cultivation System for Innovative Talents in Cyberspace Security

In June 2015, The Academic Degrees Committee of the State Council of China and the Ministry of Education decided to add the First-Level Discipline of "cyberspace security" under the category of "engineering".The establishment of the first-level discipline is aimed at implementing the national security strategy, which is not only conducive to speeding up the training of high-level talents for cyberspace security, but also puts forward higher requirements for Discipline Construction and personnel training system.Based on the analysis of the concept and connotation of cyberspace security, this paper summarizes more than 10 years experience of Chengdu University of Information Technology in the construction of information security specialty, and gives some suggestions on the construction and practice of Cyberspace Security innovation personnel training system.
Evaluation of Information Leakage of Cryptographic Chip Based on Variance

The cryptographic chip in system must be evaluated for side channel leakage detection before coming into service. However, the existing evaluation technology is too inefficient. This letter decomposes the variance of the traces of power consumption into variance of the sensitive variable and noise to estimate the signal-to-noise (SNR). According to the relationship between the success rate (SR) of the power analysis attack, SNR and conditional mutual information, the minimum number of traces is computable to evaluate the information leakage of the cryptographic chip. This method effectively estimates the minimum number of power traces when the SNR of power consumption is greater than 0.1. When the SNR is less than 0.1, the result calculated by this method is consistent with the change trend of the simulation, which means that the result also evaluates the ability of cryptographic chip to resist power analysis attacks. The method improves the evaluation efficiency by at least 60000 times compared with the simulation of CPA.
PREDIKSI PENDAPATAN ASLI DAERAH (PAD) KABUPATEN LANGKAT MENGGUNAKAN METODE BACKPROPAGATION NEURAL NETWORK

The District Government of Langkat in this case regulates and manages Regional Original Income (PAD), for example, taxes can be increased by intensification and extentification. Extensification is an expansion of the type of tax, but several studies show that controlling the potential by expanding the type of tax does not stimulate interest and even creates reluctance for investors to invest in the area. Intensification is an effort to increase tax collection. This effort requires the ability of the regions to be able to correctly identify local revenue and the ability to collect taxes based on benefits and principles of justice. By inputting training data and training targets, the artificial neural network to predict the number of Langkat Regency using the backpropagation method can predict the amount of PAD in Langkat Regency. The artificial neural network system can recognize training data and target data with an iteration of 488 target error of 0.5 and a leraning rate of 0.1, resulting in a prediction of the amount of PAD in 2020, which is Rp. 140,948,000,000.
Manajemen Referensi dengan Aplikasi Zotero

Based on the situation analysis, a Community Partnership Program (PKM) activity is proposed to train the use of reference management software for teachers in which SMA Negeri 4 Pinrang Regency is the partner. The identified problems are: (1) Lack of skills in using reference manager software, (2) Zotero as open source software is unknown, (3) The need for the ability to use reference manager software that can be applied in writing scientific papers. The material is presented through zoom meetings in plenary and in groups according to the schedule. In the plenary presentation of the material, material on basic concepts in research and writing of scientific papers was presented then continued with the provision of material on the use of Zotero in writing scientific articles. Some of the requirements to become a participant are: (1) having an interest in learning the basic concepts of reference management, (2) having never attended a similar training. (3) must attend all training activities. From the PKM activities that have been carried out as well as the team's internal survey, it can be concluded that in the implementation of this activity: (1) Participants become literate and skilled in operating the Zotero software, (2) The Zotero menu is well known to PKM participants, (3) Participants have the ability to use Zotero in writing scientific articles.
INCREASING THE STUDENTS’ ABILITY IN SPEAKING BY USING MEMORY GAME AT THE EIGHT GRADE OF SMP NEGERI 4 SIROMBU

Speaking is one of the language skills that must be mastered by the students at school besides reading, listening and writing. Speaking is one of the most difficult aspects for the students, that is why teaching speaking is generally felt challenging, especially for students in SMP 4 Sirombu, because it needs more attractiveness. The purpose of the research is to increase the students of the eighth grade of SMP 4 Sirombu’s ability in speaking. Based on the data analysis in cycle I, the percentage of the students’ activities is 79,44% (good). In this cycle the students cannot achieve the Minimum Competency Criteria which is 65, the students’ average score is 43.38. All the students get a score ? of 65, as the highest score is 56 and the lowest score is 33. Furthermore, in cycle 2 the percentage of the researcher’s done activities is 100% (excellent) and the percentage of the students’ done activities is 96.11% (very good). In this cycle, the students have achieved the minimum competence criteria, where the students’ average score is 71.76 (adequate). No one of the students gets a score of less than 65 as the highest score is 84 and the lowest is 65. Based on the result of the research can be concluded that Memory Game can increase the students’ ability in speaking.
Student Attendance Information System Using Web-Based Nodemcu ESP8266

Presence or attendance in educational institutions such as Ibn Khaldun University Bogor is an important aspect in supporting the course of the lecture system, currently the attendance system at Ibn Khaldun University Bogor, especially in the Informatics Engineering study program, still uses a conventional system where students still have to sign an attendance sheet at the time lectures. In this study, there are two problem formulations (i) How to design and implement student attendance system devices using radio frequency identification (RFID) technology and WEB-based NodeMCU ESP8266, (ii) How to test WEB to display information on the presence of Informatics Engineering students using Black Box. The purpose of this study consisted of two stages (i) Designing and implementing a student attendance system device using radio frequency identification (RFID) technology and WEB-based NodeMCU ESP8266, (ii) being able to implement WEB testing to display information on the attendance of Informatics Engineering students using Black Box. Where in this study the framework has four stages, namely (i) analysis, (ii) design, (iii) implementation and (iv) testing. The results obtained in the research (i) Design and implementation of student attendance system devices using radio frequency identification (RFID) technology and WEB-based NodeMCU ESP8266 (ii) Implementation of WEB testing to display information on the presence of Informatics Engineering students using Black Box and get results appropriate.
단어의 개념 규정 - 최소자립형을 중심으로 -

Word can be recognized easier and faster than the other grammatical units such as morpheme and sentence. Ironically, the definition on word is more difficult than other grammatical units. So we tend to pass or ignore word definition and describe the other attributes of it. But without definition of something we can not classify or analyse it properly.In this paper, I paid deep attention to the classic definition on word in Bloomfield(1933), namely ''the minimum free form'' again. The points of Bloomfield(1933) about definition on word are as follows.① Word should be free form.② Word should not be a phrase.With these criteria we can easily distinguish almost every Korean words from other grammatical units. But it may be difficult to distinguish such elements as are called bound noun, pre-noun and auxiliary verb or adjective in Korean grammar from other grammatical units, because these are not free forms. But based upon the fact that these elements can be combined with other words to make syntactic structures, we can take these for words.Korean particle which has been regarded as word traditionally in Korean grammar should not be classified as word, simply because it must be a part of morphological structure.
LibGuides: LibrarySkills@UCL: Communicating and sharing information: Independent research

A guide to scholarly communication, including sharing information through the principles of Open Research
NETWORK ROBUSTNESS TO PCA PERTURBATIONS

A key challenge in analyzing neural networks' robustness is identifying input features for which networks are robust to perturbations. Existing work focuses on direct perturbations to the inputs, thereby studies network robustness to the lowest-level features. In this work, we take a new approach and study the robustness of networks to the inputs' semantic features. We show a black-box approach to determine features for which a network is robust or weak. We leverage these features to obtain provably robust neighborhoods defined using robust features and adversarial examples defined by perturbing weak features. We evaluate our approach with PCA features. We show (1) provably robust neighborhoods are larger: on average by 1.8x and up to 4.5x, compared to the standard neighborhoods, and (2) our adversarial examples are generated using at least 8.7x fewer queries and have at least 2.8x lower L2 distortion compared to state-of-the-art. We further show that our attack is effective even against ensemble adversarial training.
Jaringan Saraf Tiruan Backpropagation Untuk Memprediksi Jumlah Ekspor Buah-Buahan Menurut Negara Tujuan

This research aims to predict the number of exports of fruits by country of destination in the coming year based on data in the previous year. The application of a prediction is very important in conducting research. The method used in conducting this prediction is the artificial neural network (JST) with its Backpropagation algorithm. The architecture used in this study is 4-2-1, 4-4-1, 4-6-1, 4-8-1, 4-4-2-1, and 4-3-6-1. Test results obtained prediction of export of fruits according to destination country with 91% accuracy rate with 4-4-1 architecture
Issues Related to Countering Cybercrimes: Russian and International Practice

This paper briefly examines the issues of countering crimes in informative technologies (cybercrimes) and pays more attention to a summary of the practice of the Russian Federation and foreign countries. It also offers ways of improving countering system.