Reviewerly/exHarmony huggingface dataset:
Edge Detection and Identification for Tooth Saw Butt Joint

Nowadays, the most well-known autonomous method in recognizing and identifying the edge of a butt joint implements the usage of vision sensor or laser-assisted vision sensor because of its performance and robustness compared to a manual approach.This research paper presents the development of a vision-based method to recognize and identify the edge of a tooth saw butt joint shape.The methodology to recognition and identification edge for tooth saw butt joint shape comprises into four processes: (1) image pre-processing (2) image segmentation (3) morphological (4) edge butt joint feature points representation and description.The edge points for tooth saw butt joint shape that is start point, support point 1 & 2 and the end point represented in x and y coordinates.The edge recognition and identification for tooth saw butt joint shape was obtain using different edge detection techniques such as Sobel, Prewitt, Roberts and Canny edge detection techniques.The repeatability is based on the standard deviation obtain from the average points observed from edge detection techniques.The results show that Canny edge detection technique is the most accurate method compare the others while all the techniques has a high repeatability due to the reliability of the variables obtained
Субъектно ориентированные технологии в профессиональной подготовке будущих педагогов

The article refers to the subject-oriented technologies, their essence and difference from the personcentered ones, their variety, educational potential, as well as the specifics of their application in the context of pedagogical subjects learning. Special attention is paid to such local technologies, as those of personal goal setting, criterial (formative) assessment, designing of individual educational pattern (route), social and educational events, and professional probes.
Usability Evaluation of AWS Quicksight for Real-Time IOT Data

Creating visualizations for Internet of Things (IoT) data can be a challenge due to the uncertain and voluminous nature of this type of data. Many different tools have been made to visualize volumi ...
Boolean Function Decomposition Based on Grover Algorithm and Its Simulation Using Quantum Language Quipper

Decomposition of functions is a general method frequently used in binary logic circuit synthesis, Data Mining and Machine Learning. Ashenhurst-Curtis (AC) decomposition belongs to one of the best known decomposition methods. However, it is really challenging to find the exact minimum AC decomposition for large functions because it requires many exhaust searches. In the hope that large scale quantum computers will be build in the future, we propose an quantum approach based on Grover algorithm to find the optimal AC decomposition in terms of partition theory. The detailed quantum circuit design was created and simulated using Quipper language. According to the experimental results, it is learnt that the quantum algorithm presented in this paper can decompose Boolean function successfully with almost 100% probability and $$ o\left( {\sqrt N } \right) $$ iterations.
Fixing Science: Innovation, Disruption, Maintenance, and Repair at a North American Open Science Non-Profit

Author(s): Harp-Rushing, Kyle Orion | Advisor(s): McMullin, Juliet | Abstract: In 2015, an article published in the journal Science set off what some regarded as a crisis of confidence which quickly swept across several social and natural sciences disciplines. The study suggested that two-thirds of the experiments published in three leading social psychology journals were non-reproducible in other labs. My ethnographic research project is based on several months of fieldwork conducted from 2016 to 2018 at one of the organizations involved with carrying out and publishing this reproducibility study, a relatively small but influential software technology, culture-change, and research non-profit based on the U.S. East Coast. I explore how a small group of dedicated and passionate computer programmers, researchers, and marketers work to expand access and transparency across entire research workflows and lifecycles. While these cognitive laborers work to align support infrastructures and research incentives with ideals of scientific practice, I argue that contemporary capitalist research structures have already made researchers and research products open-ended, modular, and flexible subjects. As a transdisciplinary figure of Scientific research becomes fixed, I argue for considering open science as a matter of social reproduction as much as decentralizing research media and workflow infrastructure.
Data Mapping System Of Riau Province Fire Potential Using K-Means Clustering Method

According to a report from the Riau Province BLHK states that hotspots in Riau Province are always present every year despite the number of hotspots that have been suppressed (http://dislhk.riau.go.id/). One of the causes is the frequent land clearing occurred as a trigger from a hotspot in Riau Province. There is a need for countermeasures as soon as possible to overcome the problem of hotspots that will cause forest fires. These problems need to be watched out quickly, one of which is to know in advance the hotspots that are likely to emerge based on existing data. Data mining processing is very suitable to be applied in order to produce relevant data to find out the possibility of hotspots. In this study the data grouping was done in the form of a visualization of hotspot mapping using the K-means Clustering method. The parameters used include 3 number of clusters (critical, alert, vigilant), 12 regencies / cities in Riau Province and 3 attributes (hotspots, number of fires, number of events). With the results of the visualization of the mapping using the K-means Clustering method, it is expected to be able to help the relevant parties, namely the Riau Provincial Forest Service in handling early the hotspots that are likely to emerge.
The impact of Smart Factory Operation Strategies on Korean Manufacturing Companies’ Growth in Enterprise Productivity: Internal Integration as a Control Variable

본 연구의 목적은 한국 제조기업측면에의 스마트팩토리 운영전략이 기업 생산성 증대에 미치는 영향을 고찰하고자 하였다. 독립변수인 스마트팩토리 운영전략의 하위요인으로 기업 생산프로세스 개선, 설비자동화, 업무효율화, 그리고 기업 내부통합화를 조절변수로 서 본 연구모델을 구축하였다. 본 연구를 수행하고자 경상도 지역을 거점으로 스마트팩토리를 도입&#8901;운영 중인 기업들을 대상으로 대면설문방식 형태의 설문을 실시하였으며, 총 212중 불성실하게 답변한 1부를 제외한 211부를 유효한 설문지로 인정하고 다중회귀분석을 활용한 실증을 진행하였다. 실증결과 설비자동화, 업무효율화, 생산프로세스의 독립변수의 하위 요인 중 설비자동화는 종속변수인 생산성과에 유의한 영향을 미치는 반면, 내부통합과의 조절변수적용을 통한 실증결과의 경우에는 업무효율화가 생산성과에 미치는 영향에 대한 내부통합부분에 있어 조절효과가 있었다. 다만 그 결과에 대한 해석에는 한계가 있다.The purpose of this study is to consider an effect of the smart factory operating strategy on the increase in Korean manufacturing companies’ productivity. It built the study model with the improvement of companies’ production processes and work approach, and the automation of facilities as the sub-factors of the smart factory operational strategy, an independent variable, and companies’ internal integration as a moderating variable. It administered face-to-face questionnaires to workers in companies introducing and operating smart factories at Gyeongsang-do areas and accepted 211 copies as effective questionnaires, except for one copy containing insincere responses, among a total of 212 copies, and then an empirical analysis on the data was conducted by using SPSS 26. The findings show that the automation of facilities, among sub-factors of independent variables such as the automation of facilities, task optimization and the production process has a significant effect on the production performance, a dependent variable, while an empirical analysis on the moderating effect of internal integration exhibits that the internal integration has a moderating effect on the effect of task optimization on production performance.
GEOCHEMICAL EVALUATION OF SURFACE WATER QUALITY AND APPROPRIATENESS FOR DRINKING AND IRRIGATION PURPOSES IN THE AIN TAFARUT, GHADAMIS CITY, SW LIBYA

The goal of the current study is the geochemical assessment of surface water at the Ain Tafarut, Ghadamis city, SW Libya. The chemical data include sulfur isotope (δ34S-SO4), major ions, trace elements, EC, TDS, TH, Alk and pH. The water is immature and hard. It falls in the field between NaCl and NaCaHCO3 types in the Piper diagram. Dominance of rock and evaporation is clear in the water. The contaminant values (except for Na, P, Cl, Br, Ba, Pb, As, Cd and Ni) are below the acceptable limit of WHO (2018). The water is seriously affected by P, Br and Ba (MI&gt;6). The as content demonstrates that the water is not suitable for irrigation.
ЛІДЕРСЬКИЙ СТИЛЬ ВИКЛАДАЧІВ ВИЩОЇ ШКОЛИ

The results of the conducted research have shown that university teachers most commonly display democratic style in their work. At the same time, nearly half of students indicate that authoritarian style is either peculiar to teachers to a greater extent than others, or to the same extent as democratic and liberal styles. There is determined the need in a purposeful development in university teachers the ability of applying the most efficient democratic style in their teaching practice.
Resnet-Based Slide Puzzle Captcha Automatic Response System

Slide puzzle captcha is a kind of dynamic cognitive game, which requires users to pass a series of cognitive tasks to verify themselves. Compared to boring text captcha, the user experience has been greatly improved, so slide puzzle captcha has gradually replaced the text-based captcha on many large platforms. In this paper, we divided slide puzzle captcha cracking into three steps: identifying the gap position, generating the sliding track, and implementing the browser automation. For the location identification of the gap, we used residual network based on object detection and yolov3-based object detection, establish Resnet-18 model and Yolov3 model, and in order to train the two models, we collect 1000 images from Bilibili, Netease Shield, Tik Tok, Jingdong, etcand estimated accuracy of gap identification; As for the generation of sliding trajectory, we analyze the sliding trajectory of human and imitated the human slider trajectory by the piecewise curve fitting of least-squares method; For the automatic implementation of browser, we calculate the offset position, use the TencentAPI, directly feed the recognition result to the page. We choose the resnet-18 and Yolov3 model to identify the location of the gap. We utilize the least-squares method to fit the sliding trajectory segmentally, increasing the degree of simulation and avoiding machine detection.
PENERAPAN TEKNIK MIND MAPPING DALAM PENGAJARAN PENULISAN ESAI SASTRA BERBAHASA INGGRIS

Some difficulties faced by students in writing a literary essay are the abilities to find the appropriate topics for the essay, develop the content paragraph structure and length in writing, and achieve cohesion and coherence. This research aims at implementing mind-mapping technique in writing a literary essay. The subjects of this research were the third semester students of English Literature Study Program at Sultan Agung Islamic University in Semarang. Observation and documentation were used to collect data in which the coherence and cohesion were analyzed. The findings show that mind-mapping technique gives significant impact to students’ abilities in writing a literary essay.
Analisis Kenyamanan Termal Ruang Kuliah

Bhakti Persada Building is one of the main buildings at Ma Chung University that serves as a place for the lecture process and student activities. Every room of Bhakti Persada Building has an AC that is on every day and there are very adequate windows and vents. The study aims to provide thermal comfort to the space users by measure temperature, humidity, and wind speed before and after the engineering of space facilities using SNI 6390: 2011 for temperature and humidity as well as the MENKES No.261 / MENKES / SK / 11/1998 standard for wind speed. In addition, this study was also conducted by paying attention to environmental issues, especially energy utilization, so that later it will be obtained scheduling to use of air conditioners as well as the efficiency of the use of electrical energy after the engineering of space facilities. The results of thermal comfort analysis after engineering the room facilities, obtained the time zone of the lecture room using a propeller fan is the time zone I and II for all sizes of lecture rooms while for time zone III all lecture rooms will use air conditioning because the temperature increases ± 0, 5 ° C, and for time zone IV lecture rooms with sizes 5 x 9 m, 6 x 9 m and 8 x 9 m the second floor will use a fan and a room size 8 x 9 m and 10 x 9 m third floor will use AC. After the engineering of space facilities, it was also found that the efficiency of the use of electrical energy in the lecture hall of the Bhakti Persada Building was 53%.
LibGuides: Canterbury - Mendeley: Getting Started

Instructions for registering an account with Mendeley as well as installing Mendeley on your desktop.
Representation of Concept Based Censor Production Rules using Neural Networks

In this paper we present an approach for representing the Concept Based Censor Production Rules (CBCPR) using Neural Networks (NN).CBCPR is a very useful rule structure where it can be used either as standard rule or as Censor Production Rule (CPR) used in real time systems applications.In the proposed approach, NN representation should be able to handle various UNLESS slots related to one CBCPR.The representation should also reflect the PRIORITY slot in the CBCPR to express the priorities of UNLESS slots.A special algorithm to perform the representation and how the knowledge base system should be treated as one NN are presented.For the learning purpose, the backward pass of the backpropagation algorithm can be adopted, whereas the forward pass can be replaced with our proposed approach since it has a direct relation with the representation mechanism.
EFEKTIVITAS PENGGUNAAN PROGRAM MYOB KOMPUTER AKUNTANSI DALAM MENINGKATKAN HASIL BELAJAR SISWA KELAS XI AKUNTANSI DI SMK NEGERI 1 SUKOHARJO

Effectiveness of the use of MYOB computer accounting Program to improve student learning outcomes of XI grade accounting at SMK Negeri 1 Sukoharjo. This research aims to describe the effectiveness of MYOB's use in improving the learning outcomes of class X1 SMK Negeri 1 Sukoharjo. This type of research is quantitative and qualitative research, which is a mix method of research that produces analytical procedures using qualitative statistical compound procedures. The subject of this research is a productive accounting teacher, deputy head of curriculum and grade XI students. Data collection using documentationtechniques, indept interviews, and observations. Data analysis techniques used descriptive deductive and different trials. Based on the results shows that the useof MYOB is effective in improving the learning outcomes of grade X1 students SMK Negeri 1 Sukoharjo. Data analysis results between knowledge assessment results before MYOB class AKL2 and Skills assessment results after the MYOB practice class AKL2 tcount of-18,148. The difference in learning results was strengthened by the value of Sig. (2-tailed) for 0.000. Findings of sucheffectiveness test results strengthened analysis result of knowledge assessment before MYOB class AKL3-Skills assessment result after MYOB class AKL3 tcount practice of-11,542. The difference in learning results was strengthened by the value of Sig. (2-tailed) for 0.000. As for the things that can improve student learning outcomes are: 1) the preparation of learning infrastructure, computers, and programs of MYOB version 18 + performed by teachers; 2) The customization and completeness of learning devices by teachers, and 3) is the proper use of learning methods in computer learning.
Android Mobile Augmented Reality Application for 3D Visualization of Museum Collectibles in Surakarta

This article discusses the process of developing and perceptional validation by prospective users of the augmented reality application on mobile devices for three-dimensional (3D) visualization of museum collectibles.The main purpose of this publication is to visualize museum collection objects in 3D models on Android mobile devices so that visitors could be able to see collections from all sides.Augmented reality application displays a 3D model by scanning a unique marker for every collection.The test results showed that the application worked properly on smartphones using Android 4.0 or later version and with a minimum of 1 GB of memory in low-light room condition or brighter.Moreover, test results on various markers conditions indicated that the application could still be able to read the marker and display a 3D model with the marker condition that was crossed out with a ballpoint or there were traces of the folded line.In addition, if the marker was covered with a solid object such as paper with a maximum of 40%, the marker was still readable by the application.The results of the perceptual evaluation by users showed that the average of acceptance rate was 82.282% at the Nusantara Keris Museum and 88.47% at the Surakarta Cultural Heritage Museum.
The Adoption of Blockchain In Supply Chain: Is Supply Chain Ready?

Recently, blockchain technology is getting its recognition in the supply chain. After the existence of bitcoin, which blockchain acts as its underlying technology, people started to recognise the advantages of the blockchain. Blockchain has been expected to eliminate unnecessary cost and at the same time, help in improving productivity by increasing the efficiency and effectiveness in daily operation. In the era of Industrial 4.0, the collaboration of blockchain technology with other autonomous technology is necessary to achieve customer satisfaction. However, based on the current practices, blockchain is yet to be adopted by all the parties in the supply chain. Therefore, this paper aims to identify the factors which are affecting the adoption of blockchain technology in the supply chain. Factors identified are perceived benefits, top management support and supply chain partner readiness. The primary data has been collected through a structured questionnaire survey. The simple random sampling method has been used to target and collect data from suitable respondents. In conclusion, the outcome of this study is expected to identify the factors affecting the adoption of the blockchain as well as to guide the organisation to act according to increase the level of adoption.
ЗАСТОСУВАННЯ ГНУЧКОЇ (AGILE) МЕТОДОЛОГІЇ ДЛЯ ВИКОНАННЯ МІЖНАРОДНИХ СПІЛЬНИХ НАУКОВИХ ПРОЕКТІВ

Active project management techniques have become one of the fastest growing and most popular aspects of IT project management. Using flexible methods in software development can make a difference between a project that has a low chance of completion, and those that will give results very quickly and continue to achieve results in time. However, flexible thinking has never been intended to restrict only the development of software. Applying this concept of project management to processes and other project types is anticipated from the outset. Agile methodologies use an iterative approach to project implementation. In contrast to the rectilinear cascade model, flexible projects consist of a few smaller cycles of sprint. Each of them is a project in miniature: It has lag and consists of stages of design, implementation, testing and deployment within a predetermined amount of work. In order to carry out international joint projects, the Agile mechanism is widely used-iterative and gradual development. This approach is very important in terms of interethnic differences and finding project performers in different countries. In particular, in the implementation of joint scientific researches for the enterprises-customers.
Detectives say unidentified ATM skimming suspect stole thousands from 25 victims in Pierce County

A warning as the weekend approaches that skimming suspects often strike on Saturdays and Sundays. That’s when Fircrest Police say an unidentified skimming suspect placed a device on an ATM outside a credit union on 19th St. S. in the City of Fircrest.
Detection of Cyber Bullying in Social Media Engineering

In the digital world the individuals in various age bunches have an enthusiasm on correspondence with social media.This increasing trend of users in the social media created a chance for cyber bullying which means harmful words communicate via electronic.From the previous research analysis one of the challenging tasks is to find out the combination of the harmful words in the dataset and it takes a long time process.We propose a technique for detection of cyber bullying is Natural Language processing along with regression technique, finding the accuracy of the statistical measures on Twitter dataset.The results show that accuracy of F1 measures produce better performance on any combination of Bully words.
information hiding using E-mail cards

Steganography, is the hiding and transmitting secret messages through apparently innocuous carriers in an effort to conceal the existence of them. The carrier can be anthing used to transfer information, including, e-mail, audio, video, images, messages, disk partitions and disk space. The aim of the research is for hiding a text message in the unused spaces of the e-mail card structure which is designed by Macromedia Flash software (SWF file).Macromedia Flash (SWF (Shockwave File) file) has been chosen because as it is widely used in Internet (Web pages), is recognized by all browsers and it is easily distributable which ensures that it lends itself to this type of activity without drawing attention to itself.The research studies different types of e-mail cards and show the possibility of them to hide secret message. The research deduces that the e-mail card which is designed from sound, animation and moving image is good for hiding (because it contains many unused spaces available for hiding).
Privacy-preserving collaborative deep learning methods for multiinstitutional training without sharing patient data

Although deep learning models have great promise for clinical applications, there are numerous obstacles to training effective deep learning models. There is a need for collecting large quantities of diverse data, which often can only be achieved through multiinstitutional collaborations. One approach to multiinstitutional studies is to build large central repositories, but this is hindered by concerns about data sharing, including patient privacy, data deidentification, regulation, intellectual property, and data storage. These challenges have made centrally hosting data less impractical. An alternative approach is to have the data hosted locally and have the model trained in a collaborative fashion. Depending on the collaborative learning approach, model weights, model gradients, or smashed data are shared instead of raw patient data. These approaches can also reduce the communication overhead while reducing the need to share private patient data. In this chapter, we will review and compare the current techniques for distributing learning, handling data heterogeneity, and preserving patient privacy for multiinstitutional applications.