Reviewerly/exHarmony huggingface dataset:
Kajian Strategi Adaptasi Masyarakat terhadap Bencana Kekeringan di Desa Rejosari Kecamatan Semin Kabupaten Gunungkidul

Almost every year all areas in Gunungkiduk Regency, Yogyakarta special Region Province experience drought, one of which in Rejosari Village, Semin District. The drought that occurs has a wide impact, such as the problem of the availability of clean water for domestic needs, agriculture and livestock. This impact is also related to changes in the socio-economic conditions of the community in Rejosari Village, semin District. The purpose of this study is to anlyze 1). socio-economic characteristics of people experiencing drought 2). analyzing community adaptation strategies to drought in Rejosari Village, Semin District, Gunungkidul Regency. The research method used a survey using a questionnaire. The sampling technique used in this research was non-probability convenience method and data analysis used in the study was descriptive quantitative. The result of this study indicate that 1). the socio-economic characteristics in Dusun KarangpilanLor, Rejosari Village, namely the average age of 53 years with majority of 27% aged 55-65 years, the average edouction level of 41% of elementary school graduates, tha majority of work 60% as a farmer, thae average income is IDR 1.108.174 which is below the UMR, and the patternof using clean water for bathing purpose the average amount of clean water is 134 liters/KK/day and the average use of clean water for livestock is 46 liters/KK/ day 2). there are 3 types of community adaptation strategies, namely socio, economic, and physical. a). adaptation strategies for social aspects in the form of efforts to make public wells, giving each other access to clean water from family / private wells and assistance from local governments b). adaptation strategy for economic aspects in the form of 13% of people buying clean water with an average purchase of Rp. 128,636 per conductor containing 100 liters and 87% of people do not buy clean water because of insufficient income, so people save money to buy water in the dry season, carry out a strategy adaptation in the form of conserving clean water by reducing the amount of clean water by 47% or 1,300 liters from the use of normal / pre-dry water. c). adaptation strategies for physical aspects in the form of drilling wells, building public wells and constructing water reservoirs to save clean water.
Design and Implementation of the Informatization Management System for the Meteorological Station Network Basic Data

Abstract The basic data of the meteorological station network has such problems as inaccuracy, untimely review and inconsistency among operational systems. Aiming to solve these problems, we design an informatization management system for the meteorological station network through the WeChat enterprise. It employs the area verification and the altitude validation based on the digital elevation model, and it performs a regular comparison with the data from the China Integrated Meteorological Information Sharing System. This system realizes the dynamic management for the filling, submitting and reviewing of the station network basic data. It has functions such as intelligent verification of the input data of the station network, efficient and convenient data review, timely reminder message and flexible data service interface. Therefore, the system effectively improves the accuracy of the station network basic data and the review efficiency.
FillingGAN: A Deep Learning-based Automatic Coloring Technique from Line Drawings for Developing Coloring Game Contents

In this paper, we contribute to the field of game by presenting FillingGAN, an automatic coloring framework using a generative adversarial network (GAN). FillingGAN is devised to generate a coloring image from a line drawing by filling empty regions between the lines in the line drawing image from the coloring styles learned from sample coloring images. Our model consists of two style extracting modules and a GAN model. The style extracting modules are designed as an auto-encoder that extracts feature from input images. One module extracts color styles from coloring sample images and the other extracts structure from a line drawing. FillingGAN executes coloring process by applying the coloring styles from coloring samples to a line drawing. It determines the similarity between the generated coloring image and the input line drawing, and calculate the perceptual loss to preserve the structural similarity. FillingGAN generates coloring images with preserved details by adjusting the weights between the structural feature vectors and the style feature vectors. As a result, it generates a stylized image without distorting the unique features of a line drawing. Our framework can be improved to apply various styles including artistic media strokes to line drawings.
The Effect of Orchestra Pit Diffusion on the Auditorium Acoustics of Opera House

Abstract A scale model of the Zhuhai Opera House, with 7 kinds of simulated orchestra pits, was made and analyzed in an experiment. The pulse response of the auditorium of the opera house was measured and analyzed. The results show that diffusion treatments for the orchestra pit can affect the sound transmission of stage source, increasing C80 and D50 in the rear part of the auditorium and can also affect the sound transmission of pit source, making the average value of G in the auditorium rise. As well, no significant changes were found on EDT and T20 under the diffusion treatment of the orchestra pit.
A GAN-based face reenactment technique for non-human game characters using coloring module

Recently, many progresses on deep learning-based facial expression reenactment are released. Applying the facial reenactment techniques to game characters should address a challenge of extracting action units (AUs) from non-human game characters. To extract AUs from non-human game characters effectively, we devise a coloring module that adjusts the face colors of the character to that of a normal human. Our framework is based on GAN. Our framework consists of a coloring module, two generators, two discriminators, and an identity preserving module. In the first, we adjust the face color using the coloring module and then generate a neutral face from the first generator according to the input AU. The second generator produces the reenacted face images from the neutral face. Finally, the coloring module applies the original face color to the reenacted facial images. We measure the quality of the generated image through the discriminators and preserve the identity through the identity preserving module. We generate reenacted images from various game characters and prove the excellency of our method.
Linking Ontology, Epistemology and Research Methodology

The purpose of this paper is to offer insights that can help researchers to link ontology, epistemology and research methodology. This paper outlines the links among ontology, epistemology and research methodology by exploring ontological, epistemological and methodological perspectives in the research. It discusses how ontological and epistemological issues influence research methodology by providing a clear understanding of different research methodologies based on ontology and epistemology. Furthermore, attention is given to research aspects such as the elements of the research process, research philosophy, research approach, research strategy, the choice of method, and research design.
Applications of Machine Learning Techniques to Predict Diagnostic Breast Cancer

This article compares six machine learning (ML) algorithms: Classification and Regression Tree (CART), Support Vector Machine (SVM), Naive Bayes (NB), K-Nearest Neighbors (KNN), Linear Regression (LR) and Multilayer Perceptron (MLP) on the Wisconsin Diagnostic Breast Cancer (WDBC) dataset by estimating their classification test accuracy, standardized data accuracy and runtime analysis. The main objective of this study is to improve the accuracy of prediction using a new statistical method of feature selection. The data set has 32 features, which are reduced using statistical techniques (mode), and the same measurements as above are applied for comparative studies. In the reduced attribute data subset (12 features), we applied 6 integrated models AdaBoost (AB), Gradient Boosting Classifier (GBC), Random Forest (RF), Extra Tree (ET) Bagging and Extra Gradient Boost (XGB), to minimize the probability of misclassification based on any single induced model. We also apply the stacking classifier (Voting Classifier) to basic learners: Logistic Regression (LR), Decision Tree (DT), Support-vector clustering (SVC), K-Nearest Neighbors (KNN), Random Forest (RF) and Naive Bays (NB) to find out the accuracy obtained by voting classifier (Meta level). To implement the ML algorithm, the data set is divided in the following manner: 80% is used in the training phase and 20% is used in the test phase. To adjust the classifier, manually assigned hyper-parameters are used. At different stages of classification, all ML algorithms perform best, with test accuracy exceeding 90% especially when it is applied to a data subset.
Analisis data penelitian eksperimen model pembelajaran

The partner in community service is the Department of Teacher Education in the Faculty of Education at the State University of Makassar. The problem: (1) Lack of understanding of experimental research methods. (2) Lack of student knowledge in analyzing experimental research data using data analysis software, and (3) Statistics courses taught are general in nature. The target of this training is the final semester students who will be writing their thesis. The methods used are: lectures, demonstrations, discussions, and data analysis practices. The results achieved (1) the compilation of research methods and statistical curriculum tools ranging from the course syllabus to the learning plan, and (2) conducting training for students about the analysis of experimental learning model data using data analysis software (SPSS 25)
28 Shifting to Virtual MDT in the COVID-19 Era and Beyond

Abstract Aim The COVID19 pandemic has accelerated the need for staff to work remotely. Our aim was to demonstrate how a next-generation digital platform could be used to create a virtual MDT ecosystem in order to manipulate holographic 2D and 3D images in real-time. Method This study involved setting up a mock virtual MDT using de-identified DICOM files from a patient who had been treated for colorectal cancer and then subsequently found to have a liver metastasis. The image file was segmented and converted into a 2D and 3D format for visualisation within Microsoft HoloLens 2 ® (smart glasses) using Holocare Solutions ® (Mixed Reality software). Results A seamless cross-border pipeline was developed that involved "clinician" training, DICOM segmentation and virtual connection. We successfully performed a virtual MDT with participants able to visualise and manipulate a virtual 3D organ in real-time. The digital network remotely connected sites in England and Norway. The streaming quality was stable and HIPAA compliant. Each participant could observe others as "avatars" interacting with images within the virtual ecosystem allowing image characteristics to be highlighted. Conclusions We successfully conducted a virtual MDT using novel hardware and software. Our intention is to conduct a large-scale study to assess the platform's effectiveness in “Real World" MDTs.
Exploring the functionality of Bulgaria eGovernment site

The object of the paper is the portal for electronic administrative services (eGov.bg), all the functions provided by it and study its functionality. The eGovernment site features offered must be examined in depth and all working and non-working functions highlighted. One of the most important tasks at the end is to derive and show the ratio of working and non-working functions and to show which of them have some activity and which have not. This information would be presented in tabular form and diagrams.
Development of an Autonomous Mobile Manipulator System for Fetch-and-Carry Tasks

This paper presents a detailed development of a mobile manipulator to perform fetch-and-carry tasks autonomously in a structured indoor environment. This system was especially designed to prevent human contact in the work environment during Covid-19 pandemic situation. The system setup includes a Baxter manipulator mounted on a two-wheeled differential drive mobile robot. The ROS melodic platform installed on Nvidia Jetson TX1 embedded system was used for software development. Autonomous navigation and visual servoing are implemented using an Intel Realsense depth camera and a tracking camera which are collaborated with ROS Simultaneous Localization and Mapping (SLAM) and navigation. The system was validated under two experiments in order to: 1) analyze the performance of mobile manipulator navigation and 2) validate the overall system performance. Through several trials in each experiment, it was demonstrated that the developed system is able to perform fetch-and-carry tasks with the collision-free navigation consistently and repeatedly.
3D 스캐닝 기술을 이용한 토공사 기성관리 감독 및 검사 가이드라인 개발

Recently, in Korea, various technology developments have been made to utilize 3D space and facility data such as unmanned aerial vehicles (UAV) and laser scanners with the goal of improving productivity at construction sites. However, the lack of related regulations for 3D laser scanner surveying has been a barrier to using the technology across the surveying industry. As a result, owners, contractors, and construction supervisors are reluctant to introduce and apply technology to the site.In this study, the guidelines (drafting and inspection work to be supervised by construction supervisors when constructing earthworks using laser scanners) was developed and presented so that the earth surveying and quantity calculation technology using a laser scanner could be applied and diffused in a construction site. Through the development of this guideline (proposal), it is judged that the supervision and inspection of earthworks quantity using a laser scanner will be activated in the field.
Impact of Web 2.0 Technologies on Academic Libraries: A Survey on Affiliated Colleges of Solapur University

The paper aims to present the results of a survey of academic libraries about the adoption andperceived impact of Web 2.0 technologies. A total of 26 college libraries affiliated with SolapurUniversity participated among the members. It was found that each library was using some formof technology, such as RSS, blogs, social networking sites, wikis, and instant messaging.Analyzing the entire college web technology usages, it is observed from the results that most ofthe web technologies are not used by the mainstream of the users due to lack of awareness,training, etc. Accurate and appropriate training should be conducted by the colleges' Librariesaccording to the necessities of the users. Systematic training will inevitably help the user for themaximum utilization of e-resources of the library. The leading web technologies such as internetsurfing, emails, search engines, wikis, photo sharing, etc. are used by a great number of users ona daily and weekly basis of frequency. On the other hand majority of the web technologies arenever used by a great number of users
Miscellaneous of direct normal solar irradiation on Rinjani Mountain: it's impact on local climate

Orographic effect of Rinjani mountain is one of the most important factor affecting local climate. It plays a significant role in driving a hydrology cycle, as well as inducing orographic rain in Lombok. A Descriptive research was conducted to identify miscellaneous of direct normal irradiation, and its possible impact on local climate. Data of solar irradiation and air temperature were freely acquired from Global solar atlas, and simple linear regression was applied to mathematically describe a spacial variation of the solar insolation, as well as temperature lapse rate from various direction, namely : north, north east, east, south east, east, south west, west and north. The results show that, the intensity of daily direct normal irradiation (DNI) was 3.7 kwh/m2 on average, which successively decreased by 0.64 kWh/m2 as increasing altitude of 1000 m above sea level. The intensity of DNI turned over at 1,490 m asl. with an average minimum intensity of 2.79 kwh/m2, and maximum intensity was 4.98 kwh/m2 at plate low lands (close to the beaches). The air temperature lapse rate was -5.23oC/1000 m on average. In conclusion, the DNI varied in accordance to local topographic condition and an “aspect” factor, i.e. direction of the mountain slope relative to the incoming light path way.
Eye Gaze Estimation Invisible and IR Spectrum for Driver Monitoring System

Driver monitoring system has gained lot of popularity in automotive sector to ensure safety while driving. Collisions due to driver inattentiveness or driver fatigue or over reliance on autonomous driving features are the major reasons for road accidents and fatalities. Driver monitoring systems aims to monitor various aspect of driving and provides appropriate warnings whenever required. Eye gaze estimation is a key element in almost all of the driver monitoring systems. Gaze estimation aims to find the point of gaze which is basically,” -where is driver looking”. This helps in understanding if the driver is attentively looking at the road or if he is distracted. Estimating gaze point also plays important role in many other applications like retail shopping, online marketing, psychological tests, healthcare etc. This paper covers the various aspects of eye gaze estimation for a driver monitoring system including sensor choice and sensor placement. There are multiple ways by which eye gaze estimation can be done. A detailed comparative study on two of the popular methods for gaze estimation using eye features is covered in this paper. An infra-red camera is used to capture data for this study. Method 1 tracks corneal reflection centre w.r.t the pupil centre and method 2 tracks the pupil centre w.r.t the eye centre to estimate gaze. There are advantages and disadvantages with both the methods which has been looked into. This paper can act as a reference for researchers working in the same field to understand possibilities and limitations of eye gaze estimation for driver monitoring system.
각 국의 민족 춤 온라인 콘텐츠 구축 설계 및 활성화 방안

The purpose of this study is to provide online content for national dances of each country performed in Korea for 20 years so that everyone can share them in the thesaurus method and activate them. The performances so far are 220 ethnic dances from Korea, Japan, China, India, Indonesia, Philippines, Bangladesh, Malaysia, Mongolia, Cambodia, Tibet, and Vietnam. The implemented website will be able to publicize the excellence of our culture, and it will be able to provide the opportunity to understand the world culture not only in Korea but also in all countries of the world by producing cultural contents through traditional cultural contents and tourism commercialization. This will contribute to enhancing the cultural understanding of the international community by establishing an academic foundation for promoting traditional culture and ethnic dance research and promoting exchanges among nations around the world.
LibGuides: Test Prep: eBook and Physical collections

Explore our collection of test prep materials. Including GMAT, MCAT, GRE, LSAT, NCLEX and more
Introduction: Big Data, Auto Machine Learning, and Data Streams

Data streams are a class of data that is continuously updated and captured and grows in volume and largely unbounded [Aggarwal, 2007; Wrench et al., 2016]. Consider how our everyday lives contribute to data streams. Every time we purchase something with a credit card, the purchasing event information about your name, purchase amount, product purchased, time and date purchased, location where it was purchased, quantity, product code, and so on are all captured in real time and stored in a data storage platform capable of storing large amounts of data. Browsing the Web also results in enormous amounts of data flowing through IP networks that are being captured by your Internet service providers (ISPs). Even the cars we drive are becoming more connected to the Internet. The car manufacturers are capturing and storing all of the telemetry and GPS data.
Hand Talk Gloves With Flex Sensor

In general, speech impaired people have difficulty in communicating with each other who has no knowledge of sign language. The past implementation of this project involved using image processing concept and accelerometer. But the drawback of the implementations of that projects were non portable and too expensive. Our project involves an IOT based hand glove which is fitted with flex sensors. Flex sensors are the input sensors which provides input to the arduino, these sensors vary the resistance value based on the degree of bend made by the fingers, that is the more the bend, the more the resistance value. The output from the sensors is in form of analog and is converted to digital and further processed by the microcontroller. In this project we have used hardware components like arduino uno, speaker for audio output, flex sensors, audio recognizer, breadboard. The programming platform used in this project is arduino ide.
The Incentive and Supervision Mechanism of Banks on Third-Party B2B Platforms in Online Supply Chain Finance Using Big Data

The incentive and supervision design of cooperation between banks and B2B platforms was studied under the electronic warehouse receipt pledge financing model. Under the assumptions of B2B platform risk, neutrality, and risk aversion, a principal-agent model for cooperation was established between banks and B2B platforms. Its purpose was to expand and compare the models by adding supervision variables. It also helps to analyze the effects of risk aversion coefficients on effort level, fixed payment, incentive coefficients, and the impact of bank income. This paper has analyzed the banking system’s incentives and supervision mechanisms by performing numerical analysis on big data. We have used MATLAB for numerical analysis. The results show that banks’ expected benefits when cooperating with risk-neutral B2B platforms are always greater than the expected benefits obtained when cooperating with risk-averse B2B platforms. But when banks act, the increase in profits exceeds the cost of regulatory measures. Besides, when the bank takes supervisory measures, the profit will be greater than the profit without supervisory measures. Hence, the B2B platform’s ability to recover losses is positively correlated with the bank’s expected utility. The cost coefficient of the B2B platform is negatively correlated with the bank’s expected utility. The risk aversion degree does not affect the optimal effort level of the B2B platform, but it affects the optimal fixed payment and the optimal incentive coefficient.