Reviewerly/exHarmony huggingface dataset:
A Meta-Discourse Analysis on Factors Affecting the Development of Dialogue between Russia and Korea in XIX Century

This study aimed to investigate the factors affecting the development of dialogue between Russia and Korea in XIX century. In this study a meta-discourse analysis was done on the issue of the first dialogue between Russians and Koreans. Some researchers recognize the contact that occurred in the XIII century as the first contact between them, while there is also significant research which deems meetings in the XVII century as the first contact. In Russia, the first Korean language courses and lectures in the history and geography of Korea started at the Saint Petersburg University and the Eastern University in Vladivostok. Notably, the Orthodox Missionary Society in Kazan created textbooks for Russian Koreans. The following methods have been used in this paper: analysis of research literature regarding the subject; case study method for analyzing examples; instrumental observation. The results suggested a substantial difference in the use of metadiscourse markers between Russia and Korea. Furthermore, each learner group displayed the specific characteristics of metadiscourse, which offer suggestions for improving L2 learners’ writings. Furthermore, this paper uses general scientific methods such as: analysis and synthesis to determine goals, resources and tools of the subject concept, as well as structural approach.
ROLE OF TECHNOLOGY TO TEACH SPEAKING SKILLS IN HSC LEVEL STUDENTS IN BANGLADESH

The study presents the way of teaching speaking skill in the context of English as a foreign language (EFL) with the best use of technology for the intermediate level students in Bangladesh. It also suggests the teachers regarding the ways of teaching spoken English to the Bangladeshi EFL learners through technology. The effectiveness and problems of using technology have also been depicted here. 20 teachers of six renowned colleges of Dhaka are interviewed as well as 4 questions are asked to the students about the inability of spoken English. After the survey it can be said undeniably that using technology in teaching spoken English to the intermediate students is more effective than any other means. At present, most of the students are using mobile phone, computer, laptop etc. and they are passing huge time. When they will get the opportunity of learning English, they will concentrate on it very easily. Most of the teachers and students are agreed to use technology for learning spoken English. Very few teachers are disagreed about it reason is that  they are not trained of using technology as well as they told if they are trained to us technology, they are eager to use computer, laptop for teaching. Keywords: Technology, teaching tactics, Projector, Spoken English,  Facebook
Multimodal Relation Extraction of Product Categories in Market Research Data

Nowadays, large amounts of unstructured data are constantly being generated and made available through websites and documents. Relation extraction, the task of automatically extracting semantic rel ...
COMPUTER-ASSISTED ALL, AML, CLL, CML DETECTION AND COUNTING FOR DIAGNOSIS OF BLOOD CANCER

Leukemia could be a cancer of white blood cells (WBCs) which damages blood and bone marrow of shape. It can be fatal illness if not diagnose at earlier stage. Typically, the complete blood count (CBC) or morphological image analysis is employed to manually diagnose the malignant neoplastic disease cells. These ways are time consuming and fewer correct that must be mounted. In this paper we've planned an automatic technique for the detection of Acute lymphocytic leukemia (ALL), Acute myeloid leukemia (AML), Chronic lymphocytic leukemia (CLL), Chronic myeloid leukemia (CML) by microscopic blood image analysis. This approach initially sections out the various kinds of cells from the image i.e. White blood cells, red blood cells and platelets. Afterward Lymphocytes are separated from the white blood cells. Then form and color options are extracted from these lymphocytes that are given to KNN to classify the cells into traditional and blast. After that the counting of the WBC cells are also detected for accurate diagnosis. This automated malignant neoplastic disease detection system found to be more practical, fast and correct as compared to manual identification ways.
Multi-Tenancy Security in Cloud Computing : Edge Computing and Distributed Cloud

With the advent of technology cloud computing has become the next generation of network computing where cloud computing can deliver both software and hardware as on-demand services over the Interne ...
Exploration of Vocal Music Teaching Mode from the Perspective of the Age of Artificial Intelligence

The country's governance system and governance capacity have opened a new era. The national strategy of artificial intelligence has penetrated into various areas of people's livelihood and is facing many changes in the new situation. The vocal teaching model and teaching methods from the perspective of artificial intelligence have also undergone tremendous changes. New models of vocal teaching under the background of artificial intelligence, such as MOOC, mobile APP, WeChat, are emerging. They broke the traditional classroom vocal teaching model and reorganized the space-time relationship of vocal teaching. This paper analyzes the unique advantages and existing problems of the new vocal music teaching model under the background of artificial intelligence through new teaching models such as modern online MOOC, mobile APP, and WeChat, and proposes corresponding solutions. This research hopes that talents in the field of vocal music teaching can keep pace with the times, make full use of network technology to quickly optimize traditional teaching models, improve teaching efficiency, and cultivate more and more vocal talents for the country.
Prediksi Pendapatan Penjualan Obat Menggunakan Metode Backpropagation Neural Network dengan Algoritma Genetika Sebagai Seleksi Fitur

The hospital is one of the means of health services for the community, in which there are multiple units, one of which was the installation of a pharmaceutical is a source of revenue for the hospitals contributed by 40 – 60%. Each month the sale of drugs on pharmaceutical erratic installation (fluctuating) and have an impact on earning spharma ceutical installations specifically and at hospitals in General, i.e. against the determination of the lead in policy development and the development of hospitals inthe future. Therefore the forecast or prediction about the drug's sales revenue is urgently needed. Forecasting technique commonly used is the technique of forecastingwith Artificial neural Network method or so-called Artificial neural Network which hasthe best accuracy with the value error. However, the method of Artificial neural Network has a number of shortcomings, so it takes an optimization method, one of themwith Genetic Algorithm optimization methods. In this study using data on drug sales revenue installation hospital Elizabeth Situbondo. In the process of training and testing data in this study using the method of Backpropagation Neural Network and Genetic Algorithm to feature selection. On this panelitian proves that the method of Backpropagation Neural Network with genetic algorithm as a selection of the best RMSE value generating features of 0115. While the test results with the method of Backpropagation Neural Network without Genetic Algorithms as a value generating features selection RMSE 0152.
LibGuides: Academic Continuity: Resources for Instructors

Information on how College Libraries are supporting CofC virtually and in-person during 2021-2022.
Evaluation of Yubimoji Based Gestures for Realizing User Authentication Method Using s-EMG

At the present time, since mobile devices such as tablet-type PCs and smart phones have penetrated deeply into our daily lives, an authentication method that prevents shoulder surfing attacks comes to be important. We are investigating a new user authentication method for mobile devices that uses surface electromyogram (s-EMG) signals, not screen touching. The s-EMG signals, which are generated by the electrical activity of muscle fibers during contraction, can be detected over the skin surface, and muscle movement can be differentiated by analyzing the s-EMG signals. Taking advantage of the characteristics, we proposed a method that uses a list of gestures as a password in the previous study. In order to realize this method, we have to prepare a sufficient number of gestures that are used to compose passwords. In this paper, we adopted fingerspelling as candidates of such gestures. We introduced manual kana of the Japanese Sign Language syllabary and selected the candidate gestures based on them. Their performances were evaluated by constructing their identifier using support vector machines.
Using Blockchain for improving communication efficiency and cooperation: the case of port logistics

Using Blockchain for improving communication efficiency and cooperation: the case of port logistics
LibGuides: Free Resources for Home Use: Storytime

Free resources to keep yourself happy and busy while staying at home during the COVID-19 epidemic.
A method of character verification code recognition in network based on artificial intelligence technology

In order to solve the problem of low recognition rate of network character captcha, a method of network character captcha recognition based on artificial intelligence is proposed. Firstly, the image preprocessing of character verification code is carried out. The weighted average method and the iterative optimal threshold method were used to process and binarise the character verification code image, and the denoised character image was obtained. For the character verification code image after binarisation, Laplace operator is used to segment the image, and the characters in the image are divided into blocks. Finally, according to the feature vector, the artificial neural network model is used for sample training and adaptive learning. Simulation results show that this method has higher recognition rate, better adaptability and robustness than the existing methods. This method can effectively recognise character verification codes.
A Security and Privacy-Preserving Path for Enhancing Information Systems that Manage Cross-Cloud Applications

Security is one of the most crucial elements of cloud solutions and at the same time one of the most important obstacles towards cloud adoption. This paper recommends a set of security-related guidelines for adoption by any advanced information system that aspires to offer DevOps capabilities for deploying and reconfiguring cross-cloud applications. These guidelines address several security challenges organised against three categories: user and component authentication, advanced access control and secure communication enablers. This paper also presents how specific security enhancements were designed, implemented and integrated for serving a PaaS platform that supports the lifecycle management of cross-cloud applications.
The Emergence of Brain-Like Functions in Neuromorphic Metallic Nanowire Network

The article by Diaz-Alvarez et al published in Nature reports rather interesting findings suggesting that human brain-like functions emerge in neuromorphic metallic nanowire networks. There are also other findings suggesting that simple systems such as plastic balls can exhibit life-like properties. In this article the TGD inspired model for the latter findings is applied to neuromorphic networks.
ANALISIS KONTRIBUSI PERPUSTAKAAN PERGURUAN TINGGI DALAM MENINGKATKAN PRESTASI AKADEMIK MAHASISWA

Introduction . This study aims to measure the extent of the contribution of libraries in sustaining the tri dharma of higher education, by analyzing the activities of students in the library while undergoing lectures with academic achievement (GPA and study period). Data collection method . Research location at the Andalas University Library Unit. The data collection method is done by purposive sampling, based on certain criteria, such as year of entry, level of education, as well as the distance between faculty and library. The study sample was taken from data on the number of visits and the number of student loan collections during the course, which were used as the dependent variable. Whereas academic achievement (independent variable) is measured by GPA and graduate study period. Data analysis . In conducting the analysis, respondents are grouped into 5 categories using a Likert scale, based on the number of visits and the number of books borrowed. After that, the effect on the GPA and the study period was tested using the ANOVA method with the SPSS version 23 application test tool. Results and Discussion . The test results of influence the number of visitors to the GPA produce a significant value of 0,000, and the effect on the study period produces a value of 0.590. While the influence of the number of loans to the GPA produces a significant value of 0,000, and the effect on the study period is 0.230, with a significant limitation of <0.05 Conclusions and recommendations . Based on the results of this study it was concluded that the level of visits and utilization of library collections on the Andalas University campus were still very low. Though these activities significantly influence the increase in student GPA but not for the study period.
LibGuides: Remote Research and Dance: Streaming Dance

This guide brings together the varied resources available to our patrons while conducting their research remotely.
CLASSIFICANDO CÉDULAS BRASILEIRAS (R$) USANDO ANÁLISE DE IMAGEM POR SMARTPHONE

CLASSIFYING BRAZILIAN BANKNOTES (R$) USING SMARTPHONE IMAGE ANALYSIS.A new method to identify the authenticity of Brazilian banknotes (R$) is proposed using digital image analysis by a smartphone application, Photometrix ® , associated with chemometric tools.Authentic banknotes (n = 4) obtained in local bank and falsified (n = 12) by the author himself by means of three printers (laser-Deskjet ® , wax-Color Qube ® and inkjet-Deskjet ® ) were used for the development of the methodology.An experimental planning was performed to evaluate the authenticity of the banknotes determining: the best region (holographic band, tactile region in the lower left and right upper number, effigy microimpressions, lower number left, animal figure, watermark and puzzle); Region of Interest (ROI) (16x16; 32x32 and 64x64 pixels), focal length (8, 12, 15 and 20 cm) and variation of the smartphone (Motorola G5 Plus, Samsung S7 and LG K10).The best regions chosen were effigy microimpressions and round the animal.Promising results were obtained from ROI 16x16 pixels with focal length fixed at 10 cm.Thus, the application presents promising features for analyzing the authenticity of banknotes by digital images making it fast, non-destructive, portable, with low cost, and can be accessed by all society.
Dataverse as a CLARIN repository application

Presentation at CLARIN Centre Meeting 2020 (online workshop). Link to the event: https://www.clarin.eu/event/2020/centre-meeting.
2018-2019 District and Campus Coordinator Resources

Student Assessment Home  | Assessment A–Z Directory | Contact Student Assessment The instructions in the District and Campus Coordinator Manual (DCCM) explain the responsibilities of testing coordinators for the STAAR, STAAR Spanish, STAAR L, STAAR A, STAAR Alternate 2, and the TELPAS assessments. To view
Neural Image Inpainting Guided with Descriptive Text

Neural image inpainting has achieved promising performance in generating semantically plausible content. Most of the recent works mainly focus on inpainting images depending on vision information, while neglecting the semantic information implied in human languages. To acquire more semantically accurate inpainting images, this paper proposes a novel inpainting model named \textit{N}eural \textit{I}mage Inpainting \textit{G}uided with \textit{D}escriptive \textit{T}ext (NIGDT). First, a dual multi-modal attention mechanism is designed to extract the explicit semantic information about corrupted regions. The mechanism is trained to combine the descriptive text and two complementary images through reciprocal attention maps. Second, an image-text matching loss is designed to enforce the model output following the descriptive text. Its goal is to maximize the semantic similarity of the generated image and the text. Finally, experiments are conducted on two open datasets with captions. Experimental results show that the proposed NIGDT model outperforms all compared models on both quantitative and qualitative comparison. The results also demonstrate that the proposed model can generate images consistent with the guidance text, which provides a flexible way for user-guided inpainting. Our systems and code will be released soon.
Assessment of the uneven use of information resources in the business process circuit

An approach is proposed for assessing the uneven use of information resources in the organization’s business processes. Formal representations of the organization’s business processes and security systems are presented, reflecting both business operations carried out in a certain sequence and information resources that ensure the implementation of the relevant business operations, the place of information resources in the general outline of business processes is indicated. The circuits of the security system business processes of and the business processes of the main object of modeling are considered, including both business processes for managing security and business processes for ensuring security management. The assessment of the non-uniform use of information resources in a business process scheme is based on the consistent construction of an information resource incidence matrix for individual business operations, a frequency relationship matrix reflecting the sharing of information resources, and a matrix of derivatives in a discrete formulation. The proposed approach is demonstrated on a conditional example containing both the notional costs of information resources and weighting factors of the importance of business operations that reflect their criticality in the general contour of business processes. Estimates obtained as a result of applying the approach make it possible to group information resources, focusing on the frequency of their joint use in the business processes, which ultimately makes it possible to justify the choice of information resources for protection against threats from cyber intruders.
Tillämpning av maskininlärning med Azure kognitivtjänst QnA-Maker : Applied machine learning with Azure cognitive service QnA-Maker

Tillampning av maskininlarning med Azure kognitivtjanst QnA-Maker : Applied machine learning with Azure cognitive service QnA-Maker
EVALUATION OF MACHINE LEARNING ALGORITHMS FOR SMS SPAM FILTERING

The purpose of this thesis is to evaluate different machine learning algorithms and methods for text representation in order to determine what is best suited to use to distinguish between spam SMS ...
Research on Least Significant Bits (LSB) Image Information Hiding Based on Random Bit Selection Embedding Algorithm

As a hot topic in the field of information security, the principle of information hiding technology is to hide secret information by using the redundant part of the cover object. As an important means of information hiding, and the Least Significant Bits (LSB) image information hiding technology directly replaces the least significant bit of the image with the secret information need to be hided. Therefore, the LSB method has a high imperceptibility and a small change of the image, which makes it widely used in the field of information hiding. This study improved the traditional LSB image information hiding algorithm, and the improved algorithm of embedding secret information in the random interval position in the image was implemented, and last achieved better concealment and security of information hiding.
PERAMALAN MENGGUNAKAN METODE WEIGHTED FUZZY INTEGRATED TIME SERIES (Studi Kasus: Harga Beras di Indonesia Bulan Januari 2011 s/d Desember 2017)

Fuzzy Time Series (FTS) is a time series data forecasting technique that uses fuzzy theory concepts. Forecasting systems using FTS are useful for capturing patterns of past data and then to using it to produce information in the future. Initially in the FTS each pattern of relations formed was considered to have the same weight besides using only the first order. In its development the Weighted Fuzzy Integrated Time Series (WFITS) which gave a difference in the weight of each relation and high order usage has been appeared. Measuring the accuracy of forecasting results is used the value of Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE). In this study both the first-order and high-order WFITS methods were applied to forecast rice prices in Indonesia based on data from January 2011 to December 2017. In this regard, the results of the analysis obtained data forecasting using Lee's high-order model WFITS algorithm (1,2,3) giving the value of RMSE and MAPE on the data testing in a row as many as 69,898 and 0.47% while for the RMSE and MAPE on the training data is as many as 70.4039 and 0.54%. Keywords: Fuzzy Time Series, Weighted Fuzzy Integrated Time Series, RMSE, MAPE, High-Order, Rice Prices
LibGuides: Student Guide: Finding Library Resources Online: Find and Access E-Books

Best practices and recommended search strategies for locating and using library resources online.
OBSTACLE AVOIDING CAR USING RASPBERRY PI 3 B

The trajectory scheme is one of the most important points of choosing and positioning the tasks performed by robotic manipulators. In this work, we have introduced a robot ,which is compact, autonomous and fully functional. This robot or a smart car is designed to feel any obstacle in its path, to avoid it and to restart it, involving pre-computation of an obstacle-free path. Ultra sonic sensors were adopted to implement a real-time obstacle rescue system for wheeled robot, so that the robot could continuously detect the surroundings, avoid obstacles, and move towards the targeted area. The model has tremendous applications in vacuum cleaners, hidden paths, parking systems, automobile assembling and chemical industries, in scientific exploration, emergency rescue and other isolated environments. We use a Raspberry Pi 3B+ with a motor shield with DC motors to make the car, and for sensing we include a ultrasonic sensor that accurately and efficiently detects any obstacle in the path of smart car. Detects from. The Raspberry Pi is coded such that the smart car moves backwards when interrupted with a maximum limit of 50cms in ideal test conditions. During the making of this model, we educated ourselves with the Raspberry Pi coding language, motor shield functionality and largely an ultrasonic.
Integrated routing wasp algorithm and scheduling wasp algorithm for job shop dynamic scheduling

The job shop scheduling problem, in which we should decide the seiresor sequence for preparing a lot of jobs through a few machines in an ideal way, has gotten extensive consideration. In this paper some of the strategies and procedures are looked into and an endeavor to order them as indicated by their propriety for successful use in job shop scheduling has been made. Dynamic scheduling technique are increasing increasingly more uncommon consideration for their fantastic robustness when stood up to with sudden events just as their impressively superior in scheduling.The wasp colony method(WCM) is a recently introduced dynamic method, which bases on natural insect society behavior models. In light of the standard of the wasp method, two unique method, to be specific the routing wasp method(RWM) and the scheduling wasp method, are consolidated to understand the job shop dynamic planning issue. The method are altered to all the more likely adjust to job shop dynamic scheduling environment.  The outcomes demonstrate the rule of the method is straightforward, their computational amount is little, and they can be useful to multi-batchschedulingthroughchangeable pass time because of positive possible.