Reviewerly/exHarmony huggingface dataset:
Classification of microcalcification in mammogram images using Enhanced Support Vector Machine (ESVM) / Muhammad Akmal Firdaus... [et al.]

Support Vector Machine (SVM) is a supervised machine learning algorithm with theability to build a classification model from a labeled dataset. SVM has been broadly usedin image classification of medical imaging such as mammogram images for breast cancerdetection due to its higher classification precision, higher prediction accuracy, bettergeneralization capability and better overall performance. Breast cancer detection iscritically dependent on early detection and accurate diagnosis. However, the existedhistopathological classification of breast cancer has clinical utility that is limited due toinsufficient prognostic and predictive power. The diagnostic decisions by experiencedphysicians can be increased by an effective medical decision support system. Therefore,this research concentrates on Enhanced Support Vector Machine (ESVM) that combinesDiscrete Wavelet Transform (DWT) and Principal Component Analysis (PCA) for betterdata classification accuracy. DWT is used for the extraction of statistical and texturesfeatures of mammogram image. Meanwhile, the employment of PCA is to reduce thedimensionality of the datasets to avoid overfitting thus better accuracy can be achieved.The ESVM focuses on classification of microcalcification in 30 mammogram imagesobtained from the National Cancer Society Malaysia (NCSM). The performance of theESVM method is measured in term of classification rate (CR), specificity (SP), sensitivity(SY) and the accuracy based on Receiving Operating Characteristics (ROC) curveobtained by comparing the images classification results of ESVM and expert findings. Theresult revealed that the classification rate is 90% while for the accuracy based on the ROCCurve is 0.9375. Based on the result obtained, it is proven that ESVM is excellent inclassifying the microcalcification in mammogram images and act as an assistance forradiologists that provides second judgment on medical image readings.
Migration and precipitation of gold in supergene zone in the area of Maopai gold deposit in Jiangxi Province, China

Jiangxi is located in an area with a warm and wet climate. Using the data from hydrochemical research and applying the geochemical modeling program AUSP, the species of aquatic gold were calculated. The results show that the predominant species of gold in water of that area is Au(S2O3)2 3-, with minor amounts of Au(OH)-. Under the hydrochemical conditions in the Maopai area and according to calculated boundary conditions, the boundary value of Cl- concentration for dominant species of AuCl- equals 35.5 g/1, the boundary value of pH for the species of Au(OH)- to be dominant in water will be 8.1, the boundary value of S2O3 2- for the species Au(S2O3)2 3- to be dominant should be 2.09×10-4 mg/l, and the boundary Eh value for Au(S2O3)2 3- to remain stable should equal or be higher than 294 mV. The hydrochemical conditions for the shallow water in the Maopai area are able to satisfy the demands that are necessary for the migration of gold in the species of Au(S2O3)2 3-, but they are located on the bottom of the stability field. When the Eh value and the concentration of S2O3 2- decrease slightly it will cause the gold to reduce and precipitate. These migration and precipitation conditions can be used to explain why the anomaly of gold in water disperses in a long distance of 3 km, and why deposits of gold exist downstream of the Maopai area.
Scene Change Localization in a Video

Millions of videos are uploaded each day to Youtube and similar platforms. One of the many issues that these services face is the extraction of useful metadata. There are a lot of tasks that arise with the processing of videos. For example, putting an ad is better in the middle of a video, and as an advertiser, one would probably prefer to show the ad in between scene cuts, where it would be less intrusive. Another example is when one would like to watch only through the most interesting or important pieces of video recording. In many cases, it is better to have an automatic scene cut detection approach instead of manually labeling thousands of videos. The scene change detection can help to analyze video-stream automatically: which characters appear in which scenes, how they interact and for how long, their relations and importance, and also to track many other issues. The potential solution can rely on different facts: objects appearance, contrast or intensity changed, other colorization, background chang, and also sound changes. In this work, we propose the method for effective scene change detection, which is based on thresholding, and also fade-in/fade-out scene analysis. It uses computer vision and image analysis approaches to identify the scene cuts. Experiments demonstrate the effectiveness of the proposed scene change detection approach.
Ore system of continental margins: Principles of delineation and estimation

Sikhate-Alin mountains are composed of two ore systems: longitudinal system is spread from north to east and controls tin-wolframic, copper and mercury mineralization; transversal one is sub-latitudinally spread and contains mostly tin-polymetallic mineralization. This peculiar feature might be determined by alpinotypical tectogenesis and durable rift development transstructurally oriented to the thrusting zone. Correlation between ore mineralization and these tectonic structures is well manifested in the anomalous fields of scattering aureols, primary and secondary, of major ore elements. Regional peculiarity of this phenomenon proved the mentioned tectonic structures to be usable for delineation of metallogenic zones, ore formation analysis and forecasting of reserves.
Seven Basic Expression Recognition Using ResNet-18

We propose to use a ResNet-18 architecture that was pre-trained on the FER+ dataset for tackling the problem of affective behavior analysis in-the-wild (ABAW) for classification of the seven basic expressions, namely, neutral, anger, disgust, fear, happiness, sadness and surprise. As part of the second workshop and competition on affective behavior analysis in-the-wild (ABAW2), a database consisting of 564 videos with around 2.8M frames is provided along with labels for these seven basic expressions. We resampled the dataset to counter class-imbalances by under-sampling the over-represented classes and over-sampling the under-represented classes along with class-wise weights. To avoid overfitting we performed data-augmentation and used L2 regularisation. Our classifier reaches an ABAW2 score of 0.4 and therefore exceeds the baseline results provided by the hosts of the competition.
Cloud Service Orchestration

There is a need for a service orchestrator which will Manage the Life cycle of the application/network services, Perform Day 0, Day 1 and Day 2 operations on these services, cater to the need of the hybrid cloud Deployment, Monitor the services and heal the services dynamically. The current work will provide Design and Implementation of a Cloud service orchestrator, which will help the application/network service providers to seamlessly deploy their application/network on a desired Cloud (Private or Public)
Feature Fusion Vision Transformer for Fine-Grained Visual Categorization

The core for tackling the fine-grained visual categorization (FGVC) is to learn subtle yet discriminative features. Most previous works achieve this by explicitly selecting the discriminative parts or integrating the attention mechanism via CNN-based approaches.However, these methods enhance the computational complexity and make the modeldominated by the regions containing the most of the objects. Recently, vision trans-former (ViT) has achieved SOTA performance on general image recognition tasks. Theself-attention mechanism aggregates and weights the information from all patches to the classification token, making it perfectly suitable for FGVC. Nonetheless, the classifi-cation token in the deep layer pays more attention to the global information, lacking the local and low-level features that are essential for FGVC. In this work, we proposea novel pure transformer-based framework Feature Fusion Vision Transformer (FFVT)where we aggregate the important tokens from each transformer layer to compensate thelocal, low-level and middle-level information. We design a novel token selection mod-ule called mutual attention weight selection (MAWS) to guide the network effectively and efficiently towards selecting discriminative tokens without introducing extra param-eters. We verify the effectiveness of FFVT on three benchmarks where FFVT achieves the state-of-the-art performance.
EUNICERT: ETHEREUM BASED DIGITAL CERTIFICATE VERIFICATION SYSTEM

The fake certificate is a special global problem in today's digital age. Thousands of universities and educational institutions around the world do not exist but can release hundreds of millions of fake degrees. Verifying the integrity of qualifications is a real challenge for today's employers. Applying the anti-data modifying properties of blockchain technology, this study proposes a solution issuing and verifying digital certificates called EUniCert to solve this problem. By changing the design and integrating new consensus algorithm used in Ethereum platform into the Unicoin network that was used to verify and store the information related to the issued digital certificate, the EUniCert improves the latency to validate transactions as well as the number of verified blocks in the blockchain network compared to the previous solution that we have proposed. We implement a simple blockchain system to illustrate the management operation of the digital certificates on the ethereum platform. Besides, we conduct a simulation to evaluate the performance of our proposal compared with the previous system. The result is that the average latency decreases by 3.27 times as well as the number of verified blocks increases by 11% compared with the previous system.
Penerapan Gamifikasi Dalam Smart Tourism : Studi Literatur

Tourism emphasizes the authenticity of an area with the principle of preservation and sustainable development, but technology is one factor that influences it enough to attract tourists or ease management in the tourism sector. The terminology of smart tourism appears as a direction in the support system for supporters in the tourism sector. One system in implementing smart tourism is gamification, which is still a lot of ordinary people in the system. This article examines the extent of the application of gamification in the concept of smart tourism and what things are still obstacles in the application of gamification in the tourism industry so that it can be a recommendation for further research. So that both are expected to provide an understanding of the application of gamification and the extent of realization in the concept of smart tourism. The method used in this research is a literature study. The results got by the application of gamification in smart tourism are very helpful in the tourism industry. This system provides tourism development, namely providing education, using the potential and use of technology. Gamification is a system where tourists are given more flexibility for activities and interacting with tourist areas, both visually and directly.
Integration of Controlled Joint Mixed-Year Teamwork for Designing Ultra Small Satellites Into the Specialist Degree Educational Program

The paper is concerned with methodological problems of search of new ways of reformation for space engineering education. The problems of renewal of the content of course units and educational forms are of special relevance in the field of education of specialists in design of small and ultra small spacecrafts. Renewal of educational forms is frequently associated with the choice between the pragmatic and ontological approaches in education. We present the experience gained at Bauman University in creation of individual plans of education of students. Our studies show that mixedteam work enables one to realize continuous transfer of practical skills, and in parallel to secure positive environment for personal growth of future engineers.
The Use of Pop-Up Book Media on the Reading and Writing Skills of Class I Elementary School Students

This research aimed to find out the effect of implementation of pop-up book media towards the first grade students’ reading and writing skills of SD Negeri 6 Gedong Air . The method was quasi experiment used in this research. The research design was non equivalent control group design. Furthermore, The population were class IA and IC consisting of 8 0 students. The samples were class IA and IC consisting of 52 students. In determining the samples, the research used purposive sampling technique. The technique of collecting data were test and non-test. The results of the analysis using simple linear regression showed that r count > r table (0,845 > 0,381) of reading skills and ( 0,869 > 0,381 ) of writing skills. W hich meant that there is a effect of the implementation of pop-up books towards students’ reading and writing skills of the first grade students at SD Negeri 6 Gedong Air Bandar Lampung city , at the year of 2019/2020. Keywords:  Reading Skills, Pop-Up Book Media, Writing
Penerapan Model Pembelajaran Scramble dalam Meningkatkan Aktivitas dan Hasil Belajar Matematika Pada Peserta Didik Kelas V SD

This study aims to improve students' mathematics learning activities and outcomes by applying the Scramble-type cooperative learning model in grade V SDN SATAP 02 Konsel in the 2019/2020 school year. This type of research is a classroom action research conducted in two cycles. The PTK Kurt Lewin Scheme was used in this research which includes planning, implementation, observation and reflection. Data collection techniques were observation sheets, tests, and documentation which were analyzed descriptively. The results showed that the application of the Scramble learning model can improve the learning activities of class V SDN SATAP 02 Konsel. The results of the observation sheet activity of students in cycle I was 67%, then increased to 86% with the Very Good category in the cycle two. Besides, the use of such method can improve the results of students’ mathematics learning. Before the treatment, the average students’ learning score was 64.46 with 60% completeness. After the first cycle, the average learning score reached to 77.25 with completeness of 75%. Then the learning outcome rose to 82.25 with 81.25% completeness in cycle II.Keywords: Scramble, Aktivitas belajar, Hasil belajar Matematika
E-Brain (Artificial Intelligence): An Edge to Indian Banking System

Banks are automating their processes, migrating their infrastructure and applications to the cloud to create a seamless customer journey. Transformative technology has enabled banks and financial institutions to automate their operations based on advanced data-driven. Banks are adopting E-BRAIN based anti-money-laundering, anti-fraud, compliance, credit-underwriting and smart contracts technology in their operations. These applications have been embraced by the investment banks as regulatory framework is failing to combat conventional way in combating against money laundering. E-BRAIN will focus on cognitive application in functional areas of business along with investment and compliance sectors of financial services industry. Adopting E-BRAIN based anti-money-laundering, anti-fraud, compliance, credit-underwriting and smart contracts technology in their operations.
LibGuides: Research Data Support Services for Researchers: Costing Data Management

This guide supports the University’s Policy on Research Data Management contained within the Research Integrity Policy Framework. The guide provides guidance for Swansea University researchers on expectations, obligations, advice and support for research Information relating to estimating the cost to manage research data
Knowledge extraction for automatic driving control by using local correlation features

In recent years, with the rapid development of artificial intelligence technology, more and more companies have shifted their attention to the field of automatic driving. The target detection is one of the core technologies in the field of automatic driving, which can perceive the environment by using distributed sensors and affect the vehicle driving control. How to describe vehicle image is particularly important in target detection for automatic driving. In this paper, we combine edge information, HOG features and local association features to describe the targets in image for automatic driving. Then, the extracted features are used to learn a classifier for further vehicle detection. The experimental results show that the proposed method can achieve better prevision, recall, and F1‐measure than merely using edge features or HOG features. The proposed method can extract more comprehensive features for vehicle detection.
AN ANALYSIS OF THE STUDENTSâ€™ WRITING ERROR IN REPORT TEXT

This research purposed to measure the studentsâ€™writing errors in report text so that it can find the kinds of errors that faced by the students in the writing of report text. The subject of this research were the students of grade X at SMA Negeri 1 Sei. Balai in academic year of 2015/2016. The population of the research were 105 students in three classes while the sample were 27 students. This research was conducted in descriptive research and the method in taking the sample was random sampling. The instruments for this researchwere observation and interview. The result of this study was that most students did errors in the word form. 11 students did errors in their construction in word form in writing report text and then followed by the errors in word choice. 10 students did errors in their word choice. Next, followed by error in punctuation. 9 students did error in the punctuation. It is suggested in teaching writing especially in writing report text, the teacher should put a serious intention in the part of word choice, word form, and also punctuation since these instruments are the most troublesome parts in this study of the studentsâ€™ writing error
The Saviour Shoe - S.O.S Sdn Bhd / Nureen Farahiyah Mat Said

The company was named as S.O.S SDN BHD is partnership business that supplied the safety shoe called the Saviour Shoe. S.O.S SDN BHD aims to be the most competitive and reliable company in provide technological shoe. Our business concept is basically to provide shoe with technology devices that mainly focus on safety of people nowadays. The concept of the saviour shoe are to reduce the risk of crime happened to people’s nowadays while improve the quality of life by providing them one step ahead of security. The Saviour Shoe used the elements of product concept such as usability by providing wireless charging to improve the productivity of usage of the shoe. The price concept of the shoe is based on “affordable- luxury” concept which offered device technology in the shoe with affordable and reasonable price while at the same time providing people the best quality and functionality of the shoe.
СОЦИАЛЬНЫЕ АСПЕКТЫ ОБРАЗОВАТЕЛЬНОЙ МОБИЛЬНОСТИ БУДУЩИХ ИНЖЕНЕРОВ

The article explores some issues of educational mobility of future engineers. Educational mobility is considered here as an important component of social mobility in two directions: external and internal. The authors point to the specific aspects of educational mobility of future engineers, manifested both internationally (studying new technological trends, familiarization with the experience of leading countries, «brain drain») and at the domestic level (uneven training, the consequences of the outflow of young specialists from the regions).
Study on the Korean language education using the Madangnori

Background: As Korean language education develops, Korean culture is emphasized, too. Even with recognition of the importance of language classes accompanying Korean culture in the classroom, there are many difficulties when connecting those in actual classes. This is because the culture is based on time, space and experience in daily life. Purpose: 'Madangnori' has the same attributes as the nature of this culture. The openness, flexibility, and distinctiveness of Madangnori are enough factors for Korean language education including Korean culture. Methodology/Approach: First, the theory of Madangnori is established. Second, from the standpoint of Korean language education, Madangnori that can be targeted at beginner, intermediate, and advanced level is selected. Third, the contents of language education and cultural education for each level are suggested. Findings/Conclusions: Therefore, this research suggests Korean language education using 'Madangnori', composed of cultural elements of Korean traditional music, dance, literature (narrative) and drama. Theme of beginner level is the daily life of Korean people, includes introducing the names of Korean food as language education, and playing 'Gatekeeper game', which is one of various forms of Ganggangsulae, as culture education. At intermediate level, I propose performing a puppet show after learning a fairy tale, 'The Sun and The Moon', and playing 'Rice cake selling' game on mingling phase. The advanced level introduces 'Pansori' through 'Chunhyangjeon' and base rhythm of 'Samulnori' through 'Ichae rhythm'. Implications: There is a great implication that 'Madangnori' has, which can embrace the multinational background of Korean language learners with an open consciousness. This is because it is likely to be developed into a common culture or a global culture beyond blood ties, religion and locality. With the activities that utilize various elements of 'Madangnori', it is possible to realize the goal of 'Korean language education', which is 'fluent communication'. We hope that this paper will be a practical and useful material that provides productive and concrete cultural contents in Korean language education.