Reviewerly/exHarmony huggingface dataset:
Prioritization of Transmission Lines in Expansion Planning Using Data Mining Techniques

In transmission expansion planning phase, a clear and multifacet understanding of proposed transmission lines and their respective associations in transmission expansion plans is crucial to analyze and compare similar expansion plans. It is also equally important to analyze that how many transmission lines are fully or partially frequent with other transmission lines to chalk down the progression pathway. While the related researches are focusing on the refinement of transmission expansion plan under different scenarios, only few researchers have observed the importance of finding the associative correlations between the expanded plans and the lines based on different scenarios. This paper attempts to discover the associative correlations among the transmission lines of different proposed plans to facilitate the effective execution during the implementation phase. This paper presents the applicability of the existing data mining approaches on this power system problem to make the transmission system more reliable and robust, while analyzing the future scenarios in expansion planning.
BOTTOM-UP THEORY AND PHONICS INSTRUCTION: IMPLICATIONS FOR BEGINNING READING

This paper discusses the relationship of bottom-up theory to phonics instruction. It views reading as a learning tool that facilitates learning in other areas of study. Hence, it highlights the link between bottom up theory and phonics-based instruction as well as their relevance to beginning reading. The paper discusses bottom-up theory in relation to phonics reading instruction. Phonics is seen as a method that is based on the framework laid out in the bottom-up theory. The application of phonics to classroom instruction was also discussed. The paper concludes that phonics seems to be effective for beginning reading instruction. It suggests that teachers who use the method should monitor the progress of their students to know the ripe time to introduce other methods of teaching reading for effective reading instruction. It finally recommends that teachers should be trained on the proper use of phonics for effective reading instruction. Article visualizations:
Functional Linear Models for the Analysis of Similarity of Waveforms

In seismology methods based on waveform similarity analysis are adopted to identify sequences of events characterized by similar fault mechanism and propagation pattern. Seismic waves can be considered as spatially interdependent, three dimensional curves depending on time and the waveform similarity analysis can be configured as a functional clustering approach, on the basis of which the membership is assessed by the shape of the temporal patterns. For providing qualitative extraction of the most important information from the recorded signals, we propose the use of metadata, related to the waves, as covariates of a functional response regression model. The temporal patterns of this effects, as well as of the residual component, obtained after having taken into account the most relevant predictors, are investigated in order to detect a cluster structure. The implemented clustering techniques are based on functional data depth.
Refactoring Misuse Case Diagrams using Model Transformation

Secure software engineering entails that security concerns needs to be considered from the early phases of development, as early as the requirements engineering phase. Misuse cases is a well-known security analysis and specifications techniques, based on the popular use case modeling technique, that takes place in the requirements engineering phase. Similar to use case modeling, misuse case modellers are prone to committing modeling mistakes and applying antipatterns. As a result, misuse case models need to be analysed to determine if they contain fallacious design decisions. Changes, known as refactoring, to the misuse case diagrams are then required to remedy any design issues and such changes which would normally be manually applied. However, manual application of such changes in misuse case models are prone to human error, further compounding the design issues in a given misuse case model. To this end, this paper presents a model transformation approach to systematically apply changes to misuse case models. A case study related to a book store is presented to illustrate the application and feasibility of the approach.
ViDupe-Duplicate Video Detection as a Service in Cloud

Detecting near-duplicate videos in the cloud is computationally intensive due to sheer number of videos and their large file sizes. To address this challenge, we propose to improve algorithm efficiency by enhancing and revising existing metadata and content comparison methods, and to enable public access by developing a web service. As a proof of concept, a duplicate video detection system called ViDupe is developed that can quickly scans user’s Google drive for duplicates.
Probe into Advancing the Process of Farmers' Organization in the New Era

Promoting farmers' organization is one of the efficient ways to promote the organic connection between small-scale farmers and modern agriculture. The main body of new-type agricultural management is the main carrier to improve the degree of farmers' organization. This article starts with the analysis of the development status of the new type of agricultural management subject, and makes a horizontal comparison to analyze the progress of peasants' organization. Finally, it puts forward some countermeasures and suggestions to promote the process of peasants' organization.
Deep Multi-instance Volumetric Image Classification with Extreme Value Distributions

Predicting the presence of a disease in volumetric images is an essential task in medical imaging. The use of state-of-the-art techniques like deep convolutional neural networks (CNN) for such tasks is challenging due to limited supervised training data and high memory usage. This paper presents a weakly supervised solution that can be used in learning deep CNN features for volumetric image classification. In the proposed method, we use extreme value theory to model the feature distribution of the images without a pathology and use it to identify positive instances in an image that contains pathology. The experimental results show that the proposed method can learn classifiers that have similar performance to a fully supervised method and have significantly better performance in comparison with methods that use fixed number of instances from a positive image.
A CNN-Based Depth Estimation Approach with Multi-scale Sub-pixel Convolutions and a Smoothness Constraint

Depth estimation from a single image is of paramount importance in various vision tasks, such as obstacle detection, robot navigation, 3D reconstruction, etc. However, how to get an accurate depth map with clear details and a fine resolution remains an unresolved issue. As an attempt to solve this problem, we propose a novel CNN-based approach, namely $$MSCN_{NS}$$ , which involves multi-scale sub-pixel convolutions and a neighborhood smoothness constraint. Specifically, $$MSCN_{NS}$$ makes use of sub-pixel convolutions which fuse multi-scale features from different branches of the network to retrieve a high resolution depth map with fine details of the scene. Furthermore, $$MSCN_{NS}$$ incorporates a neighborhood smoothness regularization term to make sure that spatially closer pixels with similar features would have close depth values. The effectiveness and efficiency of $$MSCN_{NS}$$ have been corroborated through extensive experiments conducted on benchmark datasets.
Towards a WHAT-WHY-HOW Taxonomy of Trajectories in Visualization Research

Effective analysis of movement often requires a comprehensive approach where computational and visual methods are combined to address a wide variety of tasks involving movers with diverse characteristics. In order to help the process of designing effective methods for a wide range of movement analysis cases, we develop a provisional taxonomy that links what Brehmer et al. [BM13] term statements of WHY-WHAT-HOW with tasks, types of movers, context and methods used to compute or visualize data. Within this document we present the origin of this taxonomy, the process we followed to populate it, discuss the novel categories within it, and finally use it to explore relationships between elements of trajectory analysis. Our main contribution is to provide a new means of connecting elements of WHY-WHAT-HOW when analysing trajectories.
PECULIARITIES OF A. K. LYADOV’S INDIVIDUAL STYLE (BY THE MATERIALS OF EPISTOLARY HERITAGE)

The article examines the individual style peculiarities of the composer-miniaturist A. K. Lyadov, who is known for his versatile creative thinking, brilliant composer’s, literary and performing skills. Special attention is paid to harmonious interrelation of the musician’s personality reconstructed by the materials of epistolary heritage and his refined, laconic composer’s style. The analysis of A. K. Lyadov’s letters allows the author to re-evaluate the composer’s place and role in the history of music. Being a keeper of the Russian classical traditions, he was at the same time in tune with the key trends of the beginning of the XX century - symbolism, impressionism and “The World of Art (Mir Iskusstva)” movement. These artistic trends influenced greatly the evolution of his creative thinking.
MOBILE APP SECURITY & FEATURES LEVEL ASSESSMENT

Fraud Ranking in the mobile App market refers to fraudulent or deceptive activities which have a purpose of bumping up the Applications in the popularity list. Indeed, it becomes more and more frequent for Application developers to use shady means, such as initiating their Applications sales or posting phony Application ratings, to commit ranking fraud. While the importance of preventing ranking fraud has been widely recognized,there is limited understanding and research in this area.To this end, we provide a holistic view of ranking fraud and propose a ranking fraud detection system for mobile Apps. Specially, we propose to accurately locate the ranking fraud by mining the active periods, namely leading sessions, of mobile Applications. Such leading sessions can be leveraged for detecting the local anomaly instead of global anomaly of App rankings.Furthermore, we investigate three types of evidences, i.e., ranking based evidences, rating based evidences and review based evidences, by modeling Apps ranking, rating and review behaviors through statistical hypotheses tests. In addition, we introduced an optimization based aggregation method to integrate all the evidences for fraud detection.Finally, we evaluate the proposed system with real-world App data collected from the IOS App Store for a long time period. In the experiments, we validate the effectiveness of the proposed system, and show the scalability of the detection algorithm as well as some regularity of ranking fraud activities.
Kumystin granosyenites complex of the late Cryogenian in Bolshoi Karatau (South Kazakhstan), age substantiation

The results of U–Pb geochronological studies of quartz syenites of the Kumystin complex of the Bolshoi Karatau ridge in southern Kazakhstan are presented and their late Neoproterozoic (717 ± 4 Ma) age is substantiated. Kumystin syenites complex together with rhyolites and basalts of the Kainar Formation are the youngest formations taking part in the basement of Karatau-Dzhebagly precambrian massif and formed in the second half of Cryogenian. The data set about the ages of the youngest complexes taking part in the basement of precambrian massifs of the Western part of the Central Asian belt indicates that the ending of magmatic activity within various massifs occurred asynchronously during the Neoproterozoic.
Geology differentiation: An integrative approach to imaging geology at depth

Acta Geologica Sinica - English EditionVolume 93, Issue S1 p. 344-344 Session 9: Emerging techniques for deep earth explorationFree Access Geology differentiation: An integrative approach to imaging geology at depth Yaoguo Li, Yaoguo Li ygli@mines.edu Center for Gravity, Electrical, and Magnetic Studies, Department of Geophysics, Colorado School of MinesSearch for more papers by this authorJiajia Sun, Jiajia Sun Department of Earth and Atmospheric Sciences, University of HoustonSearch for more papers by this authorAline Melo, Aline Melo Universidade Federal de Minas Gerais (UFMG)Search for more papers by this author Yaoguo Li, Yaoguo Li ygli@mines.edu Center for Gravity, Electrical, and Magnetic Studies, Department of Geophysics, Colorado School of MinesSearch for more papers by this authorJiajia Sun, Jiajia Sun Department of Earth and Atmospheric Sciences, University of HoustonSearch for more papers by this authorAline Melo, Aline Melo Universidade Federal de Minas Gerais (UFMG)Search for more papers by this author First published: 31 May 2019 https://doi.org/10.1111/1755-6724.14128AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume93, IssueS1Special Issue: Abstracts of the International Symposium on Deep Earth Exploration and Practices, 24–26 Oct 2018, Beijing, ChinaMay 2019Pages 344-344 RelatedInformation
Privacy in Multiple On-line Social Networks - Re-identification and Predictability

We consider the re-identification of users of on-line social networks when they participate in several different on-line social networks, potentially using several different accounts. The re-identification of users serves several purposes: (i) commercial use so as to avoid redundant mailing to the same user; (ii) enhancement of the information available about these users by unifying information from different sources; (iii) consolidation of accounts by on-line social network providers; (iv) identification of potentially malicious users and/or bots. We highlight that all this should occur within the bounds of the data protection and privacy laws as well as the users’ expectations on such matters to avoid backlash. In this paper, we explore this situation first by a formalization using the SAN model to conceptually structure information as a graph, which includes user and attribute type nodes. This formalization enables us to reason on two issues. First, how to identify that two or more user-accounts belong to the same user. Second, what gains in predictability are obtained after re-identification. For the first issue, we show that a set-difference approach is remarkably effective. For the second issue we explore the impact of re-identification on the predictability by two different machine learning algorithms: C4.5 (decision tree induction) and SVM-SMO (Support Vector Machine with SMO kernel). Our results show that as predictability improves, in some cases different SAN metrics emerge as predictors.
78‐4: An Evaluation of the Color Moving Picture Response Time for the Motion Blur by Brightness and Color of Actual Images

This study provides new measurement method of the motion blur close to the human visual characteristics including both brightness and color and suggests advanced index called the color MPRT which can quantify the color motion blur using primary and Macbeth colors.
The Training on Developing Teaching Materials for German Language Teachers in Ambon

The results of the first phase of this study indicate that the low results of the German Language teacher competency test (UKG) in Ambon City. This is caused by the material scope and level of difficulty of the material UKG much above average abilities German language teacher. In addition the frequency of teacher participation in training courses or German language is very low though has been teaching for years. The essence of the findings of previous studies is that the German language teacher in Ambon city still has a low linguistic competence, in some extreme cases there are teachers at level A1 and A2. The reason why can be clearly be seen from the low frequency of teachers' involvement in the activities of self-development, both individually and collectively through training and courses. On the basis of these findings there should be training for German language teachers. It required training materials as a means of supporting the implementation of the German language teacher training. This research aims to develop teaching materials training includes listening skills, speaking, reading and writing and supported by grammatical components at A2 level. Writing materials this training is based on the procedure of research and development developed by Plomp in Ratumanan et al (2013), that phase, namely (1) preliminary investigation, (2) design, (3) realization / construction, (4) test, evaluation , and revision, and (5) implementation. First to the third phase were implemented in the first phase of the research so that this phase followed by a phase of testing and revision of the well based on the observation and note validator to get the final product. The end product of this study showed that the level of training teaching materials A2 German language teachers include reading and listening skills, speaking and writing. The development of teaching materials have been fulfil several factors such as validity, practicality, and effectiveness, and has fulfilled the principles of development of teaching materials, namely the principles of relevance, consistency principle, the principle of material sufficiency, the principle of conformity with the material in trainees maturity and principles of legibility. Thus the final product of this study declared eligible to be used as teaching materials for German language teacher training in the city of Ambon, even by students who are preparing to take a test at A2 level.
Image Search Re ranking based on Topic Diversity Using K-NN Algorithm

The developing measure of client labeled sight and sound has driven social picture examination and recovery gain significance which has helped individuals arrange and get to client labeled mixed media. Client labeling is uncontrolled, includes uncertainty and profoundly customized thus a crucial inquiry emerges how to decipher the importance of client contributed tag  concerning the visual substance depicted by the tag. Picture’s significance and decent variety are considered and a social re-ranking framework for tag- based picture recovery. As per individual visual data, semantic data and social pieces of information the pictures are re-positioned. The underlying outcomes incorporate pictures contributed by various social clients. Every client may contribute a few pictures. Consequently, first, these pictures are arranged by between clients re-positioning. The clients that have a higher commitment to the given question are positioned higher. At that point, consecutive checking time stamp positioning is performed in which the ideal yield is acquired on the premise of title data and the ongoing time stamp which improves the decent variety execution of picture positioning framework. It additionally checks a number of perspectives used to enhance the importance execution of the picture recovery results. The last recovered outcomes are made out of the chose pictures. Catchphrase importance coordinates the information is recovered for the social picture dataset to quicken the seeking procedure.
PENGGUNAAN EMOJI FOOD SEBAGAI PREDIKTOR PENENTUAN STATUS GIZI BALITA USIA 3-5 TAHUN DI DESA KUBU KECAMATAN KUBU KABUPATEN KUBU RAYA

Nutritional problems are the impact of consumption of nutrients that have not met the body’s needs. Poor intake can cause malnutrition, and vice versa. To find out nutritional intake, a food consumption survey is needed. The current food consumption survey still has some weaknesses when used in describing nutritional status. Researchers make a method called emoji food. Emoji food is a method used to express the perception of eating habits. Emoji food in the form of symbols adapted from emojis in the android smartphone chat application. The purpose of this study was to determine the relationship between the use of Emoji food as a predictor of the determination of nutritional status of children aged 3-5 years in Kubu Village, Kubu District, Kubu Raya Regency. This study entered into the category of observational analytic research with a cross sectional approach where the measurement of the variables was carried out simultaneously from the individual in a single population and the measurement was only carried out at one time or period. From the results of the research BB/TB = Sig. (2-tailed) &lt;5% (0.001 &lt;0.05) which means BB/TB has a relationship with Emoji Food. BB/U value = Sig. (2-tailed) &lt;5% (0.007 &lt;0.05) which means BB/U has a relationship with Emoji Food. IMT/U Sig value. (2-tailed) &lt;5% (0.001 &lt;0.05) which means IMT/U has a relationship with Emoji Food. The conclusion of this study is the relationship of each of the variables of nutritional status, namely between BB/TB, BB/U, and IMT/U with the use of Emoji Food in children aged 3-5 years in Kubu Village, Kubu District, Kubu Raya District. Suggestions from this study Emoji food can be used as an alternative used in assessing and providing an overview of nutritional status.
Using Common User Interface Objects

A user interface must display information to the user. In addition, a user interface must also allow the user to input data such as text or numbers. Finally, a user interface must allow the user to control the app. Displaying data, accepting data, and accepting commands form the heart of any user interface.
Library Guides: Hate: Hate Crimes

This guide provides information on hate in our society. It focuses upon online hate and strategies for dealing with it.
A STUDY ON GENDER AND LANGUAGE DIFFERENCES IN WRITTEN TEXTS

This study aims at investigating gender differences in written texts using Halliday’s framework about the functions of language. Halliday claimed that females’ writing style is, what he described as, ‘involved’ while males’ writing style is more ‘informative’. The results of the study do not confirm Halliday’s assumptions about gender differences in writing. No significant differences were found between males and females in the frequencies of the use of nouns, prepositions, numerals and modifiers. The only significant difference that was found is the use of pronouns, which is not enough to account for the assumptions. This paper also aims to investigate the differences between Arabic and English in the average sentence length, lexical density, and readability. To measure readability, the Gunning-Fog index formula was used. The results show that there was no significant difference between Arabic and English in the average sentence length, but there were significant differences in lexical density and readability.