Reviewerly/exHarmony huggingface dataset:
파노라마방사선사진에서 극좌표를 이용한 안면 비대칭 분석

This study aimed to measure ramal lengths and angles on panoramic radiography applying a polar coordinate system for analyzing facial asymmetry within normal range. Panoramic radiographs taken from 15 males and 15 females (mean age 31.33±3.7 yrs in males and 28.87±2.72 yrs in females) with symmetric-looking faces were selected. The polar coordinate system, length of condylar and ramal height and angles between the ramus tangent and the connecting line of the most inferior point of bilateral orbital rim were measured from panoramic radiographic images. Bilateral differences in the ramal and condylar heights and angles were determined by asymmetric index. The polar coordinate applied for analyzing facial asymmetry uses length and angle measure. The normal range of facial asymmetry was measured using mean and standard deviation of asymmetry index of length and angle measure. A new analysis method using polar coordinate system on panoramic radiograph may provide more accurate analysis for facial asymmetry.
“ATS BREAKER”- A System for Comparing Candidate Resume and Company Requirements

In current scenario, job searching is one of the major challenge faced by people after education.In the job search process, a well-written resume is essential.As the companies receives thousands of resumes, they uses several filtering techniques to identify the most eligible ones according to the company's requirements.This one of the major challenge faced by the candidate in selection process.This paper proposes a model that computes a comparison and based on the results, suggestions are provided to the candidates to modify their resume.The proposed procedure extract information related to technical as well soft skills from the CV's submitted in text, pdf or docx format.The system also provides suggestions for correcting the grammatical errors.The proposed system is designed based on Natural Language Processing (NLP) techniques.
John Denham’s best of <i>Exploration Geophysics</i>

The results of new detailed airborne geophysical surveys over Victoria have been lauded by industry as being a great incentive to increase mineral exploration in the State. These data become especially useful when combined with new semi-detailed geological mapping. The Geological Survey of Victoria has now developed a new methodology to integrate geological mapping with the interpretation of the geophysical data to produce a single composite understanding of the rocks and their relationships. It has required a reappraisal of the way geologists and geophysicists map, both together and separately, and additional training to make the process work.Sufficiently detailed data acquired prior to the geological mapping allows a fully integrated interpretation, using the available geophysical and geological data, to produce maps that reflect both geological and geophysical reality. Previously, geologists and geophysicists worked in partial or complete isolation. Too often geophysicists gave geologists lineament or line maps that bore little resemblance to geological reality, lacked credibility and were almost immediately discarded by geologists as being “unhelpful”. The new process requires geologists and geophysicists to work as a team to reconcile all the geophysical and geological observations to produce an accurate, integrated geological map. It demands that the geologist understands the geophysical responses and the geophysicist understands the geology. Both need to acknowledge the limitations inherent in each method.Presenting the results provides a further series of challenges to the mappers, interpreters, managers and cartographers. We have also yet to integrate the mineralisation history into this mapping process. Meeting these challenges to produce a full and accurate understanding of the geology and geophysics, rather than of one or the other, is essential to ensure increased exploration success.
Reinforcement Learning as Iterative and Amortised Inference

There are several ways to categorise reinforcement learning (RL) algorithms, such as either model-based or model-free, policy-based or planning-based, on-policy or off-policy, and online or offline. Broad classification schemes such as these help provide a unified perspective on disparate techniques and can contextualise and guide the development of new algorithms. In this paper, we utilise the control as inference framework to outline a novel classification scheme based on amortised and iterative inference. We demonstrate that a wide range of algorithms can be classified in this manner providing a fresh perspective and highlighting a range of existing similarities. Moreover, we show that taking this perspective allows us to identify parts of the algorithmic design space which have been relatively unexplored, suggesting new routes to innovative RL algorithms.
Proceso de testing en localización: análisis y propuesta de un modelo de codificación de errores, de informe de errores (bug report) y de test plan

The concept of translation error has been under discussion in Translation Studies since its beg innings. The technological advance in a globalised world like this implies an increase in the provision of localisation services; a process which includes a gre ater number of tasks other than translating text. The objectives of this research are to describ e and analyse theoretical concepts as a theoretical review; to determine the necessary parameters to carry out a testing task of localised products and to standardise and system atise the testing process. There is also a need to analyse the types of errors being made in a localisation process, as well as to conduct a taxonomy of these errors and propose an error encoding. In addition, a bug report model applicable in the revision phase of t he localisation process is created together with a set of instruction s for the localisers with the aim of unifying the process of revision and testing, increasing the quality of the final product.
GAMIFICATION AS THE TRAINING METHOD OF STAFF

This article examines a new tool for staff training – gamification, its advantages and disadvantages, as well as methods for implementing this tool in the personnel training system. Developing of a game situation in the training of employees helps them to be prepared for various situations in the real workflow in the future. Such training becomes more and more relevant with the emergence of a "new generation" of employees. It makes the learning process more interesting, less scientific, and more technologically equipped.
New name, same values

Abstract This journal’s guiding philosophy is to publish academic research that enriches our collective understanding of people, society and ideas. To ensure that we articulate our mission to the many communities we serve, clearly and straightforwardly, this journal will now be published as Humanities &amp; Social Sciences Communications . This decision does not reflect any change to our scope, values or editorial standards; rather, it is done in a spirit of reaffirming our core mission.
A study on stakeholder’s satisfaction of using Education Business Management Information Systems (EBMIS) tool in the University of Rwanda

A study aimed to investigate the role of the Education Business Management Information Systems (EBMIS) tool plays in the operation and management of the University of Rwanda focusing on staff and students. We carried out a mixed-method study in five colleges of the University of Rwanda including headquarters targeting students and staff. On the one hand, the study finds out that through EBMIS, timely application and registration online were good services whereby 25.7 % of students and 27% of staff were satisfied with the services respectively. The 10.7 % of students highlighted that Information technology is able to check the history of the payment process of tuition fees and 8.8% were able to access the passing modules. In addition, 55.8% of students failed to use the system during registration and application during holidays. Consequently, students come to the registration offices for assistance by staff in each college, which is costing, and time-consuming. On the other hand, the majority of staff met the difficulties of using the EBMIS to render services in between as well as to the students due to the low skills on the system. Therefore, the students’ big lines in front of offices such as offices of Collegesꞌ registrar and repeatable claims from students are still unavoidable. Hence, the use of EBMIS is not common practice in the whole services of the colleges in University of Rwanda. About, the knowledge gap, 56 % of staff do not know Information Technology System and hence 77% have not been trained at all on Information Technology System, among the trained staff, 55.1 % used at least 20% of EBMIS. The findings of the study showed that the Information Technology System is under exploitation at the University of Rwanda. However, the management of all data information from merged colleges is still critical due to the lack of technical skills and knowledge among users. Although, the University of Rwanda supports students and staff to explore this system through pieces of training in-country and abroad. Yet, there is still a big gap in skills of efficiency using the EBMIS and therefore, its productivity is still sub-standard.&#x0D; Keywords: Information Technology (IT), students, staffs, service delivery, operation
Supervised dimensionality reduction by a Linear Discriminant Analysis on pre-trained CNN features

We explore the application of linear discriminant analysis (LDA) to the features obtained in different layers of pretrained deep convolutional neural networks (CNNs). The advantage of LDA compared to other techniques in dimensionality reduction is that it reduces dimensions while preserving the global structure of data, so distances in the low-dimensional structure found are meaningful. The LDA applied to the CNN features finds that the centroids of classes corresponding to the similar data lay closer than classes corresponding to different data. We applied the method to a modification of the MNIST dataset with ten additional classes, each new class with half of the images from one of the standard ten classes. The method finds the new classes close to the corresponding standard classes we took the data form. We also applied the method to a dataset of images of butterflies to find that related subspecies are found to be close. For both datasets, we find a performance similar to state-of-the-art methods.
한국군 군사(軍事)위기관리체계의 효율성 제고방안 고찰 -통합방위체계를 주축(主軸)으로 하는 군사위기대응기구를 중심으로-

Korea has been considered most vulnerable to crisis with the movement of the four surrounding powers due to its geopolitical location. With the conceptual expansion from traditional security to comprehensive one in the 1990s, it set the National Security Office as a control tower, and the Ministry of National Defense (Joint Chiefs of Staff) takes exclusive charge of execution in the military section of the traditional security field. And yet, generally, military responses and actions end up badly and are evaluated negatively.Now, the memories of the war may much be forgotten among postwar generations, but incidents have continued since the 2000s, including the Sinking of Naval Corvette Cheonan, North Korea’s Bombardment of Yeonpyeong, the Sinking of Ferry Sewo, repeated North Korean Wooden Boat entry, the threatening Low-altitude Flight of Japanese Maritime Patrol Aircraft However, there are few traces of improved and reinforced efforts in response to recurring incidents and follow-up. It is hardly denied that the ROK Army’s MCM still has significant vulnerabilities in policy and structure with the painful sacrifice of many people. including the command reporting system’s ambiguity and internal and external obstacles in the decision-making process. It is necessary to recogni2e the duty of the military and the purpose of its existence. This study set the ‘MCMS’ as an independent variable; ‘efficiency as a dependent variable; and the aspects of ‘conceptual keynote’, legislation/organization,) and ‘function/operation’ as parameters.In spite of preceding studies of the general crisis and disaster aspects, there are few studies of the MCMS, in particular, provision/response system. Efficiency can be secured, using the present integrated defense system as tie military crisis response organization’s main axis. This study would be a starting point for better research since there would be no answer by seeking a solution only from the external aspects, immersed in the enactment of related laws and slogans.
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Can you tell? SSNet - a Sagittal Stratum-inspired Neural Network Framework for Sentiment Analysis

When people try to understand nuanced language they typically process multiple input sensor modalities to complete this cognitive task. It turns out the human brain has even a specialized neuron formation, called sagittal stratum, to help us understand sarcasm. We use this biological formation as the inspiration for designing a neural network architecture that combines predictions of different models on the same text to construct robust, accurate and computationally efficient classifiers for sentiment analysis and study several different realizations. Among them, we propose a systematic new approach to combining multiple predictions based on a dedicated neural network and develop mathematical analysis of it along with state-of-the-art experimental results. We also propose a heuristic-hybrid technique for combining models and back it up with experimental results on a representative benchmark dataset and comparisons to other methods to show the advantages of the new approaches.
Multi-view Low-rank Preserving Embedding: A Novel Method for Multi-view Representation

In recent years, we have witnessed a surge of interest in multi-view representation learning, which is concerned with the problem of learning representations of multi-view data. When facing multiple views that are highly related but sightly different from each other, most of existing multi-view methods might fail to fully integrate multi-view information. Besides, correlations between features from multiple views always vary seriously, which makes multi-view representation challenging. Therefore, how to learn appropriate embedding from multi-view information is still an open problem but challenging. To handle this issue, this paper proposes a novel multi-view learning method, named Multi-view Low-rank Preserving Embedding (MvLPE). It integrates different views into one centroid view by minimizing the disagreement term, based on distance or similarity matrix among instances, between the centroid view and each view meanwhile maintaining low-rank reconstruction relations among samples for each view, which could make more full use of compatible and complementary information from multi-view features. Unlike existing methods with additive parameters, the proposed method could automatically allocate a suitable weight for each view in multi-view information fusion. However, MvLPE couldn't be directly solved, which makes the proposed MvLPE difficult to obtain an analytic solution. To this end, we approximate this solution based on stationary hypothesis and normalization post-processing to efficiently obtain the optimal solution. Furthermore, an iterative alternating strategy is provided to solve this multi-view representation problem. The experiments on six benchmark datasets demonstrate that the proposed method outperforms its counterparts while achieving very competitive performance.
Functional Two-sample Tests Based on Empirical Characteristic Functionals

Two-sample tests for functional data based on empirical characteristic functionals are proposed. The test statistic is of Cramér–von Mises type with integration over a preselected family of probability measures, say Q, leading a computationaly feasible and powerful test statistic. The choice of the probability measure Q is discussed and the empirical size and power of the resulting two-sample functional tests are investigated in a small simulation study.
Principles of Linguistic Information System Design

The study aims to formulate principles for developing a linguistic information system meant to act as integrated representation of linguistic resources. Scientific originality of the research is in that principles of universality and complementarity of a linguistic information system development are suggested for the first time. Universality is understood as supporting all kinds of research including theoretical, applied and informational. Complementarity refers to adequate allocation of electronic resources functioning as system components. Such types of complementarity as semantic, pragmatic and functional are identified. The results of the study have demonstrated that the system structure must include linguistic ontology and a national corpus as its core elements.
Research on the Optimization of English Automatic Translation by Weakening Grammar Rules

Abstract At present, with the development of intelligent technology, automatic translation software has been widely used. However, most of the automatic translation forms a rough language processing mechanism, which has a high error rate. To solve this problem, this paper first analyzes the principle of English automatic translation, then studies the optimization of English automatic translation algorithm by weakening grammar rules, and finally verifies the optimization of English automatic translation by weakening grammar rules.
Video Moment Localization using Object Evidence and Reverse Captioning

We address the problem of language-based temporal localization of moments in untrimmed videos. Compared to temporal localization with fixed categories, this problem is more challenging as the language-based queries have no predefined activity classes and may also contain complex descriptions. Current state-of-the-art model MAC addresses it by mining activity concepts from both video and language modalities. This method encodes the semantic activity concepts from the verb/object pair in a language query and leverages visual activity concepts from video activity classification prediction scores. We propose "Multi-faceted VideoMoment Localizer" (MML), an extension of MAC model by the introduction of visual object evidence via object segmentation masks and video understanding features via video captioning. Furthermore, we improve language modelling in sentence embedding. We experimented on Charades-STA dataset and identified that MML outperforms MAC baseline by 4.93% and 1.70% on R@1 and R@5metrics respectively. Our code and pre-trained model are publicly available at https://github.com/madhawav/MML.
COPING BEHAVIOR IN TARKINGTONâ€™S 'THE MAGNIFICENT AMBERSONS': AN INDIVIDUAL PSYCHOLOGICAL APPROACH

The object of the research is a novel the magnificent Ambersons by Newton Booth Tarkington. The problem of this study is how George Amberson Minafer, the major character copes with his problem. The objective of this study is to analyze the novel based on the psychological approach. The researcher employs a qualitative method. In this method, the researcher uses two data sources, namely primary and secondary data sources. The primary data source is the novel itself. The secondary data sources are books about psychology and other sources, which are related to the analysis. The method of data collection is documentation and the technique of data analysis is descriptive technique. Based on the analysis, the researcher draws two conclusions: first, George Amberson Minafer copes his problem through changing his behaviour, from negative behavior to a positive one. He becomes more optimistic, independent and caring for his family. Second, George Amberson Minafer copes his problem through his actions. He has the courage to admit his mistake. He asks forgiveness to the man that he hurt most.
English Expressions by Receptionists at Ubud Wana Resort

This research aims to analyze the communication ability seen from communicative functions and grammatical aspect of English by the receptionist staff at Ubud Wana Resort.It discusses the English functions of the expressions and types of grammatical errors that happen in the expressions by the staff when they serve their service and do their activity with the guests.The theoretical basis used in this research is taken from Geoffrey Leech and Jan Svartvik (1975).The data used is taken from the conversation between the receptionist staff with the guests.The data are collected and classified based on the functions of English and the grammatical errors.All of the data were collected using direct observation.Then data were analyzed descriptively based on the theory applied.Based on the result of the analysis, it was found that the receptionist staff of Ubud Wana Resort use communicative functions of English in making contact with the visitors or guests such as informational function (giving and asking information), expressive function, directive function (thanking, requesting, commanding and suggesting), aesthetic function, and phatic function (chit-chat).Beside, from the data there are some grammatical error that happen in the conversation by the staff such as error of omission (omission of subject, omission of plural, omission of auxiliary, omission of article, error of verb tense, error of addition (simple addition) , error of misformation, and error of misordering.The English used by the staff could be formal and informal, in polite and neutral ways.From all of staff or the respondents of this research, almost all of them can use these functions in good way.
DEVELOPMENT AND VERIFICATION ON ZERO ENERGY COOL TREE WHICH PROVIDING COOL COMFORT ON HOT SUMMER OUTDOOR

Since the 2020 Tokyo Olympic and Paralympic Games will be held during the hot summer, promotion of outdoor heat is an urgent issue as one of environmental measures. “Cool Tree” as a cool spot to create a beautiful shade of lumber with laminated wood, operating with zero energy using only solar energy, with the concept of “design like Japan”, “complete off-grid system” and “ultimate recycling ecology” was developed, and field measurements were carried out.
Equi-Depth Histogram Construction Methodology for Big Data Tools

In recent decades, countless data sources such as social media, machines, and networks are constantly pushing data into the digital world. The size of the data has been growing exponentially. To understand the statistical information of data query optimization, equi-depth histograms are essential. In this paper, we present approximate equi-depth histogram construction for big data using both Apache Pig Scripts and Java Web Interface interacting with Apache Hadoop. We use equi-depth histogram construction with quality guarantees for big data approaches and implement them with Apache Hadoop Map-Reduce and Apache Pig user-defined functions. We introduce a prototype implementation of the construction of the approximate equi-depth histogram from the Java Server Face page using Apache Hadoop jobs and the Hadoop Distributed Files System, and we evaluate these methods using the demonstration. We explain Apache Pig Scripts techniques to create equi-depth histograms using big data. The results indicate that our system provides the capability of writing multiple jobs using Apache Pig, and programmers can make use of the advantages of Apache Pig to create histograms and eliminate the complex implementation of Map-Reduce jobs.