Reviewerly/exHarmony huggingface dataset:
Nonlinear Filters

Semantically, nonlinear filtering concerns all image-to-image operators that are nonlinear, and since digital images do not form a vector space, all image filtering. Nonetheless, insofar as classical linear techniques are adapted to image filtering, linear methods do compose a large segment of image filtering. The algebraic structure of nonlinear filtering is now complete, insofar as nonlinear filtering is taken to mean filtering by increasing, translation-invariant filters. This chapter considers median filters, and morphological filters. As intuitively conceived, median filters are numerically based, and morphological filters are shape based. Median filters arise from classical maximum-likelihood estimation and from certain operations on logical variables; morphological filters arise from fitting shape probes within larger shapes. The one-dimensional median filter is implemented by sliding a window of odd length over the input signal one sample at a time.
Readability of Online Patient Education Materials in Radiation Oncology – Are We Improving?

Prior research from 2015 demonstrates that online radiotherapy patient education materials from various professional groups are written at reading levels above national recommendations of 6th to 8th grade, which may compromise patient understanding. Since publication of these initial findings, many materials from these sources have been updated or newly created. However, the extent to which readability was considered in the design of these new documents remains unknown. Therefore, the goal of this study was to evaluate readability of online education materials for radiotherapy from well-recognized professional societies, comparing readability of updated materials with those included in the original 2015 report. Patient education materials related to radiation oncology were identified from websites of the three professional societies used in the 2015 investigation (ACR, ACS, ASTRO). The documents included in the original analysis were securely stored and used as a comparator for the present study. In order to allow for accurate comparisons across groups, materials were matched by content; when necessary, documents were combined from the original cohort to create topically equivalent materials to reflect those currently available on society websites. Identified materials were analyzed using seven validated readability indices and results are reported in grade-level equivalents. Original 2015 materials were also reanalyzed with the same method. Mean readability levels of included materials are presented in the Table. ACS materials had the lowest baseline levels and also showed improved readability in the more recent materials. By contrast, the ASTRO materials had high baseline readability levels that actually worsened in the more recent materials. Despite previous evidence that readability levels of patient education materials in radiation oncology are unacceptably high, the readability of newly created materials is not consistently improving across professional societies. While certain groups may consider readability in the design of their educational documents, more consistent consideration of readability in the design of radiotherapy education materials across all organizations is needed.Abstract 1224; Table 1Readability ScoreACRP valueACSP valueASTROP valueOriginal 2015 MaterialsNew or Updated MaterialsOriginal 2015 MaterialsNew or Updated MaterialsOriginal 2015 MaterialsNew or Updated Materialsn=23n=18n=14n=8n=17n=9DRP(GE)15.215.00.969.98.50.1212.913.70.19FK13.512.70.119.48.10.0711.111.70.12FORCAST11.811.90.5410.310.30.7811.611.80.24Fry15.716.30.219.98.90.2513.916.20.097GF16.014.50.003*11.29.90.043*13.114.00.04*Raygor14.815.20.669.48.00.1412.714.80.11SMOG15.014.30.07411.310.50.1312.613.40.045* Open table in a new tab
Domain-independent Intent Extraction from Online Texts

Identifying user’s intents from texts on online channels has a wide range of applications from entrepreneurship, banking to e-commerce. However,intent identification is not a simple task due to the intent and its attributes are various and strongly depend on the domain of data. If the number of intent domains increases, the number of intent’s attributes will get bigger. As a result, the complexity of intent extraction task grows up significantly. Additionally, when a new domain comes, it involves considerable physical efforts to define specific labels for intent and attributes for that domain. Hence, it would be much better to come up with a new method for extracting user’s intents which is notdependent on a specific domain. In our research, we study the problem of domain-independent intent identification from posts and comments crawled from social networks and discussion forums. We present ten general labels, i.e. labels do not depend on a specific domain, and utilize them when extracting intent and its related information. We also propose a map between general labels and domain-specific labels. We extensively conduct experiments to explore the efficiency of using general labels compared to specific labels in extracting user’s intents when the number of intent domains increases. Our study is conducted on a medium-sized dataset from three selected domains: Tourism, Real Estate and Transportation. In term of accuracy, when the numberof domains grows, our proposal achieves significantly better results than domain-specific method in identifying user’s intent.
Imperfect Knowledge

Both computers and people find it difficult to organize knowledge because it is imperfect. The challenge of ambiguous knowledge is to recognize and resolve the ambiguity. The challenge of conditional knowledge is to identify conditions that distinguish between correct and incorrect applications of knowledge. The challenge of contradictory knowledge is to discover a contradiction when it is not immediately obvious. The challenge of fragmented knowledge is to integrate related knowledge stored in long-term memory. The challenge of inert knowledge is to activate relevant knowledge when it is needed. The challenge of misclassified knowledge is to identify and reclassify it. The challenge of uncertain knowledge is to incorporate probabilities into reasoning. Progress is occurring in meeting each of these challenges.
Monitoring and diagnostics of the quality of scientific and methodological work in the context of competence approach in higher pedagogical education

The article is devoted to the problem of monitoring scientific and methodological work in institutions of higher pedagogical education, in particular to the question of diagnostics of its quality in the context of the of the competence approach. The terminolog ical field of research is defined, the main purpose and tasks of creation of the monitoring system of scientific and methodological work in pedagogical institutions of higher education are outlined. Some features of monitoring research in the field of higher pedagogical education are characterized on the basis of consideration of the origin and development of the “monitoring” phenomenon, its classification, the identification of common and distinguishing features in definitions by diﬀerent authors. Pedagogical diagnostics is considered as a factor in the development of scientific and methodological work, the elements of the model, directions of implementation and stages of diagnostic examination of various aspects of scientific and methodical work realization are named, and its results are predicted. On the basis of the results of scientific generalization, analysis of scientific and methodological work practice in pedagogical institutions of higher education, the key criteria of its quality are identified and the relationship of professional as well as scientific and methodological competence is established. The contradictions that determine the implementation and the main categories of competency approach, the place of scientific and methodological competence in the system of competences of the teacher of a pedagogical institution of higher education are determined. The connection of the process of forming the scientific and methodological competence of the teacher with the innovativeness of his activity at certain stages was fixed. The components of scientific and methodological competence structure are distinguished: epistemological, axiological, traseological, professional and personal. In the context of the conducted research, the object and indicators of the scientific and methodological competence formation of the teacher of a pedagogical institution of higher education were determined, the scheme of its formation was developed and the characteristics of individual levels were drawn up.
A Novel Approach of Cloud Security by Authentication in Cloud Computing Environment

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Spectral Analysis via Continuous/Discrete Fourier Transformation

A summary is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.
Session details: Theme: Distributed systems: MCA - Mobile computing and applications track

For the past 16 years, Mobile Computing and Applications Tracks had been running successfully. The papers have been improving in quality and the competition has also become more and more severe, with dropping acceptance rate. This year, the track is experiencing a challenge in receiving fewer submissions from the past, and the set of accepted papers happens to be more concentrated geographically. With the relatively small sample size, this is perhaps the effect of statistical variations only. The track features research papers drawn from different application domains in mobile computing, with a very heavy orientation towards the recently upcoming areas of machine learning and artificial intelligence this year for security, privacy, localization and so on. To summarize, the track is dedicated to draw upon research efforts and expertise from different areas of research, so as to promote better synergy and to bring forth not only core communications and structures for application development and data management, but also important and upcoming research applications to realize the benefits of anywhere, any place and anytime pervasive and ubiquitous computing.
A Torch Without Light: Low-Light Imaging for Mobile phones

Photography used to be a hobby that required equipment such as a professional camera. Today, photography has evolved to be a daily activity conducted on an unprecedented scale due to the adoption of camera into smartphones. Mobile phone cameras are on the way to completely replace other forms of camera due to their portability and quality. Millions of images are captured on mobile devices across the globe. These images are clear and crisp. But all these images are captured in daylight. Images taken in low illumination essentially turn out to be too dark to be comprehensible. Research shows that current solutions to this problem work for dim to moderate light level but fail in extreme low light. There are certain problems involved with these techniques. Firstly, image denoising relies on image priors limiting the situations on what it will work on. Other deep learning techniques work on synthetic data and cannot be proficient on real data. Secondly, Low light image enhancement assumes that images already contain a good representation of scene content. This paper proposes to capture low illumination images and transform them to high quality images using end to end fully convolutional neural network trained on our data set of raw images shot in low aperture and their corresponding high aperture raw images. As an outcome, we will be able to transform images to high quality and identify objects.
Kimberlite/lamproite petrogenesis: geochemical and isotope evidence from North America, South Africa and Western Australia

Major, trace element and isotope results are reported for lamproites from the Leucite Hills, Wyoming, W. Australia and Smoky Butte, Montana and Group II kimberlites from Finsch Mine, South Africa.The W. Australia lamproites form more than 100 separate intrusions and grade petrographically from olivine lamproites through leucite bearing olivine-diopside lamproites to leucite lamproite lamproites with phlogopite, diopside and K-richterite.The lamproites from Smoky Butte occur in a small (3 km long) area of thin dykes and plugs and they contain armacolite, sanidine, alkali amphiboles and Ti phlogopite.Finsch Mine is a composite intrusion and the rocks are hypabyssal kimberlites containing phlogopite, olivine, diopside, serpentine and calcite.
ADOPTION OF SUSTAINABLE PRACTICES AMONG FOOD AND BEVERAGE SMES IN PENINSULAR MALAYSIA

Small and Medium-sized enterprises manufacturing sector contributed significantly to Malaysian economy.Specifically, food and beverages SMEs industry play an important part in fulfilling the increasing food demands in Malaysia.However, there is a rising concern on the environmental degradation caused by the aforementioned sector and sustainable practices have been identified as an approach to minimize the effect of manufacturing activities towards environmental degradation.Thus, the aim of this research is to examine the adoption of sustainable manufacturing practices among food and beverages SME's in Peninsular Malaysia.This study was based on a quantitative approach and the primary data were collected using structured questionnaire via face to face interview with 375 manufacturers.Data collected were analysed using descriptive and chi square analysis.Majority of the respondents agreed that improving brand image, reducing overall business costs and increasing profit as benefits gained by the SMEs from adopting sustainable practices.Chi-square analysis revealed that region of business profile is significant in the adoption of sustainable practices among food and beverages SMEs in Peninsular Malaysia.The findings provide further evidence that the adoption of sustainable practices in their manufacturing activities not only provide economic benefits but more importantly, minimize the effect towards environmental degradation.
Introduction

The introduction argues that blurring the line between score and sound design represents an important new trend in contemporary soundtrack practice. It contends that the one factor that connects all the different cultural, aesthetic, and technological influences, and all manifestations of the present shift in practice, is a musical approach to film soundtrack conceived as an integrated whole. The chapter explains how the notions of an integrated soundtrack and the musicality of the soundtrack relate to this trend and looks at how they have been addressed in the existing literature. This chapter also provides an outline of the content, arguing for an approach that addresses the interdependency of intellectual, affective, and sensory stimuli in the film experience.
https://researchopenworld.com/the-plastic-age-where-and-what-is-the-future/#

We are currently living in the "Plastic age" as rightfully predicted in the classic movie "The graduate" in the 60's where main character young Benjamin, just graduated and asking himself what to do next gets the famous advice: "I just say one word -Plastics.There is a great future in Plastics!"This was certainly correct; our daily life relies on synthetic polymers for all aspects of modern life.Going back in history, one of the first synthetic resins, a thermoset produced by a catalyzed reaction of phenol and formaldehyde, was introduced already 1909 under the name Bakelite.The creation of a synthetic plastic was revolutionary for its electrical non conductivity and chemical, solvent and heat-resistant properties in electrical insulators, radio and telephone casings and such diverse products as kitchenware, jewelry, pipe stems, children's toys, and firearms.Bakelite was particularly suitable as a molding compound, an adhesive or binding agent, a varnish, and a protective coating and as such extremely useful for the emerging electrical and automobile industries.In the following years a number of new polymeric materials, thermoplastics and thermosets were developed, mainly formed by linking small molecules -monomers -together in a repetitive formation.Plastics are today available with extremely versatile properties ranging from, resistance to corrosion, low density, high strength, transparency, low toxicity, durability and a remarkable affordability and therefore used by almost every industry in the world, from food packaging to space exploration.Plastic is the ultimate commodity of convenience.
BREAST CANCER SURVIVAL ANALYSIS USING ML MODELS

The main purpose of this study is to use machine learning techniques that have potential to predict breast cancer survival more accurately and can prevent unnecessary surgical treatment procedures.Using these machine learning models on genetic data has the potential to improve our understanding of cancers and survival prediction.The dataset is taken from 'The Molecular Taxonomy of Breast Cancer International Consortium (METABRIC)' database which contains the targeted sequencing of genomic data of primary breast cancer patients.The dataset is run through various machine learning algorithms such as Logistic Regression, KNN, Decision Tree, Random Forest, Extra Trees, Adaboost, Support Vector Machines (SVM) to predict the survival status.The results are compared to the traditional survival analysis models.This study aims to showcase that machine learning models would help accurately predict the outcomes of breast cancer prognosis, which will help survival chances by providing treatment procedures in early stages of the cancer.
“Joy” and “Fear” in Thomas Bernhard’s autobiographies: Aspects of a Computational Sentiment Analysis

This pilot-study of a computational analysis of literary texts presents the results of aspects of a "sentiment analysis".The data of analysis are the autobiographies of the Austrian novelist Thomas Bernhard.The primary object of attention are the sentiments "joy" and "fear".We elaborate on and demonstrate the impact of several preprocessing procedures, describe the characteristics of the dictionary and the annotations of its entries conceived and used for analysis.We specify the general methodology and the steps involved for quantifying of its result by the use of the functions of the R-package "Quanteda".The descriptive output of the procedures is examined with several statistical measures to compare the counts of "joy" vs "fear" that were found in the texts individually, contrastively and in combination as a corpus.We conclude that there is a proportional and relative difference between the frequencies of the sentiments of the individual texts, but that this observation is insignificant if interpreted on the basis of the nonparametric Wilcoxon rank-sum test.A "goodness of fit" test, on the other hand, shows that the two sentiments show a homogeneous distribution across the corpus.
Students’ Audience Competency Levels on the Topic “School and University in the Mirror of Audiovisual Media Texts”

Analysis of the questionnaire on the theme "School and university in the mirror of audiovisual media texts" shows that only one third of students demonstrate a high level of the motivational indicator of media competence development.The indicator implies a wide range of genre, thematic, emotional, gnoseological, hedonistic, intellectual, psychological, creative, aesthetic motives (including: the choice of a diverse genre and thematic spectrum of media texts with the mandatory inclusion of non-entertainment genres; the pursuit of philosophical/intellectual/aesthetic dispute or dialogue with the creators of media text, criticism of their position, identification, empathy, striving for aesthetic impressions, obtaining new information, confirming their own competence in various spheres of life and media culture, searching for materials for educational, scientific, research purposes etc.).Approximately half of the students surveyed exhibit an average level of motivation, and about 20 % of students are focused exclusively on entertainment media.Analysis of students' answers to questions revealing their levels of information index of media competence in relation to audiovisual media texts on school and university topics shows that approximately 15 % of students in two groups find themselves on a relatively high level, about a third of the audience -an average level, while the rest of the audience (52 %) -low.None of the students surveyed demonstrate a high level of interpretation (analytical, evaluative) indicator of media competence in relation to audiovisual media texts on the subject of school and university.The average level of analytical skills is exhibited by less than 5 % of respondents.
A Text Analysis of Arab News Headlines Relating to Education and Learning

The manner in which language is utilized to represent social issues in the public space such as in the print media can have far-reaching implications, not only on the issues being reported but also on the characters around those issues.One of the social issues often reported in the media is education and the process of its reportage including the linguistic formations of the headlines, which serves as signposts to a news item, are not always value-free.They are sometimes laden with interests and ideological flavors.Here, we take a descriptive mini critical approach to analyze educationrelated headlines obtained from Arab News between 2011 and 2016 to account for interests and ideological connections to the various choices made.The concepts of Appraisal and Theme-Rheme, offshoots of interpersonal, textual metafunctions of language, Systemic Functional Linguistics, Critical Discourse Analysis, discourse ideology are employed.The paper argues that news headlines are built on certain assumptions which are drawn upon from the society, and then reinforced to the target readers through what is known as lexical priming.Also, positive evaluative language used in constructing the headlines are largely uncritical of the status quo and are rather meant to support and motivate the stakeholders.