Reviewerly/exHarmony huggingface dataset:
Resolving Conflicts in Clinical Guidelines using Argumentation

Automatically reasoning with conflicting generic clinical guidelines is a burning issue in patient-centric medical reasoning where patient-specific conditions and goals need to be taken into account. It is even more challenging in the presence of preferences such as patient's wishes and clinician's priorities over goals. We advance a structured argumentation formalism for reasoning with conflicting clinical guidelines, patient-specific information and preferences. Our formalism integrates assumption-based reasoning and goal-driven selection among reasoning outcomes. Specifically, we assume applicability of guideline recommendations concerning the generic goal of patient well-being, resolve conflicts among recommendations using patient's conditions and preferences, and then consider prioritised patient-centered goals to yield non-conflicting, goal-maximising and preference-respecting recommendations. We rely on the state-of-the-art Transition-based Medical Recommendation model for representing guideline recommendations and augment it with context given by the patient's conditions, goals, as well as preferences over recommendations and goals. We establish desirable properties of our approach in terms of sensitivity to recommendation conflicts and patient context.
Development of Thesaurus for Hindi

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.
Content Based Image Retrivel on Non-Parametric Statistical Tests of Hypothesis

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.
Deep Embedding Sentiment Analysis on Product Reviews Using Naive Bayesian Classifier

Product reviews are valuable for upcoming buyers in helping them make decisions. To this end, different opinion mining techniques have been proposed, where judging a review sentence�s orientation (e.g. positive or negative) is one of their key challenges. Recently, deep learning has emerged as an effective means for solving sentiment classification problems. Deep learning is a class of machine learning algorithms that learn in supervised and unsupervised manners. A neural network intrinsically learns a useful representation automatically without human efforts. However, the success of deep learning highly relies on the large-scale training data. We propose a novel deep learning framework for product review sentiment classification which employs prevalently available ratings supervision signals. The framework consists of two steps: (1) learning a high-level representation (an embedding space) which captures the general sentiment distribution of sentences through rating information; (2) adding a category layer on top of the embedding layer and use labelled sentences for supervised fine-tuning. We explore two kinds of low-level network structure for modelling review sentences, namely, convolutional function extractors and long temporary memory. Convolutional layer is the core building block of a CNN and it consists of kernels. Applications are image and video recognition, natural language processing, image classification
Salt and Pepper Noise Suppression for Medical Image by Using Non-local Homogenous Information.

In this paper, we propose a method to suppress salt and pepper noise for medical images based on the homogenous information obtained by non-symmetrical and anti-packing model (NAM). The NAM could divide the image into several homogenous blocks and it is sensitive to the additive extra energy. Thus the noise could be detected effectively due to the usage of bit-plane during the division. Then corrupted points are estimated by using a distance based weighted mean filter according to the homogenous information in its non-local region, which could keep local structure. Experimental results show that our method can obtain denoising results with high quality.
Learning Models over Relational Databases (Invited Talk)

In this talk, I will make the case for a first-principles approach to machine learning over relational databases that exploits recent development in database systems and theory.The input to learning classification and regression models is defined by feature extraction queries over relational databases. The mainstream approach to learning over relational data is to materialize the training dataset, export it out of the database, and then learn over it using statistical software packages. These three steps are expensive and unnecessary. Instead, one can cast the machine learning problem as a database problem by decomposing the learning task into a batch of aggregates over the feature extraction query and by computing this batch over the input database.The performance of this database-centric approach benefits tremendously from structural properties of the relational data and of the feature extraction query; such properties may be algebraic (semi-ring), combinatorial (hypertree width), or statistical (sampling). It also benefits from database systems techniques such as factorized query evaluation and query compilation. For a variety of models, including factorization machines, decision trees, and support vector machines, this approach may come with lower computational complexity than the materialization of the training dataset used by the mainstream approach. Recent results show that this translates to several orders-of-magnitude speed-up over state-of-the-art systems such as TensorFlow, R, Scikit-learn, and mlpack. While these initial results are promising, there is much more awaiting to be discovered.
Arkeologisk geofysikk i Norge – En historisk oversikt og statusevaluering

Archaeological geophysics in Norway - an historical overview and status evaluation The introduction of archaeological geophysics to Norway has been relatively slow and the methodologies employed are still very much in their infancy. A recently compiled overview indicates that only about 120 surveys have been conducted in Norway over the last 40 years, which is a relatively low number compared with other countries. In other European countries several hundred surveys are conducted annually and archaeological geophysics is generally considered an integral part of archaeological investigations and evaluations. The article gives a short description of the most commonly used methods in archaeology, and focuses on some of the more important geophysical surveys carried out in Norway. Furthermore, it seeks to explain why the Norwegian archaeological milieu has been reluctant to adopt these methods in their work.
A Lightweight Mutual Authentication Scheme for Power Edge Computing System

Because of heavy cost, using of the traditional Public Key Infrastructure (PKI) authentication schemes is limited for the energy-constrained intelligent devices such as the power edge computing system, in which lightweight secure authentication schemes are urgent needed. In this paper, we propose a lightweight mutual authentication scheme supported by the edge computing, which is a novel cross-layer secure authentication program with asymmetric resources. The novel scheme combines lightweight symmetric cipher and physical-layer Channel State Information (CSI) to provide two-way authentication between terminals and edge devices. Experimental results show that the proposed scheme can significantly reduce the access authentication latency compared with the traditional PKI authentication scheme.
A comparison of NES and NNES assessment of Korean EFL undergraduate English Writing

This research compared 14 NES and another 14 NNES assessors’ holistic evaluation of 10 advanced Korean undergraduate students’ English writing and the reasons underpinning each score. The purpose was to ascertain whether the two groups of assessors assign analogous holistic scores (based on similar background reasons) when scoring writing, using evaluation criteria developed throughout their careers. Feedback and rankings were analyzed using keyword analysis (Shi, 2001). The findings demonstrate that both NES and NNES assessors assign similar holistic scores and place their assessment emphases on analogous aspects. Nonetheless, there are marked differences found in their comments and attitudes. The present research confirms findings from previous studies and may help both students and less experienced teachers of English writing to be mindful of the writing elements that their primary readership or experienced assessors are likely to focus on
Measuring the Impact of Employee Involvement in Decision-Making and Job Performance

Job performance is one of the important pillars in the functional aspect as it contributes to the success of the organization through its implications and impact in it and seek all organizations in the attention to performance and try to raise the level of performance of workers through a range of factors that affect directly or indirectly, The extent of the contribution of the workers in the decision-making process and the impact of this on the performance of employees that the process of participation of workers in decision-making leads to a sense of workers attention and feeling great moral incentive and therefore will affect the performance of employees and the relationship was measured between the participant (65) Employees in the General Directorate of Scholarships and Cultural from the Relationships – affiliated to the Ministry of Higher Education and Scientific Research in Iraq.. The data were collected through the adoption of the questionnaire as a main tool. Data were analyzed using the SPSS program. The results showed that there is a strong statistical significance between participation in decision making and functional performance. There is also a statistically significant effect. Participation in decision making affects performance Career for employees.
LibGuides: Environmental Science Collection: About

A guide to all aspects of Environmental Science Collection including content, searching, and viewing results on the new ProQuest platform.
Rancang Bangun Sistem Informasi Penilaian Kienrja Karyawan Pada Program Pemerintah Kota Tanpa Kumuh (KOTAKU) Berbasis Web

This research is motivated by problems faced by the Slum City Government Program (Kotaku) in evaluating employee performance. The first problem is often the inaccuracy in distributing employee performance appraisal documents, the second problem is the amount of paper used in conducting one employee performance appraisal, the third problem is the difficulty in filing and searching documents on employee performance evaluation results. Then built a web-based application to be more efficient in supporting the distribution process, reduce costs for paper use and facilitate archiving and search results of employee performance appraisals. In addition, web-based applications do not need to be installed on every computer or laptop. Then this application will be supported by a performance appraisal method that has been implemented by the Kotaku which refers to the Work Order Letter (SPK) Guidelines. Based on the results of the trials that have been carried out, the application of employee performance appraisal on city government programs without slum (my city) makes it easy to evaluate employee performance which previously takes almost 1 week now is only 2 days, this is due to the employee performance assessment system website. Keywords : Assessment, Performance, City, Website
PROMOTING REFLECTIVITY IN HIGHER EDUCATION. FROM THEORY TO PRACTICE

Appears in: INTED2019 Proceedings Publication year: 2019Page: 9227 (abstract only)ISBN: 978-84-09-08619-1ISSN: 2340-1079doi: 10.21125/inted.2019.2287Conference name: 13th International Technology, Education and Development ConferenceDates: 11-13 March, 2019Location: Valencia, Spain
LibGuides: Agricultural Science Collection: About

A guide to all aspects of Agricultural Science Collection including content, searching, and viewing results on the new ProQuest platform.
Episodes in the Life of a Chair: A New Hire, Part 1

The Department ChairVolume 29, Issue 4 p. 7-8 Articles Episodes in the Life of a Chair: A New Hire, Part 1 Stephen Aldersley, Stephen AldersleySearch for more papers by this author Stephen Aldersley, Stephen AldersleySearch for more papers by this author First published: 09 April 2019 https://doi.org/10.1002/dch.30247Read the full textAboutPDF 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. Volume29, Issue4Spring 2019Pages 7-8 RelatedInformation
Reassessing California’s Overdue Earthquake Tab

Paleoseismic records show that the current 100-year hiatus since the last major event on the San Andreas, San Jacinto, and Hayward Faults is unprecedented in recent geologic history.
Preserving data privacy in data market and obtain truthful data

People are posting their data on different sites. Huge amount of data were collected daily by the different users. Research has been done on the accumulation, different kind of applications proceeded rapidly. Whenever any user want to buy any online product, usually people will inform themselves by reading the different online reviews. Their might be chances that, those particular user is fake user and posting bogus data. Also security is also the main issue. This paper will introduce the TPDM mechanism and different privacvy preservation that are used technique will given. TPDM combines Truthfulness and Privacy Presrvation in Data Market. It will use encryption-decryption methodology for security. Also users identity is also get check whether its fake or real identity.
Application of quantitative and qualitative methods in the study of library activities in Bulgaria

The paper presents the main areas of application of quantitative and qualitative methods. It is shown the relationship between the agenda of the library area and the used research approaches. There are presented good practices in specific areas which are serving as a basis for full implementation of the qualitative and quantitative methods for evaluating the library activities.The library sector in Bulgaria is in a phase of complete transformation. This has a strong influence on the state of the research in the libraries. The priority activities are related with the modernizing of the library buildings, to attract different categories readers (children, pupils, students), the teaching of information literacy, the digitization of library collections. The study of library activities is focused mainly in a few areas: study of the general state of library system through analysis of the used new technologies; study of the professional realization of the graduated students in Library and Information Science university programs; analyzing the results of the programs of information literacy.In some university lectures at the Sofia Universiyt and SULSIT are presented also some aspects of the library research. In the specialized library periodicals are published, even occasionally, the information from surveys about the results of specific activities, conducted events about the attraction of readers, work with children and youth audience, the rate of introduction of new teaching methods and new educational disciplines and others.In the Bulgarian practice to assess the current state of libraries the most widespread method is the SWOT analysis.
Сегментация в объектно-ориентированном кодировании и передаче многоракурсных изображений

The urgency of the problem efficiency increasing of coding of the multi-view images for transmission over radio channels in mobile video surveillance systems and the need to develop methods, algorithms and specialized compression codecs with acceptable computational complexity are shown. The segmentation place in the object-oriented coding of multi-view images is determined. Expressions for the relative evaluation of the computational complexity of segmentation algorithms and object-oriented coding of multi-view images are proposed. It is shown that tree-wave segmentation and nodal quad-grids use reduces the computational complexity of object-oriented coding of multi-view images and, accordingly, reduces the delay in their transmission in mobile video surveillance systems.
Этика научного исследования: авторская свобода и стандартизация

Contemporary problems of the science development combine very acute issues — human freedom as a moral value and the need to create common principles of understanding and interaction, a certain standardization that allows disseminating of knowledge and conducting joint research. Standardization of diverse information flows, especially in modern conditions of global communications, is focused on the development of unambiguous and, therefore, quite rigid systems of description of research activities. However, when individual and collective formats of interaction come into contact, there is a risk of losing important for human life and philosophy of life qualitative characteristics of knowledge, which is especially important for the effectiveness of scientific research. This problem is quite evident in the humanities, in particular in the field of ethics and law.
A Study on the Purpose and Perception of Using EBSe in English Education : Focusing on Private Education Expense for English

The objective of this study is to investigate the perception of using Educational Broadcasting System English (hereafter, EBSe) in English education, focusing on private education expense for English. We analyzed the statistical survey results which were implemented on 43,000 elementary, middle and high school parents, homeroom teachers, and after-school teachers from all over the country by the Ministry of Education and the National Statistical Office in 2016. The Ministry of Education announced the survey results on March 14, 2017, “Private education costs for private education are falling sharply and private English education costs have decreased the most significantly”. The results were quite different from the results of the survey on private education expenses that had been conducted until 2016. When analyzing the responses of 2,793 students, parents, teachers and the public in a survey conducted by this study, EBSe showed positive expectations about reducing private education costs. It is very important that the
DESIGN OF COLLABORATIVE COMPUTATIONAL ECOSYSTEMS FOR THE DEVELOPMENT OF STEAM COMPETENCIES IN SCHOOLS

DESIGN OF COLLABORATIVE COMPUTATIONAL ECOSYSTEMS FOR THE DEVELOPMENT OF STEAM COMPETENCIES IN SCHOOLS
INCLUSION OF M-LEARNING IN HIGHER EDUCATION: AN EMPIRICAL STUDY OF BUSINESS STUDENTS IN PAKISTAN

Appears in: INTED2019 Proceedings Publication year: 2019Pages: 9889-9893ISBN: 978-84-09-08619-1ISSN: 2340-1079doi: 10.21125/inted.2019.2461Conference name: 13th International Technology, Education and Development ConferenceDates: 11-13 March, 2019Location: Valencia, Spain
Students’ Self-Evaluation of English Improvement through Internet Usage for Learning Purposes

The aims of this study were (1) to investigate students’ activities on using the Internet in English and (2) to examine benefits of using the Internet as a tool for an effective language improvement. The subjects were 50 English-Major Students from the weekend program at Pibulsongkram Rajabhat University, Phitsanulok. The subjects participating in this study were selected by using a purposive sampling technique. The instrument used to collect the data was a questionnaire adapted from that of Wongyod (2006). The statistical devices applied for the data analysis were the percentage, means, and standard deviation. The results showed that: 1) reading online materials was an activity that the students mostly did whereas writing online dairies or essays in English on blogs was employed the least; and 2) using the Internet in English could help the students learn new vocabulary, idioms, and slang but it could not help the students practice word pronunciation. The results are expected to be useful for further studies in the field of teaching and learning English as a Foreign Language.Keywords: Self-Evaluation, English Improvement, Using Internet for Learning Purpose
Clustering Algorithms for Huge Datasets: A Mathematical Approach

Identifying clusters for huge datasets are useful for finding out attributes of a particular dataset and thereby providing insights for making effective decision making.In our previous work, we have proved the concept of clustering algorithms for huge datasets theoretically by applying small computations on the available datasets.In this paper, we extend the same work by applying Mathematical calculations for the datasets so as to prove the correctness of our previous work carried out.Our proposed method is applied to various datasets and proved K-Means algorithm mathematically and the experimental calculations performed on various clustering algorithms shows that our approach provides the new idea of clustering techniques that can be applied for any number of huge and complex datasets.
The Effect of Megaprojects on the Percived Image of Country of Origin in Case of Ethiopia

Megaprojects that cost a billion dollars or more, attracts a lot of public attention.Because of substantial impacts on the environment, budgets, economy, and society that changes the structure of society as opposed to smaller and more conventional projects it attracts media converge.Hence, it brings an extraordinary impact on the host country in terms of investment; visitor's expenditures and build a positive image by increasing nation capacity and attractiveness.Therefore, this paper appraises the impact of megaprojects on products produced in Ethiopia as perceived by foreigners taking 400 respondents.The results reveal that mega projects existed in the country were significantly affecting the product produced in the country.
LibGuides: Earth, Atmospheric & Aquatic Science Collection: About

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