Reviewerly/exHarmony huggingface dataset:
Knowledge-Based Question and Answering System for Turkish

A knowledge-based QA system for Turkish is presented in this paper. The developed QA system has two phases: 1° Learning question and constitute two databases named question and answer database. 2° Uses the question and answer databases as knowledge-base for QA operation. The first phase of the project consists of pre-processing (tokenizing of sentences, parsing a word into syllable, phonological testing consonant softening, vowel reduction, haplology, head and tail letters, morphological testing, mumpsimus, foreign words), morphological parsing, finding of roles of words, interpretation of question and answering. All these parts developed according to Turkish grammar. In the first phase the QA system can understand question and answers. Later on, constitutes question and answer parallel corpus in other word data bases. The second phase consist of the same pre-processing then searches for the same and similar question in question database if finds the answer gets from answer database. In order to fine similar question similarity vectors approaches were used.
CrowdFix: An Eyetracking Dataset of Real Life Crowd Videos

Understanding human visual attention and saliency is an integral part of vision research. In this context, there is an ever-present need for fresh and diverse benchmark datasets, particularly for insight into special use cases like crowded scenes. We contribute to this end by: (1) reviewing the dynamics behind saliency and crowds. (2) using eye tracking to create a dynamic human eye fixation dataset over a new set of crowd videos gathered from the Internet. The videos are annotated into three distinct density levels. (3) Finally, we evaluate state-of-the-art saliency models on our dataset to identify possible improvements for the design and creation of a more robust saliency model.
An n-Bit Adder Realized via Coherent Optical Parallel Computing

The quantum properties of nanosystems present a new opportunity to enhance the power of classical computers, both for the parallelism of the computation and the speed of the optical operations. In this paper we present the COPAC project aiming at development of a ground-breaking nonlinear coherent spectroscopy combining optical addressing and spatially macroscopically resolved optical readout. The discrete structure of transitions between quantum levels provides a basis for implementation of logic functions even at room temperature. Exploiting the superposition of quantum states gives rise to the possibility of parallel computation by encoding different input values into transition frequencies. As an example of parallel single instruction multiple data calculation by a device developed during the COPAC project, we present a n-bit adder, showing that due to the properties of the system, the delay of this fundamental circuit can be reduced.
DITA Grammar Customization

The Darwin Information Typing Architecture (DITA) standard defines a layered extension mechanism, "specialization", for defining grammars such that the element types and attributes in any conforming DITA grammar are explicitly mapped back to one or more "base" types, with the lowest base type being the type defined in the core DITA grammar. This means that any conforming DITA document can be processed in terms of the base types of the document's elements and attributes, irrespective of how specialized the elements and attributes themselves are. The architecture itself depends only on the use of a DITA-defined attribute ( @class ), where the value is normally set as a default in the grammar. The DITA standard defines conventions for DTD and RELAX NG grammar modules that enable re-use of the declarations for base types when defining new types or constraining existing types and makes customizing content models about as easy as it can be. The DITA standard defines three types of customization: "configuration", "constraint", and "specialization". Configuration combines existing grammar modules in the context of a top-level "shell" grammar to define a unique DITA document type without directly defining or modifying any element type or attribute declarations. Constraints modify existing element type or attribute declarations to make them more constrained (such as disallowing specific elements) but does not add new element types or attributes. Specialization defines new element types or attributes. For DITA DTDs, customization is done through parameter entities and references to individual grammar modules. For DITA RNGs, customization is done through declaration or overriding of patterns. The DITA Technical Committee maintains tooling for generating conforming DITA DTDs from conforming DITA RNGs.
How do Interactive Flood Simulation Models Influence Decision-Making? An Observations-Based Evaluation Method

Interactive flood simulations models are computer models that are usable for practitioners during work sessions, allowing demand-driven flood simulations together with domain experts. It is assumed among developers of such models that these interactive models better serve decision-making processes, resulting in better informed decisions about, for example, evacuation and rescue operations. In order to test this assumption, we present a method that uses observations to monitor and evaluate decision-making processes in work sessions where interactive models are applied. We present a theoretical framework as a basis for this method, based on theory of collaborative knowledge construction, and operationalize this into measurable metrics. We demonstrate our method in two cases of flood disaster management and illustrate and discuss the strengths and weaknesses.
Interpolation and K-Nearest Neighbours Combined Imputation for Longitudinal ICU Laboratory Data

A key challenge when working with real-world data is that most datasets contain missing values, especially in the clinical domain. Many data mining and machine learning methods require complete datasets, and simple techniques for handling missing data (such as complete case analysis, overall mean imputation, and the missing-indicator method) can be an inappropriate choice under many circumstances and may lead to biased estimates of the investigated associations [1].
EVALUASI KESESUAIAN LAHAN SAWAH PASCA BANJIR BANDANG PADA TANAMAN PADI DI KABUPATEN ACEH TENGGARA

The aim of the study was to determine the level of suitability of wetland rice fields in the area before flash floods and post flash floods Lawe Tua Makmur Village, Lawe Alas Subdistrict, Southeast Aceh Regency and soil analysis at the Research and Development Laboratory of PT. Nusa Pusaka Kencana Analytical &amp; Qc. Laboratory Bahilang Tebing Tinggi Medan in April 2016 and December 2017. It is carried out by a survey method that refers to the extent of the limiting factor of land characteristics. Data from observations in the field and data from laboratory analysis were matched to the criteria for the suitability of wetland rice classes. The results showed that the actual land suitability class for paddy rice in the area prior to banjir bandang was according to marginal / S3 (r, f) and the potential land suitability class was marginal / S3 (r). Actual land suitability class for wetland crops in the post-banjir bandang area according to marginal / S3 (r, f, n) and potential land suitability classes according to marginal / S3 (r). The limiting factor is the permanent texture of the soil so that it cannot be repaired and the limiting factors of CEC, organic C and N-total can still be improved by adding organic matter and fertilizing with nitrogen.
Know Your Graph. State-of-the-Art Knowledge-Based WSD

This paper introduces several improvements over the current state of the art in knowledge-based word sense disambiguation.Those innovations are the result of modifying and enriching a knowledge base created originally on the basis of WordNet.They reflect several separate but connected strategies: manipulating the shape and the content of the knowledge base, assigning weights over the relations in the knowledge base, and the addition of new relations to it.The main contribution of the paper is to demonstrate that the previously proposed knowledge bases organize linguistic and world knowledge suboptimally for the task of word sense disambiguation.In doing so, the paper also establishes a new state of the art for knowledge-based approaches.Its best models are competitive in the broader context of supervised systems as well.
Reaching Diverse Audiences with Virtual Reference and Instruction: A Practical Guide for Librarians

"Reaching Diverse Audiences with Virtual Reference and Instruction: A Practical Guide for Librarians." Journal of Web Librarianship, 14(1-2), p. 53
Understanding Human and Predictive Moderation of Online Science Discourse

Manual moderation activities can be fatiguing, emotionally exhausting, and potentially traumatizing, yet moderation is essential to the health of the discussion community. Communities, therefore, can benefit from automated moderation systems. We report on a study with a survey about moderation behaviors and an annotation task involving forum comments to aid curating a deeper understanding of moderation towards predictive support. We also create models for distinguishing between acceptable and unacceptable scientific forum comments and discuss results given moderators responses.
Political Implications of Philosophical Pedagogy.

The article proposes the critical analyses of the P. Mehring conception of philosophical pedagogy founded on the German idealism and Humboldt’s philosophy of education. Transformations of the philosophical pedagogy are considering on the background of organizing changes in the education in the industrial and post-industrial contexts with regard to its meaning, logics and causes. The advantages of the interdisciplinary approach are proving on the problem field of the philosophical pedagogy in times of its rising and falls.The restoration of philosophical pedagogy of the early and developed industrialism is proposing with its idealistic and institutional paradigm (Humboldt-Hegel-Spranger) and the alternative one – the critical anti-institutionalism(Nietzsche -Adorno-Foucault), The heuristic metaphor of the invention of freedom shows on the political engagement of philosophical pedagogy what has both the negative and positive aspects. Some political pathologies of the state in the early post-industrial societies need pedagogical treating. That is why the revival perspective of philosophical pedagogy is inquiring. For this case some actual ideas of W. von Humboldt and its transformations are used to show the risks and dangerous of educational reforms in the post-industrial contexts.The Kantian and Hegelian transformations are researching with the aim to show different tendencies of the development of education in philosophical reflections of pedagogical issues with political consequences regarding as possible paradigmatic changes which can exist as complementary ones. The coherence of political and pedagogical ideas can exist in different constellations pursuing different purposes. The pedagogical construct of freedom as autonomy was often used in the political programs and political decisions, but the political reason is also an important factor for the transformations of contemporary educational systems and practices. The pedagogical construct of freedom foresees the autonomy of educational institutions and independency of individual which cal be lost by his transforming to a Wikipedia-citizen.
Assertional Removed Sets Merging of DL-Lite Knowledge Bases

DL-Lite is a tractable family of Description Logics that underlies the OWL-QL profile of the ontology web language, which is specifically tailored for query answering. In this paper, we consider the setting where the queried data are provided by several and potentially conflicting sources. We propose a merging approach, called “Assertional Removed Sets Fusion” (ARSF) for merging $$DL$$-$$Lite$$ assertional bases. This approach stems from the inconsistency minimization principle and consists in determining the minimal subsets of assertions, called assertional removed sets, that need to be dropped from the original assertional bases in order to resolve conflicts between them. We give several merging strategies based on different definitions of minimality criteria, and we characterize the behaviour of these strategies with respect to rational properties. The last part of the paper shows how to use the notion of hitting sets for computing the assertional removed sets, and the merging outcome.
Image Segmentation Using Fuzzy C-means Optimized by Ant Lion Optimization

Image segmentation is the indispensable part in the field of computer vision. There are tremendous methods for handling this task such as Otsu-thresholding and Fuzzy C-means (FCM). However, the segmentation results of the images are occasionally unsatisfactory due to the presence of noise. In this paper, two kinds of spatial information consisting of the relative position information and the intensity information of the neighborhood pixels in an image are taken into consideration in constructing the objective function in FCM. Moreover, Ant Lion Optimization, one of the recently proposed optimization algorithms is utilized to optimize the relevant index. Bioinspired ALO has the robust ability to find optimal parameters in search spaces. So the proposed approach to image segmentation based on Fuzzy C-Means (FCM) and Ant Lion Optimization (ALO) may alleviate this problem to a certain degree. A series of experimental validation has been implemented for demonstrating the performance of the proposed approach in the end of the paper.
Pengaruh Tanaman Bintang Air (Cyperus Papyrus) Dan Bambu Air (Equisetum Hyemale) Dalam Mengolah Limbah Domestik

&lt;p&gt;One of the technologies that will be used to overcome the problem of environmental pollution due to the generation of greywater is by applying Constructed Wetlands using aquatic plants. Aquatic plants that will be used in this study are using Bintang Air (&lt;em&gt;Cyperus papyrus&lt;/em&gt;) and Bambu Air (&lt;em&gt;Equisetum hyemale&lt;/em&gt;) plants. The purpose of this study was to determine the effectiveness of decreasing BOD&lt;sub&gt;5&lt;/sub&gt; and COD parameters and comparing the ability of each plant to absorb pollutants in greywater. The results showed that the Bintang Air (&lt;em&gt;Cyperus papyrus&lt;/em&gt;) plant was able to set aside BOD&lt;sub&gt;5&lt;/sub&gt; levels of 97.14% while the efficiency of COD levels was 95.43%. At Bambu Air (&lt;em&gt;Equisetum hyemale&lt;/em&gt;) it is able to set aside BOD&lt;sub&gt;5&lt;/sub&gt; levels by 90.34% while efficiency for COD is 89.67%. When viewed from the ability of the two types of plants to absorb pollutants in domestic wastewater, the Bintang Air (&lt;em&gt;Cyperus papyrus&lt;/em&gt;) plant is superior in absorbing pollutants than the Bambu Air (&lt;em&gt;Equisetum hyemale&lt;/em&gt;) plant.&lt;/p&gt;
SCLUSTREAM: AN EFFICIENT ALGORITHM FOR TRACKING CLUSTERS OVER SLIDING WINDOW IN BIG DATA STREAMING

Mining in data streams has been a hot research topic in the recent time. A main challenge in data stream mining lies in extracting knowledge in real time from a massive, dynamic data stream in only a single scan. Data stream clustering presents an important role in data stream processing. This paper proposes SCluStream an algorithm for tracking clusters over a sliding window to handle such challenges. The algorithm is an enhancement over CluStream which does not involve this sliding window concept. In the sliding window model, only the most recent data is used while the old data is eliminated, which allows for faster execution. A better clustering technique is also involved which managed to contribute to accuracy enhancement. The proposed algorithm has been tested on a dataset for Intrusion detection and the results showed that comparing SCluStream to CluStream has proven that the former algorithm is more efficient for online clusters generation for big data streaming in regard of the accuracy as well as the utilized time and memory resources.
The Automation Versus the Human Touch in the Boutique Hotels: Possible Limits

As a leading economic sector in many countries around the world tourism industry is changing rapidly under the pressure of information and communication technologies spread in every activity into daily life and business. Almost unnoticed, technology and artificial intelligence have replaced humans in certain spheres. The question is whether their replacement is positive for the tourism supply or it is not even close. This is especially important for the boutique hotels offering innovative accommodation concept and personalized high-quality tourist product. The aim of the current study is to prove that boutique hotels need both - automated processes and human touch and to outline the limits of the right balance how to emphasize that symbiose in order to benefit of greater loyalty and ongoing revenues.
Revelation of the Heterogeneous Redundancy Architecture

It can be seen from the foregoing chapters that the biggest security threat in cyberspace is uncertain attacks based on the unknown vulnerabilities of the target object, and the biggest defense concern lies in the ability of reliably addressing uncertain attacks based on unknown factors in the absence of priori knowledge. The theoretical challenge is how to quantify the effectiveness of defense against uncertain attacks. In order to change the current situation where cyberspace cannot effectively prevent uncertain threats, the following scientific issues must be tackled:
Human calling in the contemporary world: responsibility and expected competencies of educators

The research focuses on calling phenomenon in the context of the tasks of school reform, definition of the ways of development and motivation of educators. The study analyses social, cultural and humanity aspects of the idea of human calling in the contemporary world as well as the tasks of educators in forming of the system of appropriate competencies of students. The practical issues and international experience of taking into consideration of calling factor in education of teachers and the possibility of use of calling criterion for the assessment of professional suitability of teachers are examined. In particular, the experience of the National Council for the Accreditation of Teacher Education (NCATE) in the USA confirms the necessity of measuring not only the knowledge and psychological qualities of the potential teachers, but also of evaluation their ethical virtues. Therefore, if some teachers do experience a calling, it would fall under the “virtue ethics”.&#x0D; Regarding to the personal nature of the phenomenon of calling and moral autonomy of the person, it is unreasonable and unmoral to implement a formal requirement of calling from the candidates for any job. Whereas in the system of the professional evaluation, in particular in education, the criteria of ethical virtues and attitudes to work has to be formulated as for the indirect manifestations of the experience of calling of a personality. Such indicators are: passion – abilities – their practical implementation – the aim of social benefit. The list of personal virtues corresponding to the experience of calling in education framed as following: open-mindedness, love to children, respect, sympathy, tolerance, objectiveness, honesty, fairness, insistency, responsibility.
Application of Prototype Method on Student Monitoring System Based on WEB

Public vocational school in Subang which continues to improve its academic activities, specifically in terms of improving student discipline related to student participation in school and improving student achievement. The collection of information about student participation and the value of new students delivered at the end of the semester compilation of report cards makes students who experience difficulties in the development of grades, meetings and student learning activities at school, for that we need a system that can help students to help guardians of students and the school in activities that involve students in school. In this research, we use a prototype method for system development. The advantage of the system built is that it can send attendance messages or student grades to enter no answers or get poor test scores for student guardians, student guardians can provide feedback on incoming information and make permits through the existing information system pages, the school also can use attendance data and grades to support activities at school.
Effect of Collaborative Learning Strategies on Student Achievement in Various Engineering Courses

This study focused on determining the effectiveness of collaborative learning strategies in improving students' performance in three general engineering courses. The pretest-posttest control group experimental design was used in the study. From the results of the Z-test, there were no significant differences in the pretest scores of the experimental and control groups. However there were significant differences in the posttest scores of the respondents, with the experimental groups engagedin collaborative learning obtaining significantly higher achievement scores than their control group counterparts,who were exposed to the traditional lecture-discussion and individual learning methods. Effect sizes were also positive for the experimental groups, meaning, they were able to perform better in class compared to their control group counterparts.
Face segmentation based object localisation with deep learning from unconstrained images

Localisation and segmentation of the face region is a key step and prerequisite in automated face recognition systems. Over the past few decades, there has been particular interest and efforts in finding automated, robust, accurate and reliable face detection methods. In this paper, we propose a deep learning-based method to segment face boundaries from unconstrained images. The proposed deep learning model defines the detection of face boundary formula as a combined object localisation and segmentation task. Incorporating an object localisation in a framework developed for segmentation purpose aims to improve the segmentation accuracy achieved by a fully convolutional network. The proposed model is trained on 2800 in-the-wild face images and tested on 700 images achieving dice coefficient of 95.67%, Jaccard score of 91.89%, accuracy of 98.18%, sensitivity of 96.14% and specificity of 98.76%. The experimental results demonstrate that the proposed deep learning method outperforms most of state of the art methods in automatic face detection and segmentation on a challenging dataset.
Multiplicative Local Binary Patterns (MuLBP)

Speckle is a multiplicative noise that greatly deteriorates images. In this paper a model of Local Binary Patterns (LBP) adapted to images with speckle (MuLBP) is proposed. The multiplicative model is constructed by substituting the additive comparisons of the traditional LBP for multiplicative comparisons from the Bigeometric Calculus. The experiments were carried out considering the 10.824 images of the KTH-TIPS2, FMD, CASIA and UFI databases. To compare the additive and multiplicative models, the Euclidean distance between the LBP histograms of the image with noise and without noise is adopted. The results indicate that, the distance between the histograms, the image with noise with respect to the image without noise, is smaller for the multiplicative models than for the traditional additive models. The above means that, the multiplicative LBP represent in a better way the textures in images contaminated with speckle.
MODELLING AN HOLISTIC ARTIFICIAL INTELLIGENT EDUCATION MODEL FOR OPTIMAL LEARNER ENGAGEMENT AND INCLUSION

MODELLING AN HOLISTIC ARTIFICIAL INTELLIGENT EDUCATION MODEL FOR OPTIMAL LEARNER ENGAGEMENT AND INCLUSION
24: EFFECTS OF MONOCYTE DISTRIBUTION WIDTH AND WHITE BLOOD CELL COUNT ON A SEPSIS PREDICTION ALGORITHM

Le, Sidney1; Mataraso, Samson2; Calvert, Jacob1; Hoffman, Jana3; Kehoe, Sarah4; Tejidor, Liliana5; Crouser, Elliott6; Pan, Michael7; Persing, David8; Das, Ritankar1 Author Information