Reviewerly/exHarmony huggingface dataset:
Two‐dimensional shape‐adaptive windowing functions for image analysis

Two-dimensional (2D) windowing functions (e.g. Hann's) defined on square (or rectangular) sub-matrices are routinely used in image processing when the local 2D Fourier transform has to be computed. However, in applications where the square-shaped 2D Fourier transform has to be computed from a spatially limited subset of image data of irregular shape (e.g. from an area obtained by segmenting), windowing functions defined on square sub-matrices cannot be used. Therefore, there is a need for 2D weighting functions whose support shape is adaptable to the shape of a given binary object. Several design variants of 2D shape-adaptive windowing functions (SAW) are presented as a proposed solution to this problem. In order to quantitatively assess and compare the design variants, five criteria for measurement of 2D SAW qualities are proposed. Based on extensive testing undertaken on both simulated and real-life data, it can be concluded that qualities of each of the proposed 2D SAW design variants are generally superior to the quality of an evenly-weighting window according to these test criteria. In conclusion, one of these 2D SAW design variants is recommended as superior for generic use in image processing.
WHERE IS <i>SALUT</i>?

Abstract I first performed Salut für Caudwell (1977) at November Music in Den Bosch, two and half years ago. The festival celebrated Lachenmann's eightieth birthday in grand style, and the composer himself attended. During a backstage chat, Lachenmann, whom I've known for around 20 years, casually hinted that there were things ‘missing’ in the print edition of the work, published in 1985: that is, that performative information in the fair copy was not fully reproduced in the print edition. At that moment, my curiosity was piqued intensely, and the seed of a new edition was planted. While I understood the formidable challenges involved in properly preparing the part, rehearsing, and traversing this Everest of the guitar literature, I was not fully prepared for the astonishing array of hazards that awaited me. This article describes the labyrinth of sketches, drafts, and score iterations I encountered in beginning to prepare a new edition of Salut for Lachenmann's publishers, Breitkopf &amp; Härtel.
Science educational center as an opportunity of creation of organizational-pedagogical conditions of improvement of professional growth of biology teachers

The article deals with the problems associated with the effectiveness of school natural science education, the achievement of student’s planned results, while there is some decrease in the results in the mastery of biological knowledge and skills by students. The authors propose a model of creating a natural science educational center as a condition of optimization of the educational process and the possibility of achieving new high-quality subject results of graduates.
Virtual reality technology on health intervention for women: a literature review

Virtual Reality (VR) technology application has become more affordable, immersive and portable. This is also happening in the health intervention domain. While the usage of the VR applications is still dominated by man, we conduct a literature review study to see the state-of-the-art in the application for recent VR technologies for women's health intervention. This study is done since women are more susceptible to some disease than men, feel pain more easily, more susceptible to autoimmune diseases, and experience anxiety and phobia more easily. It will help future studies to lookup the big impact of VR health intervention for women. The result of the literature review shows that there are three types of VR technology are used in the application (non-immersive, semi-immersive, and full-immersive), there are four category of health interventions done through VR (prevention, diagnosis, treatment, diagnosis-treatment), and the domain of the disorder are focused mostly to psychological and physical aspect.
Privacy &amp; Usability of IPTV Recommender Systems

IPTV is capable of providing recommendations for upcoming TV programs based on consumer feedback. With the increasing popularity and performance of recommender systems, risks of user privacy breach emerge. Although several works about privacy-preserving designs of recommender systems exist in the literature, a detailed analysis of the current state-of-the-art regarding privacy as well as an investigation of the usability aspects of such systems, so far, have not received consideration. In this paper, we survey current approaches for recommender systems by studying their privacy and usability properties in the context of IPTV.
Parsing RDFs to Extract Object Oriented Model Using Apache Jena

Process model play a vital role in structure analysis of system as it can identify system’s classes, their attributes, operations (or methods), and the relationships among objects. These class models can be go together with state diagrams or UML state machine to identify the behavior of systems. Currently web is huge source of information which contain huge amount of data. Semantic Web idea gain popularity by its efficient manner of data representation over the web. Key concept of semantic web is based on common medium for data representation making data more flexible and support data interoperability. Semantic web stores data in ontology, which provide description of data for domain. Ontology can be written by using different standard languages i.e. XML, RDF, RDFs. RDF give semantic representation of data by showing data as Resources and their associated properties, relations Schema is vocabulary which provide description about classes and properties of RDF resources. RDF file can be manipulated by user for extraction of information in different ways according to requirement of user. In our research we proposed an APACHE Jena based methodology which take RDF file of web information system as input and convert it in to object oriented process model to illustrate structural representation of we system. Therefore “Consuming RDF Schemas for extraction of information in different required manners” is root cause of current research.
A Modified Version of AlQuAnS: An Arabic Language Question Answering System

The challenges of the Arabic language and the lack of resources have made it difficult to provide Arabic Question Answering (QA) systems with high accuracy. These challenges motivated us to propose AlQuAnS-an Arabic Language Question Answering System that gives promising accuracy results. This paper proposes a modified version of AlQuAnS with a higher accuracy. The proposed system enhances the accuracy of the question classification, semantic interpreter and answer extraction modules. The provided performance evaluation study shows that our modified system outperforms other existing Arabic QA systems, especially with the newly introduced answer extraction module.
Analysis of Customer Emotion from Video based Feedback of a Product

Due to the high levels of competition in a global market, companies have put more effort on building strong customer relationships and increasing customer satisfaction levels. Now-a-days due to technological improvements in information and communication technologies gives a highly anticipated key contributor to improve the customer experience and satisfaction in service episodes is through the application of video analytics, such as to evaluate the customer’s emotions over the complete service cycle. Currently, emotion recognition from video could be a difficult analysis space. One of the foremost effective solutions to deal with this challenge is to utilize each audio and visual part as two sources contained within the video knowledge to form an overall assessment of the emotion. The combined use of audio and visual knowledge sources presents further challenges, such as determining the optimal data fusion technique prior to classification. In this paper, we propose an audio–visual emotion recognition system to detect the universal six emotions (happy, angry, sad, disgust, surprise, and fear) from video data. The detected customer emotions are then mapped and translated to provide client satisfaction scores. The projected client satisfaction video analytics system will operate over video conferencing or video chat. The effectiveness of our proposal is verified through numerical results.
Korean-Optimized Word Representations for Out-of-Vocabulary Problems Caused by Misspelling Using Sub-character Information

In this paper, we propose Korean-optimized word representations that can better address the out-of-vocabulary (OOV) problem caused by misspelling. This problem is an important issue in many applications based on natural language processing. However, previous models do not fully consider the representations of misspelled OOV words. To overcome this problem, we propose sub-character information obtained from Korean Jamo units and also adopt additional sub-character information to better withstand the misspelling. Finally, experimental results show that our model is about 2.3 times more accurate than the conventional model in case of the misspelled word while still maintaining the semantic relationship of the words.
Drawing Similarity Measurement Using Object Alignment

Shape similarity plays important role in human perception. Humans always look for similarities between the shape of what they see and the shape of what they saw via comparison. Shape similarity has many applications in different fields such as cognitive science, medicine and computer science. This is a study in which a system is designed and implemented to measure similarities of two circular drawing shapes. The system follows different steps and techniques related to digital image processing such as; binarization, morphological operations and image segmentation. The novelty of the system comes from image alignment in which some transformation is performed to eliminate size dependency in similarity measurement. The transformation works on changing the origin point followed by stretching. In this study 30 pairs of circular shapes are considered. The results shows the system has 91.38% accuracy in average while maximum accuracy among 30 pairs of samples is 99.98% and minimum accuracy is 69.15%.
Quantum entanglement in trimer clusters

Quantum entanglement is a measure of quantum correlations which are responsible for effective work of quantum devices (in particular, quantum computers), significantly outperforming their classical counterparts.<sup>1</sup> Here, we investigate quantum entanglement in the trimer clusters consisting of three electron spins sited in vertexes of an isosceles triangle. We consider entanglement of two subsystems of the system. The first subsystem consists of spins sited on the triangle baseline and the second subsystem consists of a spin equidistant from others. We generalized the Bleany-Bowers equation<sup>2, 3</sup> for trimer clusters. It is shown that entanglement can emerge only in the case of the antiferromagnetic interaction of the subsystems. An equation for the temperature of the entanglement emergence is derived. The criterion of the double negativity<sup>4</sup> is used in order to find the dependence of the entanglement on the temperature.
Is Anybody Out There?

This chapter will explore how social media assessment is used for library marketing. It will build upon existing literature on how other libraries quantify social media impact in promoting their services. This includes methods on how libraries can gather native application statistics from popular platforms such as Facebook, Twitter, YouTube, and Instagram. An exploration into web analytics will also be explored as evidence of social media impact. The chapter will use case-studies of the Ursula C. Schwerin Library of the New York City College of Technology (City Tech), CUNY, and how social media platforms are used to advertise library events and disseminate news.
Multi-Mirror Array Optics for Augmented Reality Devices and Optical Distortion Correction

Multi-Mirror Array can minimize the optics of Augmented Reality devices. We made a glass-type display device with Multi-Mirror Array, and Wide field of view combiners for head-up displays with Fresnel reflector that has optical power to magnify the projected image. We also developed Optical Distortion Correction for projecting the images on Multi-Mirror Array. Finally, we show an application of Optical Distortion Correction.
Views of BS Information Technology Students on Academic Calendar Shift

Objectives:The matter of changing the academic calendar is a relevant and timely issue among Higher Education Institutions in the Philippines.Legislators, academic managers, student representatives and various stakeholders expressed their opinions and concerned about the issue.This study is conducted to determine the views of the BS Information Technology students on the educational calendar shift of Leyte Normal University, Tacloban City.Methods: Survey questionnaires and google form used to obtain the data.One hundred sixty-two (162) students served as a sample of the study.Findings: The data revealed that most of the students expressed favorably on academic calendar shift from June to August with (80.20%, n = 130).Shifting of classes in the tertiary level is a courageous move of the university, because of its effects after the implementation or even during the transition period.Applications/Improvements: This move is inevitable and recommended based on the current situation of the paradigm shift of educational system in the Philippines, impact of climate change, globalization impact, competitions and synchronization of activities in the region and the world.
SSCARF Education Model and Happiness Index Modelling

SCARF model has been proposed and widely adopted in most traditional classroom teaching for decades. SCARF essentially focus on Status, Certainty, Autonomy, Relatedness and Fairness, in neuroscience, which constitute to developing the character of a child in city living. However, this paper studies about the alternative education model in Heibe, China. It is found that those children lack of family supports, especially siblings (due to the one-child policy in China in the past years); and the neigbours live far apart. Hence, most of those children grow up in isolated environment. By tracing these the brought-up of those children, who attended a voluntary school where the author has taught for some years, it is noticed that those children appear to be happier in general, compared to those who did not go to such school. Hence it is pondering on the importance of social life which can be provided by attending the lessons in the voluntary school. In this paper, the authors propose extending the SCARF model to SSCARF where the prefix S symbolizing the social life that is in provision in the voluntary school. It is believed that the social aspect is a very important part of a child’s brought up. The hypothesis of SSCARF especially the social “S” is backed and verified by happiness index modelling via data mining. The results show that happiness is more related to the social aspects of the children’s childhood than material wealth.
An On-Demand Processing Framework for Faster Remote Sensing Big Data Analysis

Remote sensing data are considered as "big geo data" because of their huge data volume, significant heterogeneity and challenge of fast analysis. The traditional remote sensing analysis workflows make earth scientists to download raw data files to local workstations before processing them for science discoveries. The data transfer often costs a lot of time and slows down the analysis workflows. Due to results of remote sensing data analysis models are usually much smaller than raw data to be processed in most cases, "on-demand processing", which tries to upload and run data analysis models near the remote sensing data, can make the remote sensing analysis workflows faster. In this paper, an on-demand remote sensing data processing framework is proposed based on a three-layered architecture for faster remote sensing data analysis workflows. The evaluation on a prototype system shows that the on-demand processing framework can accelerate the execution of analysis models significantly by reducing data transfers, especially for those analysis workflows which transfer data through low bandwidth Internet.
A Comparative Study of Standard Part-of-Speech Taggers

The Part of Speech (PoS) tagging is resolving ambiguity during text processing to assign morphosyntactic tags to each word according to the context. It is an essential task in several fields, particularly corpus linguistics and Natural Language Processing (NLP). Several PoS taggers and tools are already in service as open source or as commercialized solutions. Therefore, deeper investigation regarding their performance is required especially for under-resourced languages like Arabic. Some well-known probabilistic methods were adapted for PoS tagging such as Hidden Markov Models (HMMs), Support Vector Machines (SVM), and Decision Tree (DT). Based on these methods, language-independent PoS taggers have been developed namely TnT, SVMTool, and Treetagger. In fact, this article presents very important topic which concerns, on the one hand, an adaptation of Standard PoS taggers for the Arabic language, and in the other hand conducting very rich and comparative studies and evaluation. Basically, Arabic PoS taggers are very sensitive to the number of the tagsets used and the text form processed, therefore, four different tagsets and two text forms (i.e., Classical and Modern Standard Arabic) have been used.
Domain Adaptation for Semantic Segmentation with Conditional Random Field

Fully-convolutional neural networks (CNNs) for semantic segmentation dramatically improve performance using end-to-end learning on whole images in a supervised manner. The success of CNNs for semantic segmentation depends heavily on the pixel-level ground truth, which is labor-intensive in general. To partially solve this problem, domain adaptation techniques have been adapted to the two similar tasks for semantic segmentation, one of which is fully-labelled, while the other is unlabelled. Based on the adversarial learning method for domain adaptation in the context of semantic segmentation (AdaptSegNet), this paper proposes to employ the conditional random field (CRF) to refine the output of the segmentation network before domain adaptation. The proposed system fully integrates CRF model with CNNs, making it possible to train the whole system end-to-end with the usual backpropagation algorithm. Extensive experiments demonstrate the effectiveness of our framework under various domain adaptation settings, including synthetic-to-real scenarios.
INFORMATION TECHNOLOGIES IN EXTRACURRICULAR ACTIVITIES ON ASTRONOMY (ON THE EXAMPLE OF THE WEB QUEST “FIRST IN SPACE”)

A web quest, as one of the forms of distance learning, is a tool that allows pupils to study educational material with interest. This form can be especially effective for studying the material of those school subjects, for the study of which is given less than two hours a week. The article offers a description of the web quest “First in Space”, developed and conducted as part of the celebration of the 60th anniversary of the beginning of the space age.
A New Web Service Architecture for Enhancing the Interoperability of LMS and Mobile Applications Using the Next Generation of SCORM

The evolution of mobile learning has changed the way of learning. With the growing popularity of using mobile devices, mobile learning has become important in teaching and learning in education. Most m-learning services are provided by the Learning Management Systems. This article aims to design a software architecture with LMS and focuses on integrating mobile applications to improve interoperability. This architecture is being implemented for the famous open source LMS Moodle.
Robustness of quantum correlation for accelerating two atoms coupled with electromagnetic field

In this paper, we investigate the behaviors of quantum correlation quantified by trace norm measurement-induced nonlocality (TMIN) for two uniformly accelerated atoms coupled with electromagnetic vacuum fluctuation in the Minkowski vacuum. We firstly discuss the solving process of master equation that governs the system evolution based on the Pauli matrix presentation for two-qubit state. Similar to [Y. Q. Yang et al., Phys. Rev. A 94, 032337 (2016)], we analyze the degradation, creation, revival and enhancement of quantum correlation for different initial states and polarizations of two atoms, and the influence of interatomic separation and acceleration on quantum correlation. Compared with the entanglement dynamics discussed in [Y. Q. Yang et al., Phys. Rev. A 94, 032337 (2016)], it is found that quantum correlation exhibits better robustness than entanglement. This may be helpful for quantum information processing.
Image retrieval of breast masses on ultrasound images

Presentation of images similar to a new unknown lesion as a reference can be helpful in medical image diagnosis and treatment planning. We have been investigating a method to determine similarity of breast masses as an image retrieval index for an intelligent image analytic system that may support radiologists’ efficient image interpretation. In order to retrieve perceptually similar images, we have obtained subjective similarity ratings from expert radiologists, which were then used in similarity space modeling and training deep neural networks. In this study, we investigated the use of convolutional neural network to model the similarity space for retrieval of diagnostically relevant reference images and also to directly estimate similarity ratings for pairs of images. The preliminary results show that retrieval performance was slightly better in similarity space modeling method than direct estimation method. These results indicate the potential usefulness of the proposed methods for retrieval of reference images as diagnostic assistance.
Code Verification Based on TPM Solutions for Internet of Things Platforms

Today’s Internet of Things (IoT) is achieving more and more importance, since networks of physical objects embedded with electronic components, software and sensors are gaining popularity. The connectivity of such objects becomes crucial for the services and functionalities provided by the Internet of Things, which can be used for a great range of purposes: a network of cars sharing traffic information, a network of medical services, etc. more applications require the use of embedded code. This code usually exchanged in a pre-compiled form (byte code), can be naturally the product of the compilation of a source program written in a given language (smart cards,), but can also be of a unknown source (network games, hackers,). It is therefore appropriate, before running it, to make sure it is free of errors and that its execution on the host platform will not affect the proper functioning, both in terms of the calculation time and the level of the memory resources used. We are interested here in different techniques and methods to specify and to verify the veracity of the code exchanged between the different machines, In this case, we have to focus in two different sources of action: Device authentication: to ensure that any device can be replaced by a fake one and Software state attestation: to ensure that the current software state matches the system state. The way to address this issue is through trusted element-based TPM solutions.