Reviewerly/exHarmony huggingface dataset:
LGS: LOCAL GEOMETRICAL STRUCTURE-BASED INTEREST POINT MATCHING FOR WIDE-BASELINE IMAGERY IN URBAN AREAS

Abstract. Feature matching is a fundamental technical issue in many applications of photogrammetry and remote sensing. Although recently developed local feature detectors and descriptors have contributed to the advancement of point matching, challenges remain with regard to urban area images that are characterized by large discrepancies in viewing angles. In this paper, we define a concept of local geometrical structure (LGS) and propose a novel feature matching method by exploring the LGS of interest points to specifically address difficult situations in matching points on wide-baseline urban area images. In this study, we first detect interest points from images using a popular detector and compute the LGS of each interest point. Then, the interest points are classified into three categories on the basis of LGS. Thereafter, a hierarchical matching framework that is robust to image viewpoint change is proposed to compute correspondences, in which different feature region computation methods, description methods, and matching strategies are designed for various types of interest points according to their LGS properties. Finally, random sample consensus algorithm based on fundamental matrix is applied to eliminate outliers. The proposed method can generate similar feature descriptors for corresponding interest points under large viewpoint variation even in discontinuous areas that benefit from the LGS-based adaptive feature region construction. Experimental results demonstrate that the proposed method provides significant improvements in correct match number and matching precision compared with other traditional matching methods for urban area wide-baseline images.
Experimental Study on Scanning of Degraded Braille Books for Recognition of Dots by Machine Learning

Braille books follow processes of deteriorations different from ordinary printed books because visually impaired people read the sharp dot with the finger’s belly. In frequently read braille books, braille is dirty with aging, collapses, and holes open. Then, visually impaired people cannot read braille books. For braille books manually transcribed, the only method to republish them is to rebuild though the original is often and already disposed of. Now, we read degraded braille books with a scanner and restore them. In this paper, comparative experiments on what types of scanner are appropriate to successfully read degraded braille from old braille books are carried out. The candidates are two flatbed scanners, GT-S 650 and Plustek OpticBook 4800, and a stand scanner, ScanSnap SV600. Each scanner scans three types of braille papers, fresh books, used books and old books. Next, to recognize and identify dots in braille papers, we use two methods, the Haar classifier in OpenCV as image processing function and the deep learning with Google’s TensorFlow. For aiming at improving the recognition rate, we also use scanner options suitable for reading. Experimental results show that the flatbed scanner is suitable for reading.
Primary school students' intrinsic motivation to plugged and unplugged approaches to develop computational thinking

This paper compared primary school students' intrinsic motivation to plugged and unplugged approaches to develop computational thinking using a revised Intrinsic Motivation Inventory. A total of 400 fourth-graders who have completed a school-provided coding course participated in the study. The revised instrument examined students' motivation of the two learning approaches from four dimensions: interest, perceived competence, value and relatedness. The main findings of the study are: (1) primary school students show moderate to high motivation to learn computational thinking through both plugged and unplugged approaches; (2) compared to unplugged approach, students gain higher perceived competence from plugged approach; and (3) the revised Intrinsic Motivation Inventory has good psychometric properties in the context of computational thinking except for the close correlation among different dimensions. Finally, implications for developing computational thinking with mobile devices were proposed.
An Empirical Study of Information Visualization for Decision Support in an Emergency Department Information System

Emergency departments collect large amounts of data to make decisions regarding patient care. Implementation of decision support tools with information visualization (IV) techniques in Emergency Department Information System (EDIS) is difficult to achieve and thus an evaluation of the techniques is needed. The purpose of this study is to conduct a usability study of various IV techniques in EDIS and provide recommendations for developers. Fifty-nine participants were recruited in this study. Results indicate the density chart, tree map, and network diagram have lower times, higher usability scores, and lower mental workload ratings than the 3D scatter plot, scatter plot matrix, and parallel coordinates. Findings of this study can provide insights for the development of information visualization tools to support decision making in an emergency department information system.
An Analysis of Associative Meanings in Two Songs Albums of Lorde

This research is analyzing associative meanings in Lorde’s selected songs lyric. The aimed of this study is to find out the types and the functions of associative meanings in Lorde’s selected songs lyric. This research used descriptive qualitative research approach and a major theory of associative meaning from Leech’s (1985) theory. In this research, the researcher gathered the data by collecting, marking and describing words, phrases, and sentences in the song’s lyric from two albums that contained associative meaning such as connotative meaning, social meaning, affective meaning, reflected meaning, and collocative meaning. Then, the researcher analyzed the data by classifying words, phrases, and sentences that contained types and function of associative meanings which referred to Leech’s (1985) theory, then explained the finding, and the last formulated research conclusion based on data finding and analysis. The result of this research showed that there were sixty-nine data of associative meaning as well as their functions in ten songs lyric of Lorde. There were seven data of connotative meaning, thirty-five data of social meanings, eleven data of affective meaning, eleven data of reflected meaning, and five data of collocative meanings. The dominant type of associative meaning that used in Lorde’s songs lyric is social meaning in which the lyrics used informal languages such as idioms, slangs, and colloquials.
Reach, a keyboard-based gesture recognition system for live piano sound modulation

This paper presents Reach, a keyboard-based gesture recog- nition system for live piano sound modulation. Reach is a system built using the Leap Motion Orion SDK, Pure Data and a custom C++ OSC mapper1. It provides control over the sound modulation of an acoustic piano using the pi- anist’s ancillary gestures.The system was developed using an iterative design pro- cess, incorporating research findings from two user studies and several case studies. The results that emerged show the potential of recognising and utilising the pianist’s existing technique when designing keyboard-based DMIs, reducing the requirement to learn additional techniques.
Positivity and complete positivity of differentiable quantum processes

We study quantum processes, as one parameter families of differentiable completely positive and trace preserving (CPTP) maps. Using different representations of the generator, and the Sylvester criterion for positive semi-definite matrices, we obtain conditions for the divisibility of the process into completely positive (CP-divisibility) and positive (P-divisibility) infinitesimal maps. Both concepts are directly related to the definition of quantum non-Markovianity. For the single qubit case we show that CP- and P-divisibility only depend on the dissipation matrix in the master equation form of the generator. We then discuss three classes of processes where the criteria for the different types of divisibility result in simple geometric inequalities, among these the class of non-unital anisotropic Pauli channels.
Measuring fluorescence into a nanofiber by observing field quadrature noise

We perform balanced homodyne detection of the electromagnetic field in a single-mode tapered optical nanofiber surrounded by rubidium atoms in a magneto-optical trap. Resonant fluorescence of atoms into the nanofiber mode manifests itself as increased quantum noise of the field quadratures. The autocorrelation function of the homodyne detector&#x2019;s output photocurrent exhibits exponential fall-off with a decay time constant of 26.3&#x00B1;0.6&#x2009;&#x2009;ns, which is consistent with the theoretical expectation under our experimental conditions. To the best of our knowledge, this is the first experiment in which fluorescence into a tapered optical nanofiber has been observed and measured by balanced optical homodyne detection.
A Framework for UC-Secure Commitments from Publicly Computable Smooth Projective Hashing

Hash proof systems or smooth projective hash functions (SPHFs) have been proposed by Cramer and Shoup (Eurocrypt’02) and can be seen as special type of zero-knowledge proof system for a language. While initially used to build efficient chosen-ciphertext secure public-key encryption, they found numerous applications in several other contexts. In this paper, we revisit the notion of SPHFs and introduce a new feature (a third mode of hashing) that allows to compute the hash value of an SPHF without having access to neither the witness nor the hashing key, but some additional auxiliary information. We call this new type publicly computable SPHFs (PC-SPHFs) and present a formal framework along with concrete instantiations from a large class of SPHFs. We then show that this new tool generically leads to commitment schemes that are secure against adaptive adversaries, assuming erasures in the Universal Composability (UC) framework, yielding the first UC secure commitments build from a single SPHF instance. Instantiating our PC-SPHF with an SPHF for labeled Cramer-Shoup encryption gives the currently most efficient non-interactive UC-secure commitment. Finally, we also discuss additional applications to information retrieval based on anonymous credentials being UC secure against adaptive adversaries.
Service Equivalence via Multiparty Session Type Isomorphisms

This paper addresses a problem found within the construction of Service Oriented Architecture: the adaptation of service protocols with respect to functional redundancy and heterogeneity of global communication patterns. We utilise the theory of Multiparty Session Types (MPST). Our approach is based upon the notion of a multiparty session type isomorphism, utilising a novel constructive realisation of service adapter code to establishing equivalence. We achieve this by employing trace semantics over a collection of local types and introducing meta abstractions over the syntax of global types. We develop a corresponding equational theory for MPST isomorphisms. The main motivation for this line of work is to define a type isomorphism that affords the assessment of whether two components/services are substitutables, modulo adaptation code given software components formalised as session types.
8. A survey on iterations of mappings over finite fields

We survey iterations of polynomials and rational functions over finite fields. We show precise information on periodicity and permutational properties for some classical functions over finite fields including some quadratic polynomials, Chebyshev, Rédei, linearized and power maps. It seems hard to predict the periodicity behavior of functions over a finite field, so we provide heuristic arguments aiming at understanding their behavior in comparison to random uniform mappings over a finite field. We conclude showing a well-known methodology that provides many results about uniform random mappings.
A Virtual Learning Environment to Acquire Orientation Skills in the LUSI Class Context

Virtual Reality (VR) technologies become a promising tool in the context of learning especially for learners with learning disabilities, because of their technological specificities that differentiate them from the traditional learning environments. The development of educational virtual environment is a complex task due to the interdisciplinarity intrinsic to VR and its cognitive aspects. This paper describes a research work whose objective is to propose a solution based on virtual reality to enhance the traditional learning to acquire orientation skills in the LUSI class. This research work identifies some limitations with existing solutions and studies the design and operationalization of learning situations in the form of scenario models. Our aim is providing trainers with an educational toolkit, thus allowing them to recreate virtual reality scenarios and assess the learners’ progress for learning orientation skills.
Searching Similarity Digital Image Using Color Histogram

In the era of globalization and modernization, as now, information technology is widely used in the fields of education, trade, animal husbandry, agriculture and even to the legal sector. One branch of science in the field of information technology that is growing rapidly is computer vision. One of the important roles of computer vision in everyday life is the use of computer vision. This can be applied in terms of face recognition, object detection, and can be applied to group images based on the order of similarity of the image, the ability of computer vision is applied to facilitate human work in selecting from several images to find the most similar images. In this study described the process of finding the similarity of an image with other images through several stages of research flow, the method used is to use RGB values that have been converted to grayscale, then the eucludian distance distance is calculated to determine the value of proximity of an image while calculating performance accuracy algorithm using confusion matrix. The search trial process resulted in an accuracy rate of 0.42, precision of 0.42 and recall 1 of 1000 datasets and 30 random data were taken. Found images that differ in color and shape but when converted into histograms the data has a fairly high similarity to the query. The disadvantage of this research is that images that have histograms similar to queries are displayed as similar images even though the reality is that images are very different from colors and shapes.Keywords: computer vision, similiarity, eucludian distance, grayscale, histogram
PELATIHAN PUBLIC SPEAKING UNTUK MENUNJANG KEMAMPUAN PRESENTASI BAGI SISWA SMAN 1 MARGAHAYU KABUPATEN BANDUNG

Abstract Ability in public speaking is an important part in every activity, especially activities in the academic environment. In reality, there are still few school students who have the public speaking skill. Departing from this, the Community Service Team of the Department of Communication of the University of Pasundan took the initiative to conduct services on Public Speaking Training. Dedication was carried out at SMAN 1 Margahayu Bandung Regency, the selection of these locations was inseparable from the many potential students who wanted to have the ability of public speaking to speak in public and presentation techniques, but had not been fully honed. The method used in this training is giving material, discussion and simulation. In training activities carried out, exploring the potential of students is done by asking them to speak in public without preparation. This is indicated by their ability to practice knowledge while taking public speaking training. The training which ended with the simulation showed that there was a good potential for students of SMAN 1 Margahayu Bandung Regency in the field of public speaking. Potential will just evaporate if it is not sharpened continuously to face the world of lectures and jobs in the future.
Advanced Methods of Detection of the Steganography Content

In this paper, we deal with the classification of the steganography content. Some illegal activities can perform steganography for stealing the secret information from a company internal network. Therefore, we must be prepared to protect our data. To detect steganography content, we have counter-technique known as steganalysis. There are different types of steganalysis, based on the existence of the original artifact (cover work) or if we know which algorithm embed a secret message. For practical use, most important are methods of blind steganalysis, that can be applied to the most compact and ordinary cover work - JPEG image files. This paper describes the methodology to the issues of JPEG image steganalysis. It is crucial to understand the behavior of the targeted steganography algorithm. Then we can use it is weaknesses to increase the detection capability and success of classification. We are primarily focusing on breaking the DCT steganography algorithm OutGuess2.0 and secondary on breaking the F5 algorithm. We are analyzing the ability of the detector, which utilizes the calibration process, blockiness calculation, and shallow neural network to identify the presence of steganography message in the suspected image. This approach is an improvement over our previous researches. Contribution and new results are discussed.
Trends and strategies for conducting effective STEM research and applications: a mobile and ubiquitous learning perspective

Science, Technology, Engineering, Mathematics (STEM) has been recognised by educators as an important educational objective in the 21st century. It provides a new vision of education by encouraging school teachers to engage students in problem-solving, critical-thinking and creative-thinking tasks using the knowledge and skills learned from multiple disciplines. While the effectiveness of STEM has been recognised by educators, the challenges of applying it to school settings have also been indicated, such as the difficulties in designing cross-disciplinary tasks and measuring students' learning performances. Mobile and ubiquitous technologies have been regarded as a potential facilitator which enables learners to learn across contexts with access to learning resources in anywhere and at any time. The use of these new technologies could provide new perspectives and opportunities for developing STEM activities and studies. This paper highlights the challenges as well as the strategies for implementing STEM activities in school settings and designing STEM research. It proposes several models for guiding researchers and schoolteachers to develop STEM learning design are proposed. In addition, it provides several strategies and measuring tools for developing in-depth experimental STEM studies.
Enhancing Students’ Oral Communication By Using Communicative Language Teaching (CLT)

This article aims at providing students’ oral communication in speaking class. There were two specific purposes to gain the data namely to find out the effects of Communicative Language Teaching (CLT) in teaching oral communication especially in speaking ability and to disclose the responses of students in the learning process by using Communicative Language Teaching (CLT). In order to obtain the comprehensive data, the writers used performance test and questionnaire with 32 respondents on speaking class. This research was applied in quantitative method. The writers used the design of interact group comparison. The result showed that there was a significant effect on the use of CLT approach. It was proven that t observation was bigger than t table; t observation was 2.98 while t table was 2.021 (2.98&gt; 2.021). Most of the students agreed if CLT was applied in teaching-learning activites, especially in speaking class because it could help them in improving their ability in oral communication. The results of their opinion towards the application of CLT were expressed by chosing option 4 (agree) and 5 (strongly agree) in every indicator. For indicator 1 and 10, students tent to choose option 5 (strongly agree) with the percentage of 56.3 and the mean of 2.8. In indicator 2 and 4, the students tent to choose option 5 with the percentage of 59.4 and the mean of 3.0. In indicator 3 and 7, the students tent to choose option 4 (agree) with the percentage of 62.5, and mean score of 2.5. For indicator 5 and 6, the students chose option 5 with the percentage of 50.0 and mean score of 2.5. For indicator 8 and 9, most of the students tent to choose option 5 (strongly agree). The percentage and mean score were different. In indicator 8, the percentage was 56.3 with the mean score of 2.3 whereas in indicator 9, the percentage was 68.8 which the mean score of 2.8 more of the respondents were strongly agree with the application of CLT approach in speaking class. It made the students interestend in following speaking class and the students have confidence to speak with other friend or lecturer inside or outside the classroom.
Feature weighting using a clustering approach

In recent decades, the volume and size of data has significantly increased with the growth of technology. Extracting knowledge and useful patterns in high-dimensional data are challenging. In fact, unrelated features and dimensions reduce the efficiency and increase the complexity of machine learning algorithms. However, the methods used for selecting features and weighting features are a common solution for these problems. In this study, a feature weighting approach is presented based on density-based clustering. This method has been implemented in two steps. In the first step, the features were divided into clusters using density-based clustering. In the second step, the features with a higher degree of importance were selected in accordance to the target class of each cluster. In order to evaluate the efficiency, various standard datasets were classified by the feature selection and their degree of importance. The results indicated that the simplicity and suitability of the method in the high-dimensional dataset are the main advantages of the proposed method.
Support vector machines applied to fast determination of the geographical coordinates of earthquakes, The case of El Rosal seismological station, Bogotá Colombia

AbstractThe objective of this research was to determine seismic events latitude and longitude using support vector machines (SVMs) and seismic records from “El Rosal” station, which is located 40 kilometers northwest of Bogotá, Colombia. A total of 504 SVMs models were tested to determine latitude and 504 models for longitude, with various combinations of complexity factor and kernel function exponent, applied to earthquakes of 2, 2.5, 3 and 3.5 ML in time windows of 15 , 10 and 5 seconds. The best results showed errors of 40 kilometers for latitude and 30 kilometers for longitude, with respect to the place where the earthquakes were generated. These outcomes might be improved by applying additional descriptors during SVMs training stages, such descriptors can be related to Fourier frequency spectra, predominant period and wavelet transform coefficients.
Cross-Topic Distributional Semantic Representations Via Unsupervised Mappings

Eleftheria Briakou, Nikos Athanasiou, Alexandros Potamianos. Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). 2019.
Toward Next-generation Data Centers : Principles of Software-Defined “Hardware” Infrastructures and Resource Disaggregation

The cloud is evolving due to additional demands introduced by new technological advancements and the wide movement toward digitalization. Therefore, next-generation data centers (DCs) and clouds ar ...