Reviewerly/exHarmony huggingface dataset:
Evaluating Marine Economic Bearing Capacity: A Network Analysis

Liu, J.; Liu, C.-L.; Zhang, L.-P., and Xu, Y., 2019.Evaluating marine economic bearing capacity: a network analysis. In: Gong, D.; Zhu, H., and Liu, R. (eds.), Selected Topics in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 94, pp. 597–600. Coconut Creek (Florida), ISSN 0749-0208.Because of the approximate characteristics of network analysis method, it has been used by many researchers to solve the evaluation of marine economic carrying capacity. In this paper, a method of evaluating and contributing factors of marine economic carrying capacity based on network analysis method is proposed. Based on the evaluation and contribution factors of marine economic carrying capacity, the evaluation and contribution factors of marine economic carrying capacity (MEBC), evaluation of bearing capacity (EBC) and control factors of marine economy (CFME) are established. The experimental results show that this method has wide applicability, and it is also a useful exploration for the evaluation of marine economic carrying capacity in the new period.
Secured Data Storage in Cloud Using Homomorphic Encryption

Cloud data storage is a model of data storage where data in its digital form is stored in logical pools across the physical storage which is distributed across multiple servers usually in diverse locations. The full physical environment is owned and managed by an organization called Cloud Service Provider (CSP). In this type of storage, the data is distributed and owned by third party, and there is risk of unauthorized access. This makes security, reliability, confidentiality and privacy of data more important when storage in cloud is thought of. Although there are methods available for providing security, much work is not done with emphasis on dynamic nature of the data. Hence securing the data while updating becomes important. In this paper, a method that ensures confidentiality of data stored in cloud using homomorphic encryption is presented. The paper also provides a technique to ensure confidentiality during data updates in cloud. The presented method includes byte level automorphism for ensuring data integrity and confidentiality. The tabulated experimental results show that the proposed method provides more secure frame work for ensuring confidentiality and integrity of data in cloud.
Gradient Ternary Transition based Cross Diagonal Texture Matrix for Texture Classification

This paper derives a new local descriptor gradient ternary transition based cross diagonal texture matrix (GTCDTM) for texture classification.This paper initially divides the image into a 3x3 window in an overlapped manner.On each 3x3 window, this paper computes the gradient between center pixel and each sampling point of the window.This paper divides the gradient window into cross and diagonal matrices and computes gradient transition (GT) cross unit (GTCU) and GT diagonal unit (GTDU).The GT's are derived by computing relationship between adjacent gradient pixels of cross and diagonal matrices in a clock wise manner.This research derived GTCDTM by computing the occurrence frequencies of GTCU vs. GTDU.The gray level co-occurrence matrix (GLCM) features derived on the proposed GTCDTM descriptor derive the feature vector.The proposed descriptor is tested on the popular databases using machine learning classifiers and equated with state of art local based methods.The results indicate the efficacy of the proposed method.
Pose-invariant three-dimensional face reconstruction

Three-dimensional (3-D) face reconstruction is an important task in the field of computer vision. Although 3-D face reconstruction has been developing rapidly in recent years, large pose face reconstruction is still a challenge. That is because much of the information about a face in a large pose will be unknowable. In order to address this issue, we propose a 3-D face reconstruction algorithm (PIFR) based on 3-D morphable model. A model alignment formulation is developed in which the original image and a normalized frontal image are combined to define a weighted loss in a landmark fitting process, with the intuition that the original image provides more expression and pose information, whereas the normalized image provides more identity information. Our method solves the problem of face reconstruction of a single image of a traditional method in a large pose, works on arbitrary pose and expressions, and greatly improves the accuracy of reconstruction. Experiments on the challenging AFW, LFPW, and AFLW database show that our algorithm significantly improves the accuracy of 3-D face reconstruction even under extreme poses (±90 yaw angles).
La realidad virtual en el área de educación física

espanolLa Realidad Virtual ha irrumpido en diversos ambitos de la sociedad con gran impetu desde hace ya algunos anos. Actualmente son cada vez mas frecuentes los casos en los que se aplica esta tecnologia a la educacion, ya que es capaz de ofrecer multitud de posibilidades sin tener que cambiar el contexto real que nos rodea. Debido al interes creciente de esta tematica, el presente trabajo tiene como objetivo analizar la produccion cientifica en Scopus sobre la Realidad Virtual aplicada al area de Educacion Fisica desde el inicio de las producciones hasta la actualidad. Para ello, se ha utilizado la metodologia propia de los estudios bibliometricos, estableciendo en primer lugar las palabras clave, para seguir con el analisis de siete variables basadas en otros estudios del mismo tipo: procedencia de los archivos, autores e instituciones mas prolificas, paises con mas produccion, tipos de publicaciones y las mas citadas, y conexion de descriptores. Entre los resultados destaca un interes creciente en los ultimos anos por esta area tematica con un punto algido en el 2017. Lo que indica que estamos ante un tema con previsiones de seguir avanzando y creciendo en lo que a produccion cientifica se refiere EnglishVirtual Reality has broken into various areas of society with great impetus for some years now. Nowadays, this technology is increasingly applied to education, as it is capable of offering a multitude of possibilities without having to change the real context that surrounds us. Due to the growing interest in this subject, this work aims to analyze the scientific production in Scopus on Virtual Reality applied to the area of Physical Education from the beginning of the productions until today. For this, the methodology of bibliometric studies has been used, first establishing the key words, to continue with the analysis of seven variables based on other studies of the same type: origin of files, authors and institutions more prolific, countries with more scientific production, types of publications and the most cited ones, and connection of descriptors. Among the results, there has been a growing interest in this thematic area in recent years, with a peak in 2017. This indicates that we are dealing with a subject with forecasts of continuing to advance and grow in terms of scientific production.
Measurable Observations for Network Observability

We consider the initial state observability of linear time-invariant dynamical networks based on arbitrary noisy observations (in time) from spatial locations. We assume that the observation times are Lebesgue measurable and show that the estimation problem is feasible if a properly defined continuous frame exists. Moreover, the quality of the estimation depends on the spectra of a matrix, which can be explicitly calculated using the space-time observation strategy. It turns out that total observation time dictates a fundamental limit on the best achievable estimation quality. Next, we illustrate how to synthesize observation strategies for a stable estimation. Finally, we use a randomized method that efficiently sparsifies the observation strategies, while providing a performance guarantee.
BWA-MEM Performance: Suffix Array Storage Size

Gene Sequencing is the procedure of investigating a genome to discover its differences from the human reference genome. Short Read Alignment, the first processing step in the gene sequencing pipeline, finds the location of short reads in the human reference genome. In general, Burrows Wheeler Transform based alignment tools are widely popular in gene sequencing pipelines. We investigate how storage arrangements of the Suffix Array (SA) impact the overall performance of BWA-MEM, a popular BWT based aligner. We show that partial storage of SA imposes a considerable processing burden to BWA-MEM. We study the memory-compute trade off of different SA storage arrangements and demonstrate that the performance of BWA-MEM can be improved by up to 19 percent by simply storing the whole SA in memory.
Survey of Cyber Security Awareness in Health, Social Services and Regional Government in South Ostrobothnia, Finland

As the health, social services and regional government reform set great expectations for the new technology and the savings it brings, the importance of cyber security increases. When training cyber security for the personnel of the South Ostrobothnia Hospital District (EPSHP), the shortcomings in cyber security awareness emerged. Because improving the awareness is the easiest, fastest and cheapest way to improve cyber security level in organizations, the current level of cyber security awareness was seen valuable to measure in organizations under the reform in the region of South Ostrobothnia. The study investigated the current level of cyber security awareness and the reasons affecting it. Cyber security awareness studied with three different surveys. The first two surveys organized as a part of cyber security lessons for the personnel of the Hospital District of South Ostrobothnia. The third survey conducted as an internet survey for all organizations involved in the reform in South Ostrobothnia. A total of over 1,200 responses to the questionnaires analyzed using material-based content analysis. The results enabled to create an overall view of the current level of cyber security awareness in the organizations, the coverage of the education and the reasons affecting them. According the results, the cyber security awareness and education are lacking among the personnel and management in the target organization. The overall cyber security awareness should be improved in all target organizations.
Implementasi Data Mining Pada Sistem Persediaan Barang Menggunakan Algoritma Apriori (Studi Kasus: Srikandi Cash Credit Elektronic dan Furniture)

Inventories of goods that are not carried out optimally will cause a vacancy for one of the available goods. This also happens to electronic credit and electronic credit shops, which often results in a vacuum in one of the items purchased by the customer, as a result of the lack of information regarding inventory control habits. So it is necessary to extract information on transaction data. A priori algorithm can help to find out the name of the item with the most sales. A priori algorithm including the type of association rules in data mining, an association can be known with two benchmarks, namely support and confidence. Support (supporting value) is the percentage of combinations of these items, while confidance is the relationship between items in association rules. Proof is carried out using the Tanagra application. The results obtained from the a priori algorithm process in the form of a combination of items or rules with the association value in the form of support and confidence values. By knowing the name of the goods most sold, it can anticipate the inventory of goods.
Gain Function Tracking in the Feedback Particle Filter

The feedback particle filter (FPF) was formulated to approximate the nonlinear filter and is motivated by techniques from mean-field game theory. The critical component in the implementation of the FPF is the innovations gain function. The exact computation of the gain requires obtaining the gradient of the solution to a version of Poisson's equation that is difficult to obtain. This paper advances the reproducing kernel Hilbert space (RKHS) based differential TD (temporal-difference)-learning algorithm for gain function approximation in an on-line setting. Algorithms for tracking the FPF gain are proposed based on known structure of the gain function, and by exploiting the time-continuity of the gain. Performance and parameter sensitivity are tested in simulations.
Transforming Mobile Learning and Digital Pedagogies: An Investigation of a Customized Professional Development Program for Teachers in a Hospital School

In an initiative to improve learning experiences and outcomes for students, the leaders of a school located in a hospital in Australia implemented a new digital strategy with mobile technologies and relevant digital pedagogies. This study examines the outcomes of a professional development program introduced to effect transformational change by enabling integrated use of mobile technologies in the hospital school. The study examines teachers’ views following completion of this customized professional development program, using a mixed methods investigation situated within the unique learning environment of the hospital school. A key finding is that identifying and addressing teacher needs through customized professional development, supported with individualized coaching, can increase the participating teachers’ technological pedagogical knowledge to enable the improved use of mobile technology in a hospital school setting. Additionally, hospital school teachers responded to opportunities to collaborate as a professional learning community to implement, support, and enhance mobile learning for hospitalized students. The findings from this study have significant implications for leaders in all schools and systems embarking on similar initiatives to transform pedagogical practices through professional development supporting mobile technology integration in a digital world.
Role of Device Imperfections on the Practical Performance of Continuous-Variable Quantum Key Distribution Systems

Quantum key distribution (QKD) systems based on the modulation of weak-coherent states and homodyne detection has attracted much attention over last years due to its compatibility with existing telecom equipment. The coherent state required by most of the practical protocols for continuous-variable QKD can be produced in practice using a typical laser source followed by standard phase and amplitude optical modulators. On the other hand, the homodyne detector used to measure the quadratures of the modulated light field can be implemented with high-efficient PIN photodiodes. Moreover, in continuous-variable QKD systems the security of the secret key depends on the precise estimation by Bob of the loss and excess noise of the quantum channel. In this work we discuss the impact of imperfect state preparation by Alice and the role of homodyne detector imbalance on the performance of a continuous-variable QKD system. More specifically, we will consider that Alice phase and amplitude modulators are not ideal suffering from incorrect modulation calibration and optical imbalance, and that the positive and negative currents of Bob homodyne detector are not completely canceled due to a non-ideal beam-splitter and due to different quantum efficiencies of its two photodiodes.
A Framework for Authoring Logically Ordered Visual Data Stories

Visual data storytelling has gained widespread adoption as a means of communicating information visualisation. This is partly due to the increased interest in data journalism. Besides being engaging, it has been shown to foster better comprehension and memorability of information to target audiences. The visual data story authoring process involves several stages. However, current tools neither consolidate the visual data story creation process nor integrate the essential features, such as the recommendation of logically sequenced story pieces, for producing coherent narratives. This paper briefly demonstrates our approach and framework for supporting the creation of logically sequenced visual data stories.
Adaptive Data Clustering Ensemble Algorithm Based on Stability Feature Selection and Spectral Clustering

Data Clustering algorithms are essential techniques to pattern recognition. While many clustering algorithms have been proposed, none of them could gain a desirable result on various pattern recognition problems. In this paper, an adaptive clustering ensemble algorithm based on stability feature selection and spectral clustering for data clustering is proposed. The paper chooses strong features by stability feature selection, aiming to improve the quality of clustering. LIMBO is then applied on dataset to engender ensemble instances via calculating the similarity of ensemble members, a proximity matrix could be formed. The cluster ensemble problem is then formalized as a combinatorial spectral clustering problem. Empirical studies on several benchmarks from UC Irvine Machine Learning Repository shows the favorites of the proposed algorithm compares to its competitors, and the promising results yields new inspiration of cluster ensemble and spectral clustering.
PERAN KINERJA GURU DALAM MENINGKATKAN PRESTASI BELAJAR SISWA SEKOLAH DASAR

The principal problem this reseach is how to the role of teachers in improving performance achievments learn students of class IV elementary school of 8 Pulau Rimau. This study using the thedescriptive, where the reseach used to describe the exact phenomenon hapenned in elementary school of 8 Pulau Rimau, Collecting the methods used data is  observasi, inquiries, and the seach reference. Then the tecniques processing data and data analysis done to use a technique a quantitative analysis thedescriptive.The result of reseach shows that the role of performance of the teacher good enough in improving the achievments learn students of class IV in elementary school of 8 Pulau Rimau, it can be determined by the behavior of the existence of a good is evidence that the teacher can attract the attention of students. And about of the accomplishments of learning students in elementary shcool of 8 Pulau Rimau can be seem from the undestanding of the lessons that can be used a as reject the succes of students in lerning.
Reference Model and Architecture of Interactive Cognitive Health Advisor based on Evolutional Cyber-physical Systems

This study presents a reference model (RM) and the architecture of a cognitive health advisor (CHA) that integrates information with ambient intelligence.By controlling the information using the CHA platform, the reference model can provide various ambient intelligent solutions to a user.Herein, a novel approach to a CHA RM based on evolutional cyber-physical systems is proposed.The objective of the CHA RM is to improve personal health by managing data integration from many devices as well as conduct a new feedback cycle, which includes training and consulting to improve quality of life.The RM can provide an overview of the basis for implementing concrete software architectures.The proposed RM provides a standardized clarification for developers and service designers in the design and implementation process.The CHA RM provides a new approach to developing a digital healthcare model that includes integrated systems, subsystems, and components.New features for chatbots and feedback functions set the position of the conversational interface system to improve human health by integrating information, analytics, and decisions and feedback as an advisor on the CHA platform.
Evaluation of a Reusable Technique for Refining Social Media Query Criteria for Crowd-Sourced Sentiment for Decision Making

There are three categories of users that consume social media data either for their personal use or for aggregation and presentation to others. These users rely on a preferential combination of Social Media Signals (SMS) that satisfies their information goals and aids in their decisionmaking. The research community is split on how to deal with some signals such as text originating from robotic voices; some suggest removing them while others are more interested in better identifying them. This paper statistically tests the SMS's in a dataset gathered during one of the political debates during the US Presidential Elections in 2016. It introduces a reusable technique aimed at contributing to the iterative and symbiotic user-system relationship, while improving the opportunity for arriving at empirically supported results for decision-making instances regardless of the consumer group.
Digital and non-verbal communication in preschool: A systematic review

The aim of this research is to reflect on the importance, since preschool, of both verbal and non-verbal language, which is the unintentional communication or body language.This is done to assure a better selfawareness, to establish positive and effective relationships, to prevent conflicts and to empathically understand oneself and other people's feelings.Furthermore, students are digital natives, so they require digitally equipped environments, with which they are familiar from an early age.On the other hand, teachers are digital immigrants, because they have only come in contact with digital devices as adults; as a consequence, they pay the price for the generation gap which distinguishes them from digital natives, whose mindset is more involved in the dynamics of change and whose lives are symbiotically connected to technology.Therefore, teachers need an adequate training for media management in classrooms.The review process focused on 36 international articles (20 articles and 16 investigations) and 4811participants; the inclusion.
Full-duplex quantum coherent communication

High bandwidth requirements for data communications are currently being met by classical coherent communication using multi-level modulation of amplitude and phase of light. Alternatively, down at the level of quantum signals, coherent communication enables establishment of cryptographic keys between two legitimate users, and shows higher key exchange throughput compare to single-photon-based systems. In this work, we will examine the feasibility of full duplex quantum coherent communication, where both the transmitter and the receiver engage in quantum signal recovery as well as secure key generation.
Development of the Korean Handwriting Assessment for Children Using Digital Image Processing

The efficiency and accuracy of handwriting measurement could be improved by adopting digital image processing.This study developed a computer-based Korean Handwriting Assessment tool.Second graders participated in this study by performing writing tasks of consonants, vowels, words, and sentences.We extracted boundary parameters for each letter using digital image processing and calculated the variables of size, size coefficient of variation (CV), misalignment, inter-letter space, inter-word space, and ratio of inter-letter space to inter-word space.Children were also administered traditional handwriting and visuomotor tests.Digital variables from image processing were correlated with these previous tests.Using these correlations, we established a three-point scoring system that computed test scores for each variable.We analyzed inter-rater reliability between the computer rater and human rater and test-retest reliability between the first and second performances.The validity was examined by analyzing the relationship between the Korean Handwriting Assessment and previous handwriting and visuomotor tests.We suggested the Korean Handwriting Assessment to measure size, size consistency, misalignment, inter-letter space, inter-word space, and space ratio using digital image processing.This Korean Handwriting Assessment tool proved to have reliability and validity.It is expected to be useful for assessing children's handwriting.