Reviewerly/exHarmony huggingface dataset:
Observability driven Multi-modal Line-scan Camera Calibration

Multi-modal sensors such as hyperspectral line-scan and frame cameras can be incorporated into a single camera system, enabling individual sensor limitations to be compensated. Calibration of such systems is crucial to ensure data from one modality can be related to the other. The best known approach is to capture multiple measurements of a known planar pattern, which are then used to optimize calibration parameters through non-linear least squares. The confidence in the optimized parameters is dependent on the measurements, which are contaminated by noise due to sensor hardware. Understanding how this noise transfers through the calibration is essential, especially when dealing with line-scan cameras that rely on measurements to extract feature points. This paper adopts a maximum likelihood estimation method for propagating measurement noise through the calibration, such that the optimized parameters are associated with an estimate of uncertainty. The uncertainty enables development of an active calibration algorithm, which uses observability to selectively choose images that improve parameter estimation. The algorithm is tested in both simulation and hardware, then compared to a naive approach that uses all images to calibrate. The simulation results for the algorithm show a drop of 26.4% in the total normalized error and 46.8% in the covariance trace. Results from the hardware experiments also show a decrease in the covariance trace, demonstrating the importance of selecting good measurements for parameter estimation.
K-Means++ Clustering Using MapReduce Framework for Large Datasets

Clustering techniques are important to analyze the data due to the heavy increase of data in modern investigation. In real world these techniques are mostly used in many domains, some of them are financial analysis, social networks, digital marketing, etc. To support clustering over large scale datasets, public cloud infrastructure will play the major role for presentation of the data and financial trades. In our work, MapReduce based K-means++ clustering technique is proposed to allow the better grouping of data into appropriate clusters. The results of the paper denote that the present algorithm can efficiently process large amount of data.
FULL-FLEDGED SEMANTIC ANALYSIS AS A TOOL FOR RESOLVING TRIANGLE-COPA SOCIAL SCENARIOS

Text interpretation often requires common sense knowledge and reasoning. A convenient tool for developing methods of common sense reasoning are special sets of challenge problems whose interpretation requires sophisticated reasoning. An interesting example is a recently published data set called Triangle Choice of Plausible Alternatives (Triangle-COPA), which contains 100 multiple-choice problems that test the interpretation of social scenarios. Each problem includes a statement and two alternatives. The task is to identify the more plausible alternative. For processing Triangle-COPA data we use SemETAP, a general purpose semantic analyzer. We implement the full scenario of NL understanding starting from NL texts and not from manually composed simplified logical formulas, which is a common practice in logic-based approaches to common sense reasoning. We produce Enhanced Semantic Structures of the statement and both alternatives and check which alternative manifests more semantic agreement with the statement in terms of inferences.
Morphological Awareness and Vocabulary Knowledge

This study examined the relationship between the types of vocabulary knowledge (receptive and productive) and morphological awareness in an EFL context.The participants in this study were 60 fourth year secondary school Arts students in Ain Drahem, Tunisia.Students were grouped into two groups (control/ experimental) in order to check the effectiveness of teaching morphology on vocabulary knowledge.Vocabulary size was tested using adapted versions of vocabulary tests, namely Nation's (2001) Vocabulary Levels Test as a receptive measure of vocabulary size and Laufer and Nation's (1999) productive version of the Vocabulary Levels Test.The tests were modified by increasing the total number of test items to make them more representative of the 2000 and 3000-word frequency levels.Students' morphological awareness was measured by the Morphological Awareness Test with its four subsets (roots, derivational morphemes, compounds and inflectional morphemes).The VLT results showed that students' receptive size was larger than their productive size.Results revealed also that students performed better at the 2000-word frequency level than at the 3000-word level.Besides, the informants' scores were high on the overall morphological awareness task, and the best performance was on inflectional morphemes for both groups.As predicted, morphological awareness was positively related to both receptive and productive vocabulary.
Sonic Interactions in Multimodal Virtual Environments

In this paper we present the research and teaching activities performed in the Multisensory Experience Lab at Aalborg University Copenhagen. We also briefly describe the Sound and Music Computing Education started at Aalborg University in September 2014.
Blind Digital Images Tampering Detection Based on Singular Value Decomposition

The growing use of digital images in a wide range of applications, and growing the availability of many editing photo software, cause to emerge a challenge to discover the images tampering. In this paper, we proposed a method to detect the most important type of forgery image (copy and move). We suggested many steps to classify the image as forgery or non-forgery image, started with preprocessing (included, convert image to gray image, de-noising, and image resize). Then, the image will be divided into several overlapping blocks. For each block, feature extracted (used it as a matching feature) by using the singular value decomposition (SVD) transformation. According to these features, the pixels were collected in many main groups, and then these groups clustered to many subgroups. The weight for each main group can be determined by comparing the subgroups with each other according to suggested conditions. The number of subgroups and weights are used to classify images to forgery or non-forgery images. The accuracy of detection and classified the forgery images were up to 97%. The suggested method is robust for tampered object rotation, scaling, and change of illumination.
Broad Learning Can Tolerate Noise in Image Recognition

In recent years, deep learning has achieved very good results because large amounts of learning data have become easily available due to improvements in computer capabilities and big data. However, it has a problem that the accuracy becomes very bad for strong noise. Therefore, in this study, we compare the classification accuracy of existing mainstream neural networks, including broad learning, convolutional neural network and multilayer perceptron. Then, their performance is verified according to the experimental results by using noise‐added MNIST and Fashion MNIST database. © 2020 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.
Spatial Model of Traffic Congestion by the Changes on City Transportation Route

Traffic congestion is a problem for every city in Java Island, Indonesia, including Bogor City. Factors causing congestion in Bogor City are thought to come from land use, the geometry and performance of road, and public transport routes (urban transport). The change of urban transportation (angkot) route carried out by Bogor City Government aims to reduce traffic density and congestion, but it is not a guarantee that the main problem will be solved. This study aims to determine the spatial patterns of traffic density and congestion with current angkot routes and to construct a model to predict traffic density and congestion when new angkot routes are used. Variables in this research are land use (number of schools and markets/malls), geometry and performance of road (vehicle volume, road capacity, average velocity, road type, number of lanes, number of signalled and non-signal intersection), and an angkot route passing a road. The method used in modelling is multiple regression using one dummy variable and a stepwise regression method. The result of modelling shows that the variables affecting traffic density are velocity, some signalled and non-signal intersection, and angkot route with R2 value 66.9%. At the same time, the influential variables in the traffic congestion model are vehicle volume, road capacity, number of the signalled intersection, and angkot route with R2 value 81.4%. To see accuracy in predicting model of traffic density and congestion, Mean Absolute Percentage Error (MAPE) validation is used. The results show a value of 12.46% for traffic density, which means that the model has good prediction accuracy and 5.62% for traffic congestion, which means the model has high prediction accuracy. Thus, in this study, the land use of school and market is not a factor causing traffic density and congestion, while the geometry and performance of roads and public transportation routes as a factor causing congestion.
Transformation Of Educational Standards And Issues Of Universal Competences

The paper is devoted to the formation of universal competences in accordance with the latest version of the state educational standard of higher education.The transformations of the third generation standards affect the structure and content of competences.The paper presents the results of experimental work on the application of active forms and methods of training in order to form and develop indicators of the main universal competences of a bachelor of psychology and pedagogy.The development of bachelor's universal competences included key lines of development: axiological, cognitive and activity.The positive dynamics reflected in the results of the forming experiment makes it possible to speak about the legality of applying the proposed active forms and methods in the pedagogical process, which takes into account changes in the modern educational standard.The study of this issue showed that a significant source and effective means of formation and development of universal competences is a system of forms, methods, means of pedagogical interaction based on activation of subjective experience of a student and its inclusion into active cognitive and communicative activities to solve educational and professional tasks.Active forms of training help to consolidate skills of orientation on norms and samples of universal and pedagogical culture in the process of selection of methods and means of activity, contribute to the development of ability to build a trajectory of self-development, increase the educational potential and ensure efficient cooperation and teamwork skills.
Virtual manipulatives in inquiry-based approach of 3D problems by French 5th graders

The aim of this research is to study the appropriation of a 3D environment by learners in an a-didactical situation of problem solving. We try to evaluate the relevance of the virtual 3D environment in the development of students' cognitive and metacognitive abilities. We implanted a problem-solving activity related to a 3D cube situation with an empty part in the cube in different French primary school areas in May 2019. In the experimental group each learner works individually with a PC-computer where the virtual environment ANIPPO is implemented. In the control group the pupils work in a traditional class environment. We present the results of this pre-experimentation.&#x0D; Subject Classification: 97D50, 97U60, 97U70
Intangible Property: Protection of Virtual Property in Electronic Games in China and US

With blossoming of the electronic games, the strategy of game developer preference is that the player uses real money to buy the virtual property in the game. The purpose for the strategy which keeping the game promote and developing the game system on the platform to attract more users.With the increasing amount of game, the main strategy is same. The chain, the End User License Agreement (EULA) which between the game developer and player is vital. EULA used to rule that the virtual property is belong to the game developer. However, for now, the virtual property has different acquisition way, “all virtual property belongs to the developer” since already unfair.Staring from the first virtual property lawsuit in China, this paper introduces the virtual property of electronic game and legal protection in US and China. Second, discussion the reasons to protection virtual property and provide proposals for a potential legislative solution in China. At the end, this paper presents the reason that copyright law not suitable to protect the virtual property.
INVESTIGATING THE INDONESIAN EFL STUDENTSâ€™ ARGUMENT IN ARGUMENTATIVE ESSAY

This study investigates the written test results of the Indonesian undergraduate studentsâ€™ argumentative essay. For that reason, three research questions are made. 1). what is the level of achievement of the students in the argumentative essay quantitatively? 2). what aspects of an essay appear in respect to the argumentative essay generic structure as formulated? 3). how well did they use the rhetoric reputation and argument in their essay?. 27 handwriting' answer sheets of undergraduate English Department students enrolled at semester four of a state university in Indonesia were taken purposively. The data analysis uses a quantitative and qualitative approach. The results show that the students quantitatively achieved average score 76,74 which means good. All parts of generic structures were expressed in different quality. However; the organization of the essay is the lowest part compared to the other four parts respectively content, vocabulary, and language use seen from their segmented scores. This study is confirmed to be inline the previous study in that the majority of the students did not present the refutation section in both their English essays. This implies that teachers should be more aware of promoting this absent aspect as this refutation or rebuttal is a distinguishing marker in argumentative and discussion essays.
An Analysis of Commitments in Ontology Language Design

Multiple ontology languages have been developed over the years, which brings afore two key components: how to select the appropriate language for the task at hand and language design itself. This engineering step entails examining the ontological ‘commitments’ embedded into the language, which, in turn, demands for an insight into what the effects of philosophical viewpoints may be on the design of a representation language. But what are the sort of commitments one should be able to choose from that have an underlying philosophical point of view, and which philosophical stances have a knock-on effect on the specification or selection of an ontology language? In this paper, we provide a first step towards answering these questions. We identify and analyse ontological commitments embedded in logics, or that could be, and show that they have been taken in well-known ontology languages. This contributes to reflecting on the language as enabler or inhibitor to formally characterising an ontology or an ontological investigation, as well as the design of new ontology languages following the proposed design process.
A continuous variable Born machine

Abstract Generative modelling has become a promising use case for near-term quantum computers. Due to the fundamentally probabilistic nature of quantum mechanics, quantum computers naturally model and learn probability distributions, perhaps more efficiently than can be achieved classically. The quantum circuit Born machine is an example of such a model, easily implemented on near-term quantum computers. However, the Born machine was originally defined to naturally represent discrete distributions. Since probability distributions of a continuous nature are commonplace in the world, it is essential to have a model which can efficiently represent them. Some proposals have been made in the literature to supplement the discrete Born machine with extra features to more easily learn continuous distributions; however, all invariably increase the resources required. In this work, we discuss the continuous variable Born machine, built on the alternative architecture of continuous variable quantum computing, which is much more suitable for modelling such distributions in a resource-minimal way. We provide numerical results indicating the model’s ability to learn both quantum and classical continuous distributions, including in the presence of noise.
Correction to: Benchmarking performance of machine and deep learning-based methodologies for Urdu text document classification

The article [Benchmarking performance of machine and deep learning-based methodologies for Urdu text document classification], written by [Muhammad Nabeel Asim, Muhammad Usman Ghani, Muhammad Ali Ibrahim, Waqar Mahmood, Andreas Dengel and Sheraz Ahmed], was originally published.
Engaging Design - Empowering Beyond ‘Participation’ For Active Engagement

international patents, 3 + million retailing products, lifesaving ballistics +
The Implementation of Lectora Inspire Application as Interactive Learning Media on English Writing Skill for Students at SMP N 35 Medan

Technology development demands the existence of innovation in education sector. Therefore, technology use has to be optimized well. The study aimed at developing Lectora Inspire application as interactive learning media on English writing skill for students and to know the application effectiveness toward students at SMP N 35 Medan. Research and Development was conducted in the study. There were some steps conducted such as, preliminary, developing, and evaluating. The subject of the study was 30 students of seventh, eighth, and ninth grade students at SMP N 35 Medan chosen randomly. The techniques of collecting data were documentation, interview and questionnaire. Furthermore, the data were analyzed by using descriptive qualitative and quantitative analysis. The result of the study showed that Lectora Inspire application was an appropriate interactive learning media on writing for students at SMP N 35 Medan. Since the interactive learning media had been validated by some experts and got the average percentage 95% categorized excellent. In addition, the result of the study showed that there was the students’ improvement on writing skill related to genres which meant that the media was effective media in learning writing at SMP N 35 Medan.&#x0D;
Development Of Professional Interest In Design And Graphic Activities In Future Designers

Modern changes in the social, economic, and educational structure of society pose new requirements for the professional training process.Students have to develop a set of cultural and professional competencies.The willingness of future specialists depends on deep special knowledge and creative abilities, motives, interests and attitudes to design activities.Admission to the university strengthens faith in own strengths and abilities.However, professional choice is often determined by random factors.This causes a lack of interest in learning, a negative attitude to the profession.During the adaptation, students experience difficulties, have a weak motivation for new areas of knowledge.Students have to do much homework lacking skills of independent work; it becomes difficult for them to combine lecture materials and practical exercises.They do not understand the disciplines and lose cognitive and professional interest in them.The elimination of these shortcomings is facilitated by an optimal learning process based on the development of a method for teaching design and graphic activities.
Robust Exponential Stability of Recurrent Neural Networks with Deviating Argument and Stochastic Disturbance

It is well known that deviating argument and stochastic disturbance may derail the stability of recurrent neural networks (RNNs). This paper discusses the robustness of global exponential stability (GES) of RNNs accompanied with deviating argument and stochastic disturbance. For a given global exponentially stable RNNs, it is interesting to know how much the length of the interval of piecewise function and the interference intensity so that the disturbed system may still be exponentially stable. The available upper boundary of the range of piecewise variables and the interference intensity in the disturbed RNNs to keep GES are the solutions of some transcendental equations. Finally, some examples are provided to demonstrate the efficacy of the inferential results.
Hubungan Kemampuan Membaca Pemahaman dengan Kemampuan Menulis

ABSTRACTThis article generally aims to determine the ability to read with the ability to write, while specifically to get an idea of the relationship between reading and writing in writing an article. The ability to reading comprehension and write has a very close relationship when viewed from various aspect. This certainly happens because there is continuity between the two language skills. A writer will not be able to produce a good writing if unable and skilled in reading. Skillful in reading here means being able to understand the contents of the reading and know the meaning of the reading. Vice versa, if someone is skilled in reading then he will easily produce an article. Kata kunci: kemampuan, membaca, menulis
Degree modifiers and common ground operators: The case of &lt;em&gt;at all&lt;/em&gt;

At all is among the most common negative polarity items in English. In this paper, I argue that at all has a dual use as a degree modifier and operator on the common ground. I first present an account of degree modifier at all based on Chierchia 2013 that captures its status as a minimizer as well as an NPI. I then show that a very similar account can be used for at all's common ground usage, departing from the usual quantification over worlds approach for common ground management. This degree-based account of common ground at all captures its status as an NPI and provides a possible shared semantic core between degree modifiers and common ground operators.
Attribute-based Encryption for Fine-Grained Access Control on Secure Hybrid Clouds

In the present scenario, the proliferation of cloud computing services allows hospitals and institutions to move their healthcare data to the cloud, enabling global access to data and on-demand high-quality services at a lower cost.Healthcare data has sensitive attributes to be shielded from leakage due to inference attacks by a curious intruder, either directly or indirectly.A hybrid cloud is a mix of both private and public clouds proposed for the storage of health data.Carefully distributing data between private and public clouds to provide protection.While there has been ample work for the delivery of health data for some time now, it does not appear to be more effective in terms of both data retrieval and consideration for fine-grained access control of the data.This work suggests a cordial approach for a more reliable delivery of data using geometric data disruption of health data over hybrid clouds.It is focused on an in-depth review of the results.The distribution enforces fine-grained data access control using attribute-based encryption.In addition, the approach also addresses a method to effectively extract relevant information from hybrid clouds.