Reviewerly/exHarmony huggingface dataset:
Object Tracking by Unified Semantic Knowledge and Instance Features

Instance features based deep learning methods prompt the performances of high speed object tracking systems by directly comparing target with its template during training and tracking. However, from the perspective of human vision system, prior knowledge of target also plays key role during the process of tracking. To integrate both semantic knowledge and instance features, we propose a convolutional network based object tracking framework to simultaneously output bounding boxes based on different prior knowledge as well as confidences of corresponding Assumptions. Experimental results show that our proposed approach retains both higher accuracy and efficiency than other leading methods on tracking tasks covering most daily objects.
Environmental monitoring and governance model of ion-adsorption type rare earth mining

An environmental impact assessment was performed to evaluate the environmental impact of ion-adsorption type rare earth (iRee) mining in Southern Jiangxi Province, China. Based on the research of essential factors for mining environment systems, an evaluation index system for surface water quality was established, and a special assessment model was built based on principal component analysis and fuzzy theory. On the basis of evaluating the water quality, a fuzzy comprehensive judgment model was established to conduct a comprehensive evaluation of the local mining area's geological environmental quality. Four factors such as physical geography (A), basic geology (B), mining development coverage (C), and environmental influences (D) were selected and combined with field data and measurement results. These factors were used to establish an index system using an expert system and objectivity to determine the weight of the factors. A comprehensive evaluation model for the geological environmental impact of different types of iRee mines (light and heavy rare earth mines) was established based on a support vector machine (SVM) model. The results indicate that the monitoring and governance model successfully assesses the environmental impact of typical iRee mining areas by classifying the environmental quality into four levels. The model has a strong applied value as it provides help for geo-environmental management, helps with the exploitation of iRee mineral resources, protects the geological environments and helps restoring and reconstructing mine environments.
Multiple wavelength fringe analysis for surface profile measurements

Interferometry has been widely used for surface metrology because of their precision, reliability, and versatility. Although monochromatic-light interferometery can provide high sensitivity and resolution, but it fails to quantify largediscontinuities. Multiple-wavelength techniques have been successfully used to extend the unambiguous step height measurement rage of single wavelength interferometer. The use of RGB CCD camera allows simultaneous acquisition of fringes generated at different wavelengths. In this work, we discuss details about the fringe analysis of white light interferograms acquired using colour CCD camera. The colour image acquired using RGB camera is decomposed in to red, green, blue components and corresponding interference phase is measured using phase evaluation algorithms. The approach makes the 3D surface measurements faster, cost-effective for industrial applications.
The Impact of State Financial Support on Active-Collaborative Learning Activities and Faculty-Student Interaction

Purpose -The goal of this study is to analyze the differences in education performances between students of the government's financial support program and those who do not receive support at a local university in Korea.Research design, data, and methodology -The questionnaire used was NASEL.NASEL is considered a highly suitable survey tool for professors, courses, and performances in Korean universities.The 290 students who participated and 44 students do not participate in the financial support program were surveyed for 10 days.The characteristics of students were investigated by frequency analysis and technical statistics.The analysis of student collective characteristics used independent t and f-tests,and one-way ANOVA with IBM SPSS Statistics 22.0 for statistical purposes.Results -The p-value of the group receiving financial support and the group without financial support in active-collaborative learning is 0.167.The p-value of the economically supported group and the non-supported group of the faculty-student interaction is 0.281.The confidence coefficient of the active-collaborative learning questionnaire is 0.861.The reliability coefficient of the questionnaire for the faculty-student interaction questionnaire is 0.871.Conclusions -There are no clear differences in active-collaborative learning and faculty-student interaction between participating and non-participating students in the economic program.
Model selection in utility-maximizing binary prediction

The maximum utility estimation proposed by Elliott and Lieli (2013) can be viewed as cost-sensitive binary classification; thus, its in-sample overfitting issue is similar to that of perceptron learning. A utility-maximizing prediction rule (UMPR) is constructed to alleviate the in-sample overfitting of the maximum utility estimation. We establish non-asymptotic upper bounds on the difference between the maximal expected utility and the generalized expected utility of the UMPR. Simulation results show that the UMPR with an appropriate data-dependent penalty achieves larger generalized expected utility than common estimators in the binary classification if the conditional probability of the binary outcome is misspecified.
Monocular pose measurement using contour image length matching in range

To solve the question of monocular pose measurement of the non-projected-axisymmetric targets, a Contour Image Length matching method is proposed,firstly,the contour of the targets is simplified as many triangles based on nose to solve the information redundancy and visual occlusion;secondly,the simplified target is projected to the image plane to get virtual image length，the actual image length is extracted simultaneously, then the pitch, yaw and roll angle can be obtained by length matching between virtual image and actual image. The aircraft flight calibration test shows that the precision of the pitch angle, yaw angle and roll angle was 0.9 degrees,1.2 degrees, and 1.5 degrees respectively, which indicated the result is slightly lower than intersection, but can save cost and improve efficiency. Finally, the key factors concerning method error are analyzed; the method can lay an important foundation for monocular pose measurement in range.
Second workshop on user interfaces for spatial and temporal data analysis (UISTDA2019)

The 2nd workshop on User Interfaces for Spatial-Temporal Data Analysis (UISTDA2019)1 took place in conjunction with the 24th Annual Meeting of the Intelligent Interfaces community (ACM IUI2019) in Los Angeles, USA on March 20, 2019. The goal of this workshop is to share latest progress and developments, current challenges and potential applications for exploring and exploiting large amounts of spatial and temporal data. Four papers and a keynote talk were presented in this edition of the workshop.
Transliteration Balinese Script using Finite State Automata (FSA) Algorithm

Currently only few people are able to write with Balinese script. This research has main goal to transform the Latin alphabet in the language of Bali to Balinese script using Finite State Automata (FSA). FSA algorithm is using six syllables that exist in the Balinese language structure and generates by font Bali simbar-b. In this test, the use of the Application has advantages (a) the characters generated can be copied and pasted in another document (b) completeness of Balinese script can be written (c) applications run on Linux OS, Windows, Mac OS. The Application is developed in GTK with C# language. The application was tested in (1) Syllables base (2) Basic word (3) marker vocals word (4) Vocal independent (5) marker semi-vowel word (6) Characters Swaitha (7) Pengange Tengenan (8) other markers (9 ) syllable other (10) numbers (11) punctuation (12) variations in the use of Tedung (13) stands (14) transliteration paragraphs to result 94% accuracy. Some of the drawback in this transliteration using a local database technology are some rule from Balinese Script not applied in algorithms
FqSD: Full-Quaternion Saliency Detection in Images

Saliency detection aims to segment in two groups the pixels of an image, in important or less important visual information. Important information can be used to detect objects with some semantics for tasks in computer vision. In this paper, we develop a saliency detection method using full-quaternion. The proposed method makes a combination between local and global approaches. Local features are obtained at patches level using a Module Local Binary Patterns and the comparison between feature vectors (module and phase). The salient object is obtained by a weighted combination of salient maps where a function of center-bias and refinement is applied. To verify the effectiveness of our method, this is validated using the mean absolute error metric in the ECSSD-1000 and DUT-OMRON datasets and compared with others state of the art algorithms. A statistical analysis is applied to the results to obtain the statistical significance among color spaces with the method of Wilcoxon signed test. The results show that the HSV color space is better in effectiveness than others.
Surface profilometry by employing synthetic partially spatially coherent holograms

The aim of this work is to develop a holographic method that provides the shape reconstruction with an extended measurement range and preserved high accuracy. The method requires recording of series of fully-coherent holograms generated with varying tilt of plane wave illumination. The captured holograms are numerically processed to obtain the corresponding complex fields. The complex fields are used to produce a new set of holograms, which are used for calculating the longitudinal coherence function. This function allows observing fringes of high contrast at specific heights similar to white light interferometry, and thus, shape reconstruction of the three-dimensional object is carried out. The conclusions of this work are supported with results of numerical simulations.
Adaptive Autonomous Technology in Unmanned Aerial Vehicles for Parcel Delivery

An Unmanned Aerial Vehicle (often called a Drone) is an aircraft that is not operated by a pilot on board. Drones are rapidly growing market and increasingly leverage. The Applications of these flying robots are limitless. This paper reviews and discusses about embedded vision and sensor technology which culminates in several innovative applications over drones. It introduces an industry alliance available to help product creators incorporate robust vision capabilities into their drones designs. This paper mainly deals on Autonomous Delivery of light weighted items along with the collision avoidance technology and also tracks the whereabouts of the vehicle in a cost effective approach. This can also be used for carrying out complex assignments such as rescue operations during disasters, mines surveying.
Regularization for Graph-Based Transfer Learning Text Classification

In machine learning classification problems, it is common to assume train and test sets follow a similar underlying distribution. When this is not true, this can be seen as a transfer learning problem. Sometimes, there is a set of already trained source classification models available. This work focuses on how to best use these models as an ensemble of classifiers on data from a new, but related domain, assuming train data used to train those models is not available. This scenario is common in distributed systems, where sharing all data is technically difficult or there are privacy concerns. Most current solutions are graph-based methods that propagate labels given by the models into new domain data. We propose a regularization method for one of best current solutions, OAC $$^{3}$$ , that shows improvements on accuracy on several text classification datasets.
Electronic Educational Environment Moodle in English Language Training

The article deals with the causes, methods and functions of using E-learning in the process of training students English, as well as changing teacher’s and learner’s roles in the educational process. The introduction of information and communication technologies in educational and research processes is a compulsory requirement to implement the concept of modernization in Russian education. Recently, interest in English as a means of international communication has increased significantly, it has already been recognized as the language of professional communication in various fields of activity. The relevance of this work is undoubted. Modern higher school teachers are constantly looking for more effective approaches in training English and in the process of creating an electronic educational environment that would allow students access to various sources of information and help satisfy the interests of the modern student. The goal of the research is to increase the efficiency of training English in the system of higher professional education through the development and use of educational software products that apply modern information technology. Methods to achieve this goal include the method of using computer technology, methods of network planning and project management. The research showed that the organization of the information-instrumental educational environment uses a student centered approach, the development of an electronic educational and methodological complex (EEMC) is a search for an algorithm, most adapted to the student's cognitive needs, and EEMC in English creates the best conditions for the principle of interactivity. The practical significance of the study is determined by the fact that its materials related to the method of creating multimedia tasks and virtual environments can be used in the practical work of universities, as well as in the system of further training for specialists.
Strain measurement of particle-reinforced composites at the microscale: An approach towards concurrent characterization of strain and microstructure

The mechanical behavior of particle-reinforced composites is largely determined by the interaction between the reinforcing particles and matrix. Although conventional digital image correlation (DIC) allows accurate measurements of strain at microscale, it usually requires preparation of synthetic pattern on the sample surface, which would affect the observation of reinforcing particles. An approach is proposed in this work that relies solely on the reinforcing particles as DIC pattern, thereby enabling concurrent microstructure observation and strain measurement. The main idea of the approach is that only the regions of high gray level contrast shall be correlated. The approach has been tested against the benchmarks taken from the images of rigidly translated and rotated sample, and the influence of image magnification has been discussed in detail. The approach has also been applied to actual tensile test and yielded qualitatively similar results as the conventional DIC approach.
Privacy-Aware Detection of Shilling Profiles on Arbitrarily Distributed Recommender Systems

Due to the mutual advantage of small-scale online service providers, they need to collaborate to deliver recommendations based on arbitrarily distributed preference data without jeopardizing their confidentiality. Besides privacy issues, parties also have concerns regarding the vulnerability against recommendation manipulation attempts, referred to as shilling attacks. Although there are methods for detecting these injected malicious profiles in central server-based configurations, they are not readily suitable for employing arbitrarily distributed data. In this paper, we present a novel classification-based shilling attack detection protocol enabling the recognition of malicious profiles in arbitrarily distributed configurations without compromising the privacy of collaborating parties. The analysis of the proposed protocol regarding confidentiality of parties reveals that the process is bound to collaboration by design, which does not allow parties to achieve detection by themselves. Furthermore, empirical evaluations using real-world preference data demonstrate that the protocol can achieve significantly high detection rates facilitating privacy-aware data collaboration.
Item recommendation in aggregated marketplace

In this work we introduce the task of item recommendation in an aggregated marketplace. An aggregated market place is a single place where items from multiple e-commerce sites can be viewed and compared. Our main objective while recommending items is to provide users with alternatives across different e-commerce sites. To accomplish this, we embed items in a vector space and apply retrofitting, a method used in language processing to inject relationships into word embeddings. Due to recent attention towards item recommendation using only click data without any user feedback and our particular constraints, we test our model on real click data derived from Samsung Mall App.
Preservation of Class Invariants in Refactoring UML Models

In the field of software engineering, the term class invariants is known as a valuable term employed to delineate the semantic of UML class diagram elements (attributes and relationships) and must be held throughout the life-time of instances of the class. Refactoring, the activities of re-distributing classes, attributes and methods across the class hierarchy, is a powerful technique that is used to improve the quality of software systems. Performing refactoring on UML class diagrams obviously requires a special investigation of invariant-preserving on the refactored models. In this paper, we propose an approach to preserve class invariants in refactoring UML models. In order to achieve this aim, we first formalize the class diagram along with class invariants by mathematical notations. We then constitute the rules for five refactoring operations (deal with class hierarchies) in such a way to guarantee class invariants as well as proving correctness of the refactoring rules. Finally, the paper also makes provision of the proposed approach for practical applications in software re-engineering development process.
Metrics based content layouting

Effective personalization of web experiences constitutes matching user intent to content, while optimizing a set of engagement metrics and catering to diverse consumption mediums. The diversity of user interests necessitates automation in the process of constructing personalized content experiences. We propose a genetic algorithm based framework that chooses a set of content items relevant to a target user, and decides their respective sizes and relative positions to construct a layout. This layout is designed to simultaneously optimize a chosen engagement metric subject to diversity of the information presented. Comparisons against existing frameworks based on human annotations show improved prominence of key content and increased diversity of the content presented.
3D Face Recognition with Reconstructed Faces from a Collection of 2D Images

Nowadays, there is an increasing need for systems that can accurately and quickly identify a person. Traditional identification methods utilize something a person knows or something a person has. This kind of methods has several drawbacks, being the main one the fact that it is impossible to detect an imposter who uses genuine credentials to pass as a genuine person. One way to solve these kinds of problems is to utilize biometric identification. The face is one of the biometric features that best suits the covert identification. However, in general, biometric systems based on 2D face recognition perform very poorly in unconstrained environments, common in covert identification scenarios, since the input images present variations in pose, illumination, and facial expressions. One way to mitigate this problem is to use 3D face data, but the current 3D scanners are expensive and require a lot of cooperation from people being identified. Therefore, in this work, we propose an approach based on local descriptors for 3D Face Recognition based on 3D face models reconstructed from collections of 2D images. Initial results show 95% in a subset of the LFW Face dataset.
Navigation Control of an Automatic Guided Forklift

This paper presents navigation control of an unmanned autonomous forklift. The autonomous navigation in an indoor environment is conducted using waypoints following algorithm. The forklift is equipped with on board computation and sensors to accommodate autonomous function. The experimental results show the efficiency of the waypoints tracking algorithm in comparison with the ground truth.
MOTIVATION ROLE IN FORMING A SCHOOLCHILD’S MULTILINGUAL PERSONALITY

The article determines motivation role in the formation of a multilingual personality ready for active and productive activity under the conditions of multilingualism. The notion of motivation to learn foreign languages is considered basing on the analysis of works in the field of psychology, pedagogy and methods of teaching foreign languages. The paper reveals the structure of educational motivation and the ways of motivating the schoolchildren learning two and more foreign languages. The authors present the results of diagnosing a complex structure of motives, predicting goals and determining factors affecting increase in motivation basing on an authorial questionnaire.
A Study on the Pre-service Teachers’ Stages of Concern and Perception of Free Semester System

The purpose of this research was to define implications for the pre-service teacher education course by analyzing the pre-service teachers’ stages of concern on the free semester system using the CBAM model. The research questions were as follows. Firstly, how is the stages of concern of pre-service teacher on the free semester system? Secondly, what is the difference of the stages of concern of pre-service teacher on the free semester system depending on the variables such as the grade, learning experience on free semester system and awareness of expanding the free semester system.BR The main results of this study were as follows. Firstly, as a result of analyzing the stages of concern of pre-service teachers on free semester system, the stage 0(perception) was the highest, the stage 4(result) was the lowest, and the pattern of positive non-user was shown. Secondly, there was no statistically significant difference in the stage of concern depending the grade of the pre-service teachers. Thirdly, as a result of analyzing whether there is a difference in the stage of concern depending on whether or not to study the free semester system, there was a significant difference in all the stages of concern except the stage 0 and 1. Lastly, as a result of analyzing the differences of concern stage according to whether or not they agreed to expand the free semester system, the level of concern of disagreeing group was higher than that of the agreeing group in the 6th stage (refocusing).