Miracle-dz/UniFAR-FTUs huggingface dataset:
Teacher-Guided Educational VR: Assessment of Live and Prerecorded Teachers Guiding Virtual Field Trips

We present a VR field trip framework, Kvasir-VR, and assess its two approaches to teacher-guided content. In one approach, networked student groups are guided by a live teacher captured as live-streamed depth camera imagery. The second approach is a standalone (non-networked) version allowing students to individually experience the field trip based on depth camera recordings of the same teacher. Both approaches were tested at two high schools using a VR environment that teaches students about solar energy production via tours of a solar plant. We show that our live networked approach can produce promising test score gains and very high ratings of co-presence, affective attraction, overall opinion, etc. Results show a benefit of live networked VR, as the standalone approach had lower performance in terms of gains and most ratings, although its ratings were still positive. We further consider possible differences of school environment (dedicated vs. integrated classroom), and we conclude with tradeoffs and implications to benefit future design of educational VR. Keywords:, . Index Terms: I.3. 7 [Computer Graphics]: Three-Dimensional Graphics and Realism-Virtual Reality; K.3. 0 [Computers and Education]: General
The Impact of Modular Multilevel Converter Control on DC Short-Circuit Currents of HVDC Systems

In Modular Multilevel Converter (MMC) based DC systems, during the initial stage of a DC fault, the control system operates normally, inserting and bypassing submodules. Consequently, each MMC control technique would provide a different characteristic to the DC short-circuit behavior. Therefore, this paper presents a comparative analysis of MMC control techniques, providing a better understanding on how the control techniques impact the fault currents. The analyses were performed by simulating and applying DC faults to a two-terminal VSC-HVDC system with different groups of control techniques. It was found that the DC fault current was not influenced either by control parameters, modulation or output-current control techniques. The arm-balancing control influenced the DC fault currents as it has an impact on the modulation reference signal.
An Intelligent Music Player Based on Emotion Recognition

This paper proposes an intelligent agent that sorts a music collection based on the emotions conveyed by each song, and then suggests an appropriate playlist to the user based on his/her current mood. The user's local music collection is initially clustered based on the emotion the song conveys, i.e. the mood of the song. This is calculated taking into consideration the lyrics of the song, as well as the melody. Every time the user wishes to generate a mood-based playlist, the user takes a picture of themselves at that instant. This image is subjected to facial detection and emotion recognition techniques, recognizing the emotion of the user. The music that best matches this emotion is then recommended to the user as a playlist.
Competitive Interaction Design of Cooperative Systems Against Attacks

This technical note proposes a resilient cooperative control design for networked cooperative systems when subjected to external attacks. The systems considered in this paper can have any information topology described by a leader-follower digraph. A potential attack on such systems consists of unknown bounded signals generated from any linear or nonlinear finite-$L_2$-gain exogenous dynamical system and injected distributively into nodes of the system's network. The purpose of the attack is to destabilize the consensus dynamics by intercepting the system's communication network and corrupting its local state feedback. The proposed resilient control design consists of introducing a virtual system with hidden network such that the overall system consisting of the original consensus system, the virtual system, and the attack dynamics is stable without requiring any information about the locations or nature of the attack. This is accomplished by utilizing the concept of competitive interaction to provide explicit design criteria for the hidden network of the virtual system to interact with the original system. A graph theoretical approach and a Lyapunov direct method are used to analyze the overall system and show that the proposed design ensures stability of the overall system and preserves the consensus of the original system. An example, which includes several scenarios, is used to illustrate the results.
Accurate Fall Detection Algorithm Based on SBPSO-SVM Classifier

For the purpose of improving the medical care which aims at the elderly and the chronic patients who are prone to falls, this paper makes use of Standard Binary Particle Swarm Optimization(SBPSO) to search for the combination of best feature subset and parameters (C, g), which can be used to train the SVM(Support Vector Machine). Experiments results show that the proposed method can get higher accuracy (about 99%) compared with non-optimized SVM, k-NN (k Nearest Neighbors) and threshold-based method when dealing with the classification of ADL (Activities in Daily Life) and abnormal falls.
Estimation Of Spatial Fields Of Nlos/Los Conditions For Improved Localization In Indoor Environments

A major challenge in indoor localization is the presence or absence of line-of-sight (LOS). The absence of LOS, denoted as non-line-of-sight (NLOS), directly affects the accuracy of any localization algorithm because of the induced bias in ranging. The estimation of the spatial distribution of NLOS-induced ranging bias in indoor environments remains a major challenge. In this paper, we propose a novel crowd-based Bayesian learning approach to the estimation of bias fields caused by LOS/NLOS conditions. The proposed method is based on the concept of Gaussian processes and exploits numerous measurements. The performance of the method is demonstrated with extensive experiments.
Design and Implementation of Nursing Record Assist System based on Hospital Falls and Pressure Ulcer Monitoring Method

Electronic medical record systems have been developed for efficient financial management of hospitals, personnel, and medical services. However, they require a large amount of information input and medical staff to perform various related tasks in addition to medical tasks. In this paper, we propose a system that can recognize a patient's walking behavior, falls, and pressure ulcers and store them in the system server together with photographs to support nursing records. We also propose a method of recognizing falls and pressure ulcers using the proposed system. Experiments in an actual hospital environment confirm that the proposed system is effective. In addition, the recognition accuracy of falls and pressure ulcers was measured, and it was confirmed that the fall recognition accuracy was 83 % and the pressure ulcer recognition accuracy was 97 %
Extent of Observation Parameters in Space Surveillance by Radar

For the integration of received signals in space surveillance by radar, a construction of a filter bank in various parameters is necessary. The question arises, which are the maximum and minimum expectable values for observation parameters like radial velocity, radial acceleration, etc. This paper presents a method for determining the extent of the observation parameter search space as a function of antenna beam orientation, range and maximum eccentricity of the orbit.
Towards Revisiting Passability Judgments in Real and Immersive Virtual Environments

Every task we perform in our day-to-day lives requires us to make judgements about size, distance, depth, etc. The same is true for tasks in an immersive virtual environments (IVE). Increasingly, Virtual Reality (VR) applications are being developed for training and entertainment, many of which require the user to determining whether s/he can pass through an opening. Typically, people determine their ability to pass through an aperture by comparing the width of their shoulders to the width of the opening. Thus, judgments of size and distance in an IVE are necessary for accurate judgments of passability. In this experiment, we empirically evaluate how passability judgments in an IVE, viewed through a Head-Mounted Display (HMD), compare to judgments made in the real world. An exact to scale virtual replica of the room and apparatus was used for the VR condition. Results indicate that the accuracy of passability judgments seem to be comparable to the real world.
Effects of Germination on Protein, γ-Aminobutyric Acid, Phenolic Acids, and Antioxidant Capacity in Wheat

Germinated wheat is a food material with potential health benefits due to its high phenolic and antioxidant content, but the reason why germination increases this content is unclear. The aim of this study was to investigate the relationships between protein changes (determined by two-dimensional gel electrophoresis (2-DE)), phenolics, γ-aminobutyric acid (GABA) levels, and antioxidant capacity of wheat germinated for various periods (24, 48, 72, and 96 h) compared to control. Each phenolic acid tended to increase with increasing germination time. The GABA content was highest (39.98 mg/100 g dwb) after 96 h of germination. The total oxygen radical absorbance capacity (ORAC) was 1.97 times higher after 96 h than in ungerminated seeds. Fifteen proteins, among 82 proteins separated by 2-DE, were highly related with ORAC and were identified by peptide mass fingerprinting (PMS). The PMS revealed strong expression of granule bound starch synthase (GBSS) and glutathione S-transferase (GSTF) after 96 h of germination. Overall, the ORAC at 96 h exhibited a close relationship with the levels of phenolic acids, GABA, and proteins such as GBSS and GSTF. In conclusion, these findings add to the existing knowledge of wheat protein changes and their relationship to the antioxidant properties of germinating wheat seeds.
A Marginalized Particle Filtering-Based Approach for Carrier Frequency Offset and Doubly Selective Channel Estimation in OFDM Systems

In this paper, we propose a new scheme for joint estimation of carrier frequency offset (CFO) and doubly selective channel in orthogonal frequency division multiplexing systems. In the proposed preamble-aided method, first, the time-varying channel is represented using basis expansion model (BEM) which considerably reduces the number of channel parameters to be estimated. Next CFO and BEM coefficients are estimated using principles of particle and Kalman filtering. The performance of the new method in multipath time-varying channels is investigated in comparison with previous schemes. The simulation results indicate a remarkable performance improvement in terms of the mean square errors of CFO and channel estimates.
Execution Behavior Analysis of Parallel Schemes for Implicit Solution Methods for ODEs

In this article, we consider diagonal-implicitly iterated Runge–Kutta (DIIRK) methods for the numerical solution of stiff ordinary differential equations (ODEs) and investigate their performance behavior on a modern cluster system using MPI. DIIRK methods are implicit methods and require the solution of non-linear equation systems in each iteration step. In particular, we are interested in the parallel execution behavior when using different basis Newton methods for solving the resulting non-linear equation systems of different versions of the DIIRK method. We explore the use of direct solution methods based on LU factorization for the resulting linear equation systems as well as the use of Krylov subspace methods and investigate the resulting performance and accuracy.
Vehicle Modeling and Detection in Crossroads

In this work, we proposed a novel method to detect vehicle automatically under different field of view in urban area. First, traffic flow maps are reconstructed to estimate the size and orientation of a vehicle for every position. Vehicle models are then represented by flow information and foreground blob which shows the potential appearance of a vehicle in each position in the crossroad. Finally, we perform a voting strategy to detect the potential vehicle. The experimental results show the robustness of our system. Our algorithm can be applied to the surveillance cameras with different view in crossroads.
Graphene Based Multiband Frequency Reconfigurable Antenna

This communication proffers a graphene based microstrip reconfigurable antenna capable of switching between two frequency bands (S-band 3.03 GHz and C-band 5.17 GHz and 6.13 GHz). A graphene nanoparticle based conductive ink is printed on the cotton showing surface resistance of 2.7 Sq. −1, conductivity of 0.37× 10<sup>5</sup> Sm<sup>−1</sup>. An excellent radiation efficiency of above 55% is achieved at the dominant mode (TM<inf>10</inf>, 3.03 GHz. The frequency reconfigurability is introduced by exciting the higher order modes, TM<inf>02</inf> and TM<inf>20</inf> through two different feeding locations and an external RF Switch.
Tandem DNAzyme for double digestion: a new tool for circRNA suppression

Abstract Circular RNA (circRNA) play a crucial role in many biological processes and have been proved as potential biomarkers and therapeutic targets in many diseases. Manipulation of their expression is a critical task. In this study, we developed a new strategy for circRNA suppression with DNAzyme. Data showed single-digestion DNAzymes cleaved circRNA efficiently in vitro but not in cell culture. However, tandem DNAzymes for double digestion showed higher cleavage efficacy both in vitro and in cell culture. Functional study demonstrated that double-digestion DNAzymes suppressed the miRNA sponge function of circRNA and changed the proliferation and migration rates of HCC cells.
Career Success According to New Graduates: Implications for Counseling and Management

Resumo Qualitative research on career success has been encouraged across different category of workers. This qualitative research sought to explore how do new graduates define career success and also highlight some implications for career counseling and Human Resources management. Sample included nine new graduates from two different regions of Brazil, divided in two focus groups. Discourse analysis based on interpretative repertoire approach was used for the data analyses. The graduates’ definitions emphasized both subjective (confidence in the future, career planning, professional identity construction, work adjustment, and satisfaction with the career path) and objective (work in the area of graduation with a good salary, financial independence, social recognition) career outcomes. The meanings identified in this study reinforced the multidimensional nature of the construct and also could help career counselors and human resources managers better plan their interventions contributing to new graduates’ career success during university-to-work transition.
Design of a Virtual Reality and Haptic Setup Linking Arousals to Training Scenarios: A Preliminary Stage

Using Virtual Reality (VR) to realise immersive training environments is not a new concept. However, investigating arousal in immersive environments is. By arousal, we denote a general physical and psychological activity that in the form of anxiety and stress for example, can affect trainees' performance. In this work, we describe the setup design for a two-phase explorative experiment linking arousal and performance, during training in a Virtual Reality (VR) environment. To do so we are using an appraised well-crafted VR puzzle game, questionnaires (i.e. NASA Task Load Index [3]), and sensors (skin conductance response / pulse). The experiment will involve participants from the public that will be trained in two predefined processes of variant difficulty.
FPGA-Based Hardware Design for Scale-Invariant Feature Transform

This paper proposes a novel hardware design method of scale-invariant feature transform (SIFT) algorithm for implementation on field-programmable gate array (FPGA). To reduce the computing costs, Gaussian kernels are calculated offline for use in Gaussian filters. To eliminate low-contrast points, the inverse of a Hessian matrix is required for hardware implementation, which results in poor performance because dividers are needed. To solve this problem, this paper presents a new mathematical derivation model to implement the low-contrast detection, avoiding the use of any dividers. For the implementation of the normalization module, a large number of dividers are required by traditional methods, which adversely affects the computational efficiency. This paper presents a new architecture using only one divider to implement the normalization function in hardware. Thanks to the parallel processing architecture proposed to design the image pyramid, SIFT detection, and SIFT descriptor, the computational efficiency of the SIFT algorithm is significantly improved. As a result of the proposed design method, the requirement of logic elements in the FPGA hardware is greatly reduced and system frequency is significantly increased. Experimental results show that the proposed hardware architecture outperforms existing techniques in terms of resource usage and computational efficiency for real-time image processing.
Towards IPv6-based Architecture for Big Data Processing of Community Medical Internet of Things

The application of IPv6 to the community medical Internet of things (CMIoT) is helpful to solve the heterogeneous network fusion problem. However, how to effectively implement the application of IPv6 technology in the CMIoT is still a problem that needs to be constantly explored. While the IPv6 technology can effectively solve the problem of identifying the nodes of the CMIoT, the big data in the CMIoT becomes a more prominent problem. On the basis of the research on the application of IPv6 technology to the Internet of things (IoT), this paper proposes a kind of IPv6 proxy scheme for the interconnection between the IoT subnet and the IPv6 Internet. At the same time, the big data problem of the IoT is discussed, and a big data processing architecture based on cloud platform is designed for effective processing of the big data of the CMIoT. Combined with the Ptolemy II modeling and simulation platform, the IPv6 proxy scheme and the medical big data processing architecture based on cloud platform are modeled and simulated. The simulation and analysis results show that the IPv6 proxy scheme can not only achieve more efficient implementation of IoT subnet nodes accessing the IPv6 Internet based on the IPv6 technology, but also play a certain role in the big data processing of CMIoT.
Coordination Schemes for the Integration of Transmission and Distribution System Operations

Low-voltage distribution networks are emerging as an increasingly important component of power system operations. From a computational standpoint, the proactive utilization of these resources places daunting challenges due to their vast number and the non-linear physics that govern power flow in low-voltage networks. For this reason, a hierarchical approach to the organization of distribution markets which can better cope with computational scalability may be desirable. This paper models various alternatives to the coordination of transmission and distribution system operations, and investigates their relative performance on a small-scale network in terms of allocative efficiency, consistency with physical constraints, and pricing,
Online MTPA Control of IPMSM for Automotive Applications Based on Robust Numerical Optimization Technique

This paper shows an online MTPA control which considers not only magnetic saturation but also cross-coupling effects. In automotive applications, torque accuracy and high efficiency operation are important issues. It can be dealt as a constrained optimization problem to satisfy both torque reference tracking and loss minimizing operation. Nonlinear simultaneous equations are derived from Lagrange multiplier method, which could be solved by numerical algorithms. Among them, Levenberg-Marquardt algorithm is employed to guarantee a robust calculation of optimal current references. It is optimized to alleviate calculation burden while maintaining the stability of the proposed algorithm. The feasibility of the proposed method is verified under various operating conditions by simulation and experimental results. Through the proposed algorithms, accurate MTPA control is achieved under not only unsaturated but also highly-saturated operating conditions.
Dual-Doppler and Polarimetric Radar Analysis of Hail Events in Germany

Understanding the life cycle of precipitating systems is important for better nowcasting of significant weather and for improving weather prediction models. Doppler and polarimetric weather radars have the ability to look simultaneously into the microphysics and dynamics of precipitation systems. In this work we make use of these powerful tools to perform a combined analysis of the dynamics and microphysics of precipitation systems, in order to better understand storm development. By using data from multiple Doppler radars, the 3D wind field may be retrieved. Simultaneously, the polarimetric capability of the radars allows the retrieval of hydrometeor types and microphysical processes. Therefore, we are able to identify the processes through which precipitation systems evolve by revealing the interdependence between storm dynamics and microphysics. Prominent examples of such interactions are the development of socalled Zdr columns, that are associated with storm updrafts, and consequent freezing and potential hail formation; or regions of riming that are difficult to spot from polarimetry alone, but which require an updraft for supply of supercooled water, which could be seen in the wind field retrievals; or the development of lightning through lifting of graupel in convective updrafts that cause vertical electric charge separation. In this work we apply the Dual-Doppler technique DDA to analyze two large hail events that occurred near the Bonn and Jülich radars: the 5th July 2015 and 22 June 2017. The life cycle of these 2 systems will be examined to better understand the formation and growth of hail, from the perspective of dynamics and microphysics.
Fuzzy Kalman Filter Modeling Based on Evolving Clustering of Experimental Data

A methodology to system identification based on Evolving Fuzzy Kalman Filter, is proposed in this paper. The mathematical formulation using an evolving Takagi-Sugeno (TS) structure is presented: the offline Gustafson Kessel (GK) Algorithm is used to a window of initial data set; after that, an evolving GK algorithm estimate the antecedent parameters. A fuzzy version OKID (Observer/Kalman Filter Identification) algorithm is formulated to obtain the state matrix, the input influence matrix, the output influence matrix, the direct transmission matrix, and the Kalman gain matrix, recursively, composing the consequent parameters. Computational results from the estimation of parameters of nonlinear dynamic system show the efficiency and applicability of the proposed methodology.
Beneficial Services of Arbuscular Mycorrhizal Fungi – From Ecology to Application

Arbuscular mycorrhiza (AM) is the most common symbiotic association of plants with microbes. AM fungi occur in the majority of natural habitats and they provide a range of important ecological services, in particular by improving plant nutrition, stress resistance and tolerance, soil structure and fertility. AM fungi also interact with most crop plants including cereals, vegetables, and fruit trees, therefore, they receive increasing attention for their potential use in sustainable agriculture. Basic research of the past decade has revealed the existence of a dedicated recognition and signaling pathway that is required for AM. Furthermore, recent evidence provided new insight into the exchange of nutritional benefits between the symbiotic partners. The great potential for application of AM has given rise to a thriving industry for AM-related products for agriculture, horticulture, and landscaping. Here, we discuss new developments in these fields, and we highlight future potential and limits toward the use of AM fungi for plant production.