Miracle-dz/UniFAR-FTUs huggingface dataset:
The phantom robot: predictive displays for teleoperation with time delay

An enhanced teleoperation technique for time-delayed bilateral teleoperator control is discussed. The control technique selected for time delay is based on the use of a high-fidelity graphics phantom robot that is being controlled in real time (without time delay) against the static task image. Thus, the motion of the phantom robot image on the monitor predicts the motion of the real robot. The real robot's motion will follow the phantom robot's motion on the monitor with the communication time delay implied in the task. Real-time high-fidelity graphics simulation of a PUMA arm is generated and overlaid on the actual camera view of the arm. A simple camera calibration technique is used for calibrated graphics overlay. A preliminary experiment is performed with the predictive display by using a very simple tapping task. The results with this simple task indicate that predictive display enhanced the human operator's telemanipulation task performance significantly during free motion when there is a long time delay. It appears, however, that either two-view or stereoscopic predictive displays are necessary for general three-dimensional tasks. <<ETX>>
DC Fault Tolerant Modified Parallel Hybrid Converter with Enhanced Operating Range

This paper presents a modified parallel hybrid converter (MPHC) for HVDC applications with wide operating range and dc-fault tolerant capabilities. A novel control technique is proposed for capacitors voltage balancing of MPHC. The performance evaluations of the proposed converter and its control are carried out using PSCAD/EMTDC for both under- and overmodulation index (MI) range and also for an HVDC system. Two methods are proposed to make the MPHC tolerant to dc fault. The results obtained confirm the superior performance of the proposed converter over the existing ones. The capacitor size design methodology, loss calculation of the converter and self-excited pre-charging mechanism are also presented.
Model-less Estimation Method for Robot Grasping Parameters Using 3D Shape Primitive Approximation

The vision systems of intelligent robots, such as home robots, must be capable of two important tasks: detecting objects and estimating the position for grasping them. Deep Neural Network (DNN) -based techniques are applicable for object detection; however, estimating grasping parameters is still difficult, especially when a 3D model of each object is unavailable. We propose a method to estimate the parameters (position, direction, angle, and opening width) required for a robot to grasp objects without model. First, the 3D surface shape of the object is recognized using a DNN. Next, by integrating these result of recognition, an appropriate object primitive (hexahedron, cylinder, or sphere) is fitted to the target object. Finally, the optimal grasping parameters for the object are determined using a rule database that is prepared in advance. The success rate for approximating object primitives with our method was 94.7%, which is 6.7% higher than the existing method using 3D ShapeNets. The success rate for grasping with our method was 85.6% in grasping simulations using Gazebo. This is 17.8% higher than the GPD method using a DNN.
Learning via Decision Trees Approach for Video Super-Resolution

In this paper, we propose an unsupervised learning-based multi-frame video super-resolution (SR) approach via decision trees model (DTSRV). This novel approach utilizes the temporal redundancy and coherence in consecutive video frames. Motion estimation is applied between consecutive frames to form concatenated motion compensated patches. The low resolution (LR) - high resolution (HR) pairs are then formed to be the training input of the decision trees. After the classification process with decision trees, a linear regression model is learnt to map the relationship between the concatenated LR patches and the HR patches. Results of our experiments show that the approach outperforms state-of-the-art model-based algorithms with an average of 0.97 dB PSNR increase and a much faster speed. It also achieves a 1.4 dB better results for large video sizes than the frame-by-frame image SR using decision trees learning techniques. This is the first time reporting in the literature to use comprehensive random trees/forests structures for video SR. Now the scheme only utilizes two neighbor frames and can already have a good result, which proves its efficiency in real-time application. Our analysis also proves it to have more promising possibilities and advantages for future development.
Improvement of Voltage Sags Rates by Applying Optimal Reconfiguration of Electrical Networks in Presence of DG by Using Tabu Search

This paper proposes a methodology to analyze the impact of the inclusion of distributed generation when the electric network is reconfigured to improve the voltage sag indices. The optimization algorithm for reconfiguring the electrical system is implemented using a Tabu Search technique. In order to show the effectiveness of the developed methodology, case studies using the IEEE-57 test system are presented.
Sharing by Proxy: Invisible Users in the Sharing Economy

With the future of work increasingly data-driven, platforms automate decisions based on the collection of vast quantities of user data. However, non-users constitute a challenge as they provide little to no data for either platforms or other users. We focus on a category of (non-)users that has not received any attention in research: users-by-proxy. Users-by-proxy make use of sharing services but they are not themselves part of the sharing transaction. Platforms cannot analyze their behavior to tailor services or allocate labor most effectively. Users-by-proxy also have significant implications for trust and reputation mechanisms. In this conceptual contribution, we provide a definition of users-by-proxy as a third category between users and non-users, developing a typology of users-by-proxy based on motives of non-/use. We focus on the ramifications of users-by-proxy for the future of work and their significance for the limits of data-driven decision-making.
Effects of a modelling example for teaching information problem solving skills

Although students often appear to be skilled in retrieving and making use of information from the internet, research shows that their information problem solving skills are overestimated. They show deficiencies in many of the necessary skills, such as generation of search terms, selection of sources, and critical processing of information. It is therefore necessary to design and develop effective instruction to foster information problem solving skills. Research shows that learning from examples can be an effective approach for teaching complex cognitive skills in ill-structured domains, such as writing or communicating. To explore whether this also holds for information problem solving, this study investigates the effects of presenting a modelling example in an online information problem solving training. Results of two experiments show that viewing a modelling example, presented as a screencast of an expert thinking out loud and interspersed with cognitive prompts, leads to a higher posttest performance than performing a practice task. The effect persisted on a delayed posttest 1 week later. The results imply that information problem solving instruction in an online setting can benefit from employing video-based modelling examples.
Active-Learning-Incorporated Deep Transfer Learning for Hyperspectral Image Classification

A hyperspectral image (HSI) includes a vast quantity of samples, a large number of bands, and randomly occurring redundancy. Classifying such complex data is challenging, and its classification performance can be affected significantly by the amount of labeled training samples, as well as the quality, position, and others factors of these samples. Collecting such labeled training samples is labor and time consuming, motivating the idea of taking advantage of labeled samples from other pre-existing related images. Therefore, transfer learning, which can mitigate the semantic gap between existing and new HSIs, has drawn increasing research attention. However, existing transfer learning methods for HSIs (which mainly concentrate on how to overcome the divergence among images) may fail to carefully consider the contents to be transferred and thus limit their performances. In this paper, we present two novel ideas: 1) we, for the first time, introduce an active learning process to initialize the salient samples on the HSI data, which would be transferred later; and 2) we propose constructing and connecting higher level features for the source and target HSI data to further overcome the cross-domain disparity. Different from existing methods, the proposed framework requires no a priori knowledge on the target domain, and it works for both homogeneous and heterogeneous HSI data. Experimental results on three real-world HSIs support the effectiveness of the proposed method for HSI classification.
Accessibility analysis for the automatic inspection of mechanical parts by coordinate measuring machines

An overall strategy for inspection planning is discussed, and attention is focused on local and global accessibility cones and on algorithms for computing and clustering them. The direction-cone clusters serve to generate a minimal set of directions for inspecting a part. The algorithms are based primarily on the computation on Gaussian images and Minkowski (or sweeping) operations. Applications to computer vision and automatic machining are briefly presented. <<ETX>>
Characterization of the dielectric properties of biological tissues and their correlation to tissue hydration

The aim of this paper was to investigate the correlation between the dielectric properties of biological tissues and their different states of hydration. Measurements were conducted on rat muscle and fat tissues both in vivo and ex vivo, in different states of dehydration through a loss on drying technique. Dielectric parameters were observed as a function of frequency from 500 MHz to 50 GHz by utilizing an open-ended coaxial probe at constant room temperature of 25° C. By observing which dehydration fractions fall within in vivo values, it was deduced that ex vivo samples are reliable in representing the dielectric parameters of in vivo samples, under certain controlled hydration conditions whereas, further analysis should be conducted for tissue characterized by low water content.
Perceptions of heart failure symptoms, disease severity, treatment decision-making, and side effects by patients and cardiologists: a multinational survey in a cardiology setting

Purpose Explore the extent to which heart failure (HF) symptoms and side effects of HF treatment experienced by patients are recognized by cardiologists, and concordance between patient–cardiologist perceptions of HF severity and patients’ contributions to treatment decision-making. Methods A multinational, cross-sectional survey of cardiologists and patients with HF was conducted. Patient-record forms (PRFs) were completed by cardiologists for consecutive consulting patients with HF, who completed a patient self-completion questionnaire (PSC). Responses from PRFs with an associated PSC were analyzed to compare patient- and cardiologist-reported occurrences of HF symptoms and treatment side effects, patient-perceived severity of HF and cardiologists’ perceived risk of death within 12 months, and patient input into treatment decisions. Concordance was calculated as the number of response agreements between PSCs and PRFs for total number of matched pairs. Over- or underreporting of symptoms and side effects by cardiologists relative to patient-reported occurrences were calculated. Results Overall, 2,454 patient–cardiologist pairs were identified. High levels of concordance between matched pairs were observed for the occurrence of reported HF symptoms (93%), side effects (77%–98%) and degree of patient input into treatment decisions (74%); for perceived HF severity, concordance was 54%. Most symptoms (except dyspnea when active and fatigue/weakness, experienced by >50% of patients) were underreported by cardiologists. Of patients reporting to have been informed by their cardiologist that their HF was mild, 28% were perceived by their cardiologist to have a moderate–high/very high risk of death within 12 months. Treatment choice was not discussed with almost a third of patients. When discussed, 94% of patients (n=1,540) reported the cardiologist made the final decision. Cardiologists more often under- than overreported the occurrence of side effects reported by patients. Conclusion Improved patient–cardiologist dialogue and shared decision-making is required for optimizing patient care and outcomes in HF.
Hybrid Excitation Flux Switching Motor with Permanent Magnet Placed at Middle of Field Coil Slots Employing High Filling Factor Windings

Design and experimental studies on Hybrid Excitation Flux Switching Motor (HEFSM) applied to a traction motor for hybrid electric vehicles are presented. A stator body of HEFSM generally consists of not only laminated core and three-phase armature coils, but also field excitation coils and permanent magnets as field mmf sources. Therefore, each material used in the stator body should be designed properly with the purpose of performance improvements such as efficiency, power and torque densities, cost and so forth. The configuration and the arrangement of all coils are examined to increase their filling factor for reducing copper losses. Moreover, thinner electromagnetic steel and permanent magnets with high remanent flux density are employed to achieve higher efficiency. Experimental tests using a prototype of HEFSM validate the design results.
ZVS transitions in Multi-Mode Single Stage Inverter

The scope of this paper is to describe how to achieve and optimize Zero-Voltage Switching (ZVS) in an energy buffered single-phase inverter. The inverter can be described as a three-port system in which the third port is the storage capacitor. Several operation modes are used along the line cycle, depending on the required voltages and currents in the three ports. The operation modes shape the inductor current and control the power balance among ports. Operation modes are selected to ensure ZVS in every transition and minimum power precessed by the inductor. The energy in the inductor is used to obtain ZVS. ZVS is not only important to reduce dramatically switching losses, but also to limit dv/dt in switching nodes. GaN transistors require low current in the inductor to perform ZVS compared to Silicon devices since they feature around four times lower parasitic capacitance. This paper describes a methodology to calculate the minimum current in the inductor required to perform ZVS in all transitions, and the trade-off between $\boldsymbol{R_{ds}}$ and $\boldsymbol{C_{oss}}$ of switching devices. Results obtained are applied and validated in the prototype.
AppInventory: A Visual Catalogue of Web 2.0 and Mobile Applications for Supporting Teaching and Learning Activities

The availability of hundreds of Web 2.0 and mobile applications represent a great opportunity in helping teachers adopt student centred methodologies. These applications support users in creating and sharing digital artefacts, in aggregating, remixing and collecting heterogeneous materials and in communicating within working groups. When incorporated into daily teaching and learning activities (TLA), such applications can improve the collaborative, cognitive and creative work of the students, enhancing and redefining traditional educational practices. Nevertheless, although these applications are generally easy to find and use, there is a lack of knowledge about their existence, their functions and their potential in an educational setting. In this paper we describe AppInventory, a novel platform which contains a digital catalogue of applications: they are organized by applying an original taxonomy; the users can browse among them benefiting from a visual approach and semantic connections modelled using zz-structures.
What Wrist Temperature Tells Us When We Sleep Late: A New Perspective of Sleep Health

Research has shown that sleep is tied to our internal circadian rhythms and a long-term of misalignment between sleep and circadian rhythms can have harmful effects. Being able to detect circadian patterns is a key component to understanding and supporting a person's sleep. Wrist temperature has been shown to be correlated to circadian rhythm as well as sleep/wake status. In this paper, we explore the use of wrist temperature to evaluate sleep health of 14 participants over 111 days. Our results demonstrate that our sleep detection algorithm based on wrist temperature can be used to reliably estimate individual's daily sleep parameters and can be used to support sleep-based phase assessments. A wrist temperature trend-based assessment is also presented to identify when sleep time is misaligned with circadian rythm. This work provides the first steps in future sleep systems that take into account our internal bio-rhythms.
An elective entrustable professional activity-based thematic final medical school year: an appreciative inquiry study among students, graduates, and supervisors

Purpose The transition from undergraduate to postgraduate training can be facilitated by offering electives that focus on increased patient care responsibilities. This transitional year model in the Netherlands has recently been expanded to offer packages of electives geared to specific residencies and was called “dedicated transitional year” (DTY). At University Medical Center Utrecht, an entrustable professional activity (EPA)-based multidisciplinary DTY in acute care (DTY-AC), rooted in self-determination theory (SDT), has been implemented. The current study aimed to understand strengths and challenges regarding the implementation of this specific DTY. Methods An explorative qualitative study among students, graduates, and faculty was conducted using an appreciative inquiry methodological approach. We gathered first-hand accounts of experiences with the DTY-AC in focus groups and interviews with students and interviews with graduates, supervisors, and mentors. Transcripts were analyzed with a directed content analysis approach. Results Participants found the DTY-AC to focus learning, offering coherence by clear learning objectives, aligned assessment, and teaching sessions and offering a congenial learning community. However, EPAs were not the focal point of workplace assessment and evaluation. Providing sufficient hands-on student engagement in actual acute care situations was another challenge. Conclusion The concept of the thematic DTY is embraced, and it seems to help in meeting the SDT needs. Enhancing delivery in the workplace by improving formal implementation with information and faculty development, expanding EPA-focused workplace assessment, and extending hands-on experience of students could further unlock the potential of this final medical school year design. Our lessons learned may help in the development and implementation of similar programs, other models of DTYs, and final-year redesigns.
Suggested Procedures for the Reproducible Synthesis of Poly(d,l-lactide-co-glycolide) Nanoparticles Using the Emulsification Solvent Diffusion Platform

Background: Poly(d,l-lactide-co-glycolide) (PLGA) based biodegradable nanoparticles are of key interest for the development of controlled release drug delivery systems and for other biomedical applications. It has been reported that PLGA polymers can be converted into colloidal nanoparticulate systems by various techniques, such as emulsification-diffusion, emulsification-evaporation, interfacial deposition, salting out, dialysis and nanoprecipitation. Emulsification-evaporation with water immisci-ble solvents including dichloromethane and chloroform has been the preferred method for the synthesis of PLGA nanoparticles due to the low boiling point and limited water solubility of these solvents. We and others, however, have found that when water-immiscible solvents are used for the synthesis of PLGA nanoparticles, particle aggregation, non-uniform particle size and multimodal size distribution are commonly encountered problems. This suggests that the synthesis of PLGA nanoparticles using water immiscible solvents is highly sensitive to small procedural variations that affect overall reproduc-ibility. Objective: This study presents a simple and robust procedure for the preparation of PLGA nanoparti-cles with very small batch to batch variability (<5% variability in size (z-average) as determined by dynamic light scattering). Results: The results showed that the emulsification solvent diffusion method teamed with partially water-miscible solvents, such as ethyl acetate, is a versatile approach for the preparation of PLGA na-noparticles with highly reproducible sizes (between 50 and 400 nm) and zeta potentials (between -30 and +30 mV), with relatively narrow polydispersity. Conclusion: Emulsification-diffusion with ethyl acetate is, therefore, a more reliable alternative to sev-eral existing procedures for the reproducible and refined synthesis of PLGA nanoparticles
Novel Resonance Circuit for Heaving Wave Energy Converters

Enhancing electrical power conversion of Wave Energy Converters (WECs) is a continuous research area. A variety of electrical circuits topologies have been considered, including passive and active topologies. In this paper, we propose a simple, inexpensive and efficient that combines a conventional six pulse rectifier with resonance phenomena. Electrical resonance was achieved by adding shunt capacitors between the rectifiers diodes. Capacitors value was selected based on dominant electrical frequency which, in turn, governed by the velocity of the translator of the Permanent Magnet Linear Generator (PMLG). The proposed circuit increased the output power and reduced harmonics compared to another resonance topology. Besides, the behaviour of the closed loop WEC system, including hydrodynamic interactions, was also simulated. The new resonance configuration resulted in a wider bandwidth with respect to sea state.
Integration of Capture Based Phase Voltage Measurement for Surface Permanent Magnet Machine Position Sensorless Drive

This paper improves the position sensorless drive of permanent magnet (PM) machine by measuring actual phase voltages with pulse width modulation (PWM). On the basis, the phase voltage is obtained based on the digital integration of PWM voltage using the capture modulator in existing drive microcontrollers (MCU's). Comparing to existing phase voltage measurement, no separated A/D converter and communication hardware are required because PWM pulses are directly measured using MCUs. However for standard machines without neutral points, only line-to-line AC PWM voltages can be measured for the phase voltage reconstruction. Since the capture based on TTL logics receives only digital signals, a preprocess circuit to convert AC PWM line voltages to equivalent digital signals is proposed. This paper clearly explains the hardware implementation using MCU capture modulator. According to experimental results, a 150MHz sampling rate for phase voltage measurement is achieved based on the proposed capture-based voltage measurement.