Miracle-dz/UniFAR-FTUs huggingface dataset:
Dealing With Front-End White Noise on Differentiated Measurements Such as Frequency and ROCOF in Power Systems

This paper describes the way that white noise (including quantised input section sampling) imparts errors onto frequency and rate-of-change-of-frequency (ROCOF) measurements. The main paper focus concerns the use of filtered heterodyned (i.e., Fourier) analyses for single-phase and three-phase systems, and the filtered Clarke transform for three-phase systems. The rules and equations governing the effect of white noise on frequency and ROCOF are formulated for these techniques, explaining the subtle effects of aliasing, splitting signals and noise into their positive and negative frequency components, and the correlation or decorrelation of noise. It is shown that—as expected—for three-phase ac measurements, averaging three single-phase Fourier measurements produces the same performance against noise as using a method based on Clarke’s transform, if identical filtering is used. Furthermore, by understanding the theory behind the frequency and ROCOF measurement processes, it is shown that to achieve the lowest RMS errors, in the presence of front-end white noise (alone, ignoring other dynamic signal and power quality aspects), a filter which provides ~40 dB/decade attenuation (i.e., a two-boxcar cascade) is recommended for a frequency measurement, but a filter which rolls off at ~60 dB/decade (i.e., a three-boxcar cascade) is recommended for a ROCOF measurement.
Emotion Classification using Dual-Tree Complex Wavelet Transform

In this paper, a new method of feature extraction is proposed for speech emotion classification using dual-tree complex wavelet transform (DTCWT). DTCWT is a multiresolution technique, which decomposes the speech signal into number of sub-band signals. Different emotions have different impacts on frequency-bands. The feature extracted from DTCWT sub-band coefficients may therefore be better capture the emotion information of different sub-bands. The mean, skewness, kurtosis and energy values are evaluated from each sub-band coefficient, and used as a feature. The performance of the proposed feature is evaluated using two databases, EMODB and IEMOCAP. For classification purpose, support vector machine (SVM) classifier is used. Recognition results show that the proposed feature out-performs the linear prediction coefficients (LPC) and a Teager-energy-operator (TEO) based feature (TEO-CB-Auto-Env). Combination of the proposed feature with the mel frequency cepstral coefficients (MFCC) further increases the classification performance.
Improvement of Energy Concentration in S-transform using Maximally Concentrated Window

Time-frequency representation (TFR) of a signal using S-transform (ST) provides detailed information about the local spectrum at any instant of time. One of the major limitations with conventional ST is poor time resolution at low frequencies due to very long taper of Gaussian window. It restricts the application of ST in precisely resolving the signal components in time and finite event detection. To counter this problem, we propose a variant of ST namely time-limited ST (TST) based on zero order prolate spheroidal wave function. For practical implementation, discrete counterparts of the TST is proposed based on zero order discrete prolate spheroidal sequence. This technique is particularly beneficial for effectively detecting certain finite duration event and precisely localizing the initiation and termination of an event. The simulation results indicate that the proposed TST can precisely resolve signal components in time, and simultaneously provide maximum concentration in freuuency.
Dynamic Network Formation Game With Social Awareness in D2D Communications

The benefit of having a complementary network such as device-to-device (D2D) communications underlaying cellular systems lies in alleviating the traffic overloading burdens at base stations (BSs). This is critical in modern-day scenarios, e.g., in offloading and caching of mobile data traffic, and delivery of popular Internet contents to users. In this paper, we are chiefly interested in the establishment of D2D networks and how such a network evolves dynamically over time as D2D links are continuously formed and broken. Another important yet challenging research opportunity, i.e., the leverage of human users’ social ties for D2D communications, will also be addressed in this paper. To investigate the D2D network formation problem, we look at a game-theoretic framework where the utility function is designed to balance the physical and social domains—where we systematically extract social tie strengths from a real-world data set. To study the evolution of such D2D networks through time in a dynamic stochastic context, we propose a dynamic potential game and show that its equilibrium behaviors can be achieved through some strategy and payoff learning mechanisms. Simulation results verify our analysis. Using a content delivery application to assess the performance of our proposed scheme, it can be shown that major improvements can be obtained in terms of network delay, content accessibility, and BS load reduction.
A Voice Control System for Assistive Robotic Arms: Preliminary Usability Tests on Patients

One of the major issues for the success of assistive robotics concerns the question whether patients not only accept the technology and profit from it, but also whether they can effectively use it. This is especially relevant when patients are highly impaired and present several functional limitations. Therefore, it is important to enable patients to control robots with alternative methods during their activities of daily living. This work deals with the development of a voice control system based on the ROS middleware framework. The voice control was customized on the JACO2(Kinova Technology, Montreal, QC, Canada), a 6 degree-of-freedom assistive robotic manipulator. Two subjects with different impairments due to a neurodegenerative disease tested the robot for usability controlling it through the JACO2joystick and the developed voice control system. Both subjects used the voice control system successfully and scored highly its usability. The most impaired subject preferred the voice control while, by contrast, the less impaired one preferred to use the joystick. Preliminary results showed good usability of the system, which could be an important aid for highly impaired people.
A Framework for Enhancing Word Embeddings with Task-Specific Information

Since distributed representation of words came into vogue, generating and maintaining embeddings for language data has been a basic but important support of a wide range of NLP tasks. However, word embeddings generated by Word2Vec approaches may not work perfectly on every task. One of the most possible reason is the lack of task-specific information. In this paper, we introduce a pipeline framework containing two main modules trying to solve this issue. The first module is a task-free Word2Vec model to generate word embeddings from scratch. Followed by the first one, the second module is a task-specific language model to re-train and fine tune the generated embeddings from the first one. The proposed framework is experimentally evaluated on both synthetic dataset and real-world corpus. The results show that the involvement of task-specific semantic information can actually benefit the embedding performance on the example task of entity categorization, and provide potential insight for the intrinsic understanding of semantic learning.
Motor Intention Decoding During Active and Robot-Assisted Reaching

Robotics rehabilitation is a widely used approach for the treatment of patients with severe motor disabilities, such as stroke survivors. Robots can provide intense, controlled and repeatable rehabilitation and they can also provide different levels of assistance when patients are not able to initiate or complete a movement. Nevertheless, several studies proved that completely passive movements are not sufficient to stimulate neuro-motor recovery and patients' engagement is a key factor for an effective rehabilitation. For this reason it is important to combine techniques for detection of movement intention (MI) with rehabilitation robotics. In this study we developed an algorithm capable of detecting MI before the movement onset, in order to obtain a trigger signal for providing robotics assistance. The proposed algorithm automatically selects the channels used to extract MI based on the motor-information content of each channel. The developed algorithm was tested on data recorded on n = 8 healthy subjects performing 3D reaching movements with an exoskeleton in active and assisted conditions. MI was detected about 400 ms before the beginning of the movement and the performance of the proposed method were significantly higher than the one achieved when six preselected channels, located over motor areas, were used for MI decoding. MI was also detected during robot-assisted movements. Interestingly, in active movements the highest performance was achieved with electrodes over a well-localized cluster above the contralateral and central motor areas, while in passive executions, the areas with the best performances became more sparse.
Synthesizing a Knowledge Graph of Data Scientist Job Offers with MINTE+

Data Scientist is one of the most sought-after jobs of this decade. In order to analyze the job market in this domain, interested institutions have to integrate numerous job advertising coming from heterogeneous Web sources e.g., job portals, company websites, professional community platforms such as StackOverﬂow, GitHub, etc. In this demo, we show the application of the RDF Molecule-Based Integration Framework MINTE + in the domain-speciﬁc application of job market analysis. The use of RDF molecules for knowledge representation is a core element of the framework gives MINTE + enough ﬂexibility to integrate job advertising from diﬀerent web resources and countries. Attendees will observe how exploration and analysis of the data science job market in Europe can be facilitated by synthesizing at query time a consolidated knowledge graph of job advertising. The demo is available at: https://github.com/ RDF-Molecules/MINTE/blob/master/README.md#live-demo
How happiness expectations relate to the Dark Triad traits

ABSTRACT In samples of Americans (N = 273) and Indians (N = 194) paid through Mechanical Turk (Study 1) and British (N = 132) volunteers contacted through Reddit (Study 2), we examined how the Dark Triad traits (i.e., psychopathy, narcissism, and Machiavellianism) were associated with happiness expectations when participants imagined solving adaptive tasks. In Study 1, the traits were linked to forecasted happiness in achieving status and power and mate-seeking, with psychopathy demonstrating less happiness when pursuing slow life history tasks (e.g., avoiding diseases), whereas the other two traits led to expectations of happiness when forming social bonds, retaining mates, and avoiding pathogens. In Study 2, the traits were associated with choosing to pursue mating opportunities to induce happiness. Women expected more happiness in response to ensuring their safety over pursuing mating opportunities. We suggest happiness might be an affective feedback system that rewards people for pursuing their life history goals.
Gemini Amphiphile-Based Lipoplexes for Efficient Gene Delivery: Synthesis, Formulation Development, Characterization, Gene Transfection, and Biodistribution Studies

Some quaternary gemini amphiphiles (GAs) were synthesized as nonviral gene delivery carriers. The critical miceller concentration values of these amphiphiles are indicative of their superior surface-active properties. All of the synthesized GAs, alone or along with lipids like cholesterol and/or dioleoylphosphatidyl ethanolamine (DOPE), were formulated as liposomes. Formulations of GAs with DOPE showed average particle diameters of 326–400 nm with positive ζ-potential (30.1–46.4 mV). The lipoplexes of theses formulations showed complete pDNA retention at the base at a N/P ratio higher than 1.0 in gel retardation study. The GAs were effective in condensing pDNA into a ψ-phase, as indicated by circular dichroism study, and provided complete protection of the pDNA against the enzyme DNase at a N/P ratio more than 1. In vitro cell line studies showed that GA liposomal formulations caused β-gal expression and offered a higher transfection efficiency than that of liposomes prepared with the help of N-[1-(2,3-dioleoyloxy)propyl]-N,N,N-trimethylammonium methyl-sulfate (DOTAP)/DOPE and dicyclocarbodiimide (DCC)/DOPE but comparable to those of Lipofectamine 2000 in A549 and HeLa cell lines. Modulation of head group polarity significantly affected the transfection efficacy of GAs. The cell viabilities of almost all of the formulations were comparable to those of the standards (DCC/DOPE and DOTAP/DOPE liposomes). Incorporation of cholesterol [GA/DOPE/cholesterol in the ratio of 1:1:1] further improved the serum compatibility of the formulations and improved the transfection efficacy when evaluated in A549 and HeLa cell lines. Fluorescence-assisted cell sorting studies showed comparable number of transfected cells to Lipofectamine 2000 in the HeLa cell line. Intracellular trafficking studies using confocal microscopy indicated transfection of the HeLa cells with the reporter gene within 30 min of lipoplex treatment. γ-Scintigraphy using 99mTc-labeled lipoplexes showed higher concentrations of the lipoplexes in vital tissues like liver, spleen, lungs, and kidneys.
A Frequency-Dependent Virtual Impedance for Voltage-Regulating Converters Feeding Constant Power Loads in a DC Microgrid

The power oscillations at the input of constant power loads (CPLs) fed by LC filters is a well-known phenomenon in dc microgrids. The phenomenon happens because of the negative resistance characteristic exhibited by CPLs. The oscillations can be damped by inserting virtual resistances at the output of voltage-regulating converters to offset the negative resistance of the CPLs. However, large virtual resistances lead to a poor voltage regulation of the dc bus. This paper proposes a frequency-dependent virtual impedance comprising of a parallel RL branch, which solves the issue of poor voltage regulation. Further, the large signal stability of the system in the presence of the virtual impedance is also investigated through the Brayton–Moser mixed potential analysis. Detailed simulations and analysis of the frequency-domain interactions of the system are carried out and the effectiveness of the proposed technique is showcased. Experimental results from a 250 W prototype CPL are included to validate the proposed technique.
A Software/Hardware Parallel Uniform Random Number Generation Framework

In this paper, a software/hardware framework is proposed for generating uniform random numbers in parallel. Using the Fast Jump Ahead technique, the software can produce initial states for each generator to guarantee independence of different sub-streams. With support from the software, the hardware structure can be easily constructed by simply replicating the single generator. We apply the framework to parallelize MT19937 algorithm. Experimental results shows that our framework is capable of generating arbitrary number of independent parallel random sequences while obtaining speedup roughly proportional to the number of parallel cores. Meanwhile, our framework is superior to those existing architectures reported in the literatures in both throughput rate and scalability. Furthermore, we implement 149 parallel instances of MT19937 generators on a Xilinx Virtex-5 FPGA device. It achieves the throughput of 42.61M samples/s. Compared to CPU and GPU implementations, the throughput is 10.0 and 2.5 times faster, while the throughputpower efficiency achieves 167.3 and 18.1 times speedup, respectively.
Benchmarking Stability of Bipedal Locomotion Based on Individual Full Body Dynamics and Foot Placement Strategies–Application to Impaired and Unimpaired Walking

The principles underlying smooth and effortless human walking while maintaining stability as well as the ability to quickly respond to unexpected perturbations result from a plethora of well-balanced parameters, most of them yet to be determined. In this paper, we investigate criteria that may be useful for benchmarking stability properties of human walking. We perform dynamic reconstructions of human walking motions of unimpaired subjects and subjects walking with transfemoral prostheses from motion capture recordings using optimal control. We aim at revealing subject-specific strategies in applying dynamics in order to maintain steady gait considering irregularities such as deviating gait patterns or asymmetric body segment properties. We identify foot placement with respect to the Instantaneous Capture Point as the strategy globally applied by the subjects to obtain steady gait and propose the Residual Orbital Energy as a measure allowing for benchmarking human-like gait toward confident vs. cautious gait.
Development of HF Injection Based Sensorless Method for SRM Usin an Advanced Simulation

This paper deals with development of switched reluctance motor sensorless control method for low speeds using an advanced simulation. Therefore attention is given on detailed system analysis. After this analysis the created simulation is used to develop a low speed sensorless method using active probing suitable for the selected traction drive with switched reluctance motor (SRM). The algorithm is implemented into the studied drive to verify the simulation and proposed method accuracy.
Comparative evaluation of a novel, moderately hypofractionated radiation protocol in 56 dogs with symptomatic intracranial neoplasia

Background: Use of strongly hypofractionated radiation treatments in dogs with intracranial neoplasia did not improve outcomes and yielded increased rates of toxicosis. Objectives: To evaluate safety and efficacy of a new, moderately hypofractionated radiation protocol of 10 × 4 Gy compared to a standard protocol. Animals: Convenience sample of 56 client‐owned dogs with primary symptomatic brain tumors. Methods: Retrospective observational study. Twenty‐six dogs were assigned to the control standard protocol of 20 × 2.5 Gy (group A) and 30 dogs to the new protocol of 10 × 4 Gy (group B), assigned on owners' informed consent. Statistical analysis was conducted under the “as treated” regime, using Kaplan‐Meier and Cox‐regression analysis. Treatment was delivered with technically advanced image‐guided radiation therapy. The 2 treatment groups were compared in terms of outcome and signs of toxicosis. Results: Overall progression‐free interval (PFI) and overall survival (OS) time were favorable, with 663 (95%CI: 497;828) and 637 (95%CI: 403;870) days, respectively. We found no significant difference between the two groups: PFI for dogs in group A vs B was 608 (95%CI: 437;779) days and mean (median not reached) 863 (95%CI: 644;1083) days, respectively (P = .89), and OS for dogs in group A vs B 610 (95%CI: 404;816) and mean (median not reached) 796 (95%CI: 586;1007) days (P = .83). Conclusion and Clinical Importance: In conclusion, 10 × 4 Gy is a safe and efficient protocol for treatment of primary intracranial neoplasia and future dose escalation can be considered.
Robust Adaptive Tracking Control Based on State Feedback Controller With Integrator Terms for Elastic Joint Robots With Uncertain Parameters

This brief addresses a robust adaptive control scheme based on a cascaded structure with a full state feedback controller with integrator terms as inner control loop and computed torque as outer control loop for flexible joint robots. Together with integrator effect, the adaptive control law can enhance position accuracy under uncertainties of the robot model, especially, the high friction caused by harmonic drive with high gear ratio. In this brief, the adaptive friction compensation is designed based on the LuGre friction model, which exhibits some advantages compared with the static friction model (e.g., no chattering effect at zero motor velocity). Furthermore, structural oscillations of the link side can be effectively damped by using joint torque feedback in the state feedback controller. Therefore, the proposed adaptive control approach can simultaneously provide high control performance both in terms of the dynamic behavior and the position accuracy. Global asymptotic tracking is achieved for the complete controlled system. The system stability is derived using Lyapunov approaches and Barbalat’s lemma. Experimental results validate the practical efficiency of the approach.
Force Display Device and Control System for Surgical Training Simulator Using Bone Chisel

This study aims to propose an innovative force and motion control system for use in the virtual surgical training simulators with force display. In surgical operations using a bone chisel, impact forces are applied to the bone by pounding the chisel with a mallet. To virtually represent this situation in a surgical training simulator, the force display device must exhibit high stiffness and be able to react instantaneously to the large impact force and quick acceleration. For this reason, the force display device with high stiffness and force and motion control system that react instantaneously to an impact force are developed for a surgical training simulator involving a bone chisel in this study. In this approach, this force display device is constructed with a ball-screw mechanism for translational motion and a biaxial rotation mechanism for rotational motion of the chisel while allowing high stiffness. However, the force display device's response can be reduced by increasing the mass of moving parts in the device, due to its high stiffness. Therefore, the 2 degree-of-freedom admittance control is proposed for reacting instantaneously to the impact force. The efficiency of the proposed device and control system is verified by creating a virtual experience to contact and split hard tissue using a chisel.
Thermal Characteristics of ESD Diode in FDSOI Technologies

Electrostatic discharge (ESD) protection is very important for integrated circuits. In the fully depleted silicon on insulator (FDSOI) technology, the buried oxide (BOX) caused thermal degradation is one of the factors that degrade the intrinsic ESD robustness. In this work, the thermal characteristic of FDSOI ESD diode is investigated by TCAD simulations. The results show that the reduction in BOX thickness and material optimization can improve the heat dissipation and device’s ESD performance.