Miracle-dz/UniFAR-FTUs huggingface dataset:
Nonlinear Model Predictive Control Reduction Using Truncated Single Shooting

We present a new scheme to reduce the computational burden of Nonlinear Model Predictive Controllers (NMPCs). Working with the direct single shooting formulation of NMPC, we identify the timestep as a ‘small’ parameter and conduct a perturbative analysis of Newton's step. This analysis leads to the introduction of a truncated Lagrangian that can be used to form a new quasi-Newton method with a symbolically reduced Hessian for online optimization. To the authors' knowledge, these methods have not been presented before. In this work we leverage the power of symbolic computation to generate efficient controller code for online evaluation. The reduction methods were applied to diesel engine control and electric vehicle cruise control problems and achieved turnaround times more than 2 times faster with no tradeoff in controller performance. These initial results are quite promising for the development of real-time NMPCs and introduce some new avenues for research.
Fast CU Size and PU Partition Decision for AVS2 Intra Coding

AVS2 is the new generation of video coding standard developed by the Audio Video Coding Standard Working Group of China. Similar to HEVC, a flexible partition structure is adopted to improve coding performance in AVS2. For intra coding, a coding unit (CU) is recursively split into sub CUs based on the quad-tree structure. CUs should be further split into prediction unit (PU) with various square or non-square shapes. All these processes increase encoding complexity dramatically. In this paper, a fast intra coding algorithm for CU partition and PU partition is proposed to reduce the complexity in AVS2 intra coding. Specifically, the statistical analysis model between texture complexity and partition mode is established. According to the model, an adaptive online-offline threshold selection algorithm is proposed to determine the early skipping and early termination in CU and PU level. Experimental results show that the proposed fast intra coding algorithm achieves more than a 54% encoding time reduction on average with only a 0.77% BD-rate increase under all-intra configuration for the AVS2 reference software RD18.0.
A Review Paper Between Open Source and Commercial SDK and Performance Comparisons of Face Matchers

Biometric identification systems must be able to distinguish between individuals in various conditions. This paper presents a review paper on face matchers between commercial and open source SDK and techniques available for face recognition. This paper also presents experiments done in performance comparisons between a commercial face matcher, VeriLook 5.6 and an open source matcher OpenBR 0.5 from a set of images collected from those who work in the offices in various situations including the different poses, and various illuminants. The experiment results taken from those officers in NECTEC have shown that a commercial face matcher performs better but this requires proper set up of face extraction parameters to ensure the optimal results. Further improvements would require other face detection algorithms to enhance the performance of both free and commercial face matchers according to their own particular shortcomings.
Control-observer technique for surface imaging with an experimental platform of Scanning-Tunneling-Microscope type

This paper proposes a control strategy based on synthesis of robust design techniques with state observer tools, handling nonlinearities in the driving piezoactuators, as well as in the tunneling current for a home-made Scanning-Tunneling-Microscope-like device (STM), allowing to estimate the surface of nano samples. As in standard STM operation, a tip is driven at a fixed (subnanometric) distance above the sample which is scanned. The control approach is illustrated with an example of experimental surface reconstruction, and a comparison with results provided by a commercial STM.
Robotic Herding of a Flock of Birds Using an Unmanned Aerial Vehicle

In this paper, we derive an algorithm for enabling a single robotic unmanned aerial vehicle to herd a flock of birds away from a designated volume of space, such as the air space around an airport. The herding algorithm, referred to as the $m$-waypoint algorithm, is designed using a dynamic model of bird flocking based on Reynolds’ rules. We derive bounds on its performance using a combination of reduced-order modeling of the flock's motion, heuristics, and rigorous analysis. A unique contribution of the paper is the experimental demonstration of several facets of the herding algorithm on flocks of live birds reacting to a robotic pursuer. The experiments allow us to estimate several parameters of the flocking model, and especially the interaction between the pursuer and the flock. The herding algorithm is also demonstrated using numerical simulations.
Hybrid Microgrid in Islanded Operation Based on Renewable Energy Sources

The paper provides a feasibility study of a hybrid renewable energy system, considering a combination of multiple generation sources including solar energy, wind energy, and a generator, which can be integrated into the common grid structure providing the required loads and continuous power supply when switching to islanded operation or being paralleled with the main grid. The system has been performed for rural and remote areas using MATLAB program.
An Adaptive Cross Approximation-based Method for Robust Nonlinear Feedback Control Problems

In this paper, an adaptive cross approximation-based method is proposed for nonlinear robust control problems. Firstly, taking advantage of the underlying relationship between robustness property and nonlinear optimality, the robust control problem for the original system is transformed into an infinite-horizon optimal control problem for the nominal system. Secondly, to realize online implementation, an adaptive cross approximation-based method is proposed to solve the Hamilton-Jacobi-Bellman (HJB) equation for the infinite-horizon optimal control problem. The proposed adaptive cross approximation-based method can reconstruct the value function tensor by only solving the optimal control problems on a small subset of the grids. Simulation results show that the proposed method can achieve a speed of about 200 Hz for the four-dimensional nonlinear robust control problem.
Integrating Iterative Bidding in Electricity Markets and Frequency Regulation

We study an electricity market consisting of an independent system operator (ISO) and a group of strategic generators. The ISO seeks to solve the optimal power dispatch problem and to regulate the frequency of the network. However, since generators do not share their cost functions, the ISO cannot solve the dispatch problem and instead engages the generators in an iterative bidding process. This consists of each generator submitting to the ISO a bid at which it is willing to provide power and receiving from the ISO a new power production setpoint calculated given the received bids and the network frequency. We analyze the stability of the interconnected system that results from the coupling between the iterative bidding scheme and the continuous-time swing dynamics of the power network and establish the convergence to the efficient Nash equilibrium and the optimal power dispatch.
Utilizing Graph Measure to Deduce Omitted Entities in Paragraphs

This demo deals with the problem of capturing omitted arguments in relation extraction given a proper knowledge base for entities of interest. This paper introduces the concept of a salient entity and use this information to deduce omitted entities in the paragraph which allows improving the relation extraction quality. The main idea to compute salient entities is to construct a graph on the given information (by identifying the entities but without parsing it), rank it with standard graph measures and embed it in the context of the sentences.
Asymptotic Properties of a Cheap Control Infinite Horizon Nash Differential Game

A two-person nonzero-sum differential game with linear dynamics is considered. Each player has its own infinite horizon quadratic cost functional to be minimized. The feature of the game is that the control costs of one player in both cost functionals are much smaller than the control costs of the other player and the state costs. Thus, the considered game is a cheap control game. We look for a state-feedback Nash equilibrium solution of this game. Using the control optimality conditions, the solution of this game is reduced to solution of a set of two matrix algebraic Riccati equations perturbed by a small positive parameter. For this set of equations, an asymptotic solution is constructed and justified. Using this asymptotic solution, parameter-free solvability conditions of the cheap control game are derived. These conditions also provide the solvability of a lower dimension parameter-free Nash equilibrium game (slow subgame). The optimal values of the cost functionals of the cheap control game and the slow subgame are compared. Based on the above mentioned results, a relation between solutions of the original game and the game, obtained from the original one by replacing the small control costs with zero, is studied. An illustrative example is presented.
A Switched-Capacitor Bidirectional DC–DC Converter With Wide Voltage Gain Range for Electric Vehicles With Hybrid Energy Sources

A switched-capacitor bidirectional dc–dc converter with a high step-up/step-down voltage gain is proposed for electric vehicles with a hybrid energy source system. The converter presented has the advantages of being a simple circuit, a reduced number of components, a wide voltage-gain range, a low voltage stress, and a common ground. In addition, the synchronous rectifiers allow zero voltage switching turn-on and turn-off without requiring any extra hardware, and the efficiency of the converter is improved. A 300 W prototype has been developed, which validates the wide voltage-gain range of this converter using a variable low-voltage side (40–100 V) and to give a constant high-voltage side (300 V). The maximum efficiency of the converter is 94.45% in step-down mode and 94.39% in step-up mode. The experimental results also validate the feasibility and the effectiveness of the proposed topology.
Twelve-Year Follow-up After Peptide Receptor Radionuclide Therapy

Peptide receptor radionuclide therapy (PRRT) has been used for more than 20 y as a systemic treatment approach in inoperable or metastatic somatostatin receptor–positive tumors. The purpose of this study was to analyze the long-term outcome of PRRT with regard to the most commonly used radiopharmaceuticals, 90Y-DOTATOC and 177Lu-DOTATATE. Methods: This retrospective clinical study included a total of 44 consecutive patients (27 men) with advanced tumors and enhanced somatostatin receptor expression. Mean age at initial diagnosis was 60 y (SD, 11.3 y; range, 40–84 y). Median follow-up was 80 mo. For 177Lu-PRRT, the mean number of cycles administered was 5.3 ± 2.5 and the mean activity was 27.2 ± 14.9 GBq per patient. For 90Y-PRRT, the mean number of cycles administered was 5.5 ± 2.6 and the mean activity was 14.7 ± 7.3 GBq per patient. Overall, 378 cycles were administered (mean, 8.6 ± 3.4 cycles per patient), with an overall cumulative activity of 1,514.1 GBq. Results: Median overall survival was 79 mo. Twenty-one (77.8%) of the 27 men and 9 (52.9%) of the 17 women had died 12 y after commencement of PRRT. The shortest duration of illness was 8 mo and the longest 155 mo. Severe side effects (World Health Organization grades III and IV) were seen in 9 of the 14 patients still alive. Chronic kidney disease in combination with anemia was the most common finding in the 9 patients with severe side effects. A poor prognosis was found for those patients who showed progressive disease, in comparison with patients with cumulative disease control after initial PRRT (log rank, P < 0.001), whereas women and patients with no more than 2 tumor sites seemed to especially benefit from PRRT (not reaching significance levels). Conclusion: PRRT is encouraging in terms of long-term outcome. Thirty-two percent (14/44 patients) of the patients with metastatic or inoperable disease were still alive more than 12 y after the beginning of radionuclide therapy. Possible predictors for favorable outcome are having an initial response to PRRT, having a low number of affected sites, and being female.
Large-scale Argument Visualization (LSAV)

Arguments are structures of premises and conclusions that underpin rational reasoning processes. Within complex knowledge domains, especially if they are contentious, argument structures can become large and complex. Visualization tools have been developed that support argument analysts and help them to work with arguments. Until recently, arguments were manually analyzed from natural language text, or constructed from scratch, but new communication modes mean that increasing amounts of debate and the arguments therein can be captured digitally. Furthermore, new tools and techniques for argument mining are beginning to automate the process of extracting argument structure from natural language; leading to much larger argument datasets that present problems for the current generation of argument visualization tools. Additionally, individual argument analysts have different foci which can lead to increased complexity within datasets, and additional facets that argument visualizations should account for but do not. We propose a tool for interacting with argument corpora that enable users to explore and understand the reasoning structure of large-scale arguments. The tool will support a range of interactivity techniques and will help users to explore and analyse large-scale arguments, to more rapidly comprehend complex new problem domains.
Using Ontologies for Representing Classifications of an Information Flow Based Matching Framework for Smart Manufacturing

We propose a matching framework, which is based on a novel application of the theory of Information Flow and its components, to support the production system on the decision making process on which equipment should be used to conduct a specific production step. This decision making process is part of an application scenario, which is derived from the Industrie 4.0 concept that says that products, production equipment, and production IT systems are getting more and more interconnected to finally reach a certain level of self-organization and autonomy. One of the core components of the proposed IF matching framework is a structure that is called classification. We show within this paper that the traditional approaches of using and representing those classifications with the help of simple table structures cannot be used within our application scenario satisfactorily and discuss how ontologies can be developed and used instead.
A Sawtooth Carrier-Based PWM for Asymmetrical Six-Phase Inverters With Improved Common-Mode Voltage Performance

A sawtooth carrier-based sinusoidal pulse width modulation (SC-SPWM) technique for asymmetrical six-phase two-level inverters is proposed in this paper, which could reduce both the peak-to-peak amplitude and the changing frequency of the common-mode voltage (CMV). The intersection-plotting method reveals that the mirror symmetrical sawtooth carriers for two three-phase groups can help optimize the distribution of overlapping areas, which is the CMV reduction mechanism of SC-SPWM. Additionally, the Fourier analysis is employed to quantitatively evaluate the modulation index and harmonic performance of SC-SPWM compared with the conventional SPWM and two phase-shifted SPWM methods. Also, further analysis demonstrates that dead time does not affect the reduction of CMV in a noticeable way. Finally, both simulation and experimental results coincide with the theoretical analysis that the proposed SC-SPWM shows the best performance in reducing the CMV amplitude and changing frequency among these four SPWM methods, though it leads to a higher phase current distortion.
Depressive symptoms and actigraphy‐measured circadian disruption predict head and neck cancer survival

Depressive symptoms have demonstrated prognostic significance among head and neck cancer patients. Depression is associated with circadian disruption, which is prognostic in multiple other cancer types. We hypothesized that depressive symptoms would be associated with circadian disruption in head and neck cancer, that each would be related to poorer 2‐year overall survival, and that relationships would be mediated by tumor response to treatment.
A Lower Bound on the Joint Capacity of Digital Fingerprinting Codes Using Score Functions Based on Log-Likelihood Ratio

Digital fingerprinting codes are embedded in licensed digital contents for preventing illegal distribution. Digital fingerprinting codes are usually designed so that with high probability we can identify a part (or all) of the guilty users who collude to generate a pirated copy. In this paper we first consider the situation where the number of guilty users is equal to two and their attack model is known. We give a lower bound on the joint capacity of the digital fingerprinting codes. The lower bound is expressed as the expectation of the mutual information and is obtained by using certain score functions based on the log-likelihood ratio [12]. This result can be extended to a more general case where the number of guilty users is equal to $t\geq 2$
Error-Correcting WOM Constructions through Concatenation and Joint Design

We construct error-correcting WOM (write-once memory) codes that can correct any specified number of errors in q-Ievel memories. The constructions use suitably designed short q-ary WOM codes and concatenate them with outer error-correcting codes over different alphabets, using suitably designed mappings. With a new storage-efficiency measure we call EC-rate, we show that for common error types the codes save redundancy and implementation complexity over straightforward concatenation.
The Clinical Use of Stem Cell Research in Chronic Obstructive Pulmonary Disease: A Critical Analysis of Current Policies

Chronic obstructive pulmonary disease (COPD) is a disorder affecting more than 200 million people around the world, resulting in three million deaths per year. COPD is characterized by the loss of lung tissue and airway remodelling, with chronic inflammation of the airways and progressive destruction of lung parenchyma. The use of stem cells may lead to regenerative processes that address biological damage. However, this approach raises ethical issues that need to be considered in clinical trials using stem cell therapy, such as informed consent, patient recruitment and harm minimization, as well as the inherent uncertainty of these medical procedures on human beings. Indeed, up to now, these experiments have been performed in preclinical studies using animal models, with few studies involving humans. Additional efforts should be made to assess this promising procedure.
A Lightweight ID-Based Extension for Marker Tracking Systems

The estimation of the position and orientation of the digital video camera is a central challenge in video seethrough augmented reality. Many augmented reality applications solve this problem with the help of markerbased methods, which analyze artificial fiducials in the images of the real environment, e.g., using the widespread ARToolKit library. Among the drawbacks of conventional marker tracking is the necessity to manually define marker patterns. Badly chosen patterns have a negative impact on tracking performance. Although improved methods for automatic marker generation have been described, manually controlled marker tracking is still widely used in many applications for practical reasons. In this paper, we describe a lightweight drop-in extension for IDbased marker tracking. Our system makes it possible to automatically generate a large number of trackingfiducials identified by unique numerical IDs. The created marker patterns consists of large monochrome patches, which improves the recognition rate and tracking performance compared to typical manually defined fiducials. Due to the design of our extension, only minimal adaptations are required in order to add ID-based tracking to existing augmented reality software. We discuss experimental results demonstrating the improved pattern recognition and describe an example application.
Design of MPPT Based Fuzzy Logic for Solar-Powered Unmanned Aerial Vehicle Application

By converting sun energy into electrical energy, solar cells are a technology of renewable energy that is abundant and low emissions. Meanwhile, solar cells can reduce conventional vehicle exhaust emissions by 92%. Therefore, solar panels have a great chance to be applied to a vehicle such as Unmanned Aerial Vehicle (UAV). Unfortunately, solar panel is a non-linear energy source whose output power changes depending on the irradiance and ambient temperature. If operated under normal circumstances, solar panels will not absorb the solar power optimally due to the characteristic curves of the solar panels. In order maximize the power from solar panels, it needs Maximum Power Point Tracking (MPPT), which is a power optimization method by conditioning the output voltage of the solar panel. On UAV, the sun's irradiance is changing very rapidly, so the conventional MPPT is less efficient to use, because it has a slow response and has oscillations when the power is in maximum. In this research, it has been designed and implemented of MPPT system using fuzzy logic control. Fuzzy logic control can speed up the system response towards the load changes, and reduce the oscillations that occur at maximum power as well. A DC-DC converter, as the actuator of the voltage conditioner, should be selected which has as light as possible in weight so that it will not increase the workload of the aircraft. Simulation and experiment have been done in this research. It shows that MPPT using Fuzzy Logic can reduce the power losses up to 4.5%.
Towards a Continuous Non-Invasive Cuffless Blood Pressure Monitoring System Using PPG: Systems and Circuits Review

This paper presents an overview of the cuffless, continuous time, non-invasive blood pressure measuring devices (cNIBP) based on photoplethysmography (PPG). The cNIBP fundamental challenges, such as motion artifacts (MAs), noise, low PPG signal amplitude with large DC components, and possible solutions are discussed. Techniques and circuits for MAs reduction, DC photocurrent cancellation, and sensitivity improvements are presented. To enhance the BP system performance, both the optimization of the integrated PPG receiver design and the reduction of the LED driver power consumption are introduced. Useful design considerations are proposed for designers to improve the PPG-based BP system accuracy.