Miracle-dz/UniFAR-FTUs huggingface dataset:
A robust quaternion based Kalman filter using a gradient descent algorithm for orientation measurement

This paper presents a robust quaternion based filter approach to estimate orientation from Magnetic Angular Rate Gravity (MARG)-sensors. These sensors consist of tri-axis accelerometer and gyroscope as well as a tri-axis magnetometer which allow a complete measurement of orientation relative to the direction of gravity and magnetic field of the earth. The proposed filter uses a gradient descent algorithm (GDA) to compute an orientation from magnetometer and accelerometer data. This calculated orientation is directly used as an input in a Kalman filter framework (KFF) which predicts the orientation estimation from gyroscope data. The embedding of the gradient descent algorithm into the Kalman filter allows the computation of a weighted orientation represented as quaternion. Furthermore, the designed filter can overcome short time magnetic disturbance by switching between MARG and IMU equations inside the gradient descent filter stage (GDFS) and therefore enables a more robust orientation estimation without the need for additional algorithms. Tests show the proposed filter to be superior to a commercially available sensor fusion algorithm related to orientation estimation at slow angular rates. Moreover, the proposed filter is able to maintain good orientation estimation under short term magnetic disturbance.
Sensor array calibration by a single reference in presence of measurand non-linear gradient

A calibration method exploiting a single external reference is proposed for sensors arrays in presence of a measurand non-linear gradient in the system under test. The calibration artifacts due to a non-uniform distribution of the measurand in the system under test, not detected by the single punctual reference sensor, are avoided. A proof-of-principle demonstration is carried out within the case study of a thermistors array obtaining compatible result with respect to a standard method which requires a reference sensor for each element of the sensor array. Thus, the complexity (and cost) of standard calbration setups is reduced by using a single reference sensor without sacrifying significantly the calibration accuracy.
Quo vadis, biological treatment for psoriasis and psoriatic arthritis?

Psoriasis is a chronic autoimmune disease that affects approximately 2–3% of the world’s population. Although the cutaneous manifestations of the disease are the most prevalent, psoriasis is also associated with a systemic inflammation and various co-morbidities linked with autoinflammatory processes. One of those processes is psoriatic arthritis, an inflammatory, seronegative spondyloarthropathy that develops in 13.8–30% of psoriatic patients at some point of their lives. Over the past 15 years the therapeutic options for severe and generalized psoriasis have broadened immensely with the introduction of biological agents to everyday practice. We present a quick overview of current biological therapies in the treatment of psoriasis and prospects for forthcoming advancements in biological treatment.
RF energy scavenger for battery-free Wireless Sensor Nodes

The continuous development of IoT (Internet Of Things) infrastructure and applications is paving the way to advanced and innovative ideas and solutions, some of which are pushing to the limit the state-of-the-art technology. The increasing demand of Wireless Sensor Nodes which need to be capable to collecting and sharing data wirelessly while often positioned in places hard to be reached and serviced, motivates engineers to look for innovative solutions of energy harvesting to allow battery-free sensor nodes. RF harvesting, due to the pervasiveness of RF energy, that can reach out of sight places, could be a key technology to power wirelessly IoT sensor devices, that in order to be ubiquitous, need to be wireless, maintenance free, battery free and low cost enough to be used almost anywhere. In this article will be shown the implementation of an RF energy transfer system for battery free wireless sensor nodes. The system comprises an RF power transmitter (used as Radio Frequency source) which delivers a power of 0.5 W at 868 MHz and an RF energy harvesting integrated circuit, IC (provided by STMicroelectronics) which is used as RF power receiver to power a battery-free sensor node. Experimental results will show how the system is capable to sustain a 10 mA load for a 50 ms acquisition time with the transmitted power delivered from several distances.
A Joint Multi-Feature and Scale-Adaptive Correlation Filter Tracker

Traditional tracking-by-detection trackers may fail to track targets owing to interferences, such as deformation, occlusion, fast or irregular motion, and background clutter. To improve the process of feature extraction, sample training, and the performance of the traditional kernelized correlation filter (KCF), this paper proposes a new joint multi-feature and scale-adaptive correlation filter tracking algorithm based on histogram of oriented gradients (HOG) and color-naming features. The new algorithm is composed of a position correlation filter tracker and a scale correlation filter tracker. It first uses a mask matrix to cut the training samples, obtains a higher proportion of real samples, and then trains the two correlation filter trackers. One is a position tracker that uses HOG and color-naming features to train two correlation filters, and then combines the results of the two correlation filters to calculate the target position. The second tracker is used to identify the scale with the maximum response size to select the target scale. The proposed algorithm achieves a competitive performance compared with algorithms, such as KCF, compressive tracking, and circulant structure kernel. The results show that this algorithm achieves a better performance when faced with occlusion, deformation, background clutter, and fast or irregular motion, and is able to track changes in target scale.
Mitigation of voltage fluctuation in distribution system connected with PV and PHEVs using artificial bee colony algorithm

The output power generation of photovoltaic (PV) has an intermittent nature due to cloud transients. Consequently, considerable fluctuations in the voltages are expected in distribution systems with high PV penetrations. In this paper, a method is proposed to mitigate voltage fluctuations due to PV by simultaneously optimizing the reactive power of the PV inverters and charging/discharging power of the plug-in hybrid electric vehicles (PHEV). To effectively mitigate voltage fluctuations, we introduce a new objective function that represents the deviation of the voltage from the past moving average. The use of this new objective yields a high reduction in the voltage fluctuations. The artificial bee colony (ABC) algorithm is utilized to optimally solve the real-time optimization problem while considering the constraints of the distribution system, PV inverters, and PHEVs. The simulation results on the 33-bus distribution system demonstrate the effectiveness of the proposed method for mitigating the voltage fluctuations during a high fluctuating generation profile of PV.
Reliability-Aware Multi-Vth Domain Digital Design Assessment

Resilient systems for future application as the Internet of Things (IoT), aerospace or automotive must satisfy demanding specifications over a 10-years lifespan. Thus, timedependent degradation must be considered in early design stages. To ensure a realistic estimation of degradation impact a whole matrix decomposition algorithm is implemented in a 65nm CMOS technology with different multi threshold voltage standard cells, for a required low-power design. We present an assessment method based on stochastic mission profiles saving at least 10% area and power compared to common methods.
Cybersecurity of healthcare IoT-based systems: Regulation and case-oriented assessment

The paper deals with exponentially growing technology — Internet of Things (IoT) in the field of healthcare. It is spoken about the networked healthcare and medical architecture. The attention is given to the analysis of the international regulations on medical and healthcare cybersecurity. For building a trustworthy healthcare IoT solution, a developed normative hierarchical model of the international cybersecurity standards is provided. For cybersecurity assessment of such systems the case-oriented technique, which includes Advanced Security Assurance Case (ASAC) and an example on a wireless insulin pump of its application are provided.
Two-year clinical outcomes after implantation of an everolimus-eluting bioresorbable scaffold (Absorb) in stable angina and acute coronary syndrome patients. Single-centre real-life registry data

Aim The aim of this long-term registry data was to evaluate 2-year clinical and angiographic outcomes after implantation of everolimus-eluting bioresorbable scaffolds (Absorb) from the Latvian Centre of Cardiology Real-life Registry. Material and methods Between November 2012 and December 2014 in the Centre of Cardiology Real-life Bioresorbable Vascular Scaffold Registry, 187 patients with stable angina or acute coronary syndrome and available 2-year follow-up were selected. All patients had percutaneous coronary intervention (PCI) following bioresorbable scaffold (Absorb) implantation. At 2 years, clinical parameters were analysed in stable angina and acute coronary syndrome subgroups: all-cause death, cardiac death, non-cardiac death, myocardial infarction (MI), target lesion revascularization (TLR), target vessel revascularization (TVR), scaffold thrombosis (ST), cerebral infarction, in-scaffold restenosis and bleeding. Results The clinical follow-up rate at 2 years was 96.2%. In-hospital death occurred in 2 (1.1%) patients, and 1 (0.5%) patient had in-hospital MI. At 2 years, the rate of all-cause death was 3.9% (n = 7), MI 1.6% (n = 3), TLR 3.9% (n = 7), and TVR 8.4% (n = 15). Between hospital discharge and 2-year follow-up scaffold thrombosis occurred in 2 (1.1%) patients. In-hospital scaffold thrombosis occurred in 1 (0.5%) patient due to clopidogrel resistance, and 1 additional case of scaffold thrombosis occurred at 5 days after implantation (0.5%). Conclusions Bioresorbable scaffolds showed acceptable efficacy (target lesion revascularization) and safety (cardiac death, myocardial infarction, and scaffold thrombosis) results at mid-term follow-up in stable angina and acute coronary syndrome patients.
Automatic Segmentation of Tree Structure From Point Cloud Data

Methods for capturing and modeling vegetation, such as trees or plants, typically distinguish between two components—branch skeleton and foliage. Current methods do not provide quantitatively accurate tree structure and foliage density needed for applications such as visualization, inspection, or to estimate vegetation parameters. This letter describes an automatic method for segmenting three-dimensional point cloud data of vegetation, acquired from commodity scanners, into its two main components: branches and leaves, by using geometric features computed directly on the point cloud. In this letter, the specific type of vegetation considered is broadleaf trees. We present a data-driven approach, where a Random forest classifier is used for segmentation. In contrast to state-of-the-art methods, the point cloud is not reduced to a set of primitives such as cylinders. Instead, the algorithm works at the level of the input point cloud itself, preserving quantitative accuracy in the resulting model. Computation of typical vegetation metrics follows naturally from this model. We achieve an average classification accuracy of $91\%$ on simulated data across three different species of broadleaf trees. Qualitative results on real data are also presented.
Der Einfluss intermittierender Hypoxie auf den Laktattransport in den Erythrozyten und Skelettmuskelzellen des Typ-2-Diabetikers

133 6 Abstract The role of lactate as a metabolic fuel and its transport via monocarboxylate transporters (MCTs) are only partially investigated in connection with the pathological metabolism of diabetes-type-2. On the one hand, increased resting lactate values are considered to be a risk factor in type-2-diabetes, on the other hand the oxidation of lactate could provide the energy (during physical activity) which is lacking from restricted glucose uptake due to insulin resistance. As glucose uptake into the cell is one major problem in type-2-diabetes, possibilities or interventions increasing this uptake or alternative pathways (lactate metabolism) could be beneficial. Studies showed that hypoxia and/or exercise increase glucose metabolism and the expression of MCTs. It can be speculated that these hypoxia/exercise induced changes could be beneficial for patients with a hyperglycemic status. Therefore the present study investigated the effects of six weeks of moderate exercise under intermittent normobaric hypoxic conditions. As a reference, a second group performed the same moderate exercise under normoxia, and a third group performed moderate endurance training in normoxic conditions. All subjects were sedentary male non-insulin-dependent type-2-diabetics (n = 55, age 59.9 ± 9.4 years, BMI 31.6 ± 4.0 kg/m2). Before and after the interventions, fibre type distribution, cross sectional area and MCT-density in skeletal muscle and red blood cells (RBC) were investigated. Furthermore the lactate distribution between plasma and RBC under resting and exercise conditions was analyzed. All interventions showed a significant increase in endurance capacity (VO2peak, peak power and lactate threshold) and a reduction in resting blood pressure, without differences between the groups. Skeletal muscle MCT1density showed a significant increase accompanied by a significant decrease of MCT4 in the endurance group only. Furthermore the percentage of type-1 muscle fibres increased. The density of MCT1 in RBC under resting conditions was significantly higher; under exercise conditions MCT-density significantly decreased after the endurance training only. Lactate distribution between plasma and RBC was not altered in any group.
Online continuous detection of an unbalanced metallic shaft using electrostatic sensors

Vibration detection and measurement of a rotary shaft is essential for the diagnosis and prognosis of industrial rotating machinery. However, the imbalance of a shaft, as quantified through vibration displacement, is the most common cause of machine vibration. The objective of this study is to develop a novel technique through electrostatic sensing for the online, continuous and non-contact detection of the imbalance fault of a rotary shaft. A mathematical model is established to extract useful information about the shaft displacement vibration from the simulated signal in the frequency domain. Experimental tests were conducted on a purpose-built test rig to detect the displacement vibration of the shaft at different rotational speeds (400, 800 and 1200 rpm). A normal shaft and an eccentric shaft were tested with the output signals from the electrostatic sensor analyzed. The effectiveness of the proposed method is verified through experimental tests and computational simulation.
Hand gesture recognition based on HOG-LBP feature

With the rapid development of information technology, human-computer interaction (HCI) is now experiencing the transition from traditional command line interface to novel natural user interface such as speech and gesture, thus vision-based hand gesture recognition is one of the key technologies to realize natural HCI. However, the performance of gesture recognition is often influenced by variations among lighting conditions, complex backgrounds and so on. This paper proposes a new fusion approach of hand gesture recognition by combining the HOG and uniform LBP feature on blocks, in which HOG features depict hand shape and LBP features depict hand texture. Support Vector Machine with radial basis function (RBF) as kernel function is adopted to train the hand gesture classifier. Experimental results show that HOG-LBP fused feature performs well on two sub-datasets from NUS hand posture dataset-II, reaching a relative high recognition accuracy of 97.8% and 95.07% respectively. The comparison experiments among HOG-LBP, HOG and LBP features also show that the HOG-LBP feature performs better than one single feature.
The noise characteristics of gas-liquid two phase slug flow in vertical pipe

The flow noise is produced due to fluid structure interaction and gas-liquid interaction, Flow noise signal contains a lot of information of the two-phase flow, such as flow type, phase holdup, velocity and so on, The detection and analysis of flow noise are mostly in the study of gas-solid two-phase flow, It has not been reported in gas-liquid two-phase flow research, In this paper, acoustic emission measurement technique combined with fast Fourier transform (FFT) is used to detect the acoustic signal of the gas liquid two phase flow, a new designed porous plate is installed in the vertical flow pipeline, A large number of experiments were carried out in the multiphase flow experimental facility at Hebei University. The approximate relationship between the peak frequency distribution of noise signal and the gas flow rate is obtained by measuring the peak position of the different gas flow rates under the slug flow condition. A preliminary method for estimating gas flow is proposed, which provides a new idea for the analysis of gas-liquid two-phase flow noise signal extraction of characteristic parameters of two-phase flow.
A Decoupled Direct Positioning Algorithm for Strictly Noncircular Sources Based on Doppler Shifts and Angle of Arrival

This paper discusses the localization problem for strictly noncircular sources based on Doppler shifts and angle of arrival (AOA). The conventional location methods, called two-step methods, first extract measurement parameters from the signals, and then estimate the position from these parameters. Unlike the conventional two-step methods, direct position determination (DPD) methods can locate emitter in a single step without estimating intermediate parameters, thereby receiving higher location accuracy. However, existing DPD algorithms focusing on moving receivers remain few, and ignore exploiting the noncircular property of sources to enhance the localization accuracy. To solve these problems, this paper develops a decoupled maximum likelihood (ML) DPD algorithm for strictly noncircular sources based on Doppler shifts and AOA. First, we reconstruct the DPD optimization model by exploiting the noncircular property of sources and using Doppler shifts to meet the moving receivers application. Then, since the prescribed ML DPD algorithm for multiple sources will suffer huge computation load, a decoupled iterative idea is applied to it. Compared with the straightforward implementation of ML estimators, our method substantially reduces the computation complexity via decoupling the position of each emitter from the other emitters in each iteration. In addition, we derive the Cramér-Rao Bound for strictly noncircular sources, and prove it is lower than that of circular sources. Simulation results demonstrate that the proposed algorithm achieves convergence through only a few iterations, and receives superior performance than other location methods in the test scenarios.
Fusing data from inertial measurement units and a 3D camera for body tracking

Recent developments in the domains of virtual and augmented reality have created frameworks for exploring new research topics related to applications ranging from unmanned aerial vehicles (UAVs) to devices used in the rehabilitation of patients affected by various disabilities. This paper proposes a novel architecture for a rehabilitation-focused full-body motion tracking Virtual Personal Trainer (VPT) system comprising nine Inertial Measurement Unit (IMU) sensors and a 3D camera. The 3D camera is used for the generation of a point of reference that iss shown to be important for stabilizing the output of the IMU sensors, as well as to counteract the inherent gyroscopic IMU drift and interference from surrounding electromagnetic fields. The fused data is displayed to the user as a 3D virtual reality scene containing visual cues corresponding to the correctness of the user's body. The Unity game engine was used for rendering the 3D interface as it allows for a detailed physics-based real-time visualization of the synchronized virtual skeleton-driven model. This paper therefore describes the design and implementation of the hardware and software of the VPT system, thereby enabling a completely wireless full-body sensor array system to educate, validate, and find solutions for the user's form with reference to an ideal form. Data obtained by measuring various parameters of the system will show how the resulting unrestricted 3-dimensional tracking exhibits the required accuracy for a useful rehabilitation system, thereby providing an affordable alternative to having on-site trainers.
A Power-Efficient and Social-Aware Relay Selection Method for Multi-Hop D2D Communications

Due to the short communication range, users are selected as relays to support multi-hop transmission for content sharing/downloading in D2D communications. In this letter, we first exploit social relationships from interacts and contributions, and then formulate an optimal relay selection problem to enhance cooperative multi-hop D2D communications. A Power-efficient and Social-aware Relay Selection (PSRS) algorithm is provided to solve the above problem. Simulation results show that our method has the lowest average power consumption compared to the existing methods.
An auto-balancing signal conditioning scheme for non-contact measurement of conductivity of water

This paper presents a signal conditioning approach to measure resistance and hence conductivity of water in an insulating tube through capacitively coupled electrodes. In the scheme presented, the electrodes are electrically insulated from water and measurement is taken through couple of capacitances formed between the electrode and water column. The capacitive coupling overcomes the problems of electrode polarization and contamination associated with conventional contact based approach of conductivity measurement of water. The large reactance of the coupling capacitors, compared to the resistance of the water column under measurement, is a challenge. Moreover, the variations in the coupling capacitor over time presents another challenge. The auto-balancing signal conditioning scheme presented here overcome these challenges by providing an output that is directly proportional to the resistance under measurement and is independent of the value of the coupling capacitors. Test results on a prototype of the proposed circuit show that the maximum error in the resistance measurement is less than 0.9 % and the output is independent of the coupling capacitors.